From 8b7edd4eaf0d196e674a085f744d1a69260a6c91 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 16 Nov 2023 06:02:05 +0100 Subject: Update pkgdown docs to bootstrap 5 with search --- docs/articles/FOCUS_L.html | 293 +++++++++++++++++++-------------------------- 1 file changed, 124 insertions(+), 169 deletions(-) (limited to 'docs/articles/FOCUS_L.html') diff --git a/docs/articles/FOCUS_L.html b/docs/articles/FOCUS_L.html index 7b5acf17..7aa90c4a 100644 --- a/docs/articles/FOCUS_L.html +++ b/docs/articles/FOCUS_L.html @@ -4,142 +4,104 @@ - + + Example evaluation of FOCUS Laboratory Data L1 to L3 • mkin - - - + + + - - + - + + Skip to contents -
-
-
-
-

Example evaluation of FOCUS Laboratory Data L1 -to L3

+ +
+
+

Example evaluation of FOCUS Laboratory Data L1 to L3

Johannes Ranke

Last change 18 May 2023 -(rebuilt 2023-08-09)

+(rebuilt 2023-11-16) Source: vignettes/FOCUS_L.rmd - - +
FOCUS_L.rmd
@@ -168,18 +130,18 @@ model fit. This covers the numerical analysis given in the FOCUS report.

 m.L1.SFO <- mkinfit("SFO", FOCUS_2006_L1_mkin, quiet = TRUE)
-summary(m.L1.SFO)
-
## mkin version used for fitting:    1.2.5 
-## R version used for fitting:       4.3.1 
-## Date of fit:     Wed Aug  9 17:55:39 2023 
-## Date of summary: Wed Aug  9 17:55:39 2023 
+summary(m.L1.SFO)
+
## mkin version used for fitting:    1.2.6 
+## R version used for fitting:       4.3.2 
+## Date of fit:     Thu Nov 16 04:20:13 2023 
+## Date of summary: Thu Nov 16 04:20:13 2023 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted using 133 model solutions performed in 0.031 s
+## Fitted using 133 model solutions performed in 0.011 s
 ## 
 ## Error model: Constant variance 
 ## 
@@ -256,7 +218,7 @@ report.

 
A plot of the fit is obtained with the plot function for mkinfit
 objects.

 
-plot(m.L1.SFO, show_errmin = TRUE, main = "FOCUS L1 - SFO")

+plot(m.L1.SFO, show_errmin = TRUE, main = "FOCUS L1 - SFO")

The residual plot can be easily obtained by

@@ -268,25 +230,25 @@ objects.

 
## Warning in mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet = TRUE): Optimisation did not converge:
 ## false convergence (8)

 
-plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")

+plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")

-summary(m.L1.FOMC, data = FALSE)
+summary(m.L1.FOMC, data = FALSE)
## Warning in sqrt(diag(covar)): NaNs produced
## Warning in sqrt(1/diag(V)): NaNs produced
## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result
 ## is doubtful
-
## mkin version used for fitting:    1.2.5 
-## R version used for fitting:       4.3.1 
-## Date of fit:     Wed Aug  9 17:55:39 2023 
-## Date of summary: Wed Aug  9 17:55:39 2023 
+
## mkin version used for fitting:    1.2.6 
+## R version used for fitting:       4.3.2 
+## Date of fit:     Thu Nov 16 04:20:13 2023 
+## Date of summary: Thu Nov 16 04:20:13 2023 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted using 342 model solutions performed in 0.07 s
+## Fitted using 342 model solutions performed in 0.023 s
 ## 
 ## Error model: Constant variance 
 ## 
@@ -398,7 +360,7 @@ residual plot can be obtained simply by adding the argument
 show_residuals to the plot command.

 
 m.L2.SFO <- mkinfit("SFO", FOCUS_2006_L2_mkin, quiet=TRUE)
-plot(m.L2.SFO, show_residuals = TRUE, show_errmin = TRUE,
+plot(m.L2.SFO, show_residuals = TRUE, show_errmin = TRUE,
      main = "FOCUS L2 - SFO")

 

 
The \(\chi^2\) error level of 14%
@@ -422,22 +384,22 @@ kinetics.

 
For comparison, the FOMC model is fitted as well, and the \(\chi^2\) error level is checked.

 
 m.L2.FOMC <- mkinfit("FOMC", FOCUS_2006_L2_mkin, quiet = TRUE)
-plot(m.L2.FOMC, show_residuals = TRUE,
+plot(m.L2.FOMC, show_residuals = TRUE,
      main = "FOCUS L2 - FOMC")

 

 
-summary(m.L2.FOMC, data = FALSE)

-
## mkin version used for fitting:    1.2.5 
-## R version used for fitting:       4.3.1 
-## Date of fit:     Wed Aug  9 17:55:40 2023 
-## Date of summary: Wed Aug  9 17:55:40 2023 
+summary(m.L2.FOMC, data = FALSE)
+
## mkin version used for fitting:    1.2.6 
+## R version used for fitting:       4.3.2 
+## Date of fit:     Thu Nov 16 04:20:13 2023 
+## Date of summary: Thu Nov 16 04:20:14 2023 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted using 239 model solutions performed in 0.044 s
+## Fitted using 239 model solutions performed in 0.014 s
 ## 
 ## Error model: Constant variance 
 ## 
@@ -506,15 +468,15 @@ the data.

 
Fitting the four parameter DFOP model further reduces the \(\chi^2\) error level.

 
 m.L2.DFOP <- mkinfit("DFOP", FOCUS_2006_L2_mkin, quiet = TRUE)
-plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE,
+plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE,
      main = "FOCUS L2 - DFOP")

 

 
-summary(m.L2.DFOP, data = FALSE)

-
## mkin version used for fitting:    1.2.5 
-## R version used for fitting:       4.3.1 
-## Date of fit:     Wed Aug  9 17:55:40 2023 
-## Date of summary: Wed Aug  9 17:55:40 2023 
+summary(m.L2.DFOP, data = FALSE)
+
## mkin version used for fitting:    1.2.6 
+## R version used for fitting:       4.3.2 
+## Date of fit:     Thu Nov 16 04:20:14 2023 
+## Date of summary: Thu Nov 16 04:20:14 2023 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -523,7 +485,7 @@ the data.

 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted using 581 model solutions performed in 0.119 s
+## Fitted using 581 model solutions performed in 0.041 s
 ## 
 ## Error model: Constant variance 
 ## 
@@ -611,7 +573,7 @@ only the L3 dataset prepared above.

 # Only use one core here, not to offend the CRAN checks
 mm.L3 <- mmkin(c("SFO", "FOMC", "DFOP"), cores = 1,
                list("FOCUS L3" = FOCUS_2006_L3_mkin), quiet = TRUE)
-plot(mm.L3)
+plot(mm.L3)

The \(\chi^2\) error level of 21% as well as the plot suggest that the SFO model does not fit very well. The @@ -627,11 +589,11 @@ as a row index and datasets as a column index.

using square brackets for indexing which will result in the use of the summary and plot functions working on mkinfit objects.

-summary(mm.L3[["DFOP", 1]])
-
## mkin version used for fitting:    1.2.5 
-## R version used for fitting:       4.3.1 
-## Date of fit:     Wed Aug  9 17:55:41 2023 
-## Date of summary: Wed Aug  9 17:55:41 2023 
+summary(mm.L3[["DFOP", 1]])
+
## mkin version used for fitting:    1.2.6 
+## R version used for fitting:       4.3.2 
+## Date of fit:     Thu Nov 16 04:20:14 2023 
+## Date of summary: Thu Nov 16 04:20:14 2023 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -640,7 +602,7 @@ summary and plot functions working on mkinfit objects.

 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted using 376 model solutions performed in 0.075 s
+## Fitted using 376 model solutions performed in 0.024 s
 ## 
 ## Error model: Constant variance 
 ## 
@@ -715,7 +677,7 @@ summary and plot functions working on mkinfit objects.

 ##    91   parent     15.0     15.18 -0.18181
 ##   120   parent     12.0     10.19  1.81395
-plot(mm.L3[["DFOP", 1]], show_errmin = TRUE)
+plot(mm.L3[["DFOP", 1]], show_errmin = TRUE)

Here, a look to the model plot, the confidence intervals of the parameters and the correlation matrix suggest that the parameter @@ -746,7 +708,7 @@ below:

mm.L4 <- mmkin(c("SFO", "FOMC"), cores = 1, list("FOCUS L4" = FOCUS_2006_L4_mkin), quiet = TRUE) -plot(mm.L4) +plot(mm.L4)

The \(\chi^2\) error level of 3.3% as well as the plot suggest that the SFO model fits very well. The error @@ -754,18 +716,18 @@ level at which the \(\chi^2\) test passes is slightly lower for the FOMC model. However, the difference appears negligible.

-summary(mm.L4[["SFO", 1]], data = FALSE)
-
## mkin version used for fitting:    1.2.5 
-## R version used for fitting:       4.3.1 
-## Date of fit:     Wed Aug  9 17:55:42 2023 
-## Date of summary: Wed Aug  9 17:55:42 2023 
+summary(mm.L4[["SFO", 1]], data = FALSE)
+
## mkin version used for fitting:    1.2.6 
+## R version used for fitting:       4.3.2 
+## Date of fit:     Thu Nov 16 04:20:14 2023 
+## Date of summary: Thu Nov 16 04:20:15 2023 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted using 142 model solutions performed in 0.027 s
+## Fitted using 142 model solutions performed in 0.01 s
 ## 
 ## Error model: Constant variance 
 ## 
@@ -819,18 +781,18 @@ appears negligible.

 ##        DT50 DT90
 ## parent  106  352
-summary(mm.L4[["FOMC", 1]], data = FALSE)
-
## mkin version used for fitting:    1.2.5 
-## R version used for fitting:       4.3.1 
-## Date of fit:     Wed Aug  9 17:55:42 2023 
-## Date of summary: Wed Aug  9 17:55:42 2023 
+summary(mm.L4[["FOMC", 1]], data = FALSE)
+
## mkin version used for fitting:    1.2.6 
+## R version used for fitting:       4.3.2 
+## Date of fit:     Thu Nov 16 04:20:15 2023 
+## Date of summary: Thu Nov 16 04:20:15 2023 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted using 224 model solutions performed in 0.04 s
+## Fitted using 224 model solutions performed in 0.014 s
 ## 
 ## Error model: Constant variance 
 ## 
@@ -900,34 +862,27 @@ Validierung von Modellierungssoftware als Alternative zu ModelMaker
 
 
 
-  
-
-  
 
-
 
 
-
-      

+    

   

 
Developed by Johannes Ranke.

 

 
-

+

   

 
Site built with pkgdown 2.0.7.

 

 
-      

+    

 
 
   
 
-
   
 
   
-- 
cgit v1.2.3


From 6476f5f49b373cd4cf05f2e73389df83e437d597 Mon Sep 17 00:00:00 2001
From: Johannes Ranke 
Date: Thu, 13 Feb 2025 16:30:31 +0100
Subject: Axis legend formatting, update vignettes

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diff --git a/R/multistart.R b/R/multistart.R
index aeea2d81..4ba82a43 100644
--- a/R/multistart.R
+++ b/R/multistart.R
@@ -40,7 +40,7 @@
 #' f_mmkin <- mmkin("DFOP", dmta_ds, error_model = "tc", cores = 7, quiet = TRUE)
 #' f_saem_full <- saem(f_mmkin)
 #' f_saem_full_multi <- multistart(f_saem_full, n = 16, cores = 16)
-#' parplot(f_saem_full_multi, lpos = "topleft")
+#' parplot(f_saem_full_multi, lpos = "topleft", las = 2)
 #' illparms(f_saem_full)
 #'
 #' f_saem_reduced <- update(f_saem_full, no_random_effect = "log_k2")
@@ -50,7 +50,7 @@
 #' library(parallel)
 #' cl <- makePSOCKcluster(12)
 #' f_saem_reduced_multi <- multistart(f_saem_reduced, n = 16, cluster = cl)
-#' parplot(f_saem_reduced_multi, lpos = "topright", ylim = c(0.5, 2))
+#' parplot(f_saem_reduced_multi, lpos = "topright", ylim = c(0.5, 2), las = 2)
 #' stopCluster(cl)
 #' }
 multistart <- function(object, n = 50,
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 Example evaluation of FOCUS Example Dataset D • mkin
 
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-Testing hierarchical pathway kinetics with residue data on cyantraniliprole • mkin
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-Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione • mkin
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Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione

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-Ranke

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Last change on 4 August 2023,
-last compiled on 16 November 2023

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-      Source: vignettes/prebuilt/2023_mesotrione_parent.rmd
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2023_mesotrione_parent.rmd

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When focussing on parameter identifiability using the test if the confidence interval includes zero, dfop_pH_4 would still be the preferred model. However, it should be kept in mind that parameter @@ -1947,11 +2226,9 @@ likelihood. As the confidence interval of the random effect for g only marginally includes zero, it is suggested that this is acceptable, and that dfop_pH_2 can be considered the most preferable model.

-
-plot(dfop_pH_2)
-

-
-endpoints(dfop_pH_2)
+
plot(dfop_pH_2)
+

+
endpoints(dfop_pH_2)
$covariates
       pH
 50% 5.75
@@ -1959,8 +2236,7 @@ most preferable model.

 $distimes
          DT50     DT90 DT50back  DT50_k1  DT50_k2
 meso 18.36876 73.51841 22.13125 4.191901 23.98672
-
-endpoints(dfop_pH_2, covariates = c(pH = 7))
+
endpoints(dfop_pH_2, covariates = c(pH = 7))
$covariates
      pH
 User  7
@@ -1969,22 +2245,21 @@ $distimes
          DT50     DT90 DT50back  DT50_k1  DT50_k2
 meso 8.346428 28.34437 8.532507 4.191901 8.753618
-
-

SFORB -

-
-sforb_pH <- saem(f_sep_const["SFORB", ], no_random_effect = c("meso_free_0", "log_k_meso_free_bound"),
-  covariates = pH,
-  covariate_models = list(log_k_meso_free ~ pH, log_k_meso_bound_free ~ pH))
-
-summary(sforb_pH)$confint_trans |> kable(digits = 2)
- - +
+

SFORB

+
sforb_pH <- saem(f_sep_const["SFORB", ], no_random_effect = c("meso_free_0", "log_k_meso_free_bound"),
+  covariates = pH,
+  covariate_models = list(log_k_meso_free ~ pH, log_k_meso_bound_free ~ pH))
+
summary(sforb_pH)$confint_trans |> kable(digits = 2)
+
+ + - + + @@ -2050,41 +2325,39 @@ effect on this parameter (SD.log_k_meso_bound_free) includes zero.

Using the illparms function, these ill-defined parameters can be found more conveniently.

-
-illparms(sforb_pH)
-
[1] "sd(log_k_meso_bound_free)"      "beta_pH(log_k_meso_bound_free)"
+
illparms(sforb_pH)
+
[1] "sd(log_k_meso_bound_free)"      "beta_pH(log_k_meso_bound_free)"

To remove the ill-defined parameters, a second variant of the SFORB model with pH influence is fitted. No ill-defined parameters remain.

-
-sforb_pH_2 <- update(sforb_pH,
-  no_random_effect = c("meso_free_0", "log_k_meso_free_bound", "log_k_meso_bound_free"),
-  covariate_models = list(log_k_meso_free ~ pH))
-illparms(sforb_pH_2)
+
sforb_pH_2 <- update(sforb_pH,
+  no_random_effect = c("meso_free_0", "log_k_meso_free_bound", "log_k_meso_bound_free"),
+  covariate_models = list(log_k_meso_free ~ pH))
+illparms(sforb_pH_2)

The model comparison of the SFORB fits includes the refined model without covariate effect, and both versions of the SFORB fit with covariate effect.

-
-anova(f_saem_2[["SFORB", "const"]], sforb_pH, sforb_pH_2, test = TRUE)
+
anova(f_saem_2[["SFORB", "const"]], sforb_pH, sforb_pH_2, test = TRUE)
Data: 116 observations of 1 variable(s) grouped in 18 datasets
 
                              npar    AIC    BIC     Lik   Chisq Df Pr(>Chisq)  
-f_saem_2[["SFORB", "const"]]    7 783.40 789.63 -384.70                        
+f_saem_2[["SFORB", "const"]]    7 783.40 789.63 -384.70                        
 sforb_pH_2                      7 770.94 777.17 -378.47 12.4616  0             
 sforb_pH                        9 768.81 776.83 -375.41  6.1258  2    0.04675 *
 ---
-Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
+Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

The first model including pH influence is preferable based on information criteria and the likelihood ratio test. However, as it is not fully identifiable, the second model is selected.

-
-summary(sforb_pH_2)$confint_trans |> kable(digits = 2)
-
est. lower upper
meso_free_0
- +
summary(sforb_pH_2)$confint_trans |> kable(digits = 2)
+
+ + - + + @@ -2130,11 +2403,9 @@ not fully identifiable, the second model is selected.

est. lower upper
meso_free_0
-
-plot(sforb_pH_2)
-

-
-endpoints(sforb_pH_2)
+
plot(sforb_pH_2)
+

+
endpoints(sforb_pH_2)
$covariates
       pH
 50% 5.75
@@ -2150,8 +2421,7 @@ $SFORB
 $distimes
          DT50     DT90 DT50back DT50_meso_b1 DT50_meso_b2
 meso 16.86549 73.15824 22.02282     7.119554     26.33839
-
-endpoints(sforb_pH_2, covariates = c(pH = 7))
+
endpoints(sforb_pH_2, covariates = c(pH = 7))
$covariates
      pH
 User  7
@@ -2168,22 +2438,21 @@ $distimes
          DT50     DT90 DT50back DT50_meso_b1 DT50_meso_b2
 meso 7.932495 36.93311 11.11797     5.205671        18.26
-
-

HS -

-
-hs_pH <- saem(f_sep_const["HS", ], no_random_effect = c("meso_0"),
-  covariates = pH,
-  covariate_models = list(log_k1 ~ pH, log_k2 ~ pH, log_tb ~ pH))
-
-summary(hs_pH)$confint_trans |> kable(digits = 2)
- - +
+

HS

+
hs_pH <- saem(f_sep_const["HS", ], no_random_effect = c("meso_0"),
+  covariates = pH,
+  covariate_models = list(log_k1 ~ pH, log_k2 ~ pH, log_tb ~ pH))
+
summary(hs_pH)$confint_trans |> kable(digits = 2)
+
+ + - + + @@ -2253,39 +2522,37 @@ meso 7.932495 36.93311 11.11797 5.205671 18.26
est. lower upper
meso_0
-
-illparms(hs_pH)
-
[1] "sd(log_tb)"      "beta_pH(log_tb)"
+
illparms(hs_pH)
+
[1] "sd(log_tb)"      "beta_pH(log_tb)"

According to the output of the illparms function, the random effect on the break time tb cannot reliably be quantified, neither can the influence of soil pH on tb. The fit is repeated without the corresponding covariate model, and no ill-defined parameters remain.

-
-hs_pH_2 <- update(hs_pH, covariate_models = list(log_k1 ~ pH, log_k2 ~ pH))
-illparms(hs_pH_2)
+
hs_pH_2 <- update(hs_pH, covariate_models = list(log_k1 ~ pH, log_k2 ~ pH))
+illparms(hs_pH_2)

Model comparison confirms that this model is preferable to the fit without covariate influence, and also to the first version with covariate influence.

-
-anova(f_saem_2[["HS", "const"]], hs_pH, hs_pH_2, test = TRUE)
+
anova(f_saem_2[["HS", "const"]], hs_pH, hs_pH_2, test = TRUE)
Data: 116 observations of 1 variable(s) grouped in 18 datasets
 
                           npar    AIC    BIC     Lik  Chisq Df Pr(>Chisq)    
-f_saem_2[["HS", "const"]]    8 780.08 787.20 -382.04                         
+f_saem_2[["HS", "const"]]    8 780.08 787.20 -382.04                         
 hs_pH_2                     10 766.47 775.37 -373.23 17.606  2  0.0001503 ***
 hs_pH                       11 769.80 779.59 -373.90  0.000  1  1.0000000    
 ---
-Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
-
-summary(hs_pH_2)$confint_trans |> kable(digits = 2)
- - +Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 +
summary(hs_pH_2)$confint_trans |> kable(digits = 2)
+
+ + - + + @@ -2349,11 +2616,9 @@ Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
est. lower upper
meso_0
-
-plot(hs_pH_2)
-

-
-endpoints(hs_pH_2)
+
plot(hs_pH_2)
+

+
endpoints(hs_pH_2)
$covariates
       pH
 50% 5.75
@@ -2361,8 +2626,7 @@ Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
$distimes DT50 DT90 DT50back DT50_k1 DT50_k2 meso 14.68725 82.45287 24.82079 14.68725 29.29299 -
-endpoints(hs_pH_2, covariates = c(pH = 7))
+
endpoints(hs_pH_2, covariates = c(pH = 7))
$covariates
      pH
 User  7
@@ -2371,13 +2635,11 @@ $distimes
          DT50     DT90 DT50back  DT50_k1  DT50_k2
 meso 8.298536 38.85371 11.69613 8.298536 15.71561
-
-

Comparison across parent models -

+
+

Comparison across parent models

After model reduction for all models with pH influence, they are compared with each other.

-
-anova(sfo_pH, fomc_pH_2, dfop_pH_2, dfop_pH_4, sforb_pH_2, hs_pH_2)
+
anova(sfo_pH, fomc_pH_2, dfop_pH_2, dfop_pH_4, sforb_pH_2, hs_pH_2)
Data: 116 observations of 1 variable(s) grouped in 18 datasets
 
            npar    AIC    BIC     Lik
@@ -2392,8 +2654,7 @@ hs_pH_2      10 766.47 775.37 -373.23
selected as the best fit.

The endpoints resulting from this model are listed below. Please refer to the Appendix for a detailed listing.

-
-endpoints(dfop_pH_2)
+
endpoints(dfop_pH_2)
$covariates
       pH
 50% 5.75
@@ -2401,8 +2662,7 @@ refer to the Appendix for a detailed listing.

 $distimes
          DT50     DT90 DT50back  DT50_k1  DT50_k2
 meso 18.36876 73.51841 22.13125 4.191901 23.98672
-
-endpoints(dfop_pH_2, covariates = c(pH = 7))
+
endpoints(dfop_pH_2, covariates = c(pH = 7))
$covariates
      pH
 User  7
@@ -2412,35 +2672,29 @@ $distimes
 meso 8.346428 28.34437 8.532507 4.191901 8.753618
-
-

Conclusions -

+
+

Conclusions

These evaluations demonstrate that covariate effects can be included for all types of parent degradation models. These models can then be further refined to make them fully identifiable.

-
-

Appendix -

-
-

Hierarchical fit listings -

-
-

Fits without covariate effects -

+
+

Appendix

+
+

Hierarchical fit listings

+
+

Fits without covariate effects

-
-

Fits with covariate effects -

+
+

Fits with covariate effects

-
-

Session info -

-
R version 4.3.2 (2023-10-31)
-Platform: x86_64-pc-linux-gnu (64-bit)
+

+
Session info

+
R version 4.4.2 (2024-10-31)
+Platform: x86_64-pc-linux-gnu
 Running under: Debian GNU/Linux 12 (bookworm)
 
 Matrix products: default
@@ -2463,53 +2717,74 @@ attached base packages:
 [8] base     
 
 other attached packages:
-[1] saemix_3.2 npde_3.3   knitr_1.42 mkin_1.2.6
+[1] saemix_3.3      npde_3.5        knitr_1.49      mkin_1.2.9     
+[5] rmarkdown_2.29  nvimcom_0.9-167
 
 loaded via a namespace (and not attached):
- [1] sass_0.4.6        utf8_1.2.3        generics_0.1.3    stringi_1.7.12   
- [5] lattice_0.21-8    digest_0.6.31     magrittr_2.0.3    evaluate_0.21    
- [9] grid_4.3.2        fastmap_1.1.1     rprojroot_2.0.3   jsonlite_1.8.4   
-[13] DBI_1.1.3         mclust_6.0.0      gridExtra_2.3     purrr_1.0.1      
-[17] fansi_1.0.4       scales_1.2.1      textshaping_0.3.6 jquerylib_0.1.4  
-[21] cli_3.6.1         rlang_1.1.1       munsell_0.5.0     cachem_1.0.8     
-[25] yaml_2.3.7        tools_4.3.2       memoise_2.0.1     dplyr_1.1.2      
-[29] colorspace_2.1-0  ggplot2_3.4.2     vctrs_0.6.2       R6_2.5.1         
-[33] zoo_1.8-12        lifecycle_1.0.3   stringr_1.5.0     fs_1.6.2         
-[37] MASS_7.3-60       ragg_1.2.5        pkgconfig_2.0.3   desc_1.4.2       
-[41] pkgdown_2.0.7     bslib_0.4.2       pillar_1.9.0      gtable_0.3.3     
-[45] glue_1.6.2        systemfonts_1.0.4 xfun_0.39         tibble_3.2.1     
-[49] lmtest_0.9-40     tidyselect_1.2.0  htmltools_0.5.5   nlme_3.1-163     
-[53] rmarkdown_2.21    compiler_4.3.2   

+ [1] gtable_0.3.6      jsonlite_1.8.9    dplyr_1.1.4       compiler_4.4.2   
+ [5] tidyselect_1.2.1  colorout_1.3-2    gridExtra_2.3     jquerylib_0.1.4  
+ [9] scales_1.3.0      readxl_1.4.3      yaml_2.3.10       fastmap_1.2.0    
+[13] lattice_0.22-6    ggplot2_3.5.1     R6_2.5.1          generics_0.1.3   
+[17] lmtest_0.9-40     MASS_7.3-61       tibble_3.2.1      munsell_0.5.1    
+[21] bslib_0.8.0       pillar_1.9.0      rlang_1.1.4       utf8_1.2.4       
+[25] cachem_1.1.0      xfun_0.49         sass_0.4.9        cli_3.6.3        
+[29] magrittr_2.0.3    digest_0.6.37     grid_4.4.2        mclust_6.1.1     
+[33] lifecycle_1.0.4   nlme_3.1-166      vctrs_0.6.5       evaluate_1.0.1   
+[37] glue_1.8.0        cellranger_1.1.0  codetools_0.2-20  zoo_1.8-12       
+[41] fansi_1.0.6       colorspace_2.1-1  tools_4.4.2       pkgconfig_2.0.3  
+[45] htmltools_0.5.8.1
-
-

Hardware info -

+
+

Hardware info

CPU model: AMD Ryzen 9 7950X 16-Core Processor
-
MemTotal:       64928100 kB
-
+
MemTotal:       64927788 kB
-
-
-

-

Developed by Johannes Ranke.

-
-
-

-

Site built with pkgdown 2.0.7.

-
-
+ + + + + + + - - + + - + diff --git a/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-14-1.png b/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-14-1.png index 863a48bd..719bf0e9 100644 Binary files a/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-14-1.png and b/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-14-1.png differ diff --git a/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-19-1.png b/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-19-1.png index 256b2b68..6afcac48 100644 Binary files a/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-19-1.png and b/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-19-1.png differ diff --git a/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-25-1.png b/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-25-1.png index 59011020..50253fb1 100644 Binary files a/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-25-1.png and b/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-25-1.png differ diff --git a/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-30-1.png b/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-30-1.png index f427bc39..c8b77724 100644 Binary files a/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-30-1.png and b/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-30-1.png differ diff --git a/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-8-1.png b/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-8-1.png index 7c3b460b..8fa204a3 100644 Binary files a/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-8-1.png and b/docs/articles/prebuilt/2023_mesotrione_parent_files/figure-html/unnamed-chunk-8-1.png differ diff --git a/docs/articles/twa.html b/docs/articles/twa.html index 5452a5e5..19bc4761 100644 --- a/docs/articles/twa.html +++ b/docs/articles/twa.html @@ -5,86 +5,71 @@ - Calculation of time weighted average concentrations with mkin • mkin - - - - - - + + + + Skip to contents - - 

 print(p9a)
@@ -454,7 +440,7 @@ suggest a simple exponential decline.

## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
## The half-life obtained from the IORE model may be used
-plot(p9b)
+plot(p9b)

 print(p9b)
@@ -512,7 +498,7 @@ in PestDF and g in mkin. In mkin, it is restricted to the interval from 
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
## The half-life obtained from the IORE model may be used
-plot(p10)
+plot(p10)

 print(p10)
@@ -572,7 +558,7 @@ difference in IORE model parameters between PestDF and mkin.

## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
## The half-life obtained from the IORE model may be used
-plot(p11)
+plot(p11)

 print(p11)
@@ -638,7 +624,7 @@ overparameterisation.

## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
## The half-life obtained from the IORE model may be used
-plot(p12a)
+plot(p12a) 

 print(p12a)
@@ -690,15 +676,14 @@ overparameterisation.

## Warning in qt(alpha/2, rdf): NaNs produced
## Warning in qt(1 - alpha/2, rdf): NaNs produced
## Warning in pt(abs(tval), rdf, lower.tail = FALSE): NaNs produced
-
## Warning in sqrt(1/diag(V)): NaNs produced
-
## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result
-## is doubtful
+
## Warning in cov2cor(ans$covar): diag(V) had non-positive or NA entries; the
+## non-finite result may be dubious
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
## The half-life obtained from the IORE model may be used
-
-plot(p12b)
+
+plot(p12b)

-
+
 print(p12b)

 
## Sums of squares:
 ##      SFO     IORE     DFOP 
@@ -742,14 +727,14 @@ overparameterisation.

 

 
Example on page 13
 

-
+
 p13 <- nafta(NAFTA_SOP_Attachment[["p13"]])

 
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c

 
## The half-life obtained from the IORE model may be used

-
-plot(p13)

+
+plot(p13)

 

-
+
 print(p13)

 
## Sums of squares:
 ##      SFO     IORE     DFOP 
@@ -794,18 +779,17 @@ overparameterisation.

 

 
DT50 not observed in the study and DFOP problems in PestDF
 

-
+
 p14 <- nafta(NAFTA_SOP_Attachment[["p14"]])

 
## Warning in sqrt(diag(covar)): NaNs produced

-
## Warning in sqrt(1/diag(V)): NaNs produced

-
## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result
-## is doubtful

+
## Warning in cov2cor(ans$covar): diag(V) had non-positive or NA entries; the
+## non-finite result may be dubious

 
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c

 
## The half-life obtained from the IORE model may be used

-
-plot(p14)

+
+plot(p14)

 

-
+
 print(p14)

 
## Sums of squares:
 ##      SFO     IORE     DFOP 
@@ -852,18 +836,17 @@ same results in mkin and PestDF.

 

 
N is less than 1 and DFOP fraction parameter is below zero
 

-
+
 p15a <- nafta(NAFTA_SOP_Attachment[["p15a"]])

 
## Warning in sqrt(diag(covar)): NaNs produced

-
## Warning in sqrt(1/diag(V)): NaNs produced

-
## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result
-## is doubtful

+
## Warning in cov2cor(ans$covar): diag(V) had non-positive or NA entries; the
+## non-finite result may be dubious

 
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c

 
## The half-life obtained from the IORE model may be used

-
-plot(p15a)

+
+plot(p15a)

 

-
+
 print(p15a)

 
## Sums of squares:
 ##      SFO     IORE     DFOP 
@@ -903,16 +886,16 @@ same results in mkin and PestDF.

 ## 
 ## Representative half-life:
 ## [1] 41.33

-
+
 p15b <- nafta(NAFTA_SOP_Attachment[["p15b"]])

 
## Warning in summary.mkinfit(x): Could not calculate correlation; no covariance
 ## matrix

 
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c

 
## The half-life obtained from the IORE model may be used

-
-plot(p15b)

+
+plot(p15b)

 

-
+
 print(p15b)

 
## Sums of squares:
 ##       SFO      IORE      DFOP 
@@ -960,16 +943,16 @@ mkin and PestDF.

 

 
The DFOP fraction parameter is greater than 1
 

-
+
 p16 <- nafta(NAFTA_SOP_Attachment[["p16"]])

 
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c

 
## The representative half-life of the IORE model is longer than the one corresponding

 
## to the terminal degradation rate found with the DFOP model.

 
## The representative half-life obtained from the DFOP model may be used

-
-plot(p16)

+
+plot(p16)

 

-
+
 print(p16)

 
## Sums of squares:
 ##      SFO     IORE     DFOP 
@@ -1010,10 +993,12 @@ mkin and PestDF.

 ## Representative half-life:
 ## [1] 8.93

 
In PestDF, the DFOP fit seems to have stuck in a local minimum, as
-mkin finds a solution with a much lower \(\chi^2\) error level. As the half-life from
-the slower rate constant of the DFOP model is larger than the IORE
-derived half-life, the NAFTA recommendation obtained with mkin is to use
-the DFOP representative half-life of 8.9 days.

+mkin finds a solution with a much lower
+χ2\chi^2
+error level. As the half-life from the slower rate constant of the DFOP
+model is larger than the IORE derived half-life, the NAFTA
+recommendation obtained with mkin is to use the DFOP representative
+half-life of 8.9 days.

 

 

 
Conclusions
@@ -1038,28 +1023,26 @@ Pesticide Degradation.” 

 
 
 
     
 

 
-  
 
-  
+
+
 
   
 
diff --git a/docs/articles/web_only/NAFTA_examples_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/articles/web_only/NAFTA_examples_files/accessible-code-block-0.0.1/empty-anchor.js
deleted file mode 100644
index ca349fd6..00000000
--- a/docs/articles/web_only/NAFTA_examples_files/accessible-code-block-0.0.1/empty-anchor.js
+++ /dev/null
@@ -1,15 +0,0 @@
-// Hide empty  tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
-// v0.0.1
-// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
-
-document.addEventListener('DOMContentLoaded', function() {
-  const codeList = document.getElementsByClassName("sourceCode");
-  for (var i = 0; i < codeList.length; i++) {
-    var linkList = codeList[i].getElementsByTagName('a');
-    for (var j = 0; j < linkList.length; j++) {
-      if (linkList[j].innerHTML === "") {
-        linkList[j].setAttribute('aria-hidden', 'true');
-      }
-    }
-  }
-});
diff --git a/docs/articles/web_only/NAFTA_examples_files/header-attrs-2.6/header-attrs.js b/docs/articles/web_only/NAFTA_examples_files/header-attrs-2.6/header-attrs.js
deleted file mode 100644
index dd57d92e..00000000
--- a/docs/articles/web_only/NAFTA_examples_files/header-attrs-2.6/header-attrs.js
+++ /dev/null
@@ -1,12 +0,0 @@
-// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
-// be compatible with the behavior of Pandoc < 2.8).
-document.addEventListener('DOMContentLoaded', function(e) {
-  var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
-  var i, h, a;
-  for (i = 0; i < hs.length; i++) {
-    h = hs[i];
-    if (!/^h[1-6]$/i.test(h.tagName)) continue;  // it should be a header h1-h6
-    a = h.attributes;
-    while (a.length > 0) h.removeAttribute(a[0].name);
-  }
-});
diff --git a/docs/articles/web_only/NAFTA_examples_files/header-attrs-2.7/header-attrs.js b/docs/articles/web_only/NAFTA_examples_files/header-attrs-2.7/header-attrs.js
deleted file mode 100644
index dd57d92e..00000000
--- a/docs/articles/web_only/NAFTA_examples_files/header-attrs-2.7/header-attrs.js
+++ /dev/null
@@ -1,12 +0,0 @@
-// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
-// be compatible with the behavior of Pandoc < 2.8).
-document.addEventListener('DOMContentLoaded', function(e) {
-  var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
-  var i, h, a;
-  for (i = 0; i < hs.length; i++) {
-    h = hs[i];
-    if (!/^h[1-6]$/i.test(h.tagName)) continue;  // it should be a header h1-h6
-    a = h.attributes;
-    while (a.length > 0) h.removeAttribute(a[0].name);
-  }
-});
diff --git a/docs/articles/web_only/benchmarks.html b/docs/articles/web_only/benchmarks.html
index 17c2f8d8..3566be42 100644
--- a/docs/articles/web_only/benchmarks.html
+++ b/docs/articles/web_only/benchmarks.html
@@ -5,86 +5,71 @@
 
 
 
-
 Benchmark timings for mkin • mkin
 
-
-
-
-
-
-
+
+
+
+
 
 
     Skip to contents
-    
 
-    

 
 
 
     

-  

-
Developed by Johannes Ranke.

+  
Developed by Johannes Ranke.

 

 
 

-  

-
Site built with pkgdown 2.0.7.

+  
Site built with pkgdown 2.1.1.

 

 
     

 

 
-  
 
-  
+
+
 
   
 
diff --git a/docs/articles/web_only/benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/articles/web_only/benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js
deleted file mode 100644
index ca349fd6..00000000
--- a/docs/articles/web_only/benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js
+++ /dev/null
@@ -1,15 +0,0 @@
-// Hide empty  tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
-// v0.0.1
-// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
-
-document.addEventListener('DOMContentLoaded', function() {
-  const codeList = document.getElementsByClassName("sourceCode");
-  for (var i = 0; i < codeList.length; i++) {
-    var linkList = codeList[i].getElementsByTagName('a');
-    for (var j = 0; j < linkList.length; j++) {
-      if (linkList[j].innerHTML === "") {
-        linkList[j].setAttribute('aria-hidden', 'true');
-      }
-    }
-  }
-});
diff --git a/docs/articles/web_only/benchmarks_files/header-attrs-2.6/header-attrs.js b/docs/articles/web_only/benchmarks_files/header-attrs-2.6/header-attrs.js
deleted file mode 100644
index dd57d92e..00000000
--- a/docs/articles/web_only/benchmarks_files/header-attrs-2.6/header-attrs.js
+++ /dev/null
@@ -1,12 +0,0 @@
-// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
-// be compatible with the behavior of Pandoc < 2.8).
-document.addEventListener('DOMContentLoaded', function(e) {
-  var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
-  var i, h, a;
-  for (i = 0; i < hs.length; i++) {
-    h = hs[i];
-    if (!/^h[1-6]$/i.test(h.tagName)) continue;  // it should be a header h1-h6
-    a = h.attributes;
-    while (a.length > 0) h.removeAttribute(a[0].name);
-  }
-});
diff --git a/docs/articles/web_only/benchmarks_files/header-attrs-2.7/header-attrs.js b/docs/articles/web_only/benchmarks_files/header-attrs-2.7/header-attrs.js
deleted file mode 100644
index dd57d92e..00000000
--- a/docs/articles/web_only/benchmarks_files/header-attrs-2.7/header-attrs.js
+++ /dev/null
@@ -1,12 +0,0 @@
-// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
-// be compatible with the behavior of Pandoc < 2.8).
-document.addEventListener('DOMContentLoaded', function(e) {
-  var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
-  var i, h, a;
-  for (i = 0; i < hs.length; i++) {
-    h = hs[i];
-    if (!/^h[1-6]$/i.test(h.tagName)) continue;  // it should be a header h1-h6
-    a = h.attributes;
-    while (a.length > 0) h.removeAttribute(a[0].name);
-  }
-});
diff --git a/docs/articles/web_only/compiled_models.html b/docs/articles/web_only/compiled_models.html
index 210ddaf7..bbf6e897 100644
--- a/docs/articles/web_only/compiled_models.html
+++ b/docs/articles/web_only/compiled_models.html
@@ -5,86 +5,71 @@
 
 
 
-
 Performance benefit by using compiled model definitions in mkin • mkin
 
-
-
-
-
-
-
+
+
+
+
 
 
     Skip to contents
-    
 
-    

 
##                    test replications relative elapsed
-## 4            analytical            1    1.000   0.109
-## 3     deSolve, compiled            1    1.284   0.140
-## 2      Eigenvalue based            1    1.670   0.182
-## 1 deSolve, not compiled            1   21.927   2.390

+## 4            analytical            1    1.000   0.105
+## 3     deSolve, compiled            1    1.333   0.140
+## 2      Eigenvalue based            1    1.667   0.175
+## 1 deSolve, not compiled            1   22.486   2.361

 
We see that using the compiled model is by more than a factor of 10
 faster than using deSolve without compiled code.

 

@@ -209,38 +195,36 @@ compiled code is available.

 }

 
## Temporary DLL for differentials generated and loaded

 
##                    test replications relative elapsed
-## 2     deSolve, compiled            1    1.000   0.181
-## 1 deSolve, not compiled            1   23.646   4.280

+## 2     deSolve, compiled            1    1.000   0.175
+## 1 deSolve, not compiled            1   23.937   4.189

 
Here we get a performance benefit of a factor of 24 using the version
 of the differential equation model compiled from C code!

-
This vignette was built with mkin 1.2.6 on

-
## R version 4.3.2 (2023-10-31)
-## Platform: x86_64-pc-linux-gnu (64-bit)
+
This vignette was built with mkin 1.2.9 on

+
## R version 4.4.2 (2024-10-31)
+## Platform: x86_64-pc-linux-gnu
 ## Running under: Debian GNU/Linux 12 (bookworm)

 
## CPU model: AMD Ryzen 9 7950X 16-Core Processor

 

-  

 
 
 
     

-  

-
Developed by Johannes Ranke.

+  
Developed by Johannes Ranke.

 

 
 

-  

-
Site built with pkgdown 2.0.7.

+  
Site built with pkgdown 2.1.1.

 

 
     

 

 
-  
 
-  
+
+
 
   
 
diff --git a/docs/articles/web_only/compiled_models_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/articles/web_only/compiled_models_files/accessible-code-block-0.0.1/empty-anchor.js
deleted file mode 100644
index ca349fd6..00000000
--- a/docs/articles/web_only/compiled_models_files/accessible-code-block-0.0.1/empty-anchor.js
+++ /dev/null
@@ -1,15 +0,0 @@
-// Hide empty  tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
-// v0.0.1
-// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
-
-document.addEventListener('DOMContentLoaded', function() {
-  const codeList = document.getElementsByClassName("sourceCode");
-  for (var i = 0; i < codeList.length; i++) {
-    var linkList = codeList[i].getElementsByTagName('a');
-    for (var j = 0; j < linkList.length; j++) {
-      if (linkList[j].innerHTML === "") {
-        linkList[j].setAttribute('aria-hidden', 'true');
-      }
-    }
-  }
-});
diff --git a/docs/articles/web_only/compiled_models_files/header-attrs-2.6/header-attrs.js b/docs/articles/web_only/compiled_models_files/header-attrs-2.6/header-attrs.js
deleted file mode 100644
index dd57d92e..00000000
--- a/docs/articles/web_only/compiled_models_files/header-attrs-2.6/header-attrs.js
+++ /dev/null
@@ -1,12 +0,0 @@
-// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
-// be compatible with the behavior of Pandoc < 2.8).
-document.addEventListener('DOMContentLoaded', function(e) {
-  var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
-  var i, h, a;
-  for (i = 0; i < hs.length; i++) {
-    h = hs[i];
-    if (!/^h[1-6]$/i.test(h.tagName)) continue;  // it should be a header h1-h6
-    a = h.attributes;
-    while (a.length > 0) h.removeAttribute(a[0].name);
-  }
-});
diff --git a/docs/articles/web_only/dimethenamid_2018.html b/docs/articles/web_only/dimethenamid_2018.html
index 4221ba07..5d39704d 100644
--- a/docs/articles/web_only/dimethenamid_2018.html
+++ b/docs/articles/web_only/dimethenamid_2018.html
@@ -5,86 +5,71 @@
 
 
 
-
 Example evaluations of the dimethenamid data from 2018 • mkin
 
-
-
-
-
-
-
+
+
+
+
 
 
     Skip to contents
-    
 
-    

 

 
Using biexponential decline (DFOP) results in a slightly more random
 scatter of the residuals:

 
-plot(mixed(f_parent_mkin_const["DFOP", ]))

+plot(mixed(f_parent_mkin_const["DFOP", ]))

 

 
The population curve (bold line) in the above plot results from
 taking the mean of the individual transformed parameters, i.e. of log k1
@@ -201,7 +187,7 @@ dominates the average. This is alleviated if only rate constants that
 pass the t-test for significant difference from zero (on the
 untransformed scale) are considered in the averaging:

 
-plot(mixed(f_parent_mkin_const["DFOP", ]), test_log_parms = TRUE)

+plot(mixed(f_parent_mkin_const["DFOP", ]), test_log_parms = TRUE)

While this is visually much more satisfactory, such an average procedure could introduce a bias, as not all results from the individual @@ -213,7 +199,7 @@ degradation model and the error model (see below).

predicted residues is reduced by using the two-component error model:

-plot(mixed(f_parent_mkin_tc["DFOP", ]), test_log_parms = TRUE)
+plot(mixed(f_parent_mkin_tc["DFOP", ]), test_log_parms = TRUE)

However, note that in the case of using this error model, the fits to the Flaach and BBA 2.3 datasets appear to be ill-defined, indicated by @@ -303,7 +289,7 @@ effects does not improve the fits.

The selected model (DFOP with two-component error) fitted to the data assuming no correlations between random effects is shown below.

-plot(f_parent_nlme_dfop_tc)
+plot(f_parent_nlme_dfop_tc)

@@ -320,8 +306,17 @@ implemented in the saemix package, the convergence plots need to be manually checked for every fit. We define control settings that work well for all the parent data fits shown in this vignette.

-library(saemix)
-saemix_control <- saemixControl(nbiter.saemix = c(800, 300), nb.chains = 15,
+library(saemix)
+
Loading required package: npde
+
Package saemix, version 3.3, March 2024
+  please direct bugs, questions and feedback to emmanuelle.comets@inserm.fr
+

+Attaching package: 'saemix'
+
The following objects are masked from 'package:npde':
+
+    kurtosis, skewness
+
+saemix_control <- saemixControl(nbiter.saemix = c(800, 300), nb.chains = 15,
     print = FALSE, save = FALSE, save.graphs = FALSE, displayProgress = FALSE)
 saemix_control_moreiter <- saemixControl(nbiter.saemix = c(1600, 300), nb.chains = 15,
     print = FALSE, save = FALSE, save.graphs = FALSE, displayProgress = FALSE)
@@ -329,7 +324,7 @@ well for all the parent data fits shown in this vignette.

     print = FALSE, save = FALSE, save.graphs = FALSE, displayProgress = FALSE)

The convergence plot for the SFO model using constant variance is shown below.

-
+
 f_parent_saemix_sfo_const <- mkin::saem(f_parent_mkin_const["SFO", ], quiet = TRUE,
   control = saemix_control, transformations = "saemix")
 plot(f_parent_saemix_sfo_const$so, plot.type = "convergence")

@@ -337,19 +332,19 @@ shown below.

 
Obviously the selected number of iterations is sufficient to reach
 convergence. This can also be said for the SFO fit using the
 two-component error model.

-
+
 f_parent_saemix_sfo_tc <- mkin::saem(f_parent_mkin_tc["SFO", ], quiet = TRUE,
   control = saemix_control, transformations = "saemix")
 plot(f_parent_saemix_sfo_tc$so, plot.type = "convergence")

 

 
When fitting the DFOP model with constant variance (see below),
 parameter convergence is not as unambiguous.

-
+
 f_parent_saemix_dfop_const <- mkin::saem(f_parent_mkin_const["DFOP", ], quiet = TRUE,
   control = saemix_control, transformations = "saemix")
 plot(f_parent_saemix_dfop_const$so, plot.type = "convergence")

 

-
+
 print(f_parent_saemix_dfop_const)

 
Kinetic nonlinear mixed-effects model fit by SAEM
 Structural model:
@@ -385,14 +380,14 @@ this model.

 also observe that the estimated variance of k2 becomes very small, while
 being ill-defined, as illustrated by the excessive confidence interval
 of SD.k2.

-
+
 f_parent_saemix_dfop_tc <- mkin::saem(f_parent_mkin_tc["DFOP", ], quiet = TRUE,
   control = saemix_control, transformations = "saemix")
 f_parent_saemix_dfop_tc_moreiter <- mkin::saem(f_parent_mkin_tc["DFOP", ], quiet = TRUE,
   control = saemix_control_moreiter, transformations = "saemix")
 plot(f_parent_saemix_dfop_tc$so, plot.type = "convergence")

 

-
+
 print(f_parent_saemix_dfop_tc)

 
Kinetic nonlinear mixed-effects model fit by SAEM
 Structural model:
@@ -413,11 +408,11 @@ DMTA_0    98.24165  96.29190 100.1914
 k1         0.06421   0.03352   0.0949
 k2         0.00866   0.00617   0.0111
 g          0.95340   0.91218   0.9946
-a.1        1.06463   0.86503   1.2642
-b.1        0.02964   0.02259   0.0367
-SD.DMTA_0  2.03611   0.40416   3.6681
+a.1        1.06463   0.87979   1.2495
+b.1        0.02964   0.02266   0.0366
+SD.DMTA_0  2.03611   0.40361   3.6686
 SD.k1      0.59534   0.25692   0.9338
-SD.k2      0.00042 -73.01372  73.0146
+SD.k2      0.00042 -73.00540  73.0062
 SD.g       1.04234   0.37189   1.7128

 
Doubling the number of iterations in the first phase of the algorithm
 leads to a slightly lower likelihood, and therefore to slightly higher
@@ -434,7 +429,7 @@ message.

 
The four combinations (SFO/const, SFO/tc, DFOP/const and DFOP/tc) and
 the version with increased iterations can be compared using the model
 comparison function of the saemix package:

-
+
 AIC_parent_saemix <- saemix::compare.saemix(
   f_parent_saemix_sfo_const$so,
   f_parent_saemix_sfo_tc$so,
@@ -442,7 +437,7 @@ comparison function of the saemix package:

   f_parent_saemix_dfop_tc$so,
   f_parent_saemix_dfop_tc_moreiter$so)

 
Likelihoods calculated by importance sampling

-
+
 rownames(AIC_parent_saemix) <- c(
   "SFO const", "SFO tc", "DFOP const", "DFOP tc", "DFOP tc more iterations")
 print(AIC_parent_saemix)

@@ -456,7 +451,7 @@ DFOP tc more iterations 665.85 663.76

 algorithms implemented in saemix, the likelihood from Gaussian
 quadrature is added to the best fit, and the AIC values obtained from
 the three methods are compared.

-
+
 f_parent_saemix_dfop_tc$so <-
   saemix::llgq.saemix(f_parent_saemix_dfop_tc$so)
 AIC_parent_saemix_methods <- c(
@@ -480,7 +475,7 @@ iterations makes a lot of difference. When using the LAPACK version
 coming with Debian Bullseye, the AIC based on Gaussian quadrature is
 almost the same as the one obtained with the other methods, also when
 using defaults for the fit.

-
+
 f_parent_saemix_dfop_tc_defaults <- mkin::saem(f_parent_mkin_tc["DFOP", ])
 f_parent_saemix_dfop_tc_defaults$so <-
   saemix::llgq.saemix(f_parent_saemix_dfop_tc_defaults$so)
@@ -500,7 +495,7 @@ using defaults for the fit.

 
The following table gives the AIC values obtained with both backend
 packages using the same control parameters (800 iterations burn-in, 300
 iterations second phase, 15 chains).

-
+
 AIC_all <- data.frame(
   check.names = FALSE,
   "Degradation model" = c("SFO", "SFO", "DFOP", "DFOP"),
@@ -511,7 +506,7 @@ iterations second phase, 15 chains).

   saemix_is = sapply(list(f_parent_saemix_sfo_const$so, f_parent_saemix_sfo_tc$so,
     f_parent_saemix_dfop_const$so, f_parent_saemix_dfop_tc$so), AIC, method = "is")
 )
-kable(AIC_all)

+kable(AIC_all)

 
@@ -574,10 +569,10 @@ satisfactory precision.

 
Session Info
 

-
+
-
R version 4.3.2 (2023-10-31)
-Platform: x86_64-pc-linux-gnu (64-bit)
+
R version 4.4.2 (2024-10-31)
+Platform: x86_64-pc-linux-gnu
 Running under: Debian GNU/Linux 12 (bookworm)
 
 Matrix products: default
@@ -599,23 +594,22 @@ attached base packages:
 [1] stats     graphics  grDevices utils     datasets  methods   base     
 
 other attached packages:
-[1] saemix_3.2   npde_3.3     nlme_3.1-163 mkin_1.2.6   knitr_1.42  
+[1] saemix_3.3   npde_3.5     nlme_3.1-166 mkin_1.2.9   knitr_1.49  
 
 loaded via a namespace (and not attached):
- [1] sass_0.4.6        utf8_1.2.3        generics_0.1.3    stringi_1.7.12   
- [5] lattice_0.21-8    digest_0.6.31     magrittr_2.0.3    evaluate_0.21    
- [9] grid_4.3.2        fastmap_1.1.1     rprojroot_2.0.3   jsonlite_1.8.4   
-[13] DBI_1.1.3         mclust_6.0.0      gridExtra_2.3     purrr_1.0.1      
-[17] fansi_1.0.4       scales_1.2.1      codetools_0.2-19  textshaping_0.3.6
-[21] jquerylib_0.1.4   cli_3.6.1         rlang_1.1.1       munsell_0.5.0    
-[25] cachem_1.0.8      yaml_2.3.7        tools_4.3.2       parallel_4.3.2   
-[29] memoise_2.0.1     dplyr_1.1.2       colorspace_2.1-0  ggplot2_3.4.2    
-[33] vctrs_0.6.2       R6_2.5.1          zoo_1.8-12        lifecycle_1.0.3  
-[37] stringr_1.5.0     fs_1.6.2          MASS_7.3-60       ragg_1.2.5       
-[41] pkgconfig_2.0.3   desc_1.4.2        pkgdown_2.0.7     bslib_0.4.2      
-[45] pillar_1.9.0      gtable_0.3.3      glue_1.6.2        systemfonts_1.0.4
-[49] highr_0.10        xfun_0.39         tibble_3.2.1      lmtest_0.9-40    
-[53] tidyselect_1.2.0  htmltools_0.5.5   rmarkdown_2.21    compiler_4.3.2   

+ [1] gtable_0.3.6      jsonlite_1.8.9    dplyr_1.1.4       compiler_4.4.2   
+ [5] tidyselect_1.2.1  parallel_4.4.2    gridExtra_2.3     jquerylib_0.1.4  
+ [9] systemfonts_1.1.0 scales_1.3.0      textshaping_0.4.1 yaml_2.3.10      
+[13] fastmap_1.2.0     lattice_0.22-6    ggplot2_3.5.1     R6_2.5.1         
+[17] generics_0.1.3    lmtest_0.9-40     MASS_7.3-61       htmlwidgets_1.6.4
+[21] tibble_3.2.1      desc_1.4.3        munsell_0.5.1     bslib_0.8.0      
+[25] pillar_1.9.0      rlang_1.1.4       utf8_1.2.4        cachem_1.1.0     
+[29] xfun_0.49         fs_1.6.5          sass_0.4.9        cli_3.6.3        
+[33] pkgdown_2.1.1     magrittr_2.0.3    digest_0.6.37     grid_4.4.2       
+[37] mclust_6.1.1      lifecycle_1.0.4   vctrs_0.6.5       evaluate_1.0.1   
+[41] glue_1.8.0        codetools_0.2-20  ragg_1.3.3        zoo_1.8-12       
+[45] fansi_1.0.6       colorspace_2.1-1  rmarkdown_2.29    pkgconfig_2.0.3  
+[49] tools_4.4.2       htmltools_0.5.8.1

 

 

 
References
@@ -640,28 +634,26 @@ November 2017.” 

 
 
 
     
 

 
-  
 
-  
+
+
 
   
diff --git a/docs/articles/web_only/dimethenamid_2018_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/articles/web_only/dimethenamid_2018_files/accessible-code-block-0.0.1/empty-anchor.js
deleted file mode 100644
index ca349fd6..00000000
--- a/docs/articles/web_only/dimethenamid_2018_files/accessible-code-block-0.0.1/empty-anchor.js
+++ /dev/null
@@ -1,15 +0,0 @@
-// Hide empty  tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
-// v0.0.1
-// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
-
-document.addEventListener('DOMContentLoaded', function() {
-  const codeList = document.getElementsByClassName("sourceCode");
-  for (var i = 0; i < codeList.length; i++) {
-    var linkList = codeList[i].getElementsByTagName('a');
-    for (var j = 0; j < linkList.length; j++) {
-      if (linkList[j].innerHTML === "") {
-        linkList[j].setAttribute('aria-hidden', 'true');
-      }
-    }
-  }
-});
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diff --git a/docs/articles/web_only/dimethenamid_2018_files/figure-html/plot_parent_nlme-1.png b/docs/articles/web_only/dimethenamid_2018_files/figure-html/plot_parent_nlme-1.png
index a799b14c..6bcf3434 100644
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diff --git a/docs/articles/web_only/mkin_benchmarks.rda b/docs/articles/web_only/mkin_benchmarks.rda
deleted file mode 100644
index e26caf64..00000000
Binary files a/docs/articles/web_only/mkin_benchmarks.rda and /dev/null differ
diff --git a/docs/articles/web_only/multistart.html b/docs/articles/web_only/multistart.html
index 4438adc3..f6ab46de 100644
--- a/docs/articles/web_only/multistart.html
+++ b/docs/articles/web_only/multistart.html
@@ -5,86 +5,71 @@
 
 
 
-
 Short demo of the multistart method • mkin
 
-
-
-
-
-
-
+
+
+
+
 
 
     Skip to contents
-    
 
-    

 

 Degradation model
 
 

@@ -405,6 +391,16 @@ systems. All trademarks belong to their respective owners.

+
+
+
+
+
+
+
+
+
+

 

 
 2.406
 2.478
 
Ryzen 9 7950XLinux1.2.93.31.0861.9911.9492.411

 
 

 
Two-component error fits for SFO, DFOP, SFORB and HS.

@@ -520,6 +516,16 @@ systems. All trademarks belong to their respective owners.

 3.669
 3.153
 
+
+Ryzen 9 7950X
+Linux
+1.2.9
+3.3
+2.426
+3.196
+3.256
+3.322
+
 
 
 

@@ -617,6 +623,14 @@ systems. All trademarks belong to their respective owners.

 12.007
 286.757
 
+
+Ryzen 9 7950X
+Linux
+1.2.9
+3.3
+12.420
+289.338
+
 
 
 

@@ -703,32 +717,37 @@ systems. All trademarks belong to their respective owners.

 3.2
 480.577
 
+
+Ryzen 9 7950X
+Linux
+1.2.9
+3.3
+485.836
+
 
 
 

 

-  

 
 
 
     

-  

-
Developed by Johannes Ranke.

+  
Developed by Johannes Ranke.

 

 
 

-  

-
Site built with pkgdown 2.0.7.

+  
Site built with pkgdown 2.1.1.

 

 
     

 

 
-  
 
-  
+
+
 
   
 
diff --git a/docs/articles/web_only/saem_benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/articles/web_only/saem_benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js
deleted file mode 100644
index ca349fd6..00000000
--- a/docs/articles/web_only/saem_benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js
+++ /dev/null
@@ -1,15 +0,0 @@
-// Hide empty  tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
-// v0.0.1
-// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
-
-document.addEventListener('DOMContentLoaded', function() {
-  const codeList = document.getElementsByClassName("sourceCode");
-  for (var i = 0; i < codeList.length; i++) {
-    var linkList = codeList[i].getElementsByTagName('a');
-    for (var j = 0; j < linkList.length; j++) {
-      if (linkList[j].innerHTML === "") {
-        linkList[j].setAttribute('aria-hidden', 'true');
-      }
-    }
-  }
-});
diff --git a/docs/authors.html b/docs/authors.html
index 26399e08..d3cd2a75 100644
--- a/docs/authors.html
+++ b/docs/authors.html
@@ -1,5 +1,5 @@
 
-Authors and Citation • mkin
+Authors and Citation • mkin
     Skip to contents
 
 
diff --git a/docs/bootstrap-toc.css b/docs/bootstrap-toc.css
deleted file mode 100644
index 5a859415..00000000
--- a/docs/bootstrap-toc.css
+++ /dev/null
@@ -1,60 +0,0 @@
-/*!
- * Bootstrap Table of Contents v0.4.1 (http://afeld.github.io/bootstrap-toc/)
- * Copyright 2015 Aidan Feldman
- * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */
-
-/* modified from https://github.com/twbs/bootstrap/blob/94b4076dd2efba9af71f0b18d4ee4b163aa9e0dd/docs/assets/css/src/docs.css#L548-L601 */
-
-/* All levels of nav */
-nav[data-toggle='toc'] .nav > li > a {
-  display: block;
-  padding: 4px 20px;
-  font-size: 13px;
-  font-weight: 500;
-  color: #767676;
-}
-nav[data-toggle='toc'] .nav > li > a:hover,
-nav[data-toggle='toc'] .nav > li > a:focus {
-  padding-left: 19px;
-  color: #563d7c;
-  text-decoration: none;
-  background-color: transparent;
-  border-left: 1px solid #563d7c;
-}
-nav[data-toggle='toc'] .nav > .active > a,
-nav[data-toggle='toc'] .nav > .active:hover > a,
-nav[data-toggle='toc'] .nav > .active:focus > a {
-  padding-left: 18px;
-  font-weight: bold;
-  color: #563d7c;
-  background-color: transparent;
-  border-left: 2px solid #563d7c;
-}
-
-/* Nav: second level (shown on .active) */
-nav[data-toggle='toc'] .nav .nav {
-  display: none; /* Hide by default, but at >768px, show it */
-  padding-bottom: 10px;
-}
-nav[data-toggle='toc'] .nav .nav > li > a {
-  padding-top: 1px;
-  padding-bottom: 1px;
-  padding-left: 30px;
-  font-size: 12px;
-  font-weight: normal;
-}
-nav[data-toggle='toc'] .nav .nav > li > a:hover,
-nav[data-toggle='toc'] .nav .nav > li > a:focus {
-  padding-left: 29px;
-}
-nav[data-toggle='toc'] .nav .nav > .active > a,
-nav[data-toggle='toc'] .nav .nav > .active:hover > a,
-nav[data-toggle='toc'] .nav .nav > .active:focus > a {
-  padding-left: 28px;
-  font-weight: 500;
-}
-
-/* from https://github.com/twbs/bootstrap/blob/e38f066d8c203c3e032da0ff23cd2d6098ee2dd6/docs/assets/css/src/docs.css#L631-L634 */
-nav[data-toggle='toc'] .nav > .active > ul {
-  display: block;
-}
diff --git a/docs/bootstrap-toc.js b/docs/bootstrap-toc.js
deleted file mode 100644
index 1cdd573b..00000000
--- a/docs/bootstrap-toc.js
+++ /dev/null
@@ -1,159 +0,0 @@
-/*!
- * Bootstrap Table of Contents v0.4.1 (http://afeld.github.io/bootstrap-toc/)
- * Copyright 2015 Aidan Feldman
- * Licensed under MIT (https://github.com/afeld/bootstrap-toc/blob/gh-pages/LICENSE.md) */
-(function() {
-  'use strict';
-
-  window.Toc = {
-    helpers: {
-      // return all matching elements in the set, or their descendants
-      findOrFilter: function($el, selector) {
-        // http://danielnouri.org/notes/2011/03/14/a-jquery-find-that-also-finds-the-root-element/
-        // http://stackoverflow.com/a/12731439/358804
-        var $descendants = $el.find(selector);
-        return $el.filter(selector).add($descendants).filter(':not([data-toc-skip])');
-      },
-
-      generateUniqueIdBase: function(el) {
-        var text = $(el).text();
-        var anchor = text.trim().toLowerCase().replace(/[^A-Za-z0-9]+/g, '-');
-        return anchor || el.tagName.toLowerCase();
-      },
-
-      generateUniqueId: function(el) {
-        var anchorBase = this.generateUniqueIdBase(el);
-        for (var i = 0; ; i++) {
-          var anchor = anchorBase;
-          if (i > 0) {
-            // add suffix
-            anchor += '-' + i;
-          }
-          // check if ID already exists
-          if (!document.getElementById(anchor)) {
-            return anchor;
-          }
-        }
-      },
-
-      generateAnchor: function(el) {
-        if (el.id) {
-          return el.id;
-        } else {
-          var anchor = this.generateUniqueId(el);
-          el.id = anchor;
-          return anchor;
-        }
-      },
-
-      createNavList: function() {
-        return $('
    ');
-      },
-
-      createChildNavList: function($parent) {
-        var $childList = this.createNavList();
-        $parent.append($childList);
-        return $childList;
-      },
-
-      generateNavEl: function(anchor, text) {
-        var $a = $('');
-        $a.attr('href', '#' + anchor);
-        $a.text(text);
-        var $li = $('
  • ');
-        $li.append($a);
-        return $li;
-      },
-
-      generateNavItem: function(headingEl) {
-        var anchor = this.generateAnchor(headingEl);
-        var $heading = $(headingEl);
-        var text = $heading.data('toc-text') || $heading.text();
-        return this.generateNavEl(anchor, text);
-      },
-
-      // Find the first heading level (`
    `, then `
    `, etc.) that has more than one element. Defaults to 1 (for `
    `).
-      getTopLevel: function($scope) {
-        for (var i = 1; i <= 6; i++) {
-          var $headings = this.findOrFilter($scope, 'h' + i);
-          if ($headings.length > 1) {
-            return i;
-          }
-        }
-
-        return 1;
-      },
-
-      // returns the elements for the top level, and the next below it
-      getHeadings: function($scope, topLevel) {
-        var topSelector = 'h' + topLevel;
-
-        var secondaryLevel = topLevel + 1;
-        var secondarySelector = 'h' + secondaryLevel;
-
-        return this.findOrFilter($scope, topSelector + ',' + secondarySelector);
-      },
-
-      getNavLevel: function(el) {
-        return parseInt(el.tagName.charAt(1), 10);
-      },
-
-      populateNav: function($topContext, topLevel, $headings) {
-        var $context = $topContext;
-        var $prevNav;
-
-        var helpers = this;
-        $headings.each(function(i, el) {
-          var $newNav = helpers.generateNavItem(el);
-          var navLevel = helpers.getNavLevel(el);
-
-          // determine the proper $context
-          if (navLevel === topLevel) {
-            // use top level
-            $context = $topContext;
-          } else if ($prevNav && $context === $topContext) {
-            // create a new level of the tree and switch to it
-            $context = helpers.createChildNavList($prevNav);
-          } // else use the current $context
-
-          $context.append($newNav);
-
-          $prevNav = $newNav;
-        });
-      },
-
-      parseOps: function(arg) {
-        var opts;
-        if (arg.jquery) {
-          opts = {
-            $nav: arg
-          };
-        } else {
-          opts = arg;
-        }
-        opts.$scope = opts.$scope || $(document.body);
-        return opts;
-      }
-    },
-
-    // accepts a jQuery object, or an options object
-    init: function(opts) {
-      opts = this.helpers.parseOps(opts);
-
-      // ensure that the data attribute is in place for styling
-      opts.$nav.attr('data-toggle', 'toc');
-
-      var $topContext = this.helpers.createChildNavList(opts.$nav);
-      var topLevel = this.helpers.getTopLevel(opts.$scope);
-      var $headings = this.helpers.getHeadings(opts.$scope, topLevel);
-      this.helpers.populateNav($topContext, topLevel, $headings);
-    }
-  };
-
-  $(function() {
-    $('nav[data-toggle="toc"]').each(function(i, el) {
-      var $nav = $(el);
-      Toc.init($nav);
-    });
-  });
-})();
diff --git a/docs/coverage/coverage.html b/docs/coverage/coverage.html
deleted file mode 100644
index 749ccdd0..00000000
--- a/docs/coverage/coverage.html
+++ /dev/null
@@ -1,69858 +0,0 @@
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
    
-  
-  
    
-    
    mkin coverage - 89.32%
    
-    
    
-      
-      
    
-        
    
-          
    
-          
-        
    
-        
    
-          
    
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
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-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-            
-          
    
-        
    
-      
    
-    
    
-  
    
-
    
-
-
diff --git a/docs/coverage/lib/bootstrap-3.3.5/css/bootstrap-theme.min.css b/docs/coverage/lib/bootstrap-3.3.5/css/bootstrap-theme.min.css
deleted file mode 100644
index 61358b13..00000000
--- a/docs/coverage/lib/bootstrap-3.3.5/css/bootstrap-theme.min.css
+++ /dev/null
@@ -1,5 +0,0 @@
-/*!
- * Bootstrap v3.3.5 (http://getbootstrap.com)
- * Copyright 2011-2015 Twitter, Inc.
- * Licensed under MIT (https://github.com/twbs/bootstrap/blob/master/LICENSE)
- */.btn-danger,.btn-default,.btn-info,.btn-primary,.btn-success,.btn-warning{text-shadow:0 -1px 0 rgba(0,0,0,.2);-webkit-box-shadow:inset 0 1px 0 rgba(255,255,255,.15),0 1px 1px rgba(0,0,0,.075);box-shadow:inset 0 1px 0 rgba(255,255,255,.15),0 1px 1px rgba(0,0,0,.075)}.btn-danger.active,.btn-danger:active,.btn-default.active,.btn-default:active,.btn-info.active,.btn-info:active,.btn-primary.active,.btn-primary:active,.btn-success.active,.btn-success:active,.btn-warning.active,.btn-warning:active{-webkit-box-shadow:inset 0 3px 5px rgba(0,0,0,.125);box-shadow:inset 0 3px 5px rgba(0,0,0,.125)}.btn-danger.disabled,.btn-danger[disabled],.btn-default.disabled,.btn-default[disabled],.btn-info.disabled,.btn-info[disabled],.btn-primary.disabled,.btn-primary[disabled],.btn-success.disabled,.btn-success[disabled],.btn-warning.disabled,.btn-warning[disabled],fieldset[disabled] .btn-danger,fieldset[disabled] .btn-default,fieldset[disabled] .btn-info,fieldset[disabled] 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diff --git a/docs/coverage/lib/bootstrap-3.3.5/css/bootstrap.min.css b/docs/coverage/lib/bootstrap-3.3.5/css/bootstrap.min.css
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\ No newline at end of file
diff --git a/docs/coverage/lib/bootstrap-3.3.5/shim/html5shiv.min.js b/docs/coverage/lib/bootstrap-3.3.5/shim/html5shiv.min.js
deleted file mode 100644
index 36831143..00000000
--- a/docs/coverage/lib/bootstrap-3.3.5/shim/html5shiv.min.js
+++ /dev/null
@@ -1,7 +0,0 @@
-/**
-* @preserve HTML5 Shiv 3.7.2 | @afarkas @jdalton @jon_neal @rem | MIT/GPL2 Licensed
-*/
-// Only run this code in IE 8
-if (!!window.navigator.userAgent.match("MSIE 8")) {
-!function(a,b){function c(a,b){var c=a.createElement("p"),d=a.getElementsByTagName("head")[0]||a.documentElement;return c.innerHTML="x",d.insertBefore(c.lastChild,d.firstChild)}function d(){var a=t.elements;return"string"==typeof a?a.split(" "):a}function e(a,b){var c=t.elements;"string"!=typeof c&&(c=c.join(" ")),"string"!=typeof a&&(a=a.join(" ")),t.elements=c+" "+a,j(b)}function f(a){var b=s[a[q]];return b||(b={},r++,a[q]=r,s[r]=b),b}function g(a,c,d){if(c||(c=b),l)return c.createElement(a);d||(d=f(c));var e;return e=d.cache[a]?d.cache[a].cloneNode():p.test(a)?(d.cache[a]=d.createElem(a)).cloneNode():d.createElem(a),!e.canHaveChildren||o.test(a)||e.tagUrn?e:d.frag.appendChild(e)}function h(a,c){if(a||(a=b),l)return a.createDocumentFragment();c=c||f(a);for(var e=c.frag.cloneNode(),g=0,h=d(),i=h.length;i>g;g++)e.createElement(h[g]);return e}function i(a,b){b.cache||(b.cache={},b.createElem=a.createElement,b.createFrag=a.createDocumentFragment,b.frag=b.createFrag()),a.createElement=function(c){return t.shivMethods?g(c,a,b):b.createElem(c)},a.createDocumentFragment=Function("h,f","return function(){var n=f.cloneNode(),c=n.createElement;h.shivMethods&&("+d().join().replace(/[\w\-:]+/g,function(a){return b.createElem(a),b.frag.createElement(a),'c("'+a+'")'})+");return n}")(t,b.frag)}function j(a){a||(a=b);var d=f(a);return!t.shivCSS||k||d.hasCSS||(d.hasCSS=!!c(a,"article,aside,dialog,figcaption,figure,footer,header,hgroup,main,nav,section{display:block}mark{background:#FF0;color:#000}template{display:none}")),l||i(a,d),a}var k,l,m="3.7.2",n=a.html5||{},o=/^<|^(?:button|map|select|textarea|object|iframe|option|optgroup)$/i,p=/^(?:a|b|code|div|fieldset|h1|h2|h3|h4|h5|h6|i|label|li|ol|p|q|span|strong|style|table|tbody|td|th|tr|ul)$/i,q="_html5shiv",r=0,s={};!function(){try{var a=b.createElement("a");a.innerHTML="",k="hidden"in a,l=1==a.childNodes.length||function(){b.createElement("a");var a=b.createDocumentFragment();return"undefined"==typeof a.cloneNode||"undefined"==typeof a.createDocumentFragment||"undefined"==typeof a.createElement}()}catch(c){k=!0,l=!0}}();var t={elements:n.elements||"abbr article aside audio bdi canvas data datalist details dialog figcaption figure footer header hgroup main mark meter nav output picture progress section summary template time video",version:m,shivCSS:n.shivCSS!==!1,supportsUnknownElements:l,shivMethods:n.shivMethods!==!1,type:"default",shivDocument:j,createElement:g,createDocumentFragment:h,addElements:e};a.html5=t,j(b)}(this,document);
-};
diff --git a/docs/coverage/lib/bootstrap-3.3.5/shim/respond.min.js b/docs/coverage/lib/bootstrap-3.3.5/shim/respond.min.js
deleted file mode 100644
index 22094690..00000000
--- a/docs/coverage/lib/bootstrap-3.3.5/shim/respond.min.js
+++ /dev/null
@@ -1,8 +0,0 @@
-/*! Respond.js v1.4.2: min/max-width media query polyfill * Copyright 2013 Scott Jehl
- * Licensed under https://github.com/scottjehl/Respond/blob/master/LICENSE-MIT
- *  */
-
-// Only run this code in IE 8
-if (!!window.navigator.userAgent.match("MSIE 8")) {
-!function(a){"use strict";a.matchMedia=a.matchMedia||function(a){var b,c=a.documentElement,d=c.firstElementChild||c.firstChild,e=a.createElement("body"),f=a.createElement("div");return f.id="mq-test-1",f.style.cssText="position:absolute;top:-100em",e.style.background="none",e.appendChild(f),function(a){return f.innerHTML='­',c.insertBefore(e,d),b=42===f.offsetWidth,c.removeChild(e),{matches:b,media:a}}}(a.document)}(this),function(a){"use strict";function b(){u(!0)}var c={};a.respond=c,c.update=function(){};var d=[],e=function(){var b=!1;try{b=new a.XMLHttpRequest}catch(c){b=new a.ActiveXObject("Microsoft.XMLHTTP")}return function(){return b}}(),f=function(a,b){var c=e();c&&(c.open("GET",a,!0),c.onreadystatechange=function(){4!==c.readyState||200!==c.status&&304!==c.status||b(c.responseText)},4!==c.readyState&&c.send(null))};if(c.ajax=f,c.queue=d,c.regex={media:/@media[^\{]+\{([^\{\}]*\{[^\}\{]*\})+/gi,keyframes:/@(?:\-(?:o|moz|webkit)\-)?keyframes[^\{]+\{(?:[^\{\}]*\{[^\}\{]*\})+[^\}]*\}/gi,urls:/(url\()['"]?([^\/\)'"][^:\)'"]+)['"]?(\))/g,findStyles:/@media *([^\{]+)\{([\S\s]+?)$/,only:/(only\s+)?([a-zA-Z]+)\s?/,minw:/\([\s]*min\-width\s*:[\s]*([\s]*[0-9\.]+)(px|em)[\s]*\)/,maxw:/\([\s]*max\-width\s*:[\s]*([\s]*[0-9\.]+)(px|em)[\s]*\)/},c.mediaQueriesSupported=a.matchMedia&&null!==a.matchMedia("only all")&&a.matchMedia("only all").matches,!c.mediaQueriesSupported){var g,h,i,j=a.document,k=j.documentElement,l=[],m=[],n=[],o={},p=30,q=j.getElementsByTagName("head")[0]||k,r=j.getElementsByTagName("base")[0],s=q.getElementsByTagName("link"),t=function(){var a,b=j.createElement("div"),c=j.body,d=k.style.fontSize,e=c&&c.style.fontSize,f=!1;return b.style.cssText="position:absolute;font-size:1em;width:1em",c||(c=f=j.createElement("body"),c.style.background="none"),k.style.fontSize="100%",c.style.fontSize="100%",c.appendChild(b),f&&k.insertBefore(c,k.firstChild),a=b.offsetWidth,f?k.removeChild(c):c.removeChild(b),k.style.fontSize=d,e&&(c.style.fontSize=e),a=i=parseFloat(a)},u=function(b){var c="clientWidth",d=k[c],e="CSS1Compat"===j.compatMode&&d||j.body[c]||d,f={},o=s[s.length-1],r=(new Date).getTime();if(b&&g&&p>r-g)return a.clearTimeout(h),h=a.setTimeout(u,p),void 0;g=r;for(var v in l)if(l.hasOwnProperty(v)){var w=l[v],x=w.minw,y=w.maxw,z=null===x,A=null===y,B="em";x&&(x=parseFloat(x)*(x.indexOf(B)>-1?i||t():1)),y&&(y=parseFloat(y)*(y.indexOf(B)>-1?i||t():1)),w.hasquery&&(z&&A||!(z||e>=x)||!(A||y>=e))||(f[w.media]||(f[w.media]=[]),f[w.media].push(m[w.rules]))}for(var C in n)n.hasOwnProperty(C)&&n[C]&&n[C].parentNode===q&&q.removeChild(n[C]);n.length=0;for(var D in f)if(f.hasOwnProperty(D)){var E=j.createElement("style"),F=f[D].join("\n");E.type="text/css",E.media=D,q.insertBefore(E,o.nextSibling),E.styleSheet?E.styleSheet.cssText=F:E.appendChild(j.createTextNode(F)),n.push(E)}},v=function(a,b,d){var e=a.replace(c.regex.keyframes,"").match(c.regex.media),f=e&&e.length||0;b=b.substring(0,b.lastIndexOf("/"));var g=function(a){return a.replace(c.regex.urls,"$1"+b+"$2$3")},h=!f&&d;b.length&&(b+="/"),h&&(f=1);for(var i=0;f>i;i++){var j,k,n,o;h?(j=d,m.push(g(a))):(j=e[i].match(c.regex.findStyles)&&RegExp.$1,m.push(RegExp.$2&&g(RegExp.$2))),n=j.split(","),o=n.length;for(var p=0;o>p;p++)k=n[p],l.push({media:k.split("(")[0].match(c.regex.only)&&RegExp.$2||"all",rules:m.length-1,hasquery:k.indexOf("(")>-1,minw:k.match(c.regex.minw)&&parseFloat(RegExp.$1)+(RegExp.$2||""),maxw:k.match(c.regex.maxw)&&parseFloat(RegExp.$1)+(RegExp.$2||"")})}u()},w=function(){if(d.length){var b=d.shift();f(b.href,function(c){v(c,b.href,b.media),o[b.href]=!0,a.setTimeout(function(){w()},0)})}},x=function(){for(var b=0;b.container-fluid.crosstalk-bscols{margin-left:auto;margin-right:auto}.crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column{display:inline-block;padding-right:12px;vertical-align:top}@media only screen and (max-width: 480px){.crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column{display:block;padding-right:inherit}}.crosstalk-input{margin-bottom:15px}.crosstalk-input .control-label{margin-bottom:0;vertical-align:middle}.crosstalk-input input[type="checkbox"]{margin:4px 0 0;margin-top:1px;line-height:normal}.crosstalk-input .checkbox{position:relative;display:block;margin-top:10px;margin-bottom:10px}.crosstalk-input .checkbox>label{padding-left:20px;margin-bottom:0;font-weight:400;cursor:pointer}.crosstalk-input .checkbox input[type="checkbox"],.crosstalk-input .checkbox-inline input[type="checkbox"]{position:absolute;margin-top:2px;margin-left:-20px}.crosstalk-input .checkbox+.checkbox{margin-top:-5px}.crosstalk-input .checkbox-inline{position:relative;display:inline-block;padding-left:20px;margin-bottom:0;font-weight:400;vertical-align:middle;cursor:pointer}.crosstalk-input .checkbox-inline+.checkbox-inline{margin-top:0;margin-left:10px}
diff --git a/docs/coverage/lib/crosstalk-1.2.1/js/crosstalk.js b/docs/coverage/lib/crosstalk-1.2.1/js/crosstalk.js
deleted file mode 100644
index fd9eb53d..00000000
--- a/docs/coverage/lib/crosstalk-1.2.1/js/crosstalk.js
+++ /dev/null
@@ -1,1474 +0,0 @@
-(function(){function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require=="function"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error("Cannot find module '"+o+"'");throw f.code="MODULE_NOT_FOUND",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require=="function"&&require;for(var o=0;o b) {
-    return 1;
-  }
-}
-
-/**
- * @private
- */
-
-var FilterSet = function () {
-  function FilterSet() {
-    _classCallCheck(this, FilterSet);
-
-    this.reset();
-  }
-
-  _createClass(FilterSet, [{
-    key: "reset",
-    value: function reset() {
-      // Key: handle ID, Value: array of selected keys, or null
-      this._handles = {};
-      // Key: key string, Value: count of handles that include it
-      this._keys = {};
-      this._value = null;
-      this._activeHandles = 0;
-    }
-  }, {
-    key: "update",
-    value: function update(handleId, keys) {
-      if (keys !== null) {
-        keys = keys.slice(0); // clone before sorting
-        keys.sort(naturalComparator);
-      }
-
-      var _diffSortedLists = (0, _util.diffSortedLists)(this._handles[handleId], keys),
-          added = _diffSortedLists.added,
-          removed = _diffSortedLists.removed;
-
-      this._handles[handleId] = keys;
-
-      for (var i = 0; i < added.length; i++) {
-        this._keys[added[i]] = (this._keys[added[i]] || 0) + 1;
-      }
-      for (var _i = 0; _i < removed.length; _i++) {
-        this._keys[removed[_i]]--;
-      }
-
-      this._updateValue(keys);
-    }
-
-    /**
-     * @param {string[]} keys Sorted array of strings that indicate
-     * a superset of possible keys.
-     * @private
-     */
-
-  }, {
-    key: "_updateValue",
-    value: function _updateValue() {
-      var keys = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : this._allKeys;
-
-      var handleCount = Object.keys(this._handles).length;
-      if (handleCount === 0) {
-        this._value = null;
-      } else {
-        this._value = [];
-        for (var i = 0; i < keys.length; i++) {
-          var count = this._keys[keys[i]];
-          if (count === handleCount) {
-            this._value.push(keys[i]);
-          }
-        }
-      }
-    }
-  }, {
-    key: "clear",
-    value: function clear(handleId) {
-      if (typeof this._handles[handleId] === "undefined") {
-        return;
-      }
-
-      var keys = this._handles[handleId];
-      if (!keys) {
-        keys = [];
-      }
-
-      for (var i = 0; i < keys.length; i++) {
-        this._keys[keys[i]]--;
-      }
-      delete this._handles[handleId];
-
-      this._updateValue();
-    }
-  }, {
-    key: "value",
-    get: function get() {
-      return this._value;
-    }
-  }, {
-    key: "_allKeys",
-    get: function get() {
-      var allKeys = Object.keys(this._keys);
-      allKeys.sort(naturalComparator);
-      return allKeys;
-    }
-  }]);
-
-  return FilterSet;
-}();
-
-exports.default = FilterSet;
-
-},{"./util":11}],4:[function(require,module,exports){
-(function (global){
-"use strict";
-
-Object.defineProperty(exports, "__esModule", {
-  value: true
-});
-
-var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }();
-
-var _typeof = typeof Symbol === "function" && typeof Symbol.iterator === "symbol" ? function (obj) { return typeof obj; } : function (obj) { return obj && typeof Symbol === "function" && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj; };
-
-exports.default = group;
-
-var _var2 = require("./var");
-
-var _var3 = _interopRequireDefault(_var2);
-
-function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; }
-
-function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } }
-
-// Use a global so that multiple copies of crosstalk.js can be loaded and still
-// have groups behave as singletons across all copies.
-global.__crosstalk_groups = global.__crosstalk_groups || {};
-var groups = global.__crosstalk_groups;
-
-function group(groupName) {
-  if (groupName && typeof groupName === "string") {
-    if (!groups.hasOwnProperty(groupName)) {
-      groups[groupName] = new Group(groupName);
-    }
-    return groups[groupName];
-  } else if ((typeof groupName === "undefined" ? "undefined" : _typeof(groupName)) === "object" && groupName._vars && groupName.var) {
-    // Appears to already be a group object
-    return groupName;
-  } else if (Array.isArray(groupName) && groupName.length == 1 && typeof groupName[0] === "string") {
-    return group(groupName[0]);
-  } else {
-    throw new Error("Invalid groupName argument");
-  }
-}
-
-var Group = function () {
-  function Group(name) {
-    _classCallCheck(this, Group);
-
-    this.name = name;
-    this._vars = {};
-  }
-
-  _createClass(Group, [{
-    key: "var",
-    value: function _var(name) {
-      if (!name || typeof name !== "string") {
-        throw new Error("Invalid var name");
-      }
-
-      if (!this._vars.hasOwnProperty(name)) this._vars[name] = new _var3.default(this, name);
-      return this._vars[name];
-    }
-  }, {
-    key: "has",
-    value: function has(name) {
-      if (!name || typeof name !== "string") {
-        throw new Error("Invalid var name");
-      }
-
-      return this._vars.hasOwnProperty(name);
-    }
-  }]);
-
-  return Group;
-}();
-
-}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {})
-
-},{"./var":12}],5:[function(require,module,exports){
-(function (global){
-"use strict";
-
-Object.defineProperty(exports, "__esModule", {
-  value: true
-});
-
-var _group = require("./group");
-
-var _group2 = _interopRequireDefault(_group);
-
-var _selection = require("./selection");
-
-var _filter = require("./filter");
-
-var _input = require("./input");
-
-require("./input_selectize");
-
-require("./input_checkboxgroup");
-
-require("./input_slider");
-
-function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; }
-
-var defaultGroup = (0, _group2.default)("default");
-
-function var_(name) {
-  return defaultGroup.var(name);
-}
-
-function has(name) {
-  return defaultGroup.has(name);
-}
-
-if (global.Shiny) {
-  global.Shiny.addCustomMessageHandler("update-client-value", function (message) {
-    if (typeof message.group === "string") {
-      (0, _group2.default)(message.group).var(message.name).set(message.value);
-    } else {
-      var_(message.name).set(message.value);
-    }
-  });
-}
-
-var crosstalk = {
-  group: _group2.default,
-  var: var_,
-  has: has,
-  SelectionHandle: _selection.SelectionHandle,
-  FilterHandle: _filter.FilterHandle,
-  bind: _input.bind
-};
-
-/**
- * @namespace crosstalk
- */
-exports.default = crosstalk;
-
-global.crosstalk = crosstalk;
-
-}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {})
-
-},{"./filter":2,"./group":4,"./input":6,"./input_checkboxgroup":7,"./input_selectize":8,"./input_slider":9,"./selection":10}],6:[function(require,module,exports){
-(function (global){
-"use strict";
-
-Object.defineProperty(exports, "__esModule", {
-  value: true
-});
-exports.register = register;
-exports.bind = bind;
-var $ = global.jQuery;
-
-var bindings = {};
-
-function register(reg) {
-  bindings[reg.className] = reg;
-  if (global.document && global.document.readyState !== "complete") {
-    $(function () {
-      bind();
-    });
-  } else if (global.document) {
-    setTimeout(bind, 100);
-  }
-}
-
-function bind() {
-  Object.keys(bindings).forEach(function (className) {
-    var binding = bindings[className];
-    $("." + binding.className).not(".crosstalk-input-bound").each(function (i, el) {
-      bindInstance(binding, el);
-    });
-  });
-}
-
-// Escape jQuery identifier
-function $escape(val) {
-  return val.replace(/([!"#$%&'()*+,./:;<=>?@[\\\]^`{|}~])/g, "\\$1");
-}
-
-function bindEl(el) {
-  var $el = $(el);
-  Object.keys(bindings).forEach(function (className) {
-    if ($el.hasClass(className) && !$el.hasClass("crosstalk-input-bound")) {
-      var binding = bindings[className];
-      bindInstance(binding, el);
-    }
-  });
-}
-
-function bindInstance(binding, el) {
-  var jsonEl = $(el).find("script[type='application/json'][data-for='" + $escape(el.id) + "']");
-  var data = JSON.parse(jsonEl[0].innerText);
-
-  var instance = binding.factory(el, data);
-  $(el).data("crosstalk-instance", instance);
-  $(el).addClass("crosstalk-input-bound");
-}
-
-if (global.Shiny) {
-  var inputBinding = new global.Shiny.InputBinding();
-  var _$ = global.jQuery;
-  _$.extend(inputBinding, {
-    find: function find(scope) {
-      return _$(scope).find(".crosstalk-input");
-    },
-    initialize: function initialize(el) {
-      if (!_$(el).hasClass("crosstalk-input-bound")) {
-        bindEl(el);
-      }
-    },
-    getId: function getId(el) {
-      return el.id;
-    },
-    getValue: function getValue(el) {},
-    setValue: function setValue(el, value) {},
-    receiveMessage: function receiveMessage(el, data) {},
-    subscribe: function subscribe(el, callback) {
-      _$(el).data("crosstalk-instance").resume();
-    },
-    unsubscribe: function unsubscribe(el) {
-      _$(el).data("crosstalk-instance").suspend();
-    }
-  });
-  global.Shiny.inputBindings.register(inputBinding, "crosstalk.inputBinding");
-}
-
-}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {})
-
-},{}],7:[function(require,module,exports){
-(function (global){
-"use strict";
-
-var _input = require("./input");
-
-var input = _interopRequireWildcard(_input);
-
-var _filter = require("./filter");
-
-function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } }
-
-var $ = global.jQuery;
-
-input.register({
-  className: "crosstalk-input-checkboxgroup",
-
-  factory: function factory(el, data) {
-    /*
-     * map: {"groupA": ["keyA", "keyB", ...], ...}
-     * group: "ct-groupname"
-     */
-    var ctHandle = new _filter.FilterHandle(data.group);
-
-    var lastKnownKeys = void 0;
-    var $el = $(el);
-    $el.on("change", "input[type='checkbox']", function () {
-      var checked = $el.find("input[type='checkbox']:checked");
-      if (checked.length === 0) {
-        lastKnownKeys = null;
-        ctHandle.clear();
-      } else {
-        var keys = {};
-        checked.each(function () {
-          data.map[this.value].forEach(function (key) {
-            keys[key] = true;
-          });
-        });
-        var keyArray = Object.keys(keys);
-        keyArray.sort();
-        lastKnownKeys = keyArray;
-        ctHandle.set(keyArray);
-      }
-    });
-
-    return {
-      suspend: function suspend() {
-        ctHandle.clear();
-      },
-      resume: function resume() {
-        if (lastKnownKeys) ctHandle.set(lastKnownKeys);
-      }
-    };
-  }
-});
-
-}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {})
-
-},{"./filter":2,"./input":6}],8:[function(require,module,exports){
-(function (global){
-"use strict";
-
-var _input = require("./input");
-
-var input = _interopRequireWildcard(_input);
-
-var _util = require("./util");
-
-var util = _interopRequireWildcard(_util);
-
-var _filter = require("./filter");
-
-function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } }
-
-var $ = global.jQuery;
-
-input.register({
-  className: "crosstalk-input-select",
-
-  factory: function factory(el, data) {
-    /*
-     * items: {value: [...], label: [...]}
-     * map: {"groupA": ["keyA", "keyB", ...], ...}
-     * group: "ct-groupname"
-     */
-
-    var first = [{ value: "", label: "(All)" }];
-    var items = util.dataframeToD3(data.items);
-    var opts = {
-      options: first.concat(items),
-      valueField: "value",
-      labelField: "label",
-      searchField: "label"
-    };
-
-    var select = $(el).find("select")[0];
-
-    var selectize = $(select).selectize(opts)[0].selectize;
-
-    var ctHandle = new _filter.FilterHandle(data.group);
-
-    var lastKnownKeys = void 0;
-    selectize.on("change", function () {
-      if (selectize.items.length === 0) {
-        lastKnownKeys = null;
-        ctHandle.clear();
-      } else {
-        var keys = {};
-        selectize.items.forEach(function (group) {
-          data.map[group].forEach(function (key) {
-            keys[key] = true;
-          });
-        });
-        var keyArray = Object.keys(keys);
-        keyArray.sort();
-        lastKnownKeys = keyArray;
-        ctHandle.set(keyArray);
-      }
-    });
-
-    return {
-      suspend: function suspend() {
-        ctHandle.clear();
-      },
-      resume: function resume() {
-        if (lastKnownKeys) ctHandle.set(lastKnownKeys);
-      }
-    };
-  }
-});
-
-}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {})
-
-},{"./filter":2,"./input":6,"./util":11}],9:[function(require,module,exports){
-(function (global){
-"use strict";
-
-var _slicedToArray = function () { function sliceIterator(arr, i) { var _arr = []; var _n = true; var _d = false; var _e = undefined; try { for (var _i = arr[Symbol.iterator](), _s; !(_n = (_s = _i.next()).done); _n = true) { _arr.push(_s.value); if (i && _arr.length === i) break; } } catch (err) { _d = true; _e = err; } finally { try { if (!_n && _i["return"]) _i["return"](); } finally { if (_d) throw _e; } } return _arr; } return function (arr, i) { if (Array.isArray(arr)) { return arr; } else if (Symbol.iterator in Object(arr)) { return sliceIterator(arr, i); } else { throw new TypeError("Invalid attempt to destructure non-iterable instance"); } }; }();
-
-var _input = require("./input");
-
-var input = _interopRequireWildcard(_input);
-
-var _filter = require("./filter");
-
-function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } }
-
-var $ = global.jQuery;
-var strftime = global.strftime;
-
-input.register({
-  className: "crosstalk-input-slider",
-
-  factory: function factory(el, data) {
-    /*
-     * map: {"groupA": ["keyA", "keyB", ...], ...}
-     * group: "ct-groupname"
-     */
-    var ctHandle = new _filter.FilterHandle(data.group);
-
-    var opts = {};
-    var $el = $(el).find("input");
-    var dataType = $el.data("data-type");
-    var timeFormat = $el.data("time-format");
-    var round = $el.data("round");
-    var timeFormatter = void 0;
-
-    // Set up formatting functions
-    if (dataType === "date") {
-      timeFormatter = strftime.utc();
-      opts.prettify = function (num) {
-        return timeFormatter(timeFormat, new Date(num));
-      };
-    } else if (dataType === "datetime") {
-      var timezone = $el.data("timezone");
-      if (timezone) timeFormatter = strftime.timezone(timezone);else timeFormatter = strftime;
-
-      opts.prettify = function (num) {
-        return timeFormatter(timeFormat, new Date(num));
-      };
-    } else if (dataType === "number") {
-      if (typeof round !== "undefined") opts.prettify = function (num) {
-        var factor = Math.pow(10, round);
-        return Math.round(num * factor) / factor;
-      };
-    }
-
-    $el.ionRangeSlider(opts);
-
-    function getValue() {
-      var result = $el.data("ionRangeSlider").result;
-
-      // Function for converting numeric value from slider to appropriate type.
-      var convert = void 0;
-      var dataType = $el.data("data-type");
-      if (dataType === "date") {
-        convert = function convert(val) {
-          return formatDateUTC(new Date(+val));
-        };
-      } else if (dataType === "datetime") {
-        convert = function convert(val) {
-          // Convert ms to s
-          return +val / 1000;
-        };
-      } else {
-        convert = function convert(val) {
-          return +val;
-        };
-      }
-
-      if ($el.data("ionRangeSlider").options.type === "double") {
-        return [convert(result.from), convert(result.to)];
-      } else {
-        return convert(result.from);
-      }
-    }
-
-    var lastKnownKeys = null;
-
-    $el.on("change.crosstalkSliderInput", function (event) {
-      if (!$el.data("updating") && !$el.data("animating")) {
-        var _getValue = getValue(),
-            _getValue2 = _slicedToArray(_getValue, 2),
-            from = _getValue2[0],
-            to = _getValue2[1];
-
-        var keys = [];
-        for (var i = 0; i < data.values.length; i++) {
-          var val = data.values[i];
-          if (val >= from && val <= to) {
-            keys.push(data.keys[i]);
-          }
-        }
-        keys.sort();
-        ctHandle.set(keys);
-        lastKnownKeys = keys;
-      }
-    });
-
-    // let $el = $(el);
-    // $el.on("change", "input[type="checkbox"]", function() {
-    //   let checked = $el.find("input[type="checkbox"]:checked");
-    //   if (checked.length === 0) {
-    //     ctHandle.clear();
-    //   } else {
-    //     let keys = {};
-    //     checked.each(function() {
-    //       data.map[this.value].forEach(function(key) {
-    //         keys[key] = true;
-    //       });
-    //     });
-    //     let keyArray = Object.keys(keys);
-    //     keyArray.sort();
-    //     ctHandle.set(keyArray);
-    //   }
-    // });
-
-    return {
-      suspend: function suspend() {
-        ctHandle.clear();
-      },
-      resume: function resume() {
-        if (lastKnownKeys) ctHandle.set(lastKnownKeys);
-      }
-    };
-  }
-});
-
-// Convert a number to a string with leading zeros
-function padZeros(n, digits) {
-  var str = n.toString();
-  while (str.length < digits) {
-    str = "0" + str;
-  }return str;
-}
-
-// Given a Date object, return a string in yyyy-mm-dd format, using the
-// UTC date. This may be a day off from the date in the local time zone.
-function formatDateUTC(date) {
-  if (date instanceof Date) {
-    return date.getUTCFullYear() + "-" + padZeros(date.getUTCMonth() + 1, 2) + "-" + padZeros(date.getUTCDate(), 2);
-  } else {
-    return null;
-  }
-}
-
-}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {})
-
-},{"./filter":2,"./input":6}],10:[function(require,module,exports){
-"use strict";
-
-Object.defineProperty(exports, "__esModule", {
-  value: true
-});
-exports.SelectionHandle = undefined;
-
-var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }();
-
-var _events = require("./events");
-
-var _events2 = _interopRequireDefault(_events);
-
-var _group = require("./group");
-
-var _group2 = _interopRequireDefault(_group);
-
-var _util = require("./util");
-
-var util = _interopRequireWildcard(_util);
-
-function _interopRequireWildcard(obj) { if (obj && obj.__esModule) { return obj; } else { var newObj = {}; if (obj != null) { for (var key in obj) { if (Object.prototype.hasOwnProperty.call(obj, key)) newObj[key] = obj[key]; } } newObj.default = obj; return newObj; } }
-
-function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; }
-
-function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } }
-
-/**
- * Use this class to read and write (and listen for changes to) the selection
- * for a Crosstalk group. This is intended to be used for linked brushing.
- *
- * If two (or more) `SelectionHandle` instances in the same webpage share the
- * same group name, they will share the same state. Setting the selection using
- * one `SelectionHandle` instance will result in the `value` property instantly
- * changing across the others, and `"change"` event listeners on all instances
- * (including the one that initiated the sending) will fire.
- *
- * @param {string} [group] - The name of the Crosstalk group, or if none,
- *   null or undefined (or any other falsy value). This can be changed later
- *   via the [SelectionHandle#setGroup](#setGroup) method.
- * @param {Object} [extraInfo] - An object whose properties will be copied to
- *   the event object whenever an event is emitted.
- */
-var SelectionHandle = exports.SelectionHandle = function () {
-  function SelectionHandle() {
-    var group = arguments.length > 0 && arguments[0] !== undefined ? arguments[0] : null;
-    var extraInfo = arguments.length > 1 && arguments[1] !== undefined ? arguments[1] : null;
-
-    _classCallCheck(this, SelectionHandle);
-
-    this._eventRelay = new _events2.default();
-    this._emitter = new util.SubscriptionTracker(this._eventRelay);
-
-    // Name of the group we're currently tracking, if any. Can change over time.
-    this._group = null;
-    // The Var we're currently tracking, if any. Can change over time.
-    this._var = null;
-    // The event handler subscription we currently have on var.on("change").
-    this._varOnChangeSub = null;
-
-    this._extraInfo = util.extend({ sender: this }, extraInfo);
-
-    this.setGroup(group);
-  }
-
-  /**
-   * Changes the Crosstalk group membership of this SelectionHandle. The group
-   * being switched away from (if any) will not have its selection value
-   * modified as a result of calling `setGroup`, even if this handle was the
-   * most recent handle to set the selection of the group.
-   *
-   * The group being switched to (if any) will also not have its selection value
-   * modified as a result of calling `setGroup`. If you want to set the
-   * selection value of the new group, call `set` explicitly.
-   *
-   * @param {string} group - The name of the Crosstalk group, or null (or
-   *   undefined) to clear the group.
-   */
-
-
-  _createClass(SelectionHandle, [{
-    key: "setGroup",
-    value: function setGroup(group) {
-      var _this = this;
-
-      // If group is unchanged, do nothing
-      if (this._group === group) return;
-      // Treat null, undefined, and other falsy values the same
-      if (!this._group && !group) return;
-
-      if (this._var) {
-        this._var.off("change", this._varOnChangeSub);
-        this._var = null;
-        this._varOnChangeSub = null;
-      }
-
-      this._group = group;
-
-      if (group) {
-        this._var = (0, _group2.default)(group).var("selection");
-        var sub = this._var.on("change", function (e) {
-          _this._eventRelay.trigger("change", e, _this);
-        });
-        this._varOnChangeSub = sub;
-      }
-    }
-
-    /**
-     * Retrieves the current selection for the group represented by this
-     * `SelectionHandle`.
-     *
-     * - If no selection is active, then this value will be falsy.
-     * - If a selection is active, but no data points are selected, then this
-     *   value will be an empty array.
-     * - If a selection is active, and data points are selected, then the keys
-     *   of the selected data points will be present in the array.
-     */
-
-  }, {
-    key: "_mergeExtraInfo",
-
-
-    /**
-     * Combines the given `extraInfo` (if any) with the handle's default
-     * `_extraInfo` (if any).
-     * @private
-     */
-    value: function _mergeExtraInfo(extraInfo) {
-      // Important incidental effect: shallow clone is returned
-      return util.extend({}, this._extraInfo ? this._extraInfo : null, extraInfo ? extraInfo : null);
-    }
-
-    /**
-     * Overwrites the current selection for the group, and raises the `"change"`
-     * event among all of the group's '`SelectionHandle` instances (including
-     * this one).
-     *
-     * @fires SelectionHandle#change
-     * @param {string[]} selectedKeys - Falsy, empty array, or array of keys (see
-     *   {@link SelectionHandle#value}).
-     * @param {Object} [extraInfo] - Extra properties to be included on the event
-     *   object that's passed to listeners (in addition to any options that were
-     *   passed into the `SelectionHandle` constructor).
-     */
-
-  }, {
-    key: "set",
-    value: function set(selectedKeys, extraInfo) {
-      if (this._var) this._var.set(selectedKeys, this._mergeExtraInfo(extraInfo));
-    }
-
-    /**
-     * Overwrites the current selection for the group, and raises the `"change"`
-     * event among all of the group's '`SelectionHandle` instances (including
-     * this one).
-     *
-     * @fires SelectionHandle#change
-     * @param {Object} [extraInfo] - Extra properties to be included on the event
-     *   object that's passed to listeners (in addition to any that were passed
-     *   into the `SelectionHandle` constructor).
-     */
-
-  }, {
-    key: "clear",
-    value: function clear(extraInfo) {
-      if (this._var) this.set(void 0, this._mergeExtraInfo(extraInfo));
-    }
-
-    /**
-     * Subscribes to events on this `SelectionHandle`.
-     *
-     * @param {string} eventType - Indicates the type of events to listen to.
-     *   Currently, only `"change"` is supported.
-     * @param {SelectionHandle~listener} listener - The callback function that
-     *   will be invoked when the event occurs.
-     * @return {string} - A token to pass to {@link SelectionHandle#off} to cancel
-     *   this subscription.
-     */
-
-  }, {
-    key: "on",
-    value: function on(eventType, listener) {
-      return this._emitter.on(eventType, listener);
-    }
-
-    /**
-     * Cancels event subscriptions created by {@link SelectionHandle#on}.
-     *
-     * @param {string} eventType - The type of event to unsubscribe.
-     * @param {string|SelectionHandle~listener} listener - Either the callback
-     *   function previously passed into {@link SelectionHandle#on}, or the
-     *   string that was returned from {@link SelectionHandle#on}.
-     */
-
-  }, {
-    key: "off",
-    value: function off(eventType, listener) {
-      return this._emitter.off(eventType, listener);
-    }
-
-    /**
-     * Shuts down the `SelectionHandle` object.
-     *
-     * Removes all event listeners that were added through this handle.
-     */
-
-  }, {
-    key: "close",
-    value: function close() {
-      this._emitter.removeAllListeners();
-      this.setGroup(null);
-    }
-  }, {
-    key: "value",
-    get: function get() {
-      return this._var ? this._var.get() : null;
-    }
-  }]);
-
-  return SelectionHandle;
-}();
-
-/**
- * @callback SelectionHandle~listener
- * @param {Object} event - An object containing details of the event. For
- *   `"change"` events, this includes the properties `value` (the new
- *   value of the selection, or `undefined` if no selection is active),
- *   `oldValue` (the previous value of the selection), and `sender` (the
- *   `SelectionHandle` instance that made the change).
- */
-
-/**
- * @event SelectionHandle#change
- * @type {object}
- * @property {object} value - The new value of the selection, or `undefined`
- *   if no selection is active.
- * @property {object} oldValue - The previous value of the selection.
- * @property {SelectionHandle} sender - The `SelectionHandle` instance that
- *   changed the value.
- */
-
-},{"./events":1,"./group":4,"./util":11}],11:[function(require,module,exports){
-"use strict";
-
-Object.defineProperty(exports, "__esModule", {
-  value: true
-});
-
-var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }();
-
-var _typeof = typeof Symbol === "function" && typeof Symbol.iterator === "symbol" ? function (obj) { return typeof obj; } : function (obj) { return obj && typeof Symbol === "function" && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj; };
-
-exports.extend = extend;
-exports.checkSorted = checkSorted;
-exports.diffSortedLists = diffSortedLists;
-exports.dataframeToD3 = dataframeToD3;
-
-function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } }
-
-function extend(target) {
-  for (var _len = arguments.length, sources = Array(_len > 1 ? _len - 1 : 0), _key = 1; _key < _len; _key++) {
-    sources[_key - 1] = arguments[_key];
-  }
-
-  for (var i = 0; i < sources.length; i++) {
-    var src = sources[i];
-    if (typeof src === "undefined" || src === null) continue;
-
-    for (var key in src) {
-      if (src.hasOwnProperty(key)) {
-        target[key] = src[key];
-      }
-    }
-  }
-  return target;
-}
-
-function checkSorted(list) {
-  for (var i = 1; i < list.length; i++) {
-    if (list[i] <= list[i - 1]) {
-      throw new Error("List is not sorted or contains duplicate");
-    }
-  }
-}
-
-function diffSortedLists(a, b) {
-  var i_a = 0;
-  var i_b = 0;
-
-  if (!a) a = [];
-  if (!b) b = [];
-
-  var a_only = [];
-  var b_only = [];
-
-  checkSorted(a);
-  checkSorted(b);
-
-  while (i_a < a.length && i_b < b.length) {
-    if (a[i_a] === b[i_b]) {
-      i_a++;
-      i_b++;
-    } else if (a[i_a] < b[i_b]) {
-      a_only.push(a[i_a++]);
-    } else {
-      b_only.push(b[i_b++]);
-    }
-  }
-
-  if (i_a < a.length) a_only = a_only.concat(a.slice(i_a));
-  if (i_b < b.length) b_only = b_only.concat(b.slice(i_b));
-  return {
-    removed: a_only,
-    added: b_only
-  };
-}
-
-// Convert from wide: { colA: [1,2,3], colB: [4,5,6], ... }
-// to long: [ {colA: 1, colB: 4}, {colA: 2, colB: 5}, ... ]
-function dataframeToD3(df) {
-  var names = [];
-  var length = void 0;
-  for (var name in df) {
-    if (df.hasOwnProperty(name)) names.push(name);
-    if (_typeof(df[name]) !== "object" || typeof df[name].length === "undefined") {
-      throw new Error("All fields must be arrays");
-    } else if (typeof length !== "undefined" && length !== df[name].length) {
-      throw new Error("All fields must be arrays of the same length");
-    }
-    length = df[name].length;
-  }
-  var results = [];
-  var item = void 0;
-  for (var row = 0; row < length; row++) {
-    item = {};
-    for (var col = 0; col < names.length; col++) {
-      item[names[col]] = df[names[col]][row];
-    }
-    results.push(item);
-  }
-  return results;
-}
-
-/**
- * Keeps track of all event listener additions/removals and lets all active
- * listeners be removed with a single operation.
- *
- * @private
- */
-
-var SubscriptionTracker = exports.SubscriptionTracker = function () {
-  function SubscriptionTracker(emitter) {
-    _classCallCheck(this, SubscriptionTracker);
-
-    this._emitter = emitter;
-    this._subs = {};
-  }
-
-  _createClass(SubscriptionTracker, [{
-    key: "on",
-    value: function on(eventType, listener) {
-      var sub = this._emitter.on(eventType, listener);
-      this._subs[sub] = eventType;
-      return sub;
-    }
-  }, {
-    key: "off",
-    value: function off(eventType, listener) {
-      var sub = this._emitter.off(eventType, listener);
-      if (sub) {
-        delete this._subs[sub];
-      }
-      return sub;
-    }
-  }, {
-    key: "removeAllListeners",
-    value: function removeAllListeners() {
-      var _this = this;
-
-      var current_subs = this._subs;
-      this._subs = {};
-      Object.keys(current_subs).forEach(function (sub) {
-        _this._emitter.off(current_subs[sub], sub);
-      });
-    }
-  }]);
-
-  return SubscriptionTracker;
-}();
-
-},{}],12:[function(require,module,exports){
-(function (global){
-"use strict";
-
-Object.defineProperty(exports, "__esModule", {
-  value: true
-});
-
-var _typeof = typeof Symbol === "function" && typeof Symbol.iterator === "symbol" ? function (obj) { return typeof obj; } : function (obj) { return obj && typeof Symbol === "function" && obj.constructor === Symbol && obj !== Symbol.prototype ? "symbol" : typeof obj; };
-
-var _createClass = function () { function defineProperties(target, props) { for (var i = 0; i < props.length; i++) { var descriptor = props[i]; descriptor.enumerable = descriptor.enumerable || false; descriptor.configurable = true; if ("value" in descriptor) descriptor.writable = true; Object.defineProperty(target, descriptor.key, descriptor); } } return function (Constructor, protoProps, staticProps) { if (protoProps) defineProperties(Constructor.prototype, protoProps); if (staticProps) defineProperties(Constructor, staticProps); return Constructor; }; }();
-
-var _events = require("./events");
-
-var _events2 = _interopRequireDefault(_events);
-
-function _interopRequireDefault(obj) { return obj && obj.__esModule ? obj : { default: obj }; }
-
-function _classCallCheck(instance, Constructor) { if (!(instance instanceof Constructor)) { throw new TypeError("Cannot call a class as a function"); } }
-
-var Var = function () {
-  function Var(group, name, /*optional*/value) {
-    _classCallCheck(this, Var);
-
-    this._group = group;
-    this._name = name;
-    this._value = value;
-    this._events = new _events2.default();
-  }
-
-  _createClass(Var, [{
-    key: "get",
-    value: function get() {
-      return this._value;
-    }
-  }, {
-    key: "set",
-    value: function set(value, /*optional*/event) {
-      if (this._value === value) {
-        // Do nothing; the value hasn't changed
-        return;
-      }
-      var oldValue = this._value;
-      this._value = value;
-      // Alert JavaScript listeners that the value has changed
-      var evt = {};
-      if (event && (typeof event === "undefined" ? "undefined" : _typeof(event)) === "object") {
-        for (var k in event) {
-          if (event.hasOwnProperty(k)) evt[k] = event[k];
-        }
-      }
-      evt.oldValue = oldValue;
-      evt.value = value;
-      this._events.trigger("change", evt, this);
-
-      // TODO: Make this extensible, to let arbitrary back-ends know that
-      // something has changed
-      if (global.Shiny && global.Shiny.onInputChange) {
-        global.Shiny.onInputChange(".clientValue-" + (this._group.name !== null ? this._group.name + "-" : "") + this._name, typeof value === "undefined" ? null : value);
-      }
-    }
-  }, {
-    key: "on",
-    value: function on(eventType, listener) {
-      return this._events.on(eventType, listener);
-    }
-  }, {
-    key: "off",
-    value: function off(eventType, listener) {
-      return this._events.off(eventType, listener);
-    }
-  }]);
-
-  return Var;
-}();
-
-exports.default = Var;
-
-}).call(this,typeof global !== "undefined" ? global : typeof self !== "undefined" ? self : typeof window !== "undefined" ? window : {})
-
-},{"./events":1}]},{},[5])
-//# sourceMappingURL=crosstalk.js.map
diff --git a/docs/coverage/lib/crosstalk-1.2.1/js/crosstalk.js.map b/docs/coverage/lib/crosstalk-1.2.1/js/crosstalk.js.map
deleted file mode 100644
index cff94f08..00000000
--- a/docs/coverage/lib/crosstalk-1.2.1/js/crosstalk.js.map
+++ /dev/null
@@ -1,37 +0,0 @@
-{
-  "version": 3,
-  "sources": [
-    "node_modules/browser-pack/_prelude.js",
-    "javascript/src/events.js",
-    "javascript/src/filter.js",
-    "javascript/src/filterset.js",
-    "javascript/src/group.js",
-    "javascript/src/index.js",
-    "javascript/src/input.js",
-    "javascript/src/input_checkboxgroup.js",
-    "javascript/src/input_selectize.js",
-    "javascript/src/input_slider.js",
-    "javascript/src/selection.js",
-    "javascript/src/util.js",
-    "javascript/src/var.js"
-  ],
-  "names": [],
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-  "sourceRoot": "",
-  "sourcesContent": [
-    "(function(){function e(t,n,r){function s(o,u){if(!n[o]){if(!t[o]){var a=typeof require==\"function\"&&require;if(!u&&a)return a(o,!0);if(i)return i(o,!0);var f=new Error(\"Cannot find module '\"+o+\"'\");throw f.code=\"MODULE_NOT_FOUND\",f}var l=n[o]={exports:{}};t[o][0].call(l.exports,function(e){var n=t[o][1][e];return s(n?n:e)},l,l.exports,e,t,n,r)}return n[o].exports}var i=typeof require==\"function\"&&require;for(var o=0;o {\n        this._eventRelay.trigger(\"change\", e, this);\n      });\n      this._varOnChangeSub = sub;\n    }\n  }\n\n  /**\n   * Combine the given `extraInfo` (if any) with the handle's default\n   * `_extraInfo` (if any).\n   * @private\n   */\n  _mergeExtraInfo(extraInfo) {\n    return util.extend({},\n      this._extraInfo ? this._extraInfo : null,\n      extraInfo ? extraInfo : null);\n  }\n\n  /**\n   * Close the handle. This clears this handle's contribution to the filter set,\n   * and unsubscribes all event listeners.\n   */\n  close() {\n    this._emitter.removeAllListeners();\n    this.clear();\n    this.setGroup(null);\n  }\n\n  /**\n   * Clear this handle's contribution to the filter set.\n   *\n   * @param {Object} [extraInfo] - Extra properties to be included on the event\n   *   object that's passed to listeners (in addition to any options that were\n   *   passed into the `FilterHandle` constructor).\n   * \n   * @fires FilterHandle#change\n   */\n  clear(extraInfo) {\n    if (!this._filterSet)\n      return;\n    this._filterSet.clear(this._id);\n    this._onChange(extraInfo);\n  }\n\n  /**\n   * Set this handle's contribution to the filter set. This array should consist\n   * of the keys of the rows that _should_ be displayed; any keys that are not\n   * present in the array will be considered _filtered out_. Note that multiple\n   * `FilterHandle` instances in the group may each contribute an array of keys,\n   * and only those keys that appear in _all_ of the arrays make it through the\n   * filter.\n   *\n   * @param {string[]} keys - Empty array, or array of keys. To clear the\n   *   filter, don't pass an empty array; instead, use the\n   *   {@link FilterHandle#clear} method.\n   * @param {Object} [extraInfo] - Extra properties to be included on the event\n   *   object that's passed to listeners (in addition to any options that were\n   *   passed into the `FilterHandle` constructor).\n   * \n   * @fires FilterHandle#change\n   */\n  set(keys, extraInfo) {\n    if (!this._filterSet)\n      return;\n    this._filterSet.update(this._id, keys);\n    this._onChange(extraInfo);\n  }\n\n  /**\n   * @return {string[]|null} - Either: 1) an array of keys that made it through\n   *   all of the `FilterHandle` instances, or, 2) `null`, which means no filter\n   *   is being applied (all data should be displayed).\n   */\n  get filteredKeys() {\n    return this._filterSet ? this._filterSet.value : null;\n  }\n\n  /**\n   * Subscribe to events on this `FilterHandle`.\n   *\n   * @param {string} eventType - Indicates the type of events to listen to.\n   *   Currently, only `\"change\"` is supported.\n   * @param {FilterHandle~listener} listener - The callback function that\n   *   will be invoked when the event occurs.\n   * @return {string} - A token to pass to {@link FilterHandle#off} to cancel\n   *   this subscription.\n   */\n  on(eventType, listener) {\n    return this._emitter.on(eventType, listener);\n  }\n\n  /**\n   * Cancel event subscriptions created by {@link FilterHandle#on}.\n   *\n   * @param {string} eventType - The type of event to unsubscribe.\n   * @param {string|FilterHandle~listener} listener - Either the callback\n   *   function previously passed into {@link FilterHandle#on}, or the\n   *   string that was returned from {@link FilterHandle#on}.\n   */\n  off(eventType, listener) {\n    return this._emitter.off(eventType, listener);\n  }\n\n  _onChange(extraInfo) {\n    if (!this._filterSet)\n      return;\n    this._filterVar.set(this._filterSet.value, this._mergeExtraInfo(extraInfo));\n  }\n\n  /**\n   * @callback FilterHandle~listener\n   * @param {Object} event - An object containing details of the event. For\n   *   `\"change\"` events, this includes the properties `value` (the new\n   *   value of the filter set, or `null` if no filter set is active),\n   *   `oldValue` (the previous value of the filter set), and `sender` (the\n   *   `FilterHandle` instance that made the change).\n   */\n\n}\n\n/**\n * @event FilterHandle#change\n * @type {object}\n * @property {object} value - The new value of the filter set, or `null`\n *   if no filter set is active.\n * @property {object} oldValue - The previous value of the filter set.\n * @property {FilterHandle} sender - The `FilterHandle` instance that\n *   changed the value.\n */\n",
-    "import { diffSortedLists } from \"./util\";\n\nfunction naturalComparator(a, b) {\n  if (a === b) {\n    return 0;\n  } else if (a < b) {\n    return -1;\n  } else if (a > b) {\n    return 1;\n  }\n}\n\n/**\n * @private\n */\nexport default class FilterSet {\n  constructor() {\n    this.reset();\n  }\n\n  reset() {\n    // Key: handle ID, Value: array of selected keys, or null\n    this._handles = {};\n    // Key: key string, Value: count of handles that include it\n    this._keys = {};\n    this._value = null;\n    this._activeHandles = 0;\n  }\n\n  get value() {\n    return this._value;\n  }\n\n  update(handleId, keys) {\n    if (keys !== null) {\n      keys = keys.slice(0); // clone before sorting\n      keys.sort(naturalComparator);\n    }\n\n    let {added, removed} = diffSortedLists(this._handles[handleId], keys);\n    this._handles[handleId] = keys;\n\n    for (let i = 0; i < added.length; i++) {\n      this._keys[added[i]] = (this._keys[added[i]] || 0) + 1;\n    }\n    for (let i = 0; i < removed.length; i++) {\n      this._keys[removed[i]]--;\n    }\n\n    this._updateValue(keys);\n  }\n\n  /**\n   * @param {string[]} keys Sorted array of strings that indicate\n   * a superset of possible keys.\n   * @private\n   */\n  _updateValue(keys = this._allKeys) {\n    let handleCount = Object.keys(this._handles).length;\n    if (handleCount === 0) {\n      this._value = null;\n    } else {\n      this._value = [];\n      for (let i = 0; i < keys.length; i++) {\n        let count = this._keys[keys[i]];\n        if (count === handleCount) {\n          this._value.push(keys[i]);\n        }\n      }\n    }\n  }\n\n  clear(handleId) {\n    if (typeof(this._handles[handleId]) === \"undefined\") {\n      return;\n    }\n\n    let keys = this._handles[handleId];\n    if (!keys) {\n      keys = [];\n    }\n\n    for (let i = 0; i < keys.length; i++) {\n      this._keys[keys[i]]--;\n    }\n    delete this._handles[handleId];\n\n    this._updateValue();\n  }\n\n  get _allKeys() {\n    let allKeys = Object.keys(this._keys);\n    allKeys.sort(naturalComparator);\n    return allKeys;\n  }\n}\n",
-    "import Var from \"./var\";\n\n// Use a global so that multiple copies of crosstalk.js can be loaded and still\n// have groups behave as singletons across all copies.\nglobal.__crosstalk_groups = global.__crosstalk_groups || {};\nlet groups = global.__crosstalk_groups;\n\nexport default function group(groupName) {\n  if (groupName && typeof(groupName) === \"string\") {\n    if (!groups.hasOwnProperty(groupName)) {\n      groups[groupName] = new Group(groupName);\n    }\n    return groups[groupName];\n  } else if (typeof(groupName) === \"object\" && groupName._vars && groupName.var) {\n    // Appears to already be a group object\n    return groupName;\n  } else if (Array.isArray(groupName) &&\n      groupName.length == 1 &&\n      typeof(groupName[0]) === \"string\") {\n    return group(groupName[0]);\n  } else {\n    throw new Error(\"Invalid groupName argument\");\n  }\n}\n\nclass Group {\n  constructor(name) {\n    this.name = name;\n    this._vars = {};\n  }\n\n  var(name) {\n    if (!name || typeof(name) !== \"string\") {\n      throw new Error(\"Invalid var name\");\n    }\n\n    if (!this._vars.hasOwnProperty(name))\n      this._vars[name] = new Var(this, name);\n    return this._vars[name];\n  }\n\n  has(name) {\n    if (!name || typeof(name) !== \"string\") {\n      throw new Error(\"Invalid var name\");\n    }\n\n    return this._vars.hasOwnProperty(name);\n  }\n}\n",
-    "import group from \"./group\";\nimport { SelectionHandle } from \"./selection\";\nimport { FilterHandle } from \"./filter\";\nimport { bind } from \"./input\";\nimport \"./input_selectize\";\nimport \"./input_checkboxgroup\";\nimport \"./input_slider\";\n\nconst defaultGroup = group(\"default\");\n\nfunction var_(name) {\n  return defaultGroup.var(name);\n}\n\nfunction has(name) {\n  return defaultGroup.has(name);\n}\n\nif (global.Shiny) {\n  global.Shiny.addCustomMessageHandler(\"update-client-value\", function(message) {\n    if (typeof(message.group) === \"string\") {\n      group(message.group).var(message.name).set(message.value);\n    } else {\n      var_(message.name).set(message.value);\n    }\n  });\n}\n\nconst crosstalk = {\n  group: group,\n  var: var_,\n  has: has,\n  SelectionHandle: SelectionHandle,\n  FilterHandle: FilterHandle,\n  bind: bind\n};\n\n/**\n * @namespace crosstalk\n */\nexport default crosstalk;\nglobal.crosstalk = crosstalk;\n",
-    "let $ = global.jQuery;\n\nlet bindings = {};\n\nexport function register(reg) {\n  bindings[reg.className] = reg;\n  if (global.document && global.document.readyState !== \"complete\") {\n    $(() => {\n      bind();\n    });\n  } else if (global.document) {\n    setTimeout(bind, 100);\n  }\n}\n\nexport function bind() {\n  Object.keys(bindings).forEach(function(className) {\n    let binding = bindings[className];\n    $(\".\" + binding.className).not(\".crosstalk-input-bound\").each(function(i, el) {\n      bindInstance(binding, el);\n    });\n  });\n}\n\n// Escape jQuery identifier\nfunction $escape(val) {\n  return val.replace(/([!\"#$%&'()*+,./:;<=>?@[\\\\\\]^`{|}~])/g, \"\\\\$1\");\n}\n\nfunction bindEl(el) {\n  let $el = $(el);\n  Object.keys(bindings).forEach(function(className) {\n    if ($el.hasClass(className) && !$el.hasClass(\"crosstalk-input-bound\")) {\n      let binding = bindings[className];\n      bindInstance(binding, el);\n    }\n  });\n}\n\nfunction bindInstance(binding, el) {\n  let jsonEl = $(el).find(\"script[type='application/json'][data-for='\" + $escape(el.id) + \"']\");\n  let data = JSON.parse(jsonEl[0].innerText);\n\n  let instance = binding.factory(el, data);\n  $(el).data(\"crosstalk-instance\", instance);\n  $(el).addClass(\"crosstalk-input-bound\");\n}\n\nif (global.Shiny) {\n  let inputBinding = new global.Shiny.InputBinding();\n  let $ = global.jQuery;\n  $.extend(inputBinding, {\n    find: function(scope) {\n      return $(scope).find(\".crosstalk-input\");\n    },\n    initialize: function(el) {\n      if (!$(el).hasClass(\"crosstalk-input-bound\")) {\n        bindEl(el);\n      }\n    },\n    getId: function(el) {\n      return el.id;\n    },\n    getValue: function(el) {\n\n    },\n    setValue: function(el, value) {\n\n    },\n    receiveMessage: function(el, data) {\n\n    },\n    subscribe: function(el, callback) {\n      $(el).data(\"crosstalk-instance\").resume();\n    },\n    unsubscribe: function(el) {\n      $(el).data(\"crosstalk-instance\").suspend();\n    }\n  });\n  global.Shiny.inputBindings.register(inputBinding, \"crosstalk.inputBinding\");\n}\n",
-    "import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n  className: \"crosstalk-input-checkboxgroup\",\n\n  factory: function(el, data) {\n    /*\n     * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n     * group: \"ct-groupname\"\n     */\n    let ctHandle = new FilterHandle(data.group);\n\n    let lastKnownKeys;\n    let $el = $(el);\n    $el.on(\"change\", \"input[type='checkbox']\", function() {\n      let checked = $el.find(\"input[type='checkbox']:checked\");\n      if (checked.length === 0) {\n        lastKnownKeys = null;\n        ctHandle.clear();\n      } else {\n        let keys = {};\n        checked.each(function() {\n          data.map[this.value].forEach(function(key) {\n            keys[key] = true;\n          });\n        });\n        let keyArray = Object.keys(keys);\n        keyArray.sort();\n        lastKnownKeys = keyArray;\n        ctHandle.set(keyArray);\n      }\n    });\n\n    return {\n      suspend: function() {\n        ctHandle.clear();\n      },\n      resume: function() {\n        if (lastKnownKeys)\n          ctHandle.set(lastKnownKeys);\n      }\n    };\n  }\n});\n",
-    "import * as input from \"./input\";\nimport * as util from \"./util\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n  className: \"crosstalk-input-select\",\n\n  factory: function(el, data) {\n    /*\n     * items: {value: [...], label: [...]}\n     * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n     * group: \"ct-groupname\"\n     */\n\n    let first = [{value: \"\", label: \"(All)\"}];\n    let items = util.dataframeToD3(data.items);\n    let opts = {\n      options: first.concat(items),\n      valueField: \"value\",\n      labelField: \"label\",\n      searchField: \"label\"\n    };\n\n    let select = $(el).find(\"select\")[0];\n\n    let selectize = $(select).selectize(opts)[0].selectize;\n\n    let ctHandle = new FilterHandle(data.group);\n\n    let lastKnownKeys;\n    selectize.on(\"change\", function() {\n      if (selectize.items.length === 0) {\n        lastKnownKeys = null;\n        ctHandle.clear();\n      } else {\n        let keys = {};\n        selectize.items.forEach(function(group) {\n          data.map[group].forEach(function(key) {\n            keys[key] = true;\n          });\n        });\n        let keyArray = Object.keys(keys);\n        keyArray.sort();\n        lastKnownKeys = keyArray;\n        ctHandle.set(keyArray);\n      }\n    });\n\n    return {\n      suspend: function() {\n        ctHandle.clear();\n      },\n      resume: function() {\n        if (lastKnownKeys)\n          ctHandle.set(lastKnownKeys);\n      }\n    };\n  }\n});\n",
-    "import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\nlet strftime = global.strftime;\n\ninput.register({\n  className: \"crosstalk-input-slider\",\n\n  factory: function(el, data) {\n    /*\n     * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n     * group: \"ct-groupname\"\n     */\n    let ctHandle = new FilterHandle(data.group);\n\n    let opts = {};\n    let $el = $(el).find(\"input\");\n    let dataType = $el.data(\"data-type\");\n    let timeFormat = $el.data(\"time-format\");\n    let round = $el.data(\"round\");\n    let timeFormatter;\n\n    // Set up formatting functions\n    if (dataType === \"date\") {\n      timeFormatter = strftime.utc();\n      opts.prettify = function(num) {\n        return timeFormatter(timeFormat, new Date(num));\n      };\n\n    } else if (dataType === \"datetime\") {\n      let timezone = $el.data(\"timezone\");\n      if (timezone)\n        timeFormatter = strftime.timezone(timezone);\n      else\n        timeFormatter = strftime;\n\n      opts.prettify = function(num) {\n        return timeFormatter(timeFormat, new Date(num));\n      };\n    } else if (dataType === \"number\") {\n      if (typeof round !== \"undefined\")\n        opts.prettify = function(num) {\n          let factor = Math.pow(10, round);\n          return Math.round(num * factor) / factor;\n        };\n    }\n\n    $el.ionRangeSlider(opts);\n\n    function getValue() {\n      let result = $el.data(\"ionRangeSlider\").result;\n\n      // Function for converting numeric value from slider to appropriate type.\n      let convert;\n      let dataType = $el.data(\"data-type\");\n      if (dataType === \"date\") {\n        convert = function(val) {\n          return formatDateUTC(new Date(+val));\n        };\n      } else if (dataType === \"datetime\") {\n        convert = function(val) {\n          // Convert ms to s\n          return +val / 1000;\n        };\n      } else {\n        convert = function(val) { return +val; };\n      }\n\n      if ($el.data(\"ionRangeSlider\").options.type === \"double\") {\n        return [convert(result.from), convert(result.to)];\n      } else {\n        return convert(result.from);\n      }\n    }\n\n    let lastKnownKeys = null;\n\n    $el.on(\"change.crosstalkSliderInput\", function(event) {\n      if (!$el.data(\"updating\") && !$el.data(\"animating\")) {\n        let [from, to] = getValue();\n        let keys = [];\n        for (let i = 0; i < data.values.length; i++) {\n          let val = data.values[i];\n          if (val >= from && val <= to) {\n            keys.push(data.keys[i]);\n          }\n        }\n        keys.sort();\n        ctHandle.set(keys);\n        lastKnownKeys = keys;\n      }\n    });\n\n\n    // let $el = $(el);\n    // $el.on(\"change\", \"input[type=\"checkbox\"]\", function() {\n    //   let checked = $el.find(\"input[type=\"checkbox\"]:checked\");\n    //   if (checked.length === 0) {\n    //     ctHandle.clear();\n    //   } else {\n    //     let keys = {};\n    //     checked.each(function() {\n    //       data.map[this.value].forEach(function(key) {\n    //         keys[key] = true;\n    //       });\n    //     });\n    //     let keyArray = Object.keys(keys);\n    //     keyArray.sort();\n    //     ctHandle.set(keyArray);\n    //   }\n    // });\n\n    return {\n      suspend: function() {\n        ctHandle.clear();\n      },\n      resume: function() {\n        if (lastKnownKeys)\n          ctHandle.set(lastKnownKeys);\n      }\n    };\n  }\n});\n\n\n// Convert a number to a string with leading zeros\nfunction padZeros(n, digits) {\n  let str = n.toString();\n  while (str.length < digits)\n    str = \"0\" + str;\n  return str;\n}\n\n// Given a Date object, return a string in yyyy-mm-dd format, using the\n// UTC date. This may be a day off from the date in the local time zone.\nfunction formatDateUTC(date) {\n  if (date instanceof Date) {\n    return date.getUTCFullYear() + \"-\" +\n           padZeros(date.getUTCMonth()+1, 2) + \"-\" +\n           padZeros(date.getUTCDate(), 2);\n\n  } else {\n    return null;\n  }\n}\n",
-    "import Events from \"./events\";\nimport grp from \"./group\";\nimport * as util from \"./util\";\n\n/**\n * Use this class to read and write (and listen for changes to) the selection\n * for a Crosstalk group. This is intended to be used for linked brushing.\n *\n * If two (or more) `SelectionHandle` instances in the same webpage share the\n * same group name, they will share the same state. Setting the selection using\n * one `SelectionHandle` instance will result in the `value` property instantly\n * changing across the others, and `\"change\"` event listeners on all instances\n * (including the one that initiated the sending) will fire.\n *\n * @param {string} [group] - The name of the Crosstalk group, or if none,\n *   null or undefined (or any other falsy value). This can be changed later\n *   via the [SelectionHandle#setGroup](#setGroup) method.\n * @param {Object} [extraInfo] - An object whose properties will be copied to\n *   the event object whenever an event is emitted.\n */\nexport class SelectionHandle {\n\n  constructor(group = null, extraInfo = null) {\n    this._eventRelay = new Events();\n    this._emitter = new util.SubscriptionTracker(this._eventRelay);\n\n    // Name of the group we're currently tracking, if any. Can change over time.\n    this._group = null;\n    // The Var we're currently tracking, if any. Can change over time.\n    this._var = null;\n    // The event handler subscription we currently have on var.on(\"change\").\n    this._varOnChangeSub = null;\n\n    this._extraInfo = util.extend({ sender: this }, extraInfo);\n\n    this.setGroup(group);\n  }\n\n  /**\n   * Changes the Crosstalk group membership of this SelectionHandle. The group\n   * being switched away from (if any) will not have its selection value\n   * modified as a result of calling `setGroup`, even if this handle was the\n   * most recent handle to set the selection of the group.\n   *\n   * The group being switched to (if any) will also not have its selection value\n   * modified as a result of calling `setGroup`. If you want to set the\n   * selection value of the new group, call `set` explicitly.\n   *\n   * @param {string} group - The name of the Crosstalk group, or null (or\n   *   undefined) to clear the group.\n   */\n  setGroup(group) {\n    // If group is unchanged, do nothing\n    if (this._group === group)\n      return;\n    // Treat null, undefined, and other falsy values the same\n    if (!this._group && !group)\n      return;\n\n    if (this._var) {\n      this._var.off(\"change\", this._varOnChangeSub);\n      this._var = null;\n      this._varOnChangeSub = null;\n    }\n\n    this._group = group;\n\n    if (group) {\n      this._var = grp(group).var(\"selection\");\n      let sub = this._var.on(\"change\", (e) => {\n        this._eventRelay.trigger(\"change\", e, this);\n      });\n      this._varOnChangeSub = sub;\n    }\n  }\n\n  /**\n   * Retrieves the current selection for the group represented by this\n   * `SelectionHandle`.\n   *\n   * - If no selection is active, then this value will be falsy.\n   * - If a selection is active, but no data points are selected, then this\n   *   value will be an empty array.\n   * - If a selection is active, and data points are selected, then the keys\n   *   of the selected data points will be present in the array.\n   */\n  get value() {\n    return this._var ? this._var.get() : null;\n  }\n\n  /**\n   * Combines the given `extraInfo` (if any) with the handle's default\n   * `_extraInfo` (if any).\n   * @private\n   */\n  _mergeExtraInfo(extraInfo) {\n    // Important incidental effect: shallow clone is returned\n    return util.extend({},\n      this._extraInfo ? this._extraInfo : null,\n      extraInfo ? extraInfo : null);\n  }\n\n  /**\n   * Overwrites the current selection for the group, and raises the `\"change\"`\n   * event among all of the group's '`SelectionHandle` instances (including\n   * this one).\n   *\n   * @fires SelectionHandle#change\n   * @param {string[]} selectedKeys - Falsy, empty array, or array of keys (see\n   *   {@link SelectionHandle#value}).\n   * @param {Object} [extraInfo] - Extra properties to be included on the event\n   *   object that's passed to listeners (in addition to any options that were\n   *   passed into the `SelectionHandle` constructor).\n   */\n  set(selectedKeys, extraInfo) {\n    if (this._var)\n      this._var.set(selectedKeys, this._mergeExtraInfo(extraInfo));\n  }\n\n  /**\n   * Overwrites the current selection for the group, and raises the `\"change\"`\n   * event among all of the group's '`SelectionHandle` instances (including\n   * this one).\n   *\n   * @fires SelectionHandle#change\n   * @param {Object} [extraInfo] - Extra properties to be included on the event\n   *   object that's passed to listeners (in addition to any that were passed\n   *   into the `SelectionHandle` constructor).\n   */\n  clear(extraInfo) {\n    if (this._var)\n      this.set(void 0, this._mergeExtraInfo(extraInfo));\n  }\n\n  /**\n   * Subscribes to events on this `SelectionHandle`.\n   *\n   * @param {string} eventType - Indicates the type of events to listen to.\n   *   Currently, only `\"change\"` is supported.\n   * @param {SelectionHandle~listener} listener - The callback function that\n   *   will be invoked when the event occurs.\n   * @return {string} - A token to pass to {@link SelectionHandle#off} to cancel\n   *   this subscription.\n   */\n  on(eventType, listener) {\n    return this._emitter.on(eventType, listener);\n  }\n\n  /**\n   * Cancels event subscriptions created by {@link SelectionHandle#on}.\n   *\n   * @param {string} eventType - The type of event to unsubscribe.\n   * @param {string|SelectionHandle~listener} listener - Either the callback\n   *   function previously passed into {@link SelectionHandle#on}, or the\n   *   string that was returned from {@link SelectionHandle#on}.\n   */\n  off(eventType, listener) {\n    return this._emitter.off(eventType, listener);\n  }\n\n  /**\n   * Shuts down the `SelectionHandle` object.\n   *\n   * Removes all event listeners that were added through this handle.\n   */\n  close() {\n    this._emitter.removeAllListeners();\n    this.setGroup(null);\n  }\n}\n\n/**\n * @callback SelectionHandle~listener\n * @param {Object} event - An object containing details of the event. For\n *   `\"change\"` events, this includes the properties `value` (the new\n *   value of the selection, or `undefined` if no selection is active),\n *   `oldValue` (the previous value of the selection), and `sender` (the\n *   `SelectionHandle` instance that made the change).\n */\n\n/**\n * @event SelectionHandle#change\n * @type {object}\n * @property {object} value - The new value of the selection, or `undefined`\n *   if no selection is active.\n * @property {object} oldValue - The previous value of the selection.\n * @property {SelectionHandle} sender - The `SelectionHandle` instance that\n *   changed the value.\n */\n",
-    "export function extend(target, ...sources) {\n  for (let i = 0; i < sources.length; i++) {\n    let src = sources[i];\n    if (typeof(src) === \"undefined\" || src === null)\n      continue;\n\n    for (let key in src) {\n      if (src.hasOwnProperty(key)) {\n        target[key] = src[key];\n      }\n    }\n  }\n  return target;\n}\n\nexport function checkSorted(list) {\n  for (let i = 1; i < list.length; i++) {\n    if (list[i] <= list[i-1]) {\n      throw new Error(\"List is not sorted or contains duplicate\");\n    }\n  }\n}\n\nexport function diffSortedLists(a, b) {\n  let i_a = 0;\n  let i_b = 0;\n\n  if (!a) a = [];\n  if (!b) b = [];\n\n  let a_only = [];\n  let b_only = [];\n\n  checkSorted(a);\n  checkSorted(b);\n\n  while (i_a < a.length && i_b < b.length) {\n    if (a[i_a] === b[i_b]) {\n      i_a++;\n      i_b++;\n    } else if (a[i_a] < b[i_b]) {\n      a_only.push(a[i_a++]);\n    } else {\n      b_only.push(b[i_b++]);\n    }\n  }\n\n  if (i_a < a.length)\n    a_only = a_only.concat(a.slice(i_a));\n  if (i_b < b.length)\n    b_only = b_only.concat(b.slice(i_b));\n  return {\n    removed: a_only,\n    added: b_only\n  };\n}\n\n// Convert from wide: { colA: [1,2,3], colB: [4,5,6], ... }\n// to long: [ {colA: 1, colB: 4}, {colA: 2, colB: 5}, ... ]\nexport function dataframeToD3(df) {\n  let names = [];\n  let length;\n  for (let name in df) {\n    if (df.hasOwnProperty(name))\n      names.push(name);\n    if (typeof(df[name]) !== \"object\" || typeof(df[name].length) === \"undefined\") {\n      throw new Error(\"All fields must be arrays\");\n    } else if (typeof(length) !== \"undefined\" && length !== df[name].length) {\n      throw new Error(\"All fields must be arrays of the same length\");\n    }\n    length = df[name].length;\n  }\n  let results = [];\n  let item;\n  for (let row = 0; row < length; row++) {\n    item = {};\n    for (let col = 0; col < names.length; col++) {\n      item[names[col]] = df[names[col]][row];\n    }\n    results.push(item);\n  }\n  return results;\n}\n\n/**\n * Keeps track of all event listener additions/removals and lets all active\n * listeners be removed with a single operation.\n *\n * @private\n */\nexport class SubscriptionTracker {\n  constructor(emitter) {\n    this._emitter = emitter;\n    this._subs = {};\n  }\n\n  on(eventType, listener) {\n    let sub = this._emitter.on(eventType, listener);\n    this._subs[sub] = eventType;\n    return sub;\n  }\n\n  off(eventType, listener) {\n    let sub = this._emitter.off(eventType, listener);\n    if (sub) {\n      delete this._subs[sub];\n    }\n    return sub;\n  }\n\n  removeAllListeners() {\n    let current_subs = this._subs;\n    this._subs = {};\n    Object.keys(current_subs).forEach((sub) => {\n      this._emitter.off(current_subs[sub], sub);\n    });\n  }\n}\n",
-    "import Events from \"./events\";\n\nexport default class Var {\n  constructor(group, name, /*optional*/ value) {\n    this._group = group;\n    this._name = name;\n    this._value = value;\n    this._events = new Events();\n  }\n\n  get() {\n    return this._value;\n  }\n\n  set(value, /*optional*/ event) {\n    if (this._value === value) {\n      // Do nothing; the value hasn't changed\n      return;\n    }\n    let oldValue = this._value;\n    this._value = value;\n    // Alert JavaScript listeners that the value has changed\n    let evt = {};\n    if (event && typeof(event) === \"object\") {\n      for (let k in event) {\n        if (event.hasOwnProperty(k))\n          evt[k] = event[k];\n      }\n    }\n    evt.oldValue = oldValue;\n    evt.value = value;\n    this._events.trigger(\"change\", evt, this);\n\n    // TODO: Make this extensible, to let arbitrary back-ends know that\n    // something has changed\n    if (global.Shiny && global.Shiny.onInputChange) {\n      global.Shiny.onInputChange(\n        \".clientValue-\" +\n          (this._group.name !== null ? this._group.name + \"-\" : \"\") +\n          this._name,\n        typeof(value) === \"undefined\" ? null : value\n      );\n    }\n  }\n\n  on(eventType, listener) {\n    return this._events.on(eventType, listener);\n  }\n\n  off(eventType, listener) {\n    return this._events.off(eventType, listener);\n  }\n}\n"
-  ]
-}
\ No newline at end of file
diff --git a/docs/coverage/lib/crosstalk-1.2.1/js/crosstalk.min.js b/docs/coverage/lib/crosstalk-1.2.1/js/crosstalk.min.js
deleted file mode 100644
index b7ec0ac9..00000000
--- a/docs/coverage/lib/crosstalk-1.2.1/js/crosstalk.min.js
+++ /dev/null
@@ -1,2 +0,0 @@
-!function o(u,a,l){function s(n,e){if(!a[n]){if(!u[n]){var t="function"==typeof require&&require;if(!e&&t)return t(n,!0);if(f)return f(n,!0);var r=new Error("Cannot find module '"+n+"'");throw r.code="MODULE_NOT_FOUND",r}var i=a[n]={exports:{}};u[n][0].call(i.exports,function(e){var t=u[n][1][e];return s(t||e)},i,i.exports,o,u,a,l)}return a[n].exports}for(var f="function"==typeof require&&require,e=0;e?@[\\\]^`{|}~])/g,"\\$1")+"']"),r=JSON.parse(n[0].innerText),i=e.factory(t,r);o(t).data("crosstalk-instance",i),o(t).addClass("crosstalk-input-bound")}if(t.Shiny){var e=new t.Shiny.InputBinding,u=t.jQuery;u.extend(e,{find:function(e){return u(e).find(".crosstalk-input")},initialize:function(e){var t,n;u(e).hasClass("crosstalk-input-bound")||(n=o(t=e),Object.keys(r).forEach(function(e){n.hasClass(e)&&!n.hasClass("crosstalk-input-bound")&&i(r[e],t)}))},getId:function(e){return e.id},getValue:function(e){},setValue:function(e,t){},receiveMessage:function(e,t){},subscribe:function(e,t){u(e).data("crosstalk-instance").resume()},unsubscribe:function(e){u(e).data("crosstalk-instance").suspend()}}),t.Shiny.inputBindings.register(e,"crosstalk.inputBinding")}}).call(this,"undefined"!=typeof global?global:"undefined"!=typeof self?self:"undefined"!=typeof window?window:{})},{}],7:[function(r,e,t){(function(e){"use strict";var t=function(e){{if(e&&e.__esModule)return e;var t={};if(null!=e)for(var n in e)Object.prototype.hasOwnProperty.call(e,n)&&(t[n]=e[n]);return t.default=e,t}}(r("./input")),n=r("./filter");var a=e.jQuery;t.register({className:"crosstalk-input-checkboxgroup",factory:function(e,r){var i=new n.FilterHandle(r.group),o=void 0,u=a(e);return u.on("change","input[type='checkbox']",function(){var e=u.find("input[type='checkbox']:checked");if(0===e.length)o=null,i.clear();else{var t={};e.each(function(){r.map[this.value].forEach(function(e){t[e]=!0})});var n=Object.keys(t);n.sort(),o=n,i.set(n)}}),{suspend:function(){i.clear()},resume:function(){o&&i.set(o)}}}})}).call(this,"undefined"!=typeof global?global:"undefined"!=typeof self?self:"undefined"!=typeof window?window:{})},{"./filter":2,"./input":6}],8:[function(r,e,t){(function(e){"use strict";var t=n(r("./input")),l=n(r("./util")),s=r("./filter");function n(e){if(e&&e.__esModule)return e;var t={};if(null!=e)for(var n in e)Object.prototype.hasOwnProperty.call(e,n)&&(t[n]=e[n]);return t.default=e,t}var f=e.jQuery;t.register({className:"crosstalk-input-select",factory:function(e,n){var t=l.dataframeToD3(n.items),r={options:[{value:"",label:"(All)"}].concat(t),valueField:"value",labelField:"label",searchField:"label"},i=f(e).find("select")[0],o=f(i).selectize(r)[0].selectize,u=new s.FilterHandle(n.group),a=void 0;return o.on("change",function(){if(0===o.items.length)a=null,u.clear();else{var t={};o.items.forEach(function(e){n.map[e].forEach(function(e){t[e]=!0})});var e=Object.keys(t);e.sort(),a=e,u.set(e)}}),{suspend:function(){u.clear()},resume:function(){a&&u.set(a)}}}})}).call(this,"undefined"!=typeof global?global:"undefined"!=typeof self?self:"undefined"!=typeof window?window:{})},{"./filter":2,"./input":6,"./util":11}],9:[function(n,e,t){(function(e){"use strict";var d=function(e,t){if(Array.isArray(e))return e;if(Symbol.iterator in Object(e))return function(e,t){var n=[],r=!0,i=!1,o=void 0;try{for(var u,a=e[Symbol.iterator]();!(r=(u=a.next()).done)&&(n.push(u.value),!t||n.length!==t);r=!0);}catch(e){i=!0,o=e}finally{try{!r&&a.return&&a.return()}finally{if(i)throw o}}return n}(e,t);throw new TypeError("Invalid attempt to destructure non-iterable instance")},t=function(e){{if(e&&e.__esModule)return e;var t={};if(null!=e)for(var n in e)Object.prototype.hasOwnProperty.call(e,n)&&(t[n]=e[n]);return t.default=e,t}}(n("./input")),a=n("./filter");var v=e.jQuery,p=e.strftime;function y(e,t){for(var n=e.toString();n.length {\n        this._eventRelay.trigger(\"change\", e, this);\n      });\n      this._varOnChangeSub = sub;\n    }\n  }\n\n  /**\n   * Combine the given `extraInfo` (if any) with the handle's default\n   * `_extraInfo` (if any).\n   * @private\n   */\n  _mergeExtraInfo(extraInfo) {\n    return util.extend({},\n      this._extraInfo ? this._extraInfo : null,\n      extraInfo ? extraInfo : null);\n  }\n\n  /**\n   * Close the handle. This clears this handle's contribution to the filter set,\n   * and unsubscribes all event listeners.\n   */\n  close() {\n    this._emitter.removeAllListeners();\n    this.clear();\n    this.setGroup(null);\n  }\n\n  /**\n   * Clear this handle's contribution to the filter set.\n   *\n   * @param {Object} [extraInfo] - Extra properties to be included on the event\n   *   object that's passed to listeners (in addition to any options that were\n   *   passed into the `FilterHandle` constructor).\n   * \n   * @fires FilterHandle#change\n   */\n  clear(extraInfo) {\n    if (!this._filterSet)\n      return;\n    this._filterSet.clear(this._id);\n    this._onChange(extraInfo);\n  }\n\n  /**\n   * Set this handle's contribution to the filter set. This array should consist\n   * of the keys of the rows that _should_ be displayed; any keys that are not\n   * present in the array will be considered _filtered out_. Note that multiple\n   * `FilterHandle` instances in the group may each contribute an array of keys,\n   * and only those keys that appear in _all_ of the arrays make it through the\n   * filter.\n   *\n   * @param {string[]} keys - Empty array, or array of keys. To clear the\n   *   filter, don't pass an empty array; instead, use the\n   *   {@link FilterHandle#clear} method.\n   * @param {Object} [extraInfo] - Extra properties to be included on the event\n   *   object that's passed to listeners (in addition to any options that were\n   *   passed into the `FilterHandle` constructor).\n   * \n   * @fires FilterHandle#change\n   */\n  set(keys, extraInfo) {\n    if (!this._filterSet)\n      return;\n    this._filterSet.update(this._id, keys);\n    this._onChange(extraInfo);\n  }\n\n  /**\n   * @return {string[]|null} - Either: 1) an array of keys that made it through\n   *   all of the `FilterHandle` instances, or, 2) `null`, which means no filter\n   *   is being applied (all data should be displayed).\n   */\n  get filteredKeys() {\n    return this._filterSet ? this._filterSet.value : null;\n  }\n\n  /**\n   * Subscribe to events on this `FilterHandle`.\n   *\n   * @param {string} eventType - Indicates the type of events to listen to.\n   *   Currently, only `\"change\"` is supported.\n   * @param {FilterHandle~listener} listener - The callback function that\n   *   will be invoked when the event occurs.\n   * @return {string} - A token to pass to {@link FilterHandle#off} to cancel\n   *   this subscription.\n   */\n  on(eventType, listener) {\n    return this._emitter.on(eventType, listener);\n  }\n\n  /**\n   * Cancel event subscriptions created by {@link FilterHandle#on}.\n   *\n   * @param {string} eventType - The type of event to unsubscribe.\n   * @param {string|FilterHandle~listener} listener - Either the callback\n   *   function previously passed into {@link FilterHandle#on}, or the\n   *   string that was returned from {@link FilterHandle#on}.\n   */\n  off(eventType, listener) {\n    return this._emitter.off(eventType, listener);\n  }\n\n  _onChange(extraInfo) {\n    if (!this._filterSet)\n      return;\n    this._filterVar.set(this._filterSet.value, this._mergeExtraInfo(extraInfo));\n  }\n\n  /**\n   * @callback FilterHandle~listener\n   * @param {Object} event - An object containing details of the event. For\n   *   `\"change\"` events, this includes the properties `value` (the new\n   *   value of the filter set, or `null` if no filter set is active),\n   *   `oldValue` (the previous value of the filter set), and `sender` (the\n   *   `FilterHandle` instance that made the change).\n   */\n\n}\n\n/**\n * @event FilterHandle#change\n * @type {object}\n * @property {object} value - The new value of the filter set, or `null`\n *   if no filter set is active.\n * @property {object} oldValue - The previous value of the filter set.\n * @property {FilterHandle} sender - The `FilterHandle` instance that\n *   changed the value.\n */\n","import { diffSortedLists } from \"./util\";\n\nfunction naturalComparator(a, b) {\n  if (a === b) {\n    return 0;\n  } else if (a < b) {\n    return -1;\n  } else if (a > b) {\n    return 1;\n  }\n}\n\n/**\n * @private\n */\nexport default class FilterSet {\n  constructor() {\n    this.reset();\n  }\n\n  reset() {\n    // Key: handle ID, Value: array of selected keys, or null\n    this._handles = {};\n    // Key: key string, Value: count of handles that include it\n    this._keys = {};\n    this._value = null;\n    this._activeHandles = 0;\n  }\n\n  get value() {\n    return this._value;\n  }\n\n  update(handleId, keys) {\n    if (keys !== null) {\n      keys = keys.slice(0); // clone before sorting\n      keys.sort(naturalComparator);\n    }\n\n    let {added, removed} = diffSortedLists(this._handles[handleId], keys);\n    this._handles[handleId] = keys;\n\n    for (let i = 0; i < added.length; i++) {\n      this._keys[added[i]] = (this._keys[added[i]] || 0) + 1;\n    }\n    for (let i = 0; i < removed.length; i++) {\n      this._keys[removed[i]]--;\n    }\n\n    this._updateValue(keys);\n  }\n\n  /**\n   * @param {string[]} keys Sorted array of strings that indicate\n   * a superset of possible keys.\n   * @private\n   */\n  _updateValue(keys = this._allKeys) {\n    let handleCount = Object.keys(this._handles).length;\n    if (handleCount === 0) {\n      this._value = null;\n    } else {\n      this._value = [];\n      for (let i = 0; i < keys.length; i++) {\n        let count = this._keys[keys[i]];\n        if (count === handleCount) {\n          this._value.push(keys[i]);\n        }\n      }\n    }\n  }\n\n  clear(handleId) {\n    if (typeof(this._handles[handleId]) === \"undefined\") {\n      return;\n    }\n\n    let keys = this._handles[handleId];\n    if (!keys) {\n      keys = [];\n    }\n\n    for (let i = 0; i < keys.length; i++) {\n      this._keys[keys[i]]--;\n    }\n    delete this._handles[handleId];\n\n    this._updateValue();\n  }\n\n  get _allKeys() {\n    let allKeys = Object.keys(this._keys);\n    allKeys.sort(naturalComparator);\n    return allKeys;\n  }\n}\n","import Var from \"./var\";\n\n// Use a global so that multiple copies of crosstalk.js can be loaded and still\n// have groups behave as singletons across all copies.\nglobal.__crosstalk_groups = global.__crosstalk_groups || {};\nlet groups = global.__crosstalk_groups;\n\nexport default function group(groupName) {\n  if (groupName && typeof(groupName) === \"string\") {\n    if (!groups.hasOwnProperty(groupName)) {\n      groups[groupName] = new Group(groupName);\n    }\n    return groups[groupName];\n  } else if (typeof(groupName) === \"object\" && groupName._vars && groupName.var) {\n    // Appears to already be a group object\n    return groupName;\n  } else if (Array.isArray(groupName) &&\n      groupName.length == 1 &&\n      typeof(groupName[0]) === \"string\") {\n    return group(groupName[0]);\n  } else {\n    throw new Error(\"Invalid groupName argument\");\n  }\n}\n\nclass Group {\n  constructor(name) {\n    this.name = name;\n    this._vars = {};\n  }\n\n  var(name) {\n    if (!name || typeof(name) !== \"string\") {\n      throw new Error(\"Invalid var name\");\n    }\n\n    if (!this._vars.hasOwnProperty(name))\n      this._vars[name] = new Var(this, name);\n    return this._vars[name];\n  }\n\n  has(name) {\n    if (!name || typeof(name) !== \"string\") {\n      throw new Error(\"Invalid var name\");\n    }\n\n    return this._vars.hasOwnProperty(name);\n  }\n}\n","import group from \"./group\";\nimport { SelectionHandle } from \"./selection\";\nimport { FilterHandle } from \"./filter\";\nimport { bind } from \"./input\";\nimport \"./input_selectize\";\nimport \"./input_checkboxgroup\";\nimport \"./input_slider\";\n\nconst defaultGroup = group(\"default\");\n\nfunction var_(name) {\n  return defaultGroup.var(name);\n}\n\nfunction has(name) {\n  return defaultGroup.has(name);\n}\n\nif (global.Shiny) {\n  global.Shiny.addCustomMessageHandler(\"update-client-value\", function(message) {\n    if (typeof(message.group) === \"string\") {\n      group(message.group).var(message.name).set(message.value);\n    } else {\n      var_(message.name).set(message.value);\n    }\n  });\n}\n\nconst crosstalk = {\n  group: group,\n  var: var_,\n  has: has,\n  SelectionHandle: SelectionHandle,\n  FilterHandle: FilterHandle,\n  bind: bind\n};\n\n/**\n * @namespace crosstalk\n */\nexport default crosstalk;\nglobal.crosstalk = crosstalk;\n","let $ = global.jQuery;\n\nlet bindings = {};\n\nexport function register(reg) {\n  bindings[reg.className] = reg;\n  if (global.document && global.document.readyState !== \"complete\") {\n    $(() => {\n      bind();\n    });\n  } else if (global.document) {\n    setTimeout(bind, 100);\n  }\n}\n\nexport function bind() {\n  Object.keys(bindings).forEach(function(className) {\n    let binding = bindings[className];\n    $(\".\" + binding.className).not(\".crosstalk-input-bound\").each(function(i, el) {\n      bindInstance(binding, el);\n    });\n  });\n}\n\n// Escape jQuery identifier\nfunction $escape(val) {\n  return val.replace(/([!\"#$%&'()*+,./:;<=>?@[\\\\\\]^`{|}~])/g, \"\\\\$1\");\n}\n\nfunction bindEl(el) {\n  let $el = $(el);\n  Object.keys(bindings).forEach(function(className) {\n    if ($el.hasClass(className) && !$el.hasClass(\"crosstalk-input-bound\")) {\n      let binding = bindings[className];\n      bindInstance(binding, el);\n    }\n  });\n}\n\nfunction bindInstance(binding, el) {\n  let jsonEl = $(el).find(\"script[type='application/json'][data-for='\" + $escape(el.id) + \"']\");\n  let data = JSON.parse(jsonEl[0].innerText);\n\n  let instance = binding.factory(el, data);\n  $(el).data(\"crosstalk-instance\", instance);\n  $(el).addClass(\"crosstalk-input-bound\");\n}\n\nif (global.Shiny) {\n  let inputBinding = new global.Shiny.InputBinding();\n  let $ = global.jQuery;\n  $.extend(inputBinding, {\n    find: function(scope) {\n      return $(scope).find(\".crosstalk-input\");\n    },\n    initialize: function(el) {\n      if (!$(el).hasClass(\"crosstalk-input-bound\")) {\n        bindEl(el);\n      }\n    },\n    getId: function(el) {\n      return el.id;\n    },\n    getValue: function(el) {\n\n    },\n    setValue: function(el, value) {\n\n    },\n    receiveMessage: function(el, data) {\n\n    },\n    subscribe: function(el, callback) {\n      $(el).data(\"crosstalk-instance\").resume();\n    },\n    unsubscribe: function(el) {\n      $(el).data(\"crosstalk-instance\").suspend();\n    }\n  });\n  global.Shiny.inputBindings.register(inputBinding, \"crosstalk.inputBinding\");\n}\n","import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n  className: \"crosstalk-input-checkboxgroup\",\n\n  factory: function(el, data) {\n    /*\n     * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n     * group: \"ct-groupname\"\n     */\n    let ctHandle = new FilterHandle(data.group);\n\n    let lastKnownKeys;\n    let $el = $(el);\n    $el.on(\"change\", \"input[type='checkbox']\", function() {\n      let checked = $el.find(\"input[type='checkbox']:checked\");\n      if (checked.length === 0) {\n        lastKnownKeys = null;\n        ctHandle.clear();\n      } else {\n        let keys = {};\n        checked.each(function() {\n          data.map[this.value].forEach(function(key) {\n            keys[key] = true;\n          });\n        });\n        let keyArray = Object.keys(keys);\n        keyArray.sort();\n        lastKnownKeys = keyArray;\n        ctHandle.set(keyArray);\n      }\n    });\n\n    return {\n      suspend: function() {\n        ctHandle.clear();\n      },\n      resume: function() {\n        if (lastKnownKeys)\n          ctHandle.set(lastKnownKeys);\n      }\n    };\n  }\n});\n","import * as input from \"./input\";\nimport * as util from \"./util\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\n\ninput.register({\n  className: \"crosstalk-input-select\",\n\n  factory: function(el, data) {\n    /*\n     * items: {value: [...], label: [...]}\n     * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n     * group: \"ct-groupname\"\n     */\n\n    let first = [{value: \"\", label: \"(All)\"}];\n    let items = util.dataframeToD3(data.items);\n    let opts = {\n      options: first.concat(items),\n      valueField: \"value\",\n      labelField: \"label\",\n      searchField: \"label\"\n    };\n\n    let select = $(el).find(\"select\")[0];\n\n    let selectize = $(select).selectize(opts)[0].selectize;\n\n    let ctHandle = new FilterHandle(data.group);\n\n    let lastKnownKeys;\n    selectize.on(\"change\", function() {\n      if (selectize.items.length === 0) {\n        lastKnownKeys = null;\n        ctHandle.clear();\n      } else {\n        let keys = {};\n        selectize.items.forEach(function(group) {\n          data.map[group].forEach(function(key) {\n            keys[key] = true;\n          });\n        });\n        let keyArray = Object.keys(keys);\n        keyArray.sort();\n        lastKnownKeys = keyArray;\n        ctHandle.set(keyArray);\n      }\n    });\n\n    return {\n      suspend: function() {\n        ctHandle.clear();\n      },\n      resume: function() {\n        if (lastKnownKeys)\n          ctHandle.set(lastKnownKeys);\n      }\n    };\n  }\n});\n","import * as input from \"./input\";\nimport { FilterHandle } from \"./filter\";\n\nlet $ = global.jQuery;\nlet strftime = global.strftime;\n\ninput.register({\n  className: \"crosstalk-input-slider\",\n\n  factory: function(el, data) {\n    /*\n     * map: {\"groupA\": [\"keyA\", \"keyB\", ...], ...}\n     * group: \"ct-groupname\"\n     */\n    let ctHandle = new FilterHandle(data.group);\n\n    let opts = {};\n    let $el = $(el).find(\"input\");\n    let dataType = $el.data(\"data-type\");\n    let timeFormat = $el.data(\"time-format\");\n    let round = $el.data(\"round\");\n    let timeFormatter;\n\n    // Set up formatting functions\n    if (dataType === \"date\") {\n      timeFormatter = strftime.utc();\n      opts.prettify = function(num) {\n        return timeFormatter(timeFormat, new Date(num));\n      };\n\n    } else if (dataType === \"datetime\") {\n      let timezone = $el.data(\"timezone\");\n      if (timezone)\n        timeFormatter = strftime.timezone(timezone);\n      else\n        timeFormatter = strftime;\n\n      opts.prettify = function(num) {\n        return timeFormatter(timeFormat, new Date(num));\n      };\n    } else if (dataType === \"number\") {\n      if (typeof round !== \"undefined\")\n        opts.prettify = function(num) {\n          let factor = Math.pow(10, round);\n          return Math.round(num * factor) / factor;\n        };\n    }\n\n    $el.ionRangeSlider(opts);\n\n    function getValue() {\n      let result = $el.data(\"ionRangeSlider\").result;\n\n      // Function for converting numeric value from slider to appropriate type.\n      let convert;\n      let dataType = $el.data(\"data-type\");\n      if (dataType === \"date\") {\n        convert = function(val) {\n          return formatDateUTC(new Date(+val));\n        };\n      } else if (dataType === \"datetime\") {\n        convert = function(val) {\n          // Convert ms to s\n          return +val / 1000;\n        };\n      } else {\n        convert = function(val) { return +val; };\n      }\n\n      if ($el.data(\"ionRangeSlider\").options.type === \"double\") {\n        return [convert(result.from), convert(result.to)];\n      } else {\n        return convert(result.from);\n      }\n    }\n\n    let lastKnownKeys = null;\n\n    $el.on(\"change.crosstalkSliderInput\", function(event) {\n      if (!$el.data(\"updating\") && !$el.data(\"animating\")) {\n        let [from, to] = getValue();\n        let keys = [];\n        for (let i = 0; i < data.values.length; i++) {\n          let val = data.values[i];\n          if (val >= from && val <= to) {\n            keys.push(data.keys[i]);\n          }\n        }\n        keys.sort();\n        ctHandle.set(keys);\n        lastKnownKeys = keys;\n      }\n    });\n\n\n    // let $el = $(el);\n    // $el.on(\"change\", \"input[type=\"checkbox\"]\", function() {\n    //   let checked = $el.find(\"input[type=\"checkbox\"]:checked\");\n    //   if (checked.length === 0) {\n    //     ctHandle.clear();\n    //   } else {\n    //     let keys = {};\n    //     checked.each(function() {\n    //       data.map[this.value].forEach(function(key) {\n    //         keys[key] = true;\n    //       });\n    //     });\n    //     let keyArray = Object.keys(keys);\n    //     keyArray.sort();\n    //     ctHandle.set(keyArray);\n    //   }\n    // });\n\n    return {\n      suspend: function() {\n        ctHandle.clear();\n      },\n      resume: function() {\n        if (lastKnownKeys)\n          ctHandle.set(lastKnownKeys);\n      }\n    };\n  }\n});\n\n\n// Convert a number to a string with leading zeros\nfunction padZeros(n, digits) {\n  let str = n.toString();\n  while (str.length < digits)\n    str = \"0\" + str;\n  return str;\n}\n\n// Given a Date object, return a string in yyyy-mm-dd format, using the\n// UTC date. This may be a day off from the date in the local time zone.\nfunction formatDateUTC(date) {\n  if (date instanceof Date) {\n    return date.getUTCFullYear() + \"-\" +\n           padZeros(date.getUTCMonth()+1, 2) + \"-\" +\n           padZeros(date.getUTCDate(), 2);\n\n  } else {\n    return null;\n  }\n}\n","import Events from \"./events\";\nimport grp from \"./group\";\nimport * as util from \"./util\";\n\n/**\n * Use this class to read and write (and listen for changes to) the selection\n * for a Crosstalk group. This is intended to be used for linked brushing.\n *\n * If two (or more) `SelectionHandle` instances in the same webpage share the\n * same group name, they will share the same state. Setting the selection using\n * one `SelectionHandle` instance will result in the `value` property instantly\n * changing across the others, and `\"change\"` event listeners on all instances\n * (including the one that initiated the sending) will fire.\n *\n * @param {string} [group] - The name of the Crosstalk group, or if none,\n *   null or undefined (or any other falsy value). This can be changed later\n *   via the [SelectionHandle#setGroup](#setGroup) method.\n * @param {Object} [extraInfo] - An object whose properties will be copied to\n *   the event object whenever an event is emitted.\n */\nexport class SelectionHandle {\n\n  constructor(group = null, extraInfo = null) {\n    this._eventRelay = new Events();\n    this._emitter = new util.SubscriptionTracker(this._eventRelay);\n\n    // Name of the group we're currently tracking, if any. Can change over time.\n    this._group = null;\n    // The Var we're currently tracking, if any. Can change over time.\n    this._var = null;\n    // The event handler subscription we currently have on var.on(\"change\").\n    this._varOnChangeSub = null;\n\n    this._extraInfo = util.extend({ sender: this }, extraInfo);\n\n    this.setGroup(group);\n  }\n\n  /**\n   * Changes the Crosstalk group membership of this SelectionHandle. The group\n   * being switched away from (if any) will not have its selection value\n   * modified as a result of calling `setGroup`, even if this handle was the\n   * most recent handle to set the selection of the group.\n   *\n   * The group being switched to (if any) will also not have its selection value\n   * modified as a result of calling `setGroup`. If you want to set the\n   * selection value of the new group, call `set` explicitly.\n   *\n   * @param {string} group - The name of the Crosstalk group, or null (or\n   *   undefined) to clear the group.\n   */\n  setGroup(group) {\n    // If group is unchanged, do nothing\n    if (this._group === group)\n      return;\n    // Treat null, undefined, and other falsy values the same\n    if (!this._group && !group)\n      return;\n\n    if (this._var) {\n      this._var.off(\"change\", this._varOnChangeSub);\n      this._var = null;\n      this._varOnChangeSub = null;\n    }\n\n    this._group = group;\n\n    if (group) {\n      this._var = grp(group).var(\"selection\");\n      let sub = this._var.on(\"change\", (e) => {\n        this._eventRelay.trigger(\"change\", e, this);\n      });\n      this._varOnChangeSub = sub;\n    }\n  }\n\n  /**\n   * Retrieves the current selection for the group represented by this\n   * `SelectionHandle`.\n   *\n   * - If no selection is active, then this value will be falsy.\n   * - If a selection is active, but no data points are selected, then this\n   *   value will be an empty array.\n   * - If a selection is active, and data points are selected, then the keys\n   *   of the selected data points will be present in the array.\n   */\n  get value() {\n    return this._var ? this._var.get() : null;\n  }\n\n  /**\n   * Combines the given `extraInfo` (if any) with the handle's default\n   * `_extraInfo` (if any).\n   * @private\n   */\n  _mergeExtraInfo(extraInfo) {\n    // Important incidental effect: shallow clone is returned\n    return util.extend({},\n      this._extraInfo ? this._extraInfo : null,\n      extraInfo ? extraInfo : null);\n  }\n\n  /**\n   * Overwrites the current selection for the group, and raises the `\"change\"`\n   * event among all of the group's '`SelectionHandle` instances (including\n   * this one).\n   *\n   * @fires SelectionHandle#change\n   * @param {string[]} selectedKeys - Falsy, empty array, or array of keys (see\n   *   {@link SelectionHandle#value}).\n   * @param {Object} [extraInfo] - Extra properties to be included on the event\n   *   object that's passed to listeners (in addition to any options that were\n   *   passed into the `SelectionHandle` constructor).\n   */\n  set(selectedKeys, extraInfo) {\n    if (this._var)\n      this._var.set(selectedKeys, this._mergeExtraInfo(extraInfo));\n  }\n\n  /**\n   * Overwrites the current selection for the group, and raises the `\"change\"`\n   * event among all of the group's '`SelectionHandle` instances (including\n   * this one).\n   *\n   * @fires SelectionHandle#change\n   * @param {Object} [extraInfo] - Extra properties to be included on the event\n   *   object that's passed to listeners (in addition to any that were passed\n   *   into the `SelectionHandle` constructor).\n   */\n  clear(extraInfo) {\n    if (this._var)\n      this.set(void 0, this._mergeExtraInfo(extraInfo));\n  }\n\n  /**\n   * Subscribes to events on this `SelectionHandle`.\n   *\n   * @param {string} eventType - Indicates the type of events to listen to.\n   *   Currently, only `\"change\"` is supported.\n   * @param {SelectionHandle~listener} listener - The callback function that\n   *   will be invoked when the event occurs.\n   * @return {string} - A token to pass to {@link SelectionHandle#off} to cancel\n   *   this subscription.\n   */\n  on(eventType, listener) {\n    return this._emitter.on(eventType, listener);\n  }\n\n  /**\n   * Cancels event subscriptions created by {@link SelectionHandle#on}.\n   *\n   * @param {string} eventType - The type of event to unsubscribe.\n   * @param {string|SelectionHandle~listener} listener - Either the callback\n   *   function previously passed into {@link SelectionHandle#on}, or the\n   *   string that was returned from {@link SelectionHandle#on}.\n   */\n  off(eventType, listener) {\n    return this._emitter.off(eventType, listener);\n  }\n\n  /**\n   * Shuts down the `SelectionHandle` object.\n   *\n   * Removes all event listeners that were added through this handle.\n   */\n  close() {\n    this._emitter.removeAllListeners();\n    this.setGroup(null);\n  }\n}\n\n/**\n * @callback SelectionHandle~listener\n * @param {Object} event - An object containing details of the event. For\n *   `\"change\"` events, this includes the properties `value` (the new\n *   value of the selection, or `undefined` if no selection is active),\n *   `oldValue` (the previous value of the selection), and `sender` (the\n *   `SelectionHandle` instance that made the change).\n */\n\n/**\n * @event SelectionHandle#change\n * @type {object}\n * @property {object} value - The new value of the selection, or `undefined`\n *   if no selection is active.\n * @property {object} oldValue - The previous value of the selection.\n * @property {SelectionHandle} sender - The `SelectionHandle` instance that\n *   changed the value.\n */\n","export function extend(target, ...sources) {\n  for (let i = 0; i < sources.length; i++) {\n    let src = sources[i];\n    if (typeof(src) === \"undefined\" || src === null)\n      continue;\n\n    for (let key in src) {\n      if (src.hasOwnProperty(key)) {\n        target[key] = src[key];\n      }\n    }\n  }\n  return target;\n}\n\nexport function checkSorted(list) {\n  for (let i = 1; i < list.length; i++) {\n    if (list[i] <= list[i-1]) {\n      throw new Error(\"List is not sorted or contains duplicate\");\n    }\n  }\n}\n\nexport function diffSortedLists(a, b) {\n  let i_a = 0;\n  let i_b = 0;\n\n  if (!a) a = [];\n  if (!b) b = [];\n\n  let a_only = [];\n  let b_only = [];\n\n  checkSorted(a);\n  checkSorted(b);\n\n  while (i_a < a.length && i_b < b.length) {\n    if (a[i_a] === b[i_b]) {\n      i_a++;\n      i_b++;\n    } else if (a[i_a] < b[i_b]) {\n      a_only.push(a[i_a++]);\n    } else {\n      b_only.push(b[i_b++]);\n    }\n  }\n\n  if (i_a < a.length)\n    a_only = a_only.concat(a.slice(i_a));\n  if (i_b < b.length)\n    b_only = b_only.concat(b.slice(i_b));\n  return {\n    removed: a_only,\n    added: b_only\n  };\n}\n\n// Convert from wide: { colA: [1,2,3], colB: [4,5,6], ... }\n// to long: [ {colA: 1, colB: 4}, {colA: 2, colB: 5}, ... ]\nexport function dataframeToD3(df) {\n  let names = [];\n  let length;\n  for (let name in df) {\n    if (df.hasOwnProperty(name))\n      names.push(name);\n    if (typeof(df[name]) !== \"object\" || typeof(df[name].length) === \"undefined\") {\n      throw new Error(\"All fields must be arrays\");\n    } else if (typeof(length) !== \"undefined\" && length !== df[name].length) {\n      throw new Error(\"All fields must be arrays of the same length\");\n    }\n    length = df[name].length;\n  }\n  let results = [];\n  let item;\n  for (let row = 0; row < length; row++) {\n    item = {};\n    for (let col = 0; col < names.length; col++) {\n      item[names[col]] = df[names[col]][row];\n    }\n    results.push(item);\n  }\n  return results;\n}\n\n/**\n * Keeps track of all event listener additions/removals and lets all active\n * listeners be removed with a single operation.\n *\n * @private\n */\nexport class SubscriptionTracker {\n  constructor(emitter) {\n    this._emitter = emitter;\n    this._subs = {};\n  }\n\n  on(eventType, listener) {\n    let sub = this._emitter.on(eventType, listener);\n    this._subs[sub] = eventType;\n    return sub;\n  }\n\n  off(eventType, listener) {\n    let sub = this._emitter.off(eventType, listener);\n    if (sub) {\n      delete this._subs[sub];\n    }\n    return sub;\n  }\n\n  removeAllListeners() {\n    let current_subs = this._subs;\n    this._subs = {};\n    Object.keys(current_subs).forEach((sub) => {\n      this._emitter.off(current_subs[sub], sub);\n    });\n  }\n}\n","import Events from \"./events\";\n\nexport default class Var {\n  constructor(group, name, /*optional*/ value) {\n    this._group = group;\n    this._name = name;\n    this._value = value;\n    this._events = new Events();\n  }\n\n  get() {\n    return this._value;\n  }\n\n  set(value, /*optional*/ event) {\n    if (this._value === value) {\n      // Do nothing; the value hasn't changed\n      return;\n    }\n    let oldValue = this._value;\n    this._value = value;\n    // Alert JavaScript listeners that the value has changed\n    let evt = {};\n    if (event && typeof(event) === \"object\") {\n      for (let k in event) {\n        if (event.hasOwnProperty(k))\n          evt[k] = event[k];\n      }\n    }\n    evt.oldValue = oldValue;\n    evt.value = value;\n    this._events.trigger(\"change\", evt, this);\n\n    // TODO: Make this extensible, to let arbitrary back-ends know that\n    // something has changed\n    if (global.Shiny && global.Shiny.onInputChange) {\n      global.Shiny.onInputChange(\n        \".clientValue-\" +\n          (this._group.name !== null ? this._group.name + \"-\" : \"\") +\n          this._name,\n        typeof(value) === \"undefined\" ? null : value\n      );\n    }\n  }\n\n  on(eventType, listener) {\n    return this._events.on(eventType, listener);\n  }\n\n  off(eventType, listener) {\n    return this._events.off(eventType, listener);\n  }\n}\n"]}
\ No newline at end of file
diff --git a/docs/coverage/lib/crosstalk-1.2.1/scss/crosstalk.scss b/docs/coverage/lib/crosstalk-1.2.1/scss/crosstalk.scss
deleted file mode 100644
index 35665616..00000000
--- a/docs/coverage/lib/crosstalk-1.2.1/scss/crosstalk.scss
+++ /dev/null
@@ -1,75 +0,0 @@
-/* Adjust margins outwards, so column contents line up with the edges of the
-   parent of container-fluid. */
-.container-fluid.crosstalk-bscols {
-  margin-left: -30px;
-  margin-right: -30px;
-  white-space: normal;
-}
-
-/* But don't adjust the margins outwards if we're directly under the body,
-   i.e. we were the top-level of something at the console. */
-body > .container-fluid.crosstalk-bscols {
-  margin-left: auto;
-  margin-right: auto;
-}
-
-.crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column {
-  display: inline-block;
-  padding-right: 12px;
-  vertical-align: top;
-}
-
-@media only screen and (max-width:480px) {
-  .crosstalk-input-checkboxgroup .crosstalk-options-group .crosstalk-options-column {
-    display: block;
-    padding-right: inherit;
-  }
-}
-
-/* Relevant BS3 styles to make filter_checkbox() look reasonable without Bootstrap */
-.crosstalk-input {
-  margin-bottom: 15px; /* a la .form-group */
-  .control-label {
-    margin-bottom: 0;
-    vertical-align: middle;
-  }
-  input[type="checkbox"] {
-    margin: 4px 0 0;
-    margin-top: 1px;
-    line-height: normal;
-  }
-  .checkbox {
-    position: relative;
-    display: block;
-    margin-top: 10px;
-    margin-bottom: 10px;
-  }
-  .checkbox > label{
-    padding-left: 20px;
-    margin-bottom: 0;
-    font-weight: 400;
-    cursor: pointer;
-  }
-  .checkbox input[type="checkbox"],
-  .checkbox-inline input[type="checkbox"] {
-    position: absolute;
-    margin-top: 2px;
-    margin-left: -20px;
-  }
-  .checkbox + .checkbox {
-    margin-top: -5px;
-  }
-  .checkbox-inline {
-    position: relative;
-    display: inline-block;
-    padding-left: 20px;
-    margin-bottom: 0;
-    font-weight: 400;
-    vertical-align: middle;
-    cursor: pointer;
-  }
-  .checkbox-inline + .checkbox-inline {
-    margin-top: 0;
-    margin-left: 10px;
-  }
-}
diff --git a/docs/coverage/lib/datatables-binding-0.33/datatables.js b/docs/coverage/lib/datatables-binding-0.33/datatables.js
deleted file mode 100644
index 765b53cb..00000000
--- a/docs/coverage/lib/datatables-binding-0.33/datatables.js
+++ /dev/null
@@ -1,1539 +0,0 @@
-(function() {
-
-// some helper functions: using a global object DTWidget so that it can be used
-// in JS() code, e.g. datatable(options = list(foo = JS('code'))); unlike R's
-// dynamic scoping, when 'code' is eval'ed, JavaScript does not know objects
-// from the "parent frame", e.g. JS('DTWidget') will not work unless it was made
-// a global object
-var DTWidget = {};
-
-// 123456666.7890 -> 123,456,666.7890
-var markInterval = function(d, digits, interval, mark, decMark, precision) {
-  x = precision ? d.toPrecision(digits) : d.toFixed(digits);
-  if (!/^-?[\d.]+$/.test(x)) return x;
-  var xv = x.split('.');
-  if (xv.length > 2) return x;  // should have at most one decimal point
-  xv[0] = xv[0].replace(new RegExp('\\B(?=(\\d{' + interval + '})+(?!\\d))', 'g'), mark);
-  return xv.join(decMark);
-};
-
-DTWidget.formatCurrency = function(data, currency, digits, interval, mark, decMark, before, zeroPrint) {
-  var d = parseFloat(data);
-  if (isNaN(d)) return '';
-  if (zeroPrint !== null && d === 0.0) return zeroPrint;
-  var res = markInterval(d, digits, interval, mark, decMark);
-  res = before ? (/^-/.test(res) ? '-' + currency + res.replace(/^-/, '') : currency + res) :
-    res + currency;
-  return res;
-};
-
-DTWidget.formatString = function(data, prefix, suffix) {
-  var d = data;
-  if (d === null) return '';
-  return prefix + d + suffix;
-};
-
-DTWidget.formatPercentage = function(data, digits, interval, mark, decMark, zeroPrint) {
-  var d = parseFloat(data);
-  if (isNaN(d)) return '';
-  if (zeroPrint !== null && d === 0.0) return zeroPrint;
-  return markInterval(d * 100, digits, interval, mark, decMark) + '%';
-};
-
-DTWidget.formatRound = function(data, digits, interval, mark, decMark, zeroPrint) {
-  var d = parseFloat(data);
-  if (isNaN(d)) return '';
-  if (zeroPrint !== null && d === 0.0) return zeroPrint;
-  return markInterval(d, digits, interval, mark, decMark);
-};
-
-DTWidget.formatSignif = function(data, digits, interval, mark, decMark, zeroPrint) {
-  var d = parseFloat(data);
-  if (isNaN(d)) return '';
-  if (zeroPrint !== null && d === 0.0) return zeroPrint;
-  return markInterval(d, digits, interval, mark, decMark, true);
-};
-
-DTWidget.formatDate = function(data, method, params) {
-  var d = data;
-  if (d === null) return '';
-  // (new Date('2015-10-28')).toDateString() may return 2015-10-27 because the
-  // actual time created could be like 'Tue Oct 27 2015 19:00:00 GMT-0500 (CDT)',
-  // i.e. the date-only string is treated as UTC time instead of local time
-  if ((method === 'toDateString' || method === 'toLocaleDateString') && /^\d{4,}\D\d{2}\D\d{2}$/.test(d)) {
-    d = d.split(/\D/);
-    d = new Date(d[0], d[1] - 1, d[2]);
-  } else {
-    d = new Date(d);
-  }
-  return d[method].apply(d, params);
-};
-
-window.DTWidget = DTWidget;
-
-// A helper function to update the properties of existing filters
-var setFilterProps = function(td, props) {
-  // Update enabled/disabled state
-  var $input = $(td).find('input').first();
-  var searchable = $input.data('searchable');
-  $input.prop('disabled', !searchable || props.disabled);
-
-  // Based on the filter type, set its new values
-  var type = td.getAttribute('data-type');
-  if (['factor', 'logical'].includes(type)) {
-    // Reformat the new dropdown options for use with selectize
-    var new_vals = props.params.options.map(function(item) {
-      return { text: item, value: item };
-    });
-
-    // Find the selectize object
-    var dropdown = $(td).find('.selectized').eq(0)[0].selectize;
-
-    // Note the current values
-    var old_vals = dropdown.getValue();
-
-    // Remove the existing values
-    dropdown.clearOptions();
-
-    // Add the new options
-    dropdown.addOption(new_vals);
-
-    // Preserve the existing values
-    dropdown.setValue(old_vals);
-
-  } else if (['number', 'integer', 'date', 'time'].includes(type)) {
-    // Apply internal scaling to new limits. Updating scale not yet implemented.
-    var slider = $(td).find('.noUi-target').eq(0);
-    var scale = Math.pow(10, Math.max(0, +slider.data('scale') || 0));
-    var new_vals = [props.params.min * scale, props.params.max * scale];
-
-    // Note what the new limits will be just for this filter
-    var new_lims = new_vals.slice();
-
-    // Determine the current values and limits
-    var old_vals = slider.val().map(Number);
-    var old_lims = slider.noUiSlider('options').range;
-    old_lims = [old_lims.min, old_lims.max];
-
-    // Preserve the current values if filters have been applied; otherwise, apply no filtering
-    if (old_vals[0] != old_lims[0]) {
-      new_vals[0] = Math.max(old_vals[0], new_vals[0]);
-    }
-
-    if (old_vals[1] != old_lims[1]) {
-      new_vals[1] = Math.min(old_vals[1], new_vals[1]);
-    }
-
-    // Update the endpoints of the slider
-    slider.noUiSlider({
-      start: new_vals,
-      range: {'min': new_lims[0], 'max': new_lims[1]}
-    }, true);
-  }
-};
-
-var transposeArray2D = function(a) {
-  return a.length === 0 ? a : HTMLWidgets.transposeArray2D(a);
-};
-
-var crosstalkPluginsInstalled = false;
-
-function maybeInstallCrosstalkPlugins() {
-  if (crosstalkPluginsInstalled)
-    return;
-  crosstalkPluginsInstalled = true;
-
-  $.fn.dataTable.ext.afnFiltering.push(
-    function(oSettings, aData, iDataIndex) {
-      var ctfilter = oSettings.nTable.ctfilter;
-      if (ctfilter && !ctfilter[iDataIndex])
-        return false;
-
-      var ctselect = oSettings.nTable.ctselect;
-      if (ctselect && !ctselect[iDataIndex])
-        return false;
-
-      return true;
-    }
-  );
-}
-
-HTMLWidgets.widget({
-  name: "datatables",
-  type: "output",
-  renderOnNullValue: true,
-  initialize: function(el, width, height) {
-    // in order that the type=number inputs return a number
-    $.valHooks.number = {
-      get: function(el) {
-        var value = parseFloat(el.value);
-        return isNaN(value) ? "" : value;
-      }
-    };
-    $(el).html(' ');
-    return {
-      data: null,
-      ctfilterHandle: new crosstalk.FilterHandle(),
-      ctfilterSubscription: null,
-      ctselectHandle: new crosstalk.SelectionHandle(),
-      ctselectSubscription: null
-    };
-  },
-  renderValue: function(el, data, instance) {
-    if (el.offsetWidth === 0 || el.offsetHeight === 0) {
-      instance.data = data;
-      return;
-    }
-    instance.data = null;
-    var $el = $(el);
-    $el.empty();
-
-    if (data === null) {
-      $el.append(' ');
-      // clear previous Shiny inputs (if any)
-      for (var i in instance.clearInputs) instance.clearInputs[i]();
-      instance.clearInputs = {};
-      return;
-    }
-
-    var crosstalkOptions = data.crosstalkOptions;
-    if (!crosstalkOptions) crosstalkOptions = {
-      'key': null, 'group': null
-    };
-    if (crosstalkOptions.group) {
-      maybeInstallCrosstalkPlugins();
-      instance.ctfilterHandle.setGroup(crosstalkOptions.group);
-      instance.ctselectHandle.setGroup(crosstalkOptions.group);
-    }
-
-    // if we are in the viewer then we always want to fillContainer and
-    // and autoHideNavigation (unless the user has explicitly set these)
-    if (window.HTMLWidgets.viewerMode) {
-      if (!data.hasOwnProperty("fillContainer"))
-        data.fillContainer = true;
-      if (!data.hasOwnProperty("autoHideNavigation"))
-        data.autoHideNavigation = true;
-    }
-
-    // propagate fillContainer to instance (so we have it in resize)
-    instance.fillContainer = data.fillContainer;
-
-    var cells = data.data;
-
-    if (cells instanceof Array) cells = transposeArray2D(cells);
-
-    $el.append(data.container);
-    var $table = $el.find('table');
-    if (data.class) $table.addClass(data.class);
-    if (data.caption) $table.prepend(data.caption);
-
-    if (!data.selection) data.selection = {
-      mode: 'none', selected: null, target: 'row', selectable: null
-    };
-    if (HTMLWidgets.shinyMode && data.selection.mode !== 'none' &&
-        data.selection.target === 'row+column') {
-      if ($table.children('tfoot').length === 0) {
-        $table.append($(''));
-        $table.find('thead tr').clone().appendTo($table.find('tfoot'));
-      }
-    }
-
-    // column filters
-    var filterRow;
-    switch (data.filter) {
-      case 'top':
-        $table.children('thead').append(data.filterHTML);
-        filterRow = $table.find('thead tr:last td');
-        break;
-      case 'bottom':
-        if ($table.children('tfoot').length === 0) {
-          $table.append($(''));
-        }
-        $table.children('tfoot').prepend(data.filterHTML);
-        filterRow = $table.find('tfoot tr:first td');
-        break;
-    }
-
-    var options = { searchDelay: 1000 };
-    if (cells !== null) $.extend(options, {
-      data: cells
-    });
-
-    // options for fillContainer
-    var bootstrapActive = typeof($.fn.popover) != 'undefined';
-    if (instance.fillContainer) {
-
-      // force scrollX/scrollY and turn off autoWidth
-      options.scrollX = true;
-      options.scrollY = "100px"; // can be any value, we'll adjust below
-
-      // if we aren't paginating then move around the info/filter controls
-      // to save space at the bottom and rephrase the info callback
-      if (data.options.paging === false) {
-
-        // we know how to do this cleanly for bootstrap, not so much
-        // for other themes/layouts
-        if (bootstrapActive) {
-          options.dom = "<'row'<'col-sm-4'i><'col-sm-8'f>>" +
-                        "<'row'<'col-sm-12'tr>>";
-        }
-
-        options.fnInfoCallback = function(oSettings, iStart, iEnd,
-                                           iMax, iTotal, sPre) {
-          return Number(iTotal).toLocaleString() + " records";
-        };
-      }
-    }
-
-    // auto hide navigation if requested
-    // Note, this only works on client-side processing mode as on server-side,
-    // cells (data.data) is null; In addition, we require the pageLength option
-    // being provided explicitly to enable this. Despite we may be able to deduce
-    // the default value of pageLength, it may complicate things so we'd rather
-    // put this responsiblity to users and warn them on the R side.
-    if (data.autoHideNavigation === true && data.options.paging !== false) {
-      // strip all nav if length >= cells
-      if ((cells instanceof Array) && data.options.pageLength >= cells.length)
-        options.dom = bootstrapActive ? "<'row'<'col-sm-12'tr>>" : "t";
-      // alternatively lean things out for flexdashboard mobile portrait
-      else if (bootstrapActive && window.FlexDashboard && window.FlexDashboard.isMobilePhone())
-        options.dom = "<'row'<'col-sm-12'f>>" +
-                      "<'row'<'col-sm-12'tr>>"  +
-                      "<'row'<'col-sm-12'p>>";
-    }
-
-    $.extend(true, options, data.options || {});
-
-    var searchCols = options.searchCols;
-    if (searchCols) {
-      searchCols = searchCols.map(function(x) {
-        return x === null ? '' : x.search;
-      });
-      // FIXME: this means I don't respect the escapeRegex setting
-      delete options.searchCols;
-    }
-
-    // server-side processing?
-    var server = options.serverSide === true;
-
-    // use the dataSrc function to pre-process JSON data returned from R
-    var DT_rows_all = [], DT_rows_current = [];
-    if (server && HTMLWidgets.shinyMode && typeof options.ajax === 'object' &&
-        /^session\/[\da-z]+\/dataobj/.test(options.ajax.url) && !options.ajax.dataSrc) {
-      options.ajax.dataSrc = function(json) {
-        DT_rows_all = $.makeArray(json.DT_rows_all);
-        DT_rows_current = $.makeArray(json.DT_rows_current);
-        var data = json.data;
-        if (!colReorderEnabled()) return data;
-        var table = $table.DataTable(), order = table.colReorder.order(), flag = true, i, j, row;
-        for (i = 0; i < order.length; ++i) if (order[i] !== i) flag = false;
-        if (flag) return data;
-        for (i = 0; i < data.length; ++i) {
-          row = data[i].slice();
-          for (j = 0; j < order.length; ++j) data[i][j] = row[order[j]];
-        }
-        return data;
-      };
-    }
-
-    var thiz = this;
-    if (instance.fillContainer) $table.on('init.dt', function(e) {
-      thiz.fillAvailableHeight(el, $(el).innerHeight());
-    });
-    // If the page contains serveral datatables and one of which enables colReorder,
-    // the table.colReorder.order() function will exist but throws error when called.
-    // So it seems like the only way to know if colReorder is enabled or not is to
-    // check the options.
-    var colReorderEnabled = function() { return "colReorder" in options; };
-    var table = $table.DataTable(options);
-    $el.data('datatable', table);
-
-    if ('rowGroup' in options) {
-      // Maintain RowGroup dataSrc when columns are reordered (#1109)
-      table.on('column-reorder', function(e, settings, details) {
-        var oldDataSrc = table.rowGroup().dataSrc();
-        var newDataSrc = details.mapping[oldDataSrc];
-        table.rowGroup().dataSrc(newDataSrc);
-      });
-    }
-
-    // Unregister previous Crosstalk event subscriptions, if they exist
-    if (instance.ctfilterSubscription) {
-      instance.ctfilterHandle.off("change", instance.ctfilterSubscription);
-      instance.ctfilterSubscription = null;
-    }
-    if (instance.ctselectSubscription) {
-      instance.ctselectHandle.off("change", instance.ctselectSubscription);
-      instance.ctselectSubscription = null;
-    }
-
-    if (!crosstalkOptions.group) {
-      $table[0].ctfilter = null;
-      $table[0].ctselect = null;
-    } else {
-      var key = crosstalkOptions.key;
-      function keysToMatches(keys) {
-        if (!keys) {
-          return null;
-        } else {
-          var selectedKeys = {};
-          for (var i = 0; i < keys.length; i++) {
-            selectedKeys[keys[i]] = true;
-          }
-          var matches = {};
-          for (var j = 0; j < key.length; j++) {
-            if (selectedKeys[key[j]])
-              matches[j] = true;
-          }
-          return matches;
-        }
-      }
-
-      function applyCrosstalkFilter(e) {
-        $table[0].ctfilter = keysToMatches(e.value);
-        table.draw();
-      }
-      instance.ctfilterSubscription = instance.ctfilterHandle.on("change", applyCrosstalkFilter);
-      applyCrosstalkFilter({value: instance.ctfilterHandle.filteredKeys});
-
-      function applyCrosstalkSelection(e) {
-        if (e.sender !== instance.ctselectHandle) {
-          table
-            .rows('.' + selClass, {search: 'applied'})
-            .nodes()
-            .to$()
-            .removeClass(selClass);
-          if (selectedRows)
-            changeInput('rows_selected', selectedRows(), void 0, true);
-        }
-
-        if (e.sender !== instance.ctselectHandle && e.value && e.value.length) {
-          var matches = keysToMatches(e.value);
-
-          // persistent selection with plotly (& leaflet)
-          var ctOpts = crosstalk.var("plotlyCrosstalkOpts").get() || {};
-          if (ctOpts.persistent === true) {
-            var matches = $.extend(matches, $table[0].ctselect);
-          }
-
-          $table[0].ctselect = matches;
-          table.draw();
-        } else {
-          if ($table[0].ctselect) {
-            $table[0].ctselect = null;
-            table.draw();
-          }
-        }
-      }
-      instance.ctselectSubscription = instance.ctselectHandle.on("change", applyCrosstalkSelection);
-      // TODO: This next line doesn't seem to work when renderDataTable is used
-      applyCrosstalkSelection({value: instance.ctselectHandle.value});
-    }
-
-    var inArray = function(val, array) {
-      return $.inArray(val, $.makeArray(array)) > -1;
-    };
-
-    // search the i-th column
-    var searchColumn = function(i, value) {
-      var regex = false, ci = true;
-      if (options.search) {
-        regex = options.search.regex,
-        ci = options.search.caseInsensitive !== false;
-      }
-      // need to transpose the column index when colReorder is enabled
-      if (table.colReorder) i = table.colReorder.transpose(i);
-      return table.column(i).search(value, regex, !regex, ci);
-    };
-
-    if (data.filter !== 'none') {
-      if (!data.hasOwnProperty('filterSettings')) data.filterSettings = {};
-
-      filterRow.each(function(i, td) {
-
-        var $td = $(td), type = $td.data('type'), filter;
-        var $input = $td.children('div').first().children('input');
-        var disabled = $input.prop('disabled');
-        var searchable = table.settings()[0].aoColumns[i].bSearchable;
-        $input.prop('disabled', !searchable || disabled);
-        $input.data('searchable', searchable); // for updating later
-        $input.on('input blur', function() {
-          $input.next('span').toggle(Boolean($input.val()));
-        });
-        // Bootstrap sets pointer-events to none and we won't be able to click
-        // the clear button
-        $input.next('span').css('pointer-events', 'auto').hide().click(function() {
-          $(this).hide().prev('input').val('').trigger('input').focus();
-        });
-        var searchCol;  // search string for this column
-        if (searchCols && searchCols[i]) {
-          searchCol = searchCols[i];
-          $input.val(searchCol).trigger('input');
-        }
-        var $x = $td.children('div').last();
-
-        // remove the overflow: hidden attribute of the scrollHead
-        // (otherwise the scrolling table body obscures the filters)
-        // The workaround and the discussion from
-        // https://github.com/rstudio/DT/issues/554#issuecomment-518007347
-        // Otherwise the filter selection will not be anchored to the values
-        // when the columns number is many and scrollX is enabled.
-        var scrollHead = $(el).find('.dataTables_scrollHead,.dataTables_scrollFoot');
-        var cssOverflowHead = scrollHead.css('overflow');
-        var scrollBody = $(el).find('.dataTables_scrollBody');
-        var cssOverflowBody = scrollBody.css('overflow');
-        var scrollTable = $(el).find('.dataTables_scroll');
-        var cssOverflowTable = scrollTable.css('overflow');
-        if (cssOverflowHead === 'hidden') {
-          $x.on('show hide', function(e) {
-            if (e.type === 'show') {
-              scrollHead.css('overflow', 'visible');
-              scrollBody.css('overflow', 'visible');
-              scrollTable.css('overflow-x', 'scroll');
-            } else {
-              scrollHead.css('overflow', cssOverflowHead);
-              scrollBody.css('overflow', cssOverflowBody);
-              scrollTable.css('overflow-x', cssOverflowTable);
-            }
-          });
-          $x.css('z-index', 25);
-        }
-
-        if (inArray(type, ['factor', 'logical'])) {
-          $input.on({
-            click: function() {
-              $input.parent().hide(); $x.show().trigger('show'); filter[0].selectize.focus();
-            },
-            input: function() {
-              var v1 = JSON.stringify(filter[0].selectize.getValue()), v2 = $input.val();
-              if (v1 === '[]') v1 = '';
-              if (v1 !== v2) filter[0].selectize.setValue(v2 === '' ? [] : JSON.parse(v2));
-            }
-          });
-          var $input2 = $x.children('select');
-          filter = $input2.selectize($.extend({
-            options: $input2.data('options').map(function(v, i) {
-              return ({text: v, value: v});
-            }),
-            plugins: ['remove_button'],
-            hideSelected: true,
-            onChange: function(value) {
-              if (value === null) value = []; // compatibility with jQuery 3.0
-              $input.val(value.length ? JSON.stringify(value) : '');
-              if (value.length) $input.trigger('input');
-              $input.attr('title', $input.val());
-              if (server) {
-                searchColumn(i, value.length ? JSON.stringify(value) : '').draw();
-                return;
-              }
-              // turn off filter if nothing selected
-              $td.data('filter', value.length > 0);
-              table.draw();  // redraw table, and filters will be applied
-            }
-          }, data.filterSettings.select));
-          filter[0].selectize.on('blur', function() {
-            $x.hide().trigger('hide'); $input.parent().show(); $input.trigger('blur');
-          });
-          filter.next('div').css('margin-bottom', 'auto');
-        } else if (type === 'character') {
-          var fun = function() {
-            searchColumn(i, $input.val()).draw();
-          };
-          // throttle searching for server-side processing
-          var throttledFun = $.fn.dataTable.util.throttle(fun, options.searchDelay);
-          $input.on('input', function(e, immediate) {
-            // always bypass throttling when immediate = true (via the updateSearch method)
-            (immediate || !server) ? fun() : throttledFun();
-          });
-        } else if (inArray(type, ['number', 'integer', 'date', 'time'])) {
-          var $x0 = $x;
-          $x = $x0.children('div').first();
-          $x0.css({
-            'background-color': '#fff',
-            'border': '1px #ddd solid',
-            'border-radius': '4px',
-            'padding': data.vertical ? '35px 20px': '20px 20px 10px 20px'
-          });
-          var $spans = $x0.children('span').css({
-            'margin-top': data.vertical ? '0' : '10px',
-            'white-space': 'nowrap'
-          });
-          var $span1 = $spans.first(), $span2 = $spans.last();
-          var r1 = +$x.data('min'), r2 = +$x.data('max');
-          // when the numbers are too small or have many decimal places, the
-          // slider may have numeric precision problems (#150)
-          var scale = Math.pow(10, Math.max(0, +$x.data('scale') || 0));
-          r1 = Math.round(r1 * scale); r2 = Math.round(r2 * scale);
-          var scaleBack = function(x, scale) {
-            if (scale === 1) return x;
-            var d = Math.round(Math.log(scale) / Math.log(10));
-            // to avoid problems like 3.423/100 -> 0.034230000000000003
-            return (x / scale).toFixed(d);
-          };
-          var slider_min = function() {
-            return filter.noUiSlider('options').range.min;
-          };
-          var slider_max = function() {
-            return filter.noUiSlider('options').range.max;
-          };
-          $input.on({
-            focus: function() {
-              $x0.show().trigger('show');
-              // first, make sure the slider div leaves at least 20px between
-              // the two (slider value) span's
-              $x0.width(Math.max(160, $span1.outerWidth() + $span2.outerWidth() + 20));
-              // then, if the input is really wide or slider is vertical,
-              // make the slider the same width as the input
-              if ($x0.outerWidth() < $input.outerWidth() || data.vertical) {
-                $x0.outerWidth($input.outerWidth());
-              }
-              // make sure the slider div does not reach beyond the right margin
-              if ($(window).width() < $x0.offset().left + $x0.width()) {
-                $x0.offset({
-                  'left': $input.offset().left + $input.outerWidth() - $x0.outerWidth()
-                });
-              }
-            },
-            blur: function() {
-              $x0.hide().trigger('hide');
-            },
-            input: function() {
-              if ($input.val() === '') filter.val([slider_min(), slider_max()]);
-            },
-            change: function() {
-              var v = $input.val().replace(/\s/g, '');
-              if (v === '') return;
-              v = v.split('...');
-              if (v.length !== 2) {
-                $input.parent().addClass('has-error');
-                return;
-              }
-              if (v[0] === '') v[0] = slider_min();
-              if (v[1] === '') v[1] = slider_max();
-              $input.parent().removeClass('has-error');
-              // treat date as UTC time at midnight
-              var strTime = function(x) {
-                var s = type === 'date' ? 'T00:00:00Z' : '';
-                var t = new Date(x + s).getTime();
-                // add 10 minutes to date since it does not hurt the date, and
-                // it helps avoid the tricky floating point arithmetic problems,
-                // e.g. sometimes the date may be a few milliseconds earlier
-                // than the midnight due to precision problems in noUiSlider
-                return type === 'date' ? t + 3600000 : t;
-              };
-              if (inArray(type, ['date', 'time'])) {
-                v[0] = strTime(v[0]);
-                v[1] = strTime(v[1]);
-              }
-              if (v[0] != slider_min()) v[0] *= scale;
-              if (v[1] != slider_max()) v[1] *= scale;
-              filter.val(v);
-            }
-          });
-          var formatDate = function(d) {
-            d = scaleBack(d, scale);
-            if (type === 'number') return d;
-            if (type === 'integer') return parseInt(d);
-            var x = new Date(+d);
-            if (type === 'date') {
-              var pad0 = function(x) {
-                return ('0' + x).substr(-2, 2);
-              };
-              return x.getUTCFullYear() + '-' + pad0(1 + x.getUTCMonth())
-                      + '-' + pad0(x.getUTCDate());
-            } else {
-              return x.toISOString();
-            }
-          };
-          var opts = type === 'date' ? { step: 60 * 60 * 1000 } :
-                     type === 'integer' ? { step: 1 } : {};
-
-          opts.orientation = data.vertical ? 'vertical': 'horizontal';
-          opts.direction = data.vertical ? 'rtl': 'ltr';
-
-          filter = $x.noUiSlider($.extend({
-            start: [r1, r2],
-            range: {min: r1, max: r2},
-            connect: true
-          }, opts, data.filterSettings.slider));
-          if (scale > 1) (function() {
-            var t1 = r1, t2 = r2;
-            var val = filter.val();
-            while (val[0] > r1 || val[1] < r2) {
-              if (val[0] > r1) {
-                t1 -= val[0] - r1;
-              }
-              if (val[1] < r2) {
-                t2 += r2 - val[1];
-              }
-              filter = $x.noUiSlider($.extend({
-                start: [t1, t2],
-                range: {min: t1, max: t2},
-                connect: true
-              }, opts, data.filterSettings.slider), true);
-              val = filter.val();
-            }
-            r1  = t1; r2 = t2;
-          })();
-          // format with active column renderer, if defined
-          var colDef = data.options.columnDefs.find(function(def) {
-            return (def.targets === i || inArray(i, def.targets)) && 'render' in def;
-          });
-          var updateSliderText = function(v1, v2) {
-            // we only know how to use function renderers
-            if (colDef && typeof colDef.render === 'function') {
-              var restore = function(v) {
-                v = scaleBack(v, scale);
-                return inArray(type, ['date', 'time']) ? new Date(+v) : v;
-              }
-              $span1.text(colDef.render(restore(v1), 'display'));
-              $span2.text(colDef.render(restore(v2), 'display'));
-            } else {
-              $span1.text(formatDate(v1));
-              $span2.text(formatDate(v2));
-            }
-          };
-          updateSliderText(r1, r2);
-          var updateSlider = function(e) {
-            var val = filter.val();
-            // turn off filter if in full range
-            $td.data('filter', val[0] > slider_min() || val[1] < slider_max());
-            var v1 = formatDate(val[0]), v2 = formatDate(val[1]), ival;
-            if ($td.data('filter')) {
-              ival = v1 + ' ... ' + v2;
-              $input.attr('title', ival).val(ival).trigger('input');
-            } else {
-              $input.attr('title', '').val('');
-            }
-            updateSliderText(val[0], val[1]);
-            if (e.type === 'slide') return;  // no searching when sliding only
-            if (server) {
-              searchColumn(i, $td.data('filter') ? ival : '').draw();
-              return;
-            }
-            table.draw();
-          };
-          filter.on({
-            set: updateSlider,
-            slide: updateSlider
-          });
-        }
-
-        // server-side processing will be handled by R (or whatever server
-        // language you use); the following code is only needed for client-side
-        // processing
-        if (server) {
-          // if a search string has been pre-set, search now
-          if (searchCol) $input.trigger('input').trigger('change');
-          return;
-        }
-
-        var customFilter = function(settings, data, dataIndex) {
-          // there is no way to attach a search function to a specific table,
-          // and we need to make sure a global search function is not applied to
-          // all tables (i.e. a range filter in a previous table should not be
-          // applied to the current table); we use the settings object to
-          // determine if we want to perform searching on the current table,
-          // since settings.sTableId will be different to different tables
-          if (table.settings()[0] !== settings) return true;
-          // no filter on this column or no need to filter this column
-          if (typeof filter === 'undefined' || !$td.data('filter')) return true;
-
-          var r = filter.val(), v, r0, r1;
-          var i_data = function(i) {
-            if (!colReorderEnabled()) return i;
-            var order = table.colReorder.order(), k;
-            for (k = 0; k < order.length; ++k) if (order[k] === i) return k;
-            return i; // in theory it will never be here...
-          }
-          v = data[i_data(i)];
-          if (type === 'number' || type === 'integer') {
-            v = parseFloat(v);
-            // how to handle NaN? currently exclude these rows
-            if (isNaN(v)) return(false);
-            r0 = parseFloat(scaleBack(r[0], scale))
-            r1 = parseFloat(scaleBack(r[1], scale));
-            if (v >= r0 && v <= r1) return true;
-          } else if (type === 'date' || type === 'time') {
-            v = new Date(v);
-            r0 = new Date(r[0] / scale); r1 = new Date(r[1] / scale);
-            if (v >= r0 && v <= r1) return true;
-          } else if (type === 'factor') {
-            if (r.length === 0 || inArray(v, r)) return true;
-          } else if (type === 'logical') {
-            if (r.length === 0) return true;
-            if (inArray(v === '' ? 'na' : v, r)) return true;
-          }
-          return false;
-        };
-
-        $.fn.dataTable.ext.search.push(customFilter);
-
-        // search for the preset search strings if it is non-empty
-        if (searchCol) $input.trigger('input').trigger('change');
-
-      });
-
-    }
-
-    // highlight search keywords
-    var highlight = function() {
-      var body = $(table.table().body());
-      // removing the old highlighting first
-      body.unhighlight();
-
-      // don't highlight the "not found" row, so we get the rows using the api
-      if (table.rows({ filter: 'applied' }).data().length === 0) return;
-      // highlight global search keywords
-      body.highlight($.trim(table.search()).split(/\s+/));
-      // then highlight keywords from individual column filters
-      if (filterRow) filterRow.each(function(i, td) {
-        var $td = $(td), type = $td.data('type');
-        if (type !== 'character') return;
-        var $input = $td.children('div').first().children('input');
-        var column = table.column(i).nodes().to$(),
-            val = $.trim($input.val());
-        if (type !== 'character' || val === '') return;
-        column.highlight(val.split(/\s+/));
-      });
-    };
-
-    if (options.searchHighlight) {
-      table
-      .on('draw.dt.dth column-visibility.dt.dth column-reorder.dt.dth', highlight)
-      .on('destroy', function() {
-        // remove event handler
-        table.off('draw.dt.dth column-visibility.dt.dth column-reorder.dt.dth');
-      });
-
-      // Set the option for escaping regex characters in our search string.  This will be used
-      // for all future matching.
-      jQuery.fn.highlight.options.escapeRegex = (!options.search || !options.search.regex);
-
-      // initial highlight for state saved conditions and initial states
-      highlight();
-    }
-
-    // run the callback function on the table instance
-    if (typeof data.callback === 'function') data.callback(table);
-
-    // double click to edit the cell, row, column, or all cells
-    if (data.editable) table.on('dblclick.dt', 'tbody td', function(e) {
-      // only bring up the editor when the cell itself is dbclicked, and ignore
-      // other dbclick events bubbled up (e.g. from the )
-      if (e.target !== this) return;
-      var target = [], immediate = false;
-      switch (data.editable.target) {
-        case 'cell':
-          target = [this];
-          immediate = true;  // edit will take effect immediately
-          break;
-        case 'row':
-          target = table.cells(table.cell(this).index().row, '*').nodes();
-          break;
-        case 'column':
-          target = table.cells('*', table.cell(this).index().column).nodes();
-          break;
-        case 'all':
-          target = table.cells().nodes();
-          break;
-        default:
-          throw 'The editable parameter must be "cell", "row", "column", or "all"';
-      }
-      var disableCols = data.editable.disable ? data.editable.disable.columns : null;
-      var numericCols = data.editable.numeric;
-      var areaCols = data.editable.area;
-      var dateCols = data.editable.date;
-      for (var i = 0; i < target.length; i++) {
-        (function(cell, current) {
-          var $cell = $(cell), html = $cell.html();
-          var _cell = table.cell(cell), value = _cell.data(), index = _cell.index().column;
-          var $input;
-          if (inArray(index, numericCols)) {
-            $input = $('');
-          } else if (inArray(index, areaCols)) {
-            $input = $('');
-          } else if (inArray(index, dateCols)) {
-            $input = $('');
-          } else {
-            $input = $('');
-          }
-          if (!immediate) {
-            $cell.data('input', $input).data('html', html);
-            $input.attr('title', 'Hit Ctrl+Enter to finish editing, or Esc to cancel');
-          }
-          $input.val(value);
-          if (inArray(index, disableCols)) {
-            $input.attr('readonly', '').css('filter', 'invert(25%)');
-          }
-          $cell.empty().append($input);
-          if (cell === current) $input.focus();
-          $input.css('width', '100%');
-
-          if (immediate) $input.on('blur', function(e) {
-            var valueNew = $input.val();
-            if (valueNew !== value) {
-              _cell.data(valueNew);
-              if (HTMLWidgets.shinyMode) {
-                changeInput('cell_edit', [cellInfo(cell)], 'DT.cellInfo', null, {priority: 'event'});
-              }
-              // for server-side processing, users have to call replaceData() to update the table
-              if (!server) table.draw(false);
-            } else {
-              $cell.html(html);
-            }
-          }).on('keyup', function(e) {
-            // hit Escape to cancel editing
-            if (e.keyCode === 27) $input.trigger('blur');
-          });
-
-          // bulk edit (row, column, or all)
-          if (!immediate) $input.on('keyup', function(e) {
-            var removeInput = function($cell, restore) {
-              $cell.data('input').remove();
-              if (restore) $cell.html($cell.data('html'));
-            }
-            if (e.keyCode === 27) {
-              for (var i = 0; i < target.length; i++) {
-                removeInput($(target[i]), true);
-              }
-            } else if (e.keyCode === 13 && e.ctrlKey) {
-              // Ctrl + Enter
-              var cell, $cell, _cell, cellData = [];
-              for (var i = 0; i < target.length; i++) {
-                cell = target[i]; $cell = $(cell); _cell = table.cell(cell);
-                _cell.data($cell.data('input').val());
-                HTMLWidgets.shinyMode && cellData.push(cellInfo(cell));
-                removeInput($cell, false);
-              }
-              if (HTMLWidgets.shinyMode) {
-                changeInput('cell_edit', cellData, 'DT.cellInfo', null, {priority: "event"});
-              }
-              if (!server) table.draw(false);
-            }
-          });
-        })(target[i], this);
-      }
-    });
-
-    // interaction with shiny
-    if (!HTMLWidgets.shinyMode && !crosstalkOptions.group) return;
-
-    var methods = {};
-    var shinyData = {};
-
-    methods.updateCaption = function(caption) {
-      if (!caption) return;
-      $table.children('caption').replaceWith(caption);
-    }
-
-    // register clear functions to remove input values when the table is removed
-    instance.clearInputs = {};
-
-    var changeInput = function(id, value, type, noCrosstalk, opts) {
-      var event = id;
-      id = el.id + '_' + id;
-      if (type) id = id + ':' + type;
-      // do not update if the new value is the same as old value
-      if (event !== 'cell_edit' && !/_clicked$/.test(event) && shinyData.hasOwnProperty(id) && shinyData[id] === JSON.stringify(value))
-        return;
-      shinyData[id] = JSON.stringify(value);
-      if (HTMLWidgets.shinyMode && Shiny.setInputValue) {
-        Shiny.setInputValue(id, value, opts);
-        if (!instance.clearInputs[id]) instance.clearInputs[id] = function() {
-          Shiny.setInputValue(id, null);
-        }
-      }
-
-      // HACK
-      if (event === "rows_selected" && !noCrosstalk) {
-        if (crosstalkOptions.group) {
-          var keys = crosstalkOptions.key;
-          var selectedKeys = null;
-          if (value) {
-            selectedKeys = [];
-            for (var i = 0; i < value.length; i++) {
-              // The value array's contents use 1-based row numbers, so we must
-              // convert to 0-based before indexing into the keys array.
-              selectedKeys.push(keys[value[i] - 1]);
-            }
-          }
-          instance.ctselectHandle.set(selectedKeys);
-        }
-      }
-    };
-
-    var addOne = function(x) {
-      return x.map(function(i) { return 1 + i; });
-    };
-
-    var unique = function(x) {
-      var ux = [];
-      $.each(x, function(i, el){
-        if ($.inArray(el, ux) === -1) ux.push(el);
-      });
-      return ux;
-    }
-
-    // change the row index of a cell
-    var tweakCellIndex = function(cell) {
-      var info = cell.index();
-      // some cell may not be valid. e.g, #759
-      // when using the RowGroup extension, datatables will
-      // generate the row label and the cells are not part of
-      // the data thus contain no row/col info
-      if (info === undefined)
-        return {row: null, col: null};
-      if (server) {
-        info.row = DT_rows_current[info.row];
-      } else {
-        info.row += 1;
-      }
-      return {row: info.row, col: info.column};
-    }
-
-    var cleanSelectedValues = function() {
-      changeInput('rows_selected', []);
-      changeInput('columns_selected', []);
-      changeInput('cells_selected', transposeArray2D([]), 'shiny.matrix');
-    }
-    // #828 we should clean the selection on the server-side when the table reloads
-    cleanSelectedValues();
-
-    // a flag to indicates if select extension is initialized or not
-    var flagSelectExt = table.settings()[0]._select !== undefined;
-    // the Select extension should only be used in the client mode and
-    // when the selection.mode is set to none
-    if (data.selection.mode === 'none' && !server && flagSelectExt) {
-      var updateRowsSelected = function() {
-        var rows = table.rows({selected: true});
-        var selected = [];
-        $.each(rows.indexes().toArray(), function(i, v) {
-          selected.push(v + 1);
-        });
-        changeInput('rows_selected', selected);
-      }
-      var updateColsSelected = function() {
-        var columns = table.columns({selected: true});
-        changeInput('columns_selected', columns.indexes().toArray());
-      }
-      var updateCellsSelected = function() {
-        var cells = table.cells({selected: true});
-        var selected = [];
-        cells.every(function() {
-          var row = this.index().row;
-          var col = this.index().column;
-          selected = selected.concat([[row + 1, col]]);
-        });
-        changeInput('cells_selected', transposeArray2D(selected), 'shiny.matrix');
-      }
-      table.on('select deselect', function(e, dt, type, indexes) {
-        updateRowsSelected();
-        updateColsSelected();
-        updateCellsSelected();
-      })
-      updateRowsSelected();
-      updateColsSelected();
-      updateCellsSelected();
-    }
-
-    var selMode = data.selection.mode, selTarget = data.selection.target;
-    var selDisable = data.selection.selectable === false;
-    if (inArray(selMode, ['single', 'multiple'])) {
-      var selClass = inArray(data.style, ['bootstrap', 'bootstrap4']) ? 'active' : 'selected';
-      // selected1: row indices; selected2: column indices
-      var initSel = function(x) {
-        if (x === null || typeof x === 'boolean' || selTarget === 'cell') {
-          return {rows: [], cols: []};
-        } else if (selTarget === 'row') {
-          return {rows: $.makeArray(x), cols: []};
-        } else if (selTarget === 'column') {
-          return {rows: [], cols: $.makeArray(x)};
-        } else if (selTarget === 'row+column') {
-          return {rows: $.makeArray(x.rows), cols: $.makeArray(x.cols)};
-        }
-      }
-      var selected = data.selection.selected;
-      var selected1 = initSel(selected).rows, selected2 = initSel(selected).cols;
-      // selectable should contain either all positive or all non-positive values, not both
-      // positive values indicate "selectable" while non-positive values means "nonselectable"
-      // the assertion is performed on R side. (only column indicides could be zero which indicates
-      // the row name)
-      var selectable = data.selection.selectable;
-      var selectable1 = initSel(selectable).rows, selectable2 = initSel(selectable).cols;
-
-      // After users reorder the rows or filter the table, we cannot use the table index
-      // directly. Instead, we need this function to find out the rows between the two clicks.
-      // If user filter the table again between the start click and the end click, the behavior
-      // would be undefined, but it should not be a problem.
-      var shiftSelRowsIndex = function(start, end) {
-        var indexes = server ? DT_rows_all : table.rows({ search: 'applied' }).indexes().toArray();
-        start = indexes.indexOf(start); end = indexes.indexOf(end);
-        // if start is larger than end, we need to swap
-        if (start > end) {
-          var tmp = end; end = start; start = tmp;
-        }
-        return indexes.slice(start, end + 1);
-      }
-
-      var serverRowIndex = function(clientRowIndex) {
-        return server ? DT_rows_current[clientRowIndex] : clientRowIndex + 1;
-      }
-
-      // row, column, or cell selection
-      var lastClickedRow;
-      if (inArray(selTarget, ['row', 'row+column'])) {
-        // Get the current selected rows. It will also
-        // update the selected1's value based on the current row selection state
-        // Note we can't put this function inside selectRows() directly,
-        // the reason is method.selectRows() will override selected1's value but this
-        // function will add rows to selected1 (keep the existing selection), which is
-        // inconsistent with column and cell selection.
-        var selectedRows = function() {
-          var rows = table.rows('.' + selClass);
-          var idx = rows.indexes().toArray();
-          if (!server) {
-            selected1 = addOne(idx);
-            return selected1;
-          }
-          idx = idx.map(function(i) {
-            return DT_rows_current[i];
-          });
-          selected1 = selMode === 'multiple' ? unique(selected1.concat(idx)) : idx;
-          return selected1;
-        }
-        // Change selected1's value based on selectable1, then refresh the row state
-        var onlyKeepSelectableRows = function() {
-          if (selDisable) { // users can't select; useful when only want backend select
-            selected1 = [];
-            return;
-          }
-          if (selectable1.length === 0) return;
-          var nonselectable = selectable1[0] <= 0;
-          if (nonselectable) {
-            // should make selectable1 positive
-            selected1 = $(selected1).not(selectable1.map(function(i) { return -i; })).get();
-          } else {
-            selected1 = $(selected1).filter(selectable1).get();
-          }
-        }
-        // Change selected1's value based on selectable1, then
-        // refresh the row selection state according to values in selected1
-        var selectRows = function(ignoreSelectable) {
-          if (!ignoreSelectable) onlyKeepSelectableRows();
-          table.$('tr.' + selClass).removeClass(selClass);
-          if (selected1.length === 0) return;
-          if (server) {
-            table.rows({page: 'current'}).every(function() {
-              if (inArray(DT_rows_current[this.index()], selected1)) {
-                $(this.node()).addClass(selClass);
-              }
-            });
-          } else {
-            var selected0 = selected1.map(function(i) { return i - 1; });
-            $(table.rows(selected0).nodes()).addClass(selClass);
-          }
-        }
-        table.on('mousedown.dt', 'tbody tr', function(e) {
-          var $this = $(this), thisRow = table.row(this);
-          if (selMode === 'multiple') {
-            if (e.shiftKey && lastClickedRow !== undefined) {
-              // select or de-select depends on the last clicked row's status
-              var flagSel = !$this.hasClass(selClass);
-              var crtClickedRow = serverRowIndex(thisRow.index());
-              if (server) {
-                var rowsIndex = shiftSelRowsIndex(lastClickedRow, crtClickedRow);
-                // update current page's selClass
-                rowsIndex.map(function(i) {
-                  var rowIndex = DT_rows_current.indexOf(i);
-                  if (rowIndex >= 0) {
-                    var row = table.row(rowIndex).nodes().to$();
-                    var flagRowSel = !row.hasClass(selClass);
-                    if (flagSel === flagRowSel) row.toggleClass(selClass);
-                  }
-                });
-                // update selected1
-                if (flagSel) {
-                  selected1 = unique(selected1.concat(rowsIndex));
-                } else {
-                  selected1 = selected1.filter(function(index) {
-                    return !inArray(index, rowsIndex);
-                  });
-                }
-              } else {
-                // js starts from 0
-                shiftSelRowsIndex(lastClickedRow - 1, crtClickedRow - 1).map(function(value) {
-                  var row = table.row(value).nodes().to$();
-                  var flagRowSel = !row.hasClass(selClass);
-                  if (flagSel === flagRowSel) row.toggleClass(selClass);
-                });
-              }
-              e.preventDefault();
-            } else {
-              $this.toggleClass(selClass);
-            }
-          } else {
-            if ($this.hasClass(selClass)) {
-              $this.removeClass(selClass);
-            } else {
-              table.$('tr.' + selClass).removeClass(selClass);
-              $this.addClass(selClass);
-            }
-          }
-          if (server && !$this.hasClass(selClass)) {
-            var id = DT_rows_current[thisRow.index()];
-            // remove id from selected1 since its class .selected has been removed
-            if (inArray(id, selected1)) selected1.splice($.inArray(id, selected1), 1);
-          }
-          selectedRows(); // update selected1's value based on selClass
-          selectRows(false); // only keep the selectable rows
-          changeInput('rows_selected', selected1);
-          changeInput('row_last_clicked', serverRowIndex(thisRow.index()), null, null, {priority: 'event'});
-          lastClickedRow = serverRowIndex(thisRow.index());
-        });
-        selectRows(false);  // in case users have specified pre-selected rows
-        // restore selected rows after the table is redrawn (e.g. sort/search/page);
-        // client-side tables will preserve the selections automatically; for
-        // server-side tables, we have to *real* row indices are in `selected1`
-        changeInput('rows_selected', selected1);
-        if (server) table.on('draw.dt', function(e) { selectRows(false); });
-        methods.selectRows = function(selected, ignoreSelectable) {
-          selected1 = $.makeArray(selected);
-          selectRows(ignoreSelectable);
-          changeInput('rows_selected', selected1);
-        }
-      }
-
-      if (inArray(selTarget, ['column', 'row+column'])) {
-        if (selTarget === 'row+column') {
-          $(table.columns().footer()).css('cursor', 'pointer');
-        }
-        // update selected2's value based on selectable2
-        var onlyKeepSelectableCols = function() {
-          if (selDisable) { // users can't select; useful when only want backend select
-            selected2 = [];
-            return;
-          }
-          if (selectable2.length === 0) return;
-          var nonselectable = selectable2[0] <= 0;
-          if (nonselectable) {
-            // need to make selectable2 positive
-            selected2 = $(selected2).not(selectable2.map(function(i) { return -i; })).get();
-          } else {
-            selected2 = $(selected2).filter(selectable2).get();
-          }
-        }
-        // update selected2 and then
-        // refresh the col selection state according to values in selected2
-        var selectCols = function(ignoreSelectable) {
-          if (!ignoreSelectable) onlyKeepSelectableCols();
-          // if selected2 is not a valide index (e.g., larger than the column number)
-          // table.columns(selected2) will fail and result in a blank table
-          // this is different from the table.rows(), where the out-of-range indexes
-          // doesn't affect at all
-          selected2 = $(selected2).filter(table.columns().indexes()).get();
-          table.columns().nodes().flatten().to$().removeClass(selClass);
-          if (selected2.length > 0)
-            table.columns(selected2).nodes().flatten().to$().addClass(selClass);
-        }
-        var callback = function() {
-          var colIdx = selTarget === 'column' ? table.cell(this).index().column :
-              $.inArray(this, table.columns().footer()),
-              thisCol = $(table.column(colIdx).nodes());
-          if (colIdx === -1) return;
-          if (thisCol.hasClass(selClass)) {
-            thisCol.removeClass(selClass);
-            selected2.splice($.inArray(colIdx, selected2), 1);
-          } else {
-            if (selMode === 'single') $(table.cells().nodes()).removeClass(selClass);
-            thisCol.addClass(selClass);
-            selected2 = selMode === 'single' ? [colIdx] : unique(selected2.concat([colIdx]));
-          }
-          selectCols(false); // update selected2 based on selectable
-          changeInput('columns_selected', selected2);
-        }
-        if (selTarget === 'column') {
-          $(table.table().body()).on('click.dt', 'td', callback);
-        } else {
-          $(table.table().footer()).on('click.dt', 'tr th', callback);
-        }
-        selectCols(false);  // in case users have specified pre-selected columns
-        changeInput('columns_selected', selected2);
-        if (server) table.on('draw.dt', function(e) { selectCols(false); });
-        methods.selectColumns = function(selected, ignoreSelectable) {
-          selected2 = $.makeArray(selected);
-          selectCols(ignoreSelectable);
-          changeInput('columns_selected', selected2);
-        }
-      }
-
-      if (selTarget === 'cell') {
-        var selected3 = [], selectable3 = [];
-        if (selected !== null) selected3 = selected;
-        if (selectable !== null && typeof selectable !== 'boolean') selectable3 = selectable;
-        var findIndex = function(ij, sel) {
-          for (var i = 0; i < sel.length; i++) {
-            if (ij[0] === sel[i][0] && ij[1] === sel[i][1]) return i;
-          }
-          return -1;
-        }
-         // Change selected3's value based on selectable3, then refresh the cell state
-        var onlyKeepSelectableCells = function() {
-          if (selDisable) { // users can't select; useful when only want backend select
-            selected3 = [];
-            return;
-          }
-          if (selectable3.length === 0) return;
-          var nonselectable = selectable3[0][0] <= 0;
-          var out = [];
-          if (nonselectable) {
-            selected3.map(function(ij) {
-              // should make selectable3 positive
-              if (findIndex([-ij[0], -ij[1]], selectable3) === -1) { out.push(ij); }
-            });
-          } else {
-            selected3.map(function(ij) {
-              if (findIndex(ij, selectable3) > -1) { out.push(ij); }
-            });
-          }
-          selected3 = out;
-        }
-        // Change selected3's value based on selectable3, then
-        // refresh the cell selection state according to values in selected3
-        var selectCells = function(ignoreSelectable) {
-          if (!ignoreSelectable) onlyKeepSelectableCells();
-          table.$('td.' + selClass).removeClass(selClass);
-          if (selected3.length === 0) return;
-          if (server) {
-            table.cells({page: 'current'}).every(function() {
-              var info = tweakCellIndex(this);
-              if (findIndex([info.row, info.col], selected3) > -1)
-                $(this.node()).addClass(selClass);
-            });
-          } else {
-            selected3.map(function(ij) {
-              $(table.cell(ij[0] - 1, ij[1]).node()).addClass(selClass);
-            });
-          }
-        };
-        table.on('click.dt', 'tbody td', function() {
-          var $this = $(this), info = tweakCellIndex(table.cell(this));
-          if ($this.hasClass(selClass)) {
-            $this.removeClass(selClass);
-            selected3.splice(findIndex([info.row, info.col], selected3), 1);
-          } else {
-            if (selMode === 'single') $(table.cells().nodes()).removeClass(selClass);
-            $this.addClass(selClass);
-            selected3 = selMode === 'single' ? [[info.row, info.col]] :
-              unique(selected3.concat([[info.row, info.col]]));
-          }
-          selectCells(false); // must call this to update selected3 based on selectable3
-          changeInput('cells_selected', transposeArray2D(selected3), 'shiny.matrix');
-        });
-        selectCells(false);  // in case users have specified pre-selected columns
-        changeInput('cells_selected', transposeArray2D(selected3), 'shiny.matrix');
-
-        if (server) table.on('draw.dt', function(e) { selectCells(false); });
-        methods.selectCells = function(selected, ignoreSelectable) {
-          selected3 = selected ? selected : [];
-          selectCells(ignoreSelectable);
-          changeInput('cells_selected', transposeArray2D(selected3), 'shiny.matrix');
-        }
-      }
-    }
-
-    // expose some table info to Shiny
-    var updateTableInfo = function(e, settings) {
-      // TODO: is anyone interested in the page info?
-      // changeInput('page_info', table.page.info());
-      var updateRowInfo = function(id, modifier) {
-        var idx;
-        if (server) {
-          idx = modifier.page === 'current' ? DT_rows_current : DT_rows_all;
-        } else {
-          var rows = table.rows($.extend({
-            search: 'applied',
-            page: 'all'
-          }, modifier));
-          idx = addOne(rows.indexes().toArray());
-        }
-        changeInput('rows' + '_' + id, idx);
-      };
-      updateRowInfo('current', {page: 'current'});
-      updateRowInfo('all', {});
-    }
-    table.on('draw.dt', updateTableInfo);
-    updateTableInfo();
-
-    // state info
-    table.on('draw.dt column-visibility.dt', function() {
-      changeInput('state', table.state());
-    });
-    changeInput('state', table.state());
-
-    // search info
-    var updateSearchInfo = function() {
-      changeInput('search', table.search());
-      if (filterRow) changeInput('search_columns', filterRow.toArray().map(function(td) {
-        return $(td).find('input').first().val();
-      }));
-    }
-    table.on('draw.dt', updateSearchInfo);
-    updateSearchInfo();
-
-    var cellInfo = function(thiz) {
-      var info = tweakCellIndex(table.cell(thiz));
-      info.value = table.cell(thiz).data();
-      return info;
-    }
-    // the current cell clicked on
-    table.on('click.dt', 'tbody td', function() {
-      changeInput('cell_clicked', cellInfo(this), null, null, {priority: 'event'});
-    })
-    changeInput('cell_clicked', {});
-
-    // do not trigger table selection when clicking on links unless they have classes
-    table.on('mousedown.dt', 'tbody td a', function(e) {
-      if (this.className === '') e.stopPropagation();
-    });
-
-    methods.addRow = function(data, rowname, resetPaging) {
-      var n = table.columns().indexes().length, d = n - data.length;
-      if (d === 1) {
-        data = rowname.concat(data)
-      } else if (d !== 0) {
-        console.log(data);
-        console.log(table.columns().indexes());
-        throw 'New data must be of the same length as current data (' + n + ')';
-      };
-      table.row.add(data).draw(resetPaging);
-    }
-
-    methods.updateSearch = function(keywords) {
-      if (keywords.global !== null)
-        $(table.table().container()).find('input[type=search]').first()
-             .val(keywords.global).trigger('input');
-      var columns = keywords.columns;
-      if (!filterRow || columns === null) return;
-      filterRow.toArray().map(function(td, i) {
-        var v = typeof columns === 'string' ? columns : columns[i];
-        if (typeof v === 'undefined') {
-          console.log('The search keyword for column ' + i + ' is undefined')
-          return;
-        }
-        // Update column search string and values on linked filter widgets.
-        // 'input' for factor and char filters, 'change' for numeric filters.
-        $(td).find('input').first().val(v).trigger('input', [true]).trigger('change');
-      });
-      table.draw();
-    }
-
-    methods.hideCols = function(hide, reset) {
-      if (reset) table.columns().visible(true, false);
-      table.columns(hide).visible(false);
-    }
-
-    methods.showCols = function(show, reset) {
-      if (reset) table.columns().visible(false, false);
-      table.columns(show).visible(true);
-    }
-
-    methods.colReorder = function(order, origOrder) {
-      table.colReorder.order(order, origOrder);
-    }
-
-    methods.selectPage = function(page) {
-      if (table.page.info().pages < page || page < 1) {
-        throw 'Selected page is out of range';
-      };
-      table.page(page - 1).draw(false);
-    }
-
-    methods.reloadData = function(resetPaging, clearSelection) {
-      // empty selections first if necessary
-      if (methods.selectRows && inArray('row', clearSelection)) methods.selectRows([]);
-      if (methods.selectColumns && inArray('column', clearSelection)) methods.selectColumns([]);
-      if (methods.selectCells && inArray('cell', clearSelection)) methods.selectCells([]);
-      table.ajax.reload(null, resetPaging);
-    }
-
-    // update table filters (set new limits of sliders)
-    methods.updateFilters = function(newProps) {
-      // loop through each filter in the filter row
-      filterRow.each(function(i, td) {
-        var k = i;
-        if (filterRow.length > newProps.length) {
-          if (i === 0) return;  // first column is row names
-          k = i - 1;
-        }
-        // Update the filters to reflect the updated data.
-        // Allow "falsy" (e.g. NULL) to signify a no-op.
-        if (newProps[k]) {
-          setFilterProps(td, newProps[k]);
-        }
-      });
-    };
-
-    table.shinyMethods = methods;
-  },
-  resize: function(el, width, height, instance) {
-    if (instance.data) this.renderValue(el, instance.data, instance);
-
-    // dynamically adjust height if fillContainer = TRUE
-    if (instance.fillContainer)
-      this.fillAvailableHeight(el, height);
-
-    this.adjustWidth(el);
-  },
-
-  // dynamically set the scroll body to fill available height
-  // (used with fillContainer = TRUE)
-  fillAvailableHeight: function(el, availableHeight) {
-
-    // see how much of the table is occupied by header/footer elements
-    // and use that to compute a target scroll body height
-    var dtWrapper = $(el).find('div.dataTables_wrapper');
-    var dtScrollBody = $(el).find($('div.dataTables_scrollBody'));
-    var framingHeight = dtWrapper.innerHeight() - dtScrollBody.innerHeight();
-    var scrollBodyHeight = availableHeight - framingHeight;
-
-    // we need to set `max-height` to none as datatables library now sets this
-    // to a fixed height, disabling the ability to resize to fill the window,
-    // as it will be set to a fixed 100px under such circumstances, e.g., RStudio IDE,
-    // or FlexDashboard
-    // see https://github.com/rstudio/DT/issues/951#issuecomment-1026464509
-    dtScrollBody.css('max-height', 'none');
-    // set the height
-    dtScrollBody.height(scrollBodyHeight + 'px');
-  },
-
-  // adjust the width of columns; remove the hard-coded widths on table and the
-  // scroll header when scrollX/Y are enabled
-  adjustWidth: function(el) {
-    var $el = $(el), table = $el.data('datatable');
-    if (table) table.columns.adjust();
-    $el.find('.dataTables_scrollHeadInner').css('width', '')
-        .children('table').css('margin-left', '');
-  }
-});
-
-  if (!HTMLWidgets.shinyMode) return;
-
-  Shiny.addCustomMessageHandler('datatable-calls', function(data) {
-    var id = data.id;
-    var el = document.getElementById(id);
-    var table = el ? $(el).data('datatable') : null;
-    if (!table) {
-      console.log("Couldn't find table with id " + id);
-      return;
-    }
-
-    var methods = table.shinyMethods, call = data.call;
-    if (methods[call.method]) {
-      methods[call.method].apply(table, call.args);
-    } else {
-      console.log("Unknown method " + call.method);
-    }
-  });
-
-})();
diff --git a/docs/coverage/lib/datatables-css-0.0.0/datatables-crosstalk.css b/docs/coverage/lib/datatables-css-0.0.0/datatables-crosstalk.css
deleted file mode 100644
index bd1159c8..00000000
--- a/docs/coverage/lib/datatables-css-0.0.0/datatables-crosstalk.css
+++ /dev/null
@@ -1,32 +0,0 @@
-.dt-crosstalk-fade {
-  opacity: 0.2;
-}
-
-html body div.DTS div.dataTables_scrollBody {
-  background: none;
-}
-
-
-/*
-Fix https://github.com/rstudio/DT/issues/563
-If the `table.display` is set to "block" (e.g., pkgdown), the browser will display
-datatable objects strangely. The search panel and the page buttons will still be
-in full-width but the table body will be "compact" and shorter.
-In therory, having this attributes will affect `dom="t"`
-with `display: block` users. But in reality, there should be no one.
-We may remove the below lines in the future if the upstream agree to have this there.
-See https://github.com/DataTables/DataTablesSrc/issues/160
-*/
-
-table.dataTable {
-  display: table;
-}
-
-
-/*
-When DTOutput(fill = TRUE), it receives a .html-fill-item class (via htmltools::bindFillRole()), which effectively amounts to `flex: 1 1 auto`. That's mostly fine, but the case where `fillContainer=TRUE`+`height:auto`+`flex-basis:auto` and the container (e.g., a bslib::card()) doesn't have a defined height is a bit problematic since the table wants to fit the parent but the parent wants to fit the table, which results pretty small table height (maybe because there is a minimum height somewhere?). It seems better in this case to impose a 400px height default for the table, which we can do by setting `flex-basis` to 400px (the table is still allowed to grow/shrink when the container has an opinionated height).
-*/
-
-.html-fill-container > .html-fill-item.datatables {
-  flex-basis: 400px;
-}
diff --git a/docs/coverage/lib/dt-core-1.13.6/css/jquery.dataTables.extra.css b/docs/coverage/lib/dt-core-1.13.6/css/jquery.dataTables.extra.css
deleted file mode 100644
index b2dd141f..00000000
--- a/docs/coverage/lib/dt-core-1.13.6/css/jquery.dataTables.extra.css
+++ /dev/null
@@ -1,28 +0,0 @@
-/* Selected rows/cells */
-table.dataTable tr.selected td, table.dataTable td.selected {
-  background-color: #b0bed9 !important;
-}
-/* In case of scrollX/Y or FixedHeader */
-.dataTables_scrollBody .dataTables_sizing {
-  visibility: hidden;
-}
-
-/* The datatables' theme CSS file doesn't define
-the color but with white background. It leads to an issue that
-when the HTML's body color is set to 'white', the user can't
-see the text since the background is white. One case happens in the
-RStudio's IDE when inline viewing the DT table inside an Rmd file,
-if the IDE theme is set to "Cobalt".
-
-See https://github.com/rstudio/DT/issues/447 for more info
-
-This fixes should have little side-effects because all the other elements
-of the default theme use the #333 font color.
-
-TODO: The upstream may use relative colors for both the table background
-and the color. It means the table can display well without this patch
-then. At that time, we need to remove the below CSS attributes.
-*/
-div.datatables {
-  color: #333;
-}
diff --git a/docs/coverage/lib/dt-core-1.13.6/css/jquery.dataTables.min.css b/docs/coverage/lib/dt-core-1.13.6/css/jquery.dataTables.min.css
deleted file mode 100644
index ad59f843..00000000
--- a/docs/coverage/lib/dt-core-1.13.6/css/jquery.dataTables.min.css
+++ /dev/null
@@ -1 +0,0 @@
-:root{--dt-row-selected: 13, 110, 253;--dt-row-selected-text: 255, 255, 255;--dt-row-selected-link: 9, 10, 11;--dt-row-stripe: 0, 0, 0;--dt-row-hover: 0, 0, 0;--dt-column-ordering: 0, 0, 0;--dt-html-background: white}:root.dark{--dt-html-background: rgb(33, 37, 41)}table.dataTable td.dt-control{text-align:center;cursor:pointer}table.dataTable td.dt-control:before{display:inline-block;color:rgba(0, 0, 0, 0.5);content:"►"}table.dataTable tr.dt-hasChild td.dt-control:before{content:"▼"}html.dark table.dataTable td.dt-control:before{color:rgba(255, 255, 255, 0.5)}html.dark table.dataTable tr.dt-hasChild td.dt-control:before{color:rgba(255, 255, 255, 0.5)}table.dataTable thead>tr>th.sorting,table.dataTable thead>tr>th.sorting_asc,table.dataTable thead>tr>th.sorting_desc,table.dataTable thead>tr>th.sorting_asc_disabled,table.dataTable thead>tr>th.sorting_desc_disabled,table.dataTable thead>tr>td.sorting,table.dataTable thead>tr>td.sorting_asc,table.dataTable thead>tr>td.sorting_desc,table.dataTable thead>tr>td.sorting_asc_disabled,table.dataTable thead>tr>td.sorting_desc_disabled{cursor:pointer;position:relative;padding-right:26px}table.dataTable thead>tr>th.sorting:before,table.dataTable thead>tr>th.sorting:after,table.dataTable thead>tr>th.sorting_asc:before,table.dataTable thead>tr>th.sorting_asc:after,table.dataTable thead>tr>th.sorting_desc:before,table.dataTable thead>tr>th.sorting_desc:after,table.dataTable thead>tr>th.sorting_asc_disabled:before,table.dataTable thead>tr>th.sorting_asc_disabled:after,table.dataTable thead>tr>th.sorting_desc_disabled:before,table.dataTable thead>tr>th.sorting_desc_disabled:after,table.dataTable thead>tr>td.sorting:before,table.dataTable thead>tr>td.sorting:after,table.dataTable thead>tr>td.sorting_asc:before,table.dataTable thead>tr>td.sorting_asc:after,table.dataTable thead>tr>td.sorting_desc:before,table.dataTable thead>tr>td.sorting_desc:after,table.dataTable thead>tr>td.sorting_asc_disabled:before,table.dataTable thead>tr>td.sorting_asc_disabled:after,table.dataTable thead>tr>td.sorting_desc_disabled:before,table.dataTable thead>tr>td.sorting_desc_disabled:after{position:absolute;display:block;opacity:.125;right:10px;line-height:9px;font-size:.8em}table.dataTable thead>tr>th.sorting:before,table.dataTable thead>tr>th.sorting_asc:before,table.dataTable thead>tr>th.sorting_desc:before,table.dataTable thead>tr>th.sorting_asc_disabled:before,table.dataTable thead>tr>th.sorting_desc_disabled:before,table.dataTable thead>tr>td.sorting:before,table.dataTable thead>tr>td.sorting_asc:before,table.dataTable thead>tr>td.sorting_desc:before,table.dataTable thead>tr>td.sorting_asc_disabled:before,table.dataTable thead>tr>td.sorting_desc_disabled:before{bottom:50%;content:"▲";content:"▲"/""}table.dataTable thead>tr>th.sorting:after,table.dataTable thead>tr>th.sorting_asc:after,table.dataTable thead>tr>th.sorting_desc:after,table.dataTable thead>tr>th.sorting_asc_disabled:after,table.dataTable thead>tr>th.sorting_desc_disabled:after,table.dataTable thead>tr>td.sorting:after,table.dataTable thead>tr>td.sorting_asc:after,table.dataTable thead>tr>td.sorting_desc:after,table.dataTable thead>tr>td.sorting_asc_disabled:after,table.dataTable thead>tr>td.sorting_desc_disabled:after{top:50%;content:"▼";content:"▼"/""}table.dataTable thead>tr>th.sorting_asc:before,table.dataTable thead>tr>th.sorting_desc:after,table.dataTable thead>tr>td.sorting_asc:before,table.dataTable thead>tr>td.sorting_desc:after{opacity:.6}table.dataTable thead>tr>th.sorting_desc_disabled:after,table.dataTable thead>tr>th.sorting_asc_disabled:before,table.dataTable thead>tr>td.sorting_desc_disabled:after,table.dataTable thead>tr>td.sorting_asc_disabled:before{display:none}table.dataTable thead>tr>th:active,table.dataTable thead>tr>td:active{outline:none}div.dataTables_scrollBody>table.dataTable>thead>tr>th:before,div.dataTables_scrollBody>table.dataTable>thead>tr>th:after,div.dataTables_scrollBody>table.dataTable>thead>tr>td:before,div.dataTables_scrollBody>table.dataTable>thead>tr>td:after{display:none}div.dataTables_processing{position:absolute;top:50%;left:50%;width:200px;margin-left:-100px;margin-top:-26px;text-align:center;padding:2px}div.dataTables_processing>div:last-child{position:relative;width:80px;height:15px;margin:1em auto}div.dataTables_processing>div:last-child>div{position:absolute;top:0;width:13px;height:13px;border-radius:50%;background:rgb(13, 110, 253);background:rgb(var(--dt-row-selected));animation-timing-function:cubic-bezier(0, 1, 1, 0)}div.dataTables_processing>div:last-child>div:nth-child(1){left:8px;animation:datatables-loader-1 .6s infinite}div.dataTables_processing>div:last-child>div:nth-child(2){left:8px;animation:datatables-loader-2 .6s infinite}div.dataTables_processing>div:last-child>div:nth-child(3){left:32px;animation:datatables-loader-2 .6s infinite}div.dataTables_processing>div:last-child>div:nth-child(4){left:56px;animation:datatables-loader-3 .6s infinite}@keyframes datatables-loader-1{0%{transform:scale(0)}100%{transform:scale(1)}}@keyframes datatables-loader-3{0%{transform:scale(1)}100%{transform:scale(0)}}@keyframes datatables-loader-2{0%{transform:translate(0, 0)}100%{transform:translate(24px, 0)}}table.dataTable.nowrap th,table.dataTable.nowrap td{white-space:nowrap}table.dataTable th.dt-left,table.dataTable td.dt-left{text-align:left}table.dataTable th.dt-center,table.dataTable td.dt-center,table.dataTable td.dataTables_empty{text-align:center}table.dataTable th.dt-right,table.dataTable td.dt-right{text-align:right}table.dataTable th.dt-justify,table.dataTable td.dt-justify{text-align:justify}table.dataTable th.dt-nowrap,table.dataTable td.dt-nowrap{white-space:nowrap}table.dataTable thead th,table.dataTable thead td,table.dataTable tfoot th,table.dataTable tfoot td{text-align:left}table.dataTable thead th.dt-head-left,table.dataTable thead td.dt-head-left,table.dataTable tfoot th.dt-head-left,table.dataTable tfoot td.dt-head-left{text-align:left}table.dataTable thead th.dt-head-center,table.dataTable thead td.dt-head-center,table.dataTable tfoot th.dt-head-center,table.dataTable tfoot td.dt-head-center{text-align:center}table.dataTable thead th.dt-head-right,table.dataTable thead td.dt-head-right,table.dataTable tfoot th.dt-head-right,table.dataTable tfoot td.dt-head-right{text-align:right}table.dataTable thead th.dt-head-justify,table.dataTable thead td.dt-head-justify,table.dataTable tfoot th.dt-head-justify,table.dataTable tfoot td.dt-head-justify{text-align:justify}table.dataTable thead th.dt-head-nowrap,table.dataTable thead td.dt-head-nowrap,table.dataTable tfoot th.dt-head-nowrap,table.dataTable tfoot td.dt-head-nowrap{white-space:nowrap}table.dataTable tbody 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diff --git a/docs/coverage/lib/dt-core-1.13.6/js/jquery.dataTables.min.js b/docs/coverage/lib/dt-core-1.13.6/js/jquery.dataTables.min.js
deleted file mode 100644
index f786b0da..00000000
--- a/docs/coverage/lib/dt-core-1.13.6/js/jquery.dataTables.min.js
+++ /dev/null
@@ -1,4 +0,0 @@
-/*! DataTables 1.13.6
- * ©2008-2023 SpryMedia Ltd - datatables.net/license
- */
-!function(n){"use strict";var a;"function"==typeof define&&define.amd?define(["jquery"],function(t){return n(t,window,document)}):"object"==typeof exports?(a=require("jquery"),"undefined"==typeof window?module.exports=function(t,e){return t=t||window,e=e||a(t),n(e,t,t.document)}:n(a,window,window.document)):window.DataTable=n(jQuery,window,document)}(function(P,j,v,H){"use strict";function d(t){var e=parseInt(t,10);return!isNaN(e)&&isFinite(t)?e:null}function l(t,e,n){var a=typeof t,r="string"==a;return"number"==a||"bigint"==a||!!h(t)||(e&&r&&(t=$(t,e)),n&&r&&(t=t.replace(q,"")),!isNaN(parseFloat(t))&&isFinite(t))}function a(t,e,n){var a;return!!h(t)||(h(a=t)||"string"==typeof a)&&!!l(t.replace(V,"").replace(/
 
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diff --git a/docs/deps/font-awesome-6.5.2/css/all.css b/docs/deps/font-awesome-6.5.2/css/all.css
new file mode 100644
index 00000000..151dd57c
--- /dev/null
+++ b/docs/deps/font-awesome-6.5.2/css/all.css
@@ -0,0 +1,8028 @@
+/*!
+ * Font Awesome Free 6.5.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2024 Fonticons, Inc.
+ */
+.fa {
+  font-family: var(--fa-style-family, "Font Awesome 6 Free");
+  font-weight: var(--fa-style, 900); }
+
+.fa,
+.fa-classic,
+.fa-sharp,
+.fas,
+.fa-solid,
+.far,
+.fa-regular,
+.fab,
+.fa-brands {
+  -moz-osx-font-smoothing: grayscale;
+  -webkit-font-smoothing: antialiased;
+  display: var(--fa-display, inline-block);
+  font-style: normal;
+  font-variant: normal;
+  line-height: 1;
+  text-rendering: auto; }
+
+.fas,
+.fa-classic,
+.fa-solid,
+.far,
+.fa-regular {
+  font-family: 'Font Awesome 6 Free'; }
+
+.fab,
+.fa-brands {
+  font-family: 'Font Awesome 6 Brands'; }
+
+.fa-1x {
+  font-size: 1em; }
+
+.fa-2x {
+  font-size: 2em; }
+
+.fa-3x {
+  font-size: 3em; }
+
+.fa-4x {
+  font-size: 4em; }
+
+.fa-5x {
+  font-size: 5em; }
+
+.fa-6x {
+  font-size: 6em; }
+
+.fa-7x {
+  font-size: 7em; }
+
+.fa-8x {
+  font-size: 8em; }
+
+.fa-9x {
+  font-size: 9em; }
+
+.fa-10x {
+  font-size: 10em; }
+
+.fa-2xs {
+  font-size: 0.625em;
+  line-height: 0.1em;
+  vertical-align: 0.225em; }
+
+.fa-xs {
+  font-size: 0.75em;
+  line-height: 0.08333em;
+  vertical-align: 0.125em; }
+
+.fa-sm {
+  font-size: 0.875em;
+  line-height: 0.07143em;
+  vertical-align: 0.05357em; }
+
+.fa-lg {
+  font-size: 1.25em;
+  line-height: 0.05em;
+  vertical-align: -0.075em; }
+
+.fa-xl {
+  font-size: 1.5em;
+  line-height: 0.04167em;
+  vertical-align: -0.125em; }
+
+.fa-2xl {
+  font-size: 2em;
+  line-height: 0.03125em;
+  vertical-align: -0.1875em; }
+
+.fa-fw {
+  text-align: center;
+  width: 1.25em; }
+
+.fa-ul {
+  list-style-type: none;
+  margin-left: var(--fa-li-margin, 2.5em);
+  padding-left: 0; }
+  .fa-ul > li {
+    position: relative; }
+
+.fa-li {
+  left: calc(var(--fa-li-width, 2em) * -1);
+  position: absolute;
+  text-align: center;
+  width: var(--fa-li-width, 2em);
+  line-height: inherit; }
+
+.fa-border {
+  border-color: var(--fa-border-color, #eee);
+  border-radius: var(--fa-border-radius, 0.1em);
+  border-style: var(--fa-border-style, solid);
+  border-width: var(--fa-border-width, 0.08em);
+  padding: var(--fa-border-padding, 0.2em 0.25em 0.15em); }
+
+.fa-pull-left {
+  float: left;
+  margin-right: var(--fa-pull-margin, 0.3em); }
+
+.fa-pull-right {
+  float: right;
+  margin-left: var(--fa-pull-margin, 0.3em); }
+
+.fa-beat {
+  -webkit-animation-name: fa-beat;
+          animation-name: fa-beat;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, ease-in-out);
+          animation-timing-function: var(--fa-animation-timing, ease-in-out); }
+
+.fa-bounce {
+  -webkit-animation-name: fa-bounce;
+          animation-name: fa-bounce;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.28, 0.84, 0.42, 1));
+          animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.28, 0.84, 0.42, 1)); }
+
+.fa-fade {
+  -webkit-animation-name: fa-fade;
+          animation-name: fa-fade;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1));
+          animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); }
+
+.fa-beat-fade {
+  -webkit-animation-name: fa-beat-fade;
+          animation-name: fa-beat-fade;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1));
+          animation-timing-function: var(--fa-animation-timing, cubic-bezier(0.4, 0, 0.6, 1)); }
+
+.fa-flip {
+  -webkit-animation-name: fa-flip;
+          animation-name: fa-flip;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, ease-in-out);
+          animation-timing-function: var(--fa-animation-timing, ease-in-out); }
+
+.fa-shake {
+  -webkit-animation-name: fa-shake;
+          animation-name: fa-shake;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, linear);
+          animation-timing-function: var(--fa-animation-timing, linear); }
+
+.fa-spin {
+  -webkit-animation-name: fa-spin;
+          animation-name: fa-spin;
+  -webkit-animation-delay: var(--fa-animation-delay, 0s);
+          animation-delay: var(--fa-animation-delay, 0s);
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 2s);
+          animation-duration: var(--fa-animation-duration, 2s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, linear);
+          animation-timing-function: var(--fa-animation-timing, linear); }
+
+.fa-spin-reverse {
+  --fa-animation-direction: reverse; }
+
+.fa-pulse,
+.fa-spin-pulse {
+  -webkit-animation-name: fa-spin;
+          animation-name: fa-spin;
+  -webkit-animation-direction: var(--fa-animation-direction, normal);
+          animation-direction: var(--fa-animation-direction, normal);
+  -webkit-animation-duration: var(--fa-animation-duration, 1s);
+          animation-duration: var(--fa-animation-duration, 1s);
+  -webkit-animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+          animation-iteration-count: var(--fa-animation-iteration-count, infinite);
+  -webkit-animation-timing-function: var(--fa-animation-timing, steps(8));
+          animation-timing-function: var(--fa-animation-timing, steps(8)); }
+
+@media (prefers-reduced-motion: reduce) {
+  .fa-beat,
+  .fa-bounce,
+  .fa-fade,
+  .fa-beat-fade,
+  .fa-flip,
+  .fa-pulse,
+  .fa-shake,
+  .fa-spin,
+  .fa-spin-pulse {
+    -webkit-animation-delay: -1ms;
+            animation-delay: -1ms;
+    -webkit-animation-duration: 1ms;
+            animation-duration: 1ms;
+    -webkit-animation-iteration-count: 1;
+            animation-iteration-count: 1;
+    -webkit-transition-delay: 0s;
+            transition-delay: 0s;
+    -webkit-transition-duration: 0s;
+            transition-duration: 0s; } }
+
+@-webkit-keyframes fa-beat {
+  0%, 90% {
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  45% {
+    -webkit-transform: scale(var(--fa-beat-scale, 1.25));
+            transform: scale(var(--fa-beat-scale, 1.25)); } }
+
+@keyframes fa-beat {
+  0%, 90% {
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  45% {
+    -webkit-transform: scale(var(--fa-beat-scale, 1.25));
+            transform: scale(var(--fa-beat-scale, 1.25)); } }
+
+@-webkit-keyframes fa-bounce {
+  0% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  10% {
+    -webkit-transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0);
+            transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); }
+  30% {
+    -webkit-transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em));
+            transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); }
+  50% {
+    -webkit-transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0);
+            transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); }
+  57% {
+    -webkit-transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em));
+            transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); }
+  64% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  100% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); } }
+
+@keyframes fa-bounce {
+  0% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  10% {
+    -webkit-transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0);
+            transform: scale(var(--fa-bounce-start-scale-x, 1.1), var(--fa-bounce-start-scale-y, 0.9)) translateY(0); }
+  30% {
+    -webkit-transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em));
+            transform: scale(var(--fa-bounce-jump-scale-x, 0.9), var(--fa-bounce-jump-scale-y, 1.1)) translateY(var(--fa-bounce-height, -0.5em)); }
+  50% {
+    -webkit-transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0);
+            transform: scale(var(--fa-bounce-land-scale-x, 1.05), var(--fa-bounce-land-scale-y, 0.95)) translateY(0); }
+  57% {
+    -webkit-transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em));
+            transform: scale(1, 1) translateY(var(--fa-bounce-rebound, -0.125em)); }
+  64% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); }
+  100% {
+    -webkit-transform: scale(1, 1) translateY(0);
+            transform: scale(1, 1) translateY(0); } }
+
+@-webkit-keyframes fa-fade {
+  50% {
+    opacity: var(--fa-fade-opacity, 0.4); } }
+
+@keyframes fa-fade {
+  50% {
+    opacity: var(--fa-fade-opacity, 0.4); } }
+
+@-webkit-keyframes fa-beat-fade {
+  0%, 100% {
+    opacity: var(--fa-beat-fade-opacity, 0.4);
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  50% {
+    opacity: 1;
+    -webkit-transform: scale(var(--fa-beat-fade-scale, 1.125));
+            transform: scale(var(--fa-beat-fade-scale, 1.125)); } }
+
+@keyframes fa-beat-fade {
+  0%, 100% {
+    opacity: var(--fa-beat-fade-opacity, 0.4);
+    -webkit-transform: scale(1);
+            transform: scale(1); }
+  50% {
+    opacity: 1;
+    -webkit-transform: scale(var(--fa-beat-fade-scale, 1.125));
+            transform: scale(var(--fa-beat-fade-scale, 1.125)); } }
+
+@-webkit-keyframes fa-flip {
+  50% {
+    -webkit-transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg));
+            transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); } }
+
+@keyframes fa-flip {
+  50% {
+    -webkit-transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg));
+            transform: rotate3d(var(--fa-flip-x, 0), var(--fa-flip-y, 1), var(--fa-flip-z, 0), var(--fa-flip-angle, -180deg)); } }
+
+@-webkit-keyframes fa-shake {
+  0% {
+    -webkit-transform: rotate(-15deg);
+            transform: rotate(-15deg); }
+  4% {
+    -webkit-transform: rotate(15deg);
+            transform: rotate(15deg); }
+  8%, 24% {
+    -webkit-transform: rotate(-18deg);
+            transform: rotate(-18deg); }
+  12%, 28% {
+    -webkit-transform: rotate(18deg);
+            transform: rotate(18deg); }
+  16% {
+    -webkit-transform: rotate(-22deg);
+            transform: rotate(-22deg); }
+  20% {
+    -webkit-transform: rotate(22deg);
+            transform: rotate(22deg); }
+  32% {
+    -webkit-transform: rotate(-12deg);
+            transform: rotate(-12deg); }
+  36% {
+    -webkit-transform: rotate(12deg);
+            transform: rotate(12deg); }
+  40%, 100% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); } }
+
+@keyframes fa-shake {
+  0% {
+    -webkit-transform: rotate(-15deg);
+            transform: rotate(-15deg); }
+  4% {
+    -webkit-transform: rotate(15deg);
+            transform: rotate(15deg); }
+  8%, 24% {
+    -webkit-transform: rotate(-18deg);
+            transform: rotate(-18deg); }
+  12%, 28% {
+    -webkit-transform: rotate(18deg);
+            transform: rotate(18deg); }
+  16% {
+    -webkit-transform: rotate(-22deg);
+            transform: rotate(-22deg); }
+  20% {
+    -webkit-transform: rotate(22deg);
+            transform: rotate(22deg); }
+  32% {
+    -webkit-transform: rotate(-12deg);
+            transform: rotate(-12deg); }
+  36% {
+    -webkit-transform: rotate(12deg);
+            transform: rotate(12deg); }
+  40%, 100% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); } }
+
+@-webkit-keyframes fa-spin {
+  0% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); }
+  100% {
+    -webkit-transform: rotate(360deg);
+            transform: rotate(360deg); } }
+
+@keyframes fa-spin {
+  0% {
+    -webkit-transform: rotate(0deg);
+            transform: rotate(0deg); }
+  100% {
+    -webkit-transform: rotate(360deg);
+            transform: rotate(360deg); } }
+
+.fa-rotate-90 {
+  -webkit-transform: rotate(90deg);
+          transform: rotate(90deg); }
+
+.fa-rotate-180 {
+  -webkit-transform: rotate(180deg);
+          transform: rotate(180deg); }
+
+.fa-rotate-270 {
+  -webkit-transform: rotate(270deg);
+          transform: rotate(270deg); }
+
+.fa-flip-horizontal {
+  -webkit-transform: scale(-1, 1);
+          transform: scale(-1, 1); }
+
+.fa-flip-vertical {
+  -webkit-transform: scale(1, -1);
+          transform: scale(1, -1); }
+
+.fa-flip-both,
+.fa-flip-horizontal.fa-flip-vertical {
+  -webkit-transform: scale(-1, -1);
+          transform: scale(-1, -1); }
+
+.fa-rotate-by {
+  -webkit-transform: rotate(var(--fa-rotate-angle, 0));
+          transform: rotate(var(--fa-rotate-angle, 0)); }
+
+.fa-stack {
+  display: inline-block;
+  height: 2em;
+  line-height: 2em;
+  position: relative;
+  vertical-align: middle;
+  width: 2.5em; }
+
+.fa-stack-1x,
+.fa-stack-2x {
+  left: 0;
+  position: absolute;
+  text-align: center;
+  width: 100%;
+  z-index: var(--fa-stack-z-index, auto); }
+
+.fa-stack-1x {
+  line-height: inherit; }
+
+.fa-stack-2x {
+  font-size: 2em; }
+
+.fa-inverse {
+  color: var(--fa-inverse, #fff); }
+
+/* Font Awesome uses the Unicode Private Use Area (PUA) to ensure screen
+readers do not read off random characters that represent icons */
+
+.fa-0::before {
+  content: "\30"; }
+
+.fa-1::before {
+  content: "\31"; }
+
+.fa-2::before {
+  content: "\32"; }
+
+.fa-3::before {
+  content: "\33"; }
+
+.fa-4::before {
+  content: "\34"; }
+
+.fa-5::before {
+  content: "\35"; }
+
+.fa-6::before {
+  content: "\36"; }
+
+.fa-7::before {
+  content: "\37"; }
+
+.fa-8::before {
+  content: "\38"; }
+
+.fa-9::before {
+  content: "\39"; }
+
+.fa-fill-drip::before {
+  content: "\f576"; }
+
+.fa-arrows-to-circle::before {
+  content: "\e4bd"; }
+
+.fa-circle-chevron-right::before {
+  content: "\f138"; }
+
+.fa-chevron-circle-right::before {
+  content: "\f138"; }
+
+.fa-at::before {
+  content: "\40"; }
+
+.fa-trash-can::before {
+  content: "\f2ed"; }
+
+.fa-trash-alt::before {
+  content: "\f2ed"; }
+
+.fa-text-height::before {
+  content: "\f034"; }
+
+.fa-user-xmark::before {
+  content: "\f235"; }
+
+.fa-user-times::before {
+  content: "\f235"; }
+
+.fa-stethoscope::before {
+  content: "\f0f1"; }
+
+.fa-message::before {
+  content: "\f27a"; }
+
+.fa-comment-alt::before {
+  content: "\f27a"; }
+
+.fa-info::before {
+  content: "\f129"; }
+
+.fa-down-left-and-up-right-to-center::before {
+  content: "\f422"; }
+
+.fa-compress-alt::before {
+  content: "\f422"; }
+
+.fa-explosion::before {
+  content: "\e4e9"; }
+
+.fa-file-lines::before {
+  content: "\f15c"; }
+
+.fa-file-alt::before {
+  content: "\f15c"; }
+
+.fa-file-text::before {
+  content: "\f15c"; }
+
+.fa-wave-square::before {
+  content: "\f83e"; }
+
+.fa-ring::before {
+  content: "\f70b"; }
+
+.fa-building-un::before {
+  content: "\e4d9"; }
+
+.fa-dice-three::before {
+  content: "\f527"; }
+
+.fa-calendar-days::before {
+  content: "\f073"; }
+
+.fa-calendar-alt::before {
+  content: "\f073"; }
+
+.fa-anchor-circle-check::before {
+  content: "\e4aa"; }
+
+.fa-building-circle-arrow-right::before {
+  content: "\e4d1"; }
+
+.fa-volleyball::before {
+  content: "\f45f"; }
+
+.fa-volleyball-ball::before {
+  content: "\f45f"; }
+
+.fa-arrows-up-to-line::before {
+  content: "\e4c2"; }
+
+.fa-sort-down::before {
+  content: "\f0dd"; }
+
+.fa-sort-desc::before {
+  content: "\f0dd"; }
+
+.fa-circle-minus::before {
+  content: "\f056"; }
+
+.fa-minus-circle::before {
+  content: "\f056"; }
+
+.fa-door-open::before {
+  content: "\f52b"; }
+
+.fa-right-from-bracket::before {
+  content: "\f2f5"; }
+
+.fa-sign-out-alt::before {
+  content: "\f2f5"; }
+
+.fa-atom::before {
+  content: "\f5d2"; }
+
+.fa-soap::before {
+  content: "\e06e"; }
+
+.fa-icons::before {
+  content: "\f86d"; }
+
+.fa-heart-music-camera-bolt::before {
+  content: "\f86d"; }
+
+.fa-microphone-lines-slash::before {
+  content: "\f539"; }
+
+.fa-microphone-alt-slash::before {
+  content: "\f539"; }
+
+.fa-bridge-circle-check::before {
+  content: "\e4c9"; }
+
+.fa-pump-medical::before {
+  content: "\e06a"; }
+
+.fa-fingerprint::before {
+  content: "\f577"; }
+
+.fa-hand-point-right::before {
+  content: "\f0a4"; }
+
+.fa-magnifying-glass-location::before {
+  content: "\f689"; }
+
+.fa-search-location::before {
+  content: "\f689"; }
+
+.fa-forward-step::before {
+  content: "\f051"; }
+
+.fa-step-forward::before {
+  content: "\f051"; }
+
+.fa-face-smile-beam::before {
+  content: "\f5b8"; }
+
+.fa-smile-beam::before {
+  content: "\f5b8"; }
+
+.fa-flag-checkered::before {
+  content: "\f11e"; }
+
+.fa-football::before {
+  content: "\f44e"; }
+
+.fa-football-ball::before {
+  content: "\f44e"; }
+
+.fa-school-circle-exclamation::before {
+  content: "\e56c"; }
+
+.fa-crop::before {
+  content: "\f125"; }
+
+.fa-angles-down::before {
+  content: "\f103"; }
+
+.fa-angle-double-down::before {
+  content: "\f103"; }
+
+.fa-users-rectangle::before {
+  content: "\e594"; }
+
+.fa-people-roof::before {
+  content: "\e537"; }
+
+.fa-people-line::before {
+  content: "\e534"; }
+
+.fa-beer-mug-empty::before {
+  content: "\f0fc"; }
+
+.fa-beer::before {
+  content: "\f0fc"; }
+
+.fa-diagram-predecessor::before {
+  content: "\e477"; }
+
+.fa-arrow-up-long::before {
+  content: "\f176"; }
+
+.fa-long-arrow-up::before {
+  content: "\f176"; }
+
+.fa-fire-flame-simple::before {
+  content: "\f46a"; }
+
+.fa-burn::before {
+  content: "\f46a"; }
+
+.fa-person::before {
+  content: "\f183"; }
+
+.fa-male::before {
+  content: "\f183"; }
+
+.fa-laptop::before {
+  content: "\f109"; }
+
+.fa-file-csv::before {
+  content: "\f6dd"; }
+
+.fa-menorah::before {
+  content: "\f676"; }
+
+.fa-truck-plane::before {
+  content: "\e58f"; }
+
+.fa-record-vinyl::before {
+  content: "\f8d9"; }
+
+.fa-face-grin-stars::before {
+  content: "\f587"; }
+
+.fa-grin-stars::before {
+  content: "\f587"; }
+
+.fa-bong::before {
+  content: "\f55c"; }
+
+.fa-spaghetti-monster-flying::before {
+  content: "\f67b"; }
+
+.fa-pastafarianism::before {
+  content: "\f67b"; }
+
+.fa-arrow-down-up-across-line::before {
+  content: "\e4af"; }
+
+.fa-spoon::before {
+  content: "\f2e5"; }
+
+.fa-utensil-spoon::before {
+  content: "\f2e5"; }
+
+.fa-jar-wheat::before {
+  content: "\e517"; }
+
+.fa-envelopes-bulk::before {
+  content: "\f674"; }
+
+.fa-mail-bulk::before {
+  content: "\f674"; }
+
+.fa-file-circle-exclamation::before {
+  content: "\e4eb"; }
+
+.fa-circle-h::before {
+  content: "\f47e"; }
+
+.fa-hospital-symbol::before {
+  content: "\f47e"; }
+
+.fa-pager::before {
+  content: "\f815"; }
+
+.fa-address-book::before {
+  content: "\f2b9"; }
+
+.fa-contact-book::before {
+  content: "\f2b9"; }
+
+.fa-strikethrough::before {
+  content: "\f0cc"; }
+
+.fa-k::before {
+  content: "\4b"; }
+
+.fa-landmark-flag::before {
+  content: "\e51c"; }
+
+.fa-pencil::before {
+  content: "\f303"; }
+
+.fa-pencil-alt::before {
+  content: "\f303"; }
+
+.fa-backward::before {
+  content: "\f04a"; }
+
+.fa-caret-right::before {
+  content: "\f0da"; }
+
+.fa-comments::before {
+  content: "\f086"; }
+
+.fa-paste::before {
+  content: "\f0ea"; }
+
+.fa-file-clipboard::before {
+  content: "\f0ea"; }
+
+.fa-code-pull-request::before {
+  content: "\e13c"; }
+
+.fa-clipboard-list::before {
+  content: "\f46d"; }
+
+.fa-truck-ramp-box::before {
+  content: "\f4de"; }
+
+.fa-truck-loading::before {
+  content: "\f4de"; }
+
+.fa-user-check::before {
+  content: "\f4fc"; }
+
+.fa-vial-virus::before {
+  content: "\e597"; }
+
+.fa-sheet-plastic::before {
+  content: "\e571"; }
+
+.fa-blog::before {
+  content: "\f781"; }
+
+.fa-user-ninja::before {
+  content: "\f504"; }
+
+.fa-person-arrow-up-from-line::before {
+  content: "\e539"; }
+
+.fa-scroll-torah::before {
+  content: "\f6a0"; }
+
+.fa-torah::before {
+  content: "\f6a0"; }
+
+.fa-broom-ball::before {
+  content: "\f458"; }
+
+.fa-quidditch::before {
+  content: "\f458"; }
+
+.fa-quidditch-broom-ball::before {
+  content: "\f458"; }
+
+.fa-toggle-off::before {
+  content: "\f204"; }
+
+.fa-box-archive::before {
+  content: "\f187"; }
+
+.fa-archive::before {
+  content: "\f187"; }
+
+.fa-person-drowning::before {
+  content: "\e545"; }
+
+.fa-arrow-down-9-1::before {
+  content: "\f886"; }
+
+.fa-sort-numeric-desc::before {
+  content: "\f886"; }
+
+.fa-sort-numeric-down-alt::before {
+  content: "\f886"; }
+
+.fa-face-grin-tongue-squint::before {
+  content: "\f58a"; }
+
+.fa-grin-tongue-squint::before {
+  content: "\f58a"; }
+
+.fa-spray-can::before {
+  content: "\f5bd"; }
+
+.fa-truck-monster::before {
+  content: "\f63b"; }
+
+.fa-w::before {
+  content: "\57"; }
+
+.fa-earth-africa::before {
+  content: "\f57c"; }
+
+.fa-globe-africa::before {
+  content: "\f57c"; }
+
+.fa-rainbow::before {
+  content: "\f75b"; }
+
+.fa-circle-notch::before {
+  content: "\f1ce"; }
+
+.fa-tablet-screen-button::before {
+  content: "\f3fa"; }
+
+.fa-tablet-alt::before {
+  content: "\f3fa"; }
+
+.fa-paw::before {
+  content: "\f1b0"; }
+
+.fa-cloud::before {
+  content: "\f0c2"; }
+
+.fa-trowel-bricks::before {
+  content: "\e58a"; }
+
+.fa-face-flushed::before {
+  content: "\f579"; }
+
+.fa-flushed::before {
+  content: "\f579"; }
+
+.fa-hospital-user::before {
+  content: "\f80d"; }
+
+.fa-tent-arrow-left-right::before {
+  content: "\e57f"; }
+
+.fa-gavel::before {
+  content: "\f0e3"; }
+
+.fa-legal::before {
+  content: "\f0e3"; }
+
+.fa-binoculars::before {
+  content: "\f1e5"; }
+
+.fa-microphone-slash::before {
+  content: "\f131"; }
+
+.fa-box-tissue::before {
+  content: "\e05b"; }
+
+.fa-motorcycle::before {
+  content: "\f21c"; }
+
+.fa-bell-concierge::before {
+  content: "\f562"; }
+
+.fa-concierge-bell::before {
+  content: "\f562"; }
+
+.fa-pen-ruler::before {
+  content: "\f5ae"; }
+
+.fa-pencil-ruler::before {
+  content: "\f5ae"; }
+
+.fa-people-arrows::before {
+  content: "\e068"; }
+
+.fa-people-arrows-left-right::before {
+  content: "\e068"; }
+
+.fa-mars-and-venus-burst::before {
+  content: "\e523"; }
+
+.fa-square-caret-right::before {
+  content: "\f152"; }
+
+.fa-caret-square-right::before {
+  content: "\f152"; }
+
+.fa-scissors::before {
+  content: "\f0c4"; }
+
+.fa-cut::before {
+  content: "\f0c4"; }
+
+.fa-sun-plant-wilt::before {
+  content: "\e57a"; }
+
+.fa-toilets-portable::before {
+  content: "\e584"; }
+
+.fa-hockey-puck::before {
+  content: "\f453"; }
+
+.fa-table::before {
+  content: "\f0ce"; }
+
+.fa-magnifying-glass-arrow-right::before {
+  content: "\e521"; }
+
+.fa-tachograph-digital::before {
+  content: "\f566"; }
+
+.fa-digital-tachograph::before {
+  content: "\f566"; }
+
+.fa-users-slash::before {
+  content: "\e073"; }
+
+.fa-clover::before {
+  content: "\e139"; }
+
+.fa-reply::before {
+  content: "\f3e5"; }
+
+.fa-mail-reply::before {
+  content: "\f3e5"; }
+
+.fa-star-and-crescent::before {
+  content: "\f699"; }
+
+.fa-house-fire::before {
+  content: "\e50c"; }
+
+.fa-square-minus::before {
+  content: "\f146"; }
+
+.fa-minus-square::before {
+  content: "\f146"; }
+
+.fa-helicopter::before {
+  content: "\f533"; }
+
+.fa-compass::before {
+  content: "\f14e"; }
+
+.fa-square-caret-down::before {
+  content: "\f150"; }
+
+.fa-caret-square-down::before {
+  content: "\f150"; }
+
+.fa-file-circle-question::before {
+  content: "\e4ef"; }
+
+.fa-laptop-code::before {
+  content: "\f5fc"; }
+
+.fa-swatchbook::before {
+  content: "\f5c3"; }
+
+.fa-prescription-bottle::before {
+  content: "\f485"; }
+
+.fa-bars::before {
+  content: "\f0c9"; }
+
+.fa-navicon::before {
+  content: "\f0c9"; }
+
+.fa-people-group::before {
+  content: "\e533"; }
+
+.fa-hourglass-end::before {
+  content: "\f253"; }
+
+.fa-hourglass-3::before {
+  content: "\f253"; }
+
+.fa-heart-crack::before {
+  content: "\f7a9"; }
+
+.fa-heart-broken::before {
+  content: "\f7a9"; }
+
+.fa-square-up-right::before {
+  content: "\f360"; }
+
+.fa-external-link-square-alt::before {
+  content: "\f360"; }
+
+.fa-face-kiss-beam::before {
+  content: "\f597"; }
+
+.fa-kiss-beam::before {
+  content: "\f597"; }
+
+.fa-film::before {
+  content: "\f008"; }
+
+.fa-ruler-horizontal::before {
+  content: "\f547"; }
+
+.fa-people-robbery::before {
+  content: "\e536"; }
+
+.fa-lightbulb::before {
+  content: "\f0eb"; }
+
+.fa-caret-left::before {
+  content: "\f0d9"; }
+
+.fa-circle-exclamation::before {
+  content: "\f06a"; }
+
+.fa-exclamation-circle::before {
+  content: "\f06a"; }
+
+.fa-school-circle-xmark::before {
+  content: "\e56d"; }
+
+.fa-arrow-right-from-bracket::before {
+  content: "\f08b"; }
+
+.fa-sign-out::before {
+  content: "\f08b"; }
+
+.fa-circle-chevron-down::before {
+  content: "\f13a"; }
+
+.fa-chevron-circle-down::before {
+  content: "\f13a"; }
+
+.fa-unlock-keyhole::before {
+  content: "\f13e"; }
+
+.fa-unlock-alt::before {
+  content: "\f13e"; }
+
+.fa-cloud-showers-heavy::before {
+  content: "\f740"; }
+
+.fa-headphones-simple::before {
+  content: "\f58f"; }
+
+.fa-headphones-alt::before {
+  content: "\f58f"; }
+
+.fa-sitemap::before {
+  content: "\f0e8"; }
+
+.fa-circle-dollar-to-slot::before {
+  content: "\f4b9"; }
+
+.fa-donate::before {
+  content: "\f4b9"; }
+
+.fa-memory::before {
+  content: "\f538"; }
+
+.fa-road-spikes::before {
+  content: "\e568"; }
+
+.fa-fire-burner::before {
+  content: "\e4f1"; }
+
+.fa-flag::before {
+  content: "\f024"; }
+
+.fa-hanukiah::before {
+  content: "\f6e6"; }
+
+.fa-feather::before {
+  content: "\f52d"; }
+
+.fa-volume-low::before {
+  content: "\f027"; }
+
+.fa-volume-down::before {
+  content: "\f027"; }
+
+.fa-comment-slash::before {
+  content: "\f4b3"; }
+
+.fa-cloud-sun-rain::before {
+  content: "\f743"; }
+
+.fa-compress::before {
+  content: "\f066"; }
+
+.fa-wheat-awn::before {
+  content: "\e2cd"; }
+
+.fa-wheat-alt::before {
+  content: "\e2cd"; }
+
+.fa-ankh::before {
+  content: "\f644"; }
+
+.fa-hands-holding-child::before {
+  content: "\e4fa"; }
+
+.fa-asterisk::before {
+  content: "\2a"; }
+
+.fa-square-check::before {
+  content: "\f14a"; }
+
+.fa-check-square::before {
+  content: "\f14a"; }
+
+.fa-peseta-sign::before {
+  content: "\e221"; }
+
+.fa-heading::before {
+  content: "\f1dc"; }
+
+.fa-header::before {
+  content: "\f1dc"; }
+
+.fa-ghost::before {
+  content: "\f6e2"; }
+
+.fa-list::before {
+  content: "\f03a"; }
+
+.fa-list-squares::before {
+  content: "\f03a"; }
+
+.fa-square-phone-flip::before {
+  content: "\f87b"; }
+
+.fa-phone-square-alt::before {
+  content: "\f87b"; }
+
+.fa-cart-plus::before {
+  content: "\f217"; }
+
+.fa-gamepad::before {
+  content: "\f11b"; }
+
+.fa-circle-dot::before {
+  content: "\f192"; }
+
+.fa-dot-circle::before {
+  content: "\f192"; }
+
+.fa-face-dizzy::before {
+  content: "\f567"; }
+
+.fa-dizzy::before {
+  content: "\f567"; }
+
+.fa-egg::before {
+  content: "\f7fb"; }
+
+.fa-house-medical-circle-xmark::before {
+  content: "\e513"; }
+
+.fa-campground::before {
+  content: "\f6bb"; }
+
+.fa-folder-plus::before {
+  content: "\f65e"; }
+
+.fa-futbol::before {
+  content: "\f1e3"; }
+
+.fa-futbol-ball::before {
+  content: "\f1e3"; }
+
+.fa-soccer-ball::before {
+  content: "\f1e3"; }
+
+.fa-paintbrush::before {
+  content: "\f1fc"; }
+
+.fa-paint-brush::before {
+  content: "\f1fc"; }
+
+.fa-lock::before {
+  content: "\f023"; }
+
+.fa-gas-pump::before {
+  content: "\f52f"; }
+
+.fa-hot-tub-person::before {
+  content: "\f593"; }
+
+.fa-hot-tub::before {
+  content: "\f593"; }
+
+.fa-map-location::before {
+  content: "\f59f"; }
+
+.fa-map-marked::before {
+  content: "\f59f"; }
+
+.fa-house-flood-water::before {
+  content: "\e50e"; }
+
+.fa-tree::before {
+  content: "\f1bb"; }
+
+.fa-bridge-lock::before {
+  content: "\e4cc"; }
+
+.fa-sack-dollar::before {
+  content: "\f81d"; }
+
+.fa-pen-to-square::before {
+  content: "\f044"; }
+
+.fa-edit::before {
+  content: "\f044"; }
+
+.fa-car-side::before {
+  content: "\f5e4"; }
+
+.fa-share-nodes::before {
+  content: "\f1e0"; }
+
+.fa-share-alt::before {
+  content: "\f1e0"; }
+
+.fa-heart-circle-minus::before {
+  content: "\e4ff"; }
+
+.fa-hourglass-half::before {
+  content: "\f252"; }
+
+.fa-hourglass-2::before {
+  content: "\f252"; }
+
+.fa-microscope::before {
+  content: "\f610"; }
+
+.fa-sink::before {
+  content: "\e06d"; }
+
+.fa-bag-shopping::before {
+  content: "\f290"; }
+
+.fa-shopping-bag::before {
+  content: "\f290"; }
+
+.fa-arrow-down-z-a::before {
+  content: "\f881"; }
+
+.fa-sort-alpha-desc::before {
+  content: "\f881"; }
+
+.fa-sort-alpha-down-alt::before {
+  content: "\f881"; }
+
+.fa-mitten::before {
+  content: "\f7b5"; }
+
+.fa-person-rays::before {
+  content: "\e54d"; }
+
+.fa-users::before {
+  content: "\f0c0"; }
+
+.fa-eye-slash::before {
+  content: "\f070"; }
+
+.fa-flask-vial::before {
+  content: "\e4f3"; }
+
+.fa-hand::before {
+  content: "\f256"; }
+
+.fa-hand-paper::before {
+  content: "\f256"; }
+
+.fa-om::before {
+  content: "\f679"; }
+
+.fa-worm::before {
+  content: "\e599"; }
+
+.fa-house-circle-xmark::before {
+  content: "\e50b"; }
+
+.fa-plug::before {
+  content: "\f1e6"; }
+
+.fa-chevron-up::before {
+  content: "\f077"; }
+
+.fa-hand-spock::before {
+  content: "\f259"; }
+
+.fa-stopwatch::before {
+  content: "\f2f2"; }
+
+.fa-face-kiss::before {
+  content: "\f596"; }
+
+.fa-kiss::before {
+  content: "\f596"; }
+
+.fa-bridge-circle-xmark::before {
+  content: "\e4cb"; }
+
+.fa-face-grin-tongue::before {
+  content: "\f589"; }
+
+.fa-grin-tongue::before {
+  content: "\f589"; }
+
+.fa-chess-bishop::before {
+  content: "\f43a"; }
+
+.fa-face-grin-wink::before {
+  content: "\f58c"; }
+
+.fa-grin-wink::before {
+  content: "\f58c"; }
+
+.fa-ear-deaf::before {
+  content: "\f2a4"; }
+
+.fa-deaf::before {
+  content: "\f2a4"; }
+
+.fa-deafness::before {
+  content: "\f2a4"; }
+
+.fa-hard-of-hearing::before {
+  content: "\f2a4"; }
+
+.fa-road-circle-check::before {
+  content: "\e564"; }
+
+.fa-dice-five::before {
+  content: "\f523"; }
+
+.fa-square-rss::before {
+  content: "\f143"; }
+
+.fa-rss-square::before {
+  content: "\f143"; }
+
+.fa-land-mine-on::before {
+  content: "\e51b"; }
+
+.fa-i-cursor::before {
+  content: "\f246"; }
+
+.fa-stamp::before {
+  content: "\f5bf"; }
+
+.fa-stairs::before {
+  content: "\e289"; }
+
+.fa-i::before {
+  content: "\49"; }
+
+.fa-hryvnia-sign::before {
+  content: "\f6f2"; }
+
+.fa-hryvnia::before {
+  content: "\f6f2"; }
+
+.fa-pills::before {
+  content: "\f484"; }
+
+.fa-face-grin-wide::before {
+  content: "\f581"; }
+
+.fa-grin-alt::before {
+  content: "\f581"; }
+
+.fa-tooth::before {
+  content: "\f5c9"; }
+
+.fa-v::before {
+  content: "\56"; }
+
+.fa-bangladeshi-taka-sign::before {
+  content: "\e2e6"; }
+
+.fa-bicycle::before {
+  content: "\f206"; }
+
+.fa-staff-snake::before {
+  content: "\e579"; }
+
+.fa-rod-asclepius::before {
+  content: "\e579"; }
+
+.fa-rod-snake::before {
+  content: "\e579"; }
+
+.fa-staff-aesculapius::before {
+  content: "\e579"; }
+
+.fa-head-side-cough-slash::before {
+  content: "\e062"; }
+
+.fa-truck-medical::before {
+  content: "\f0f9"; }
+
+.fa-ambulance::before {
+  content: "\f0f9"; }
+
+.fa-wheat-awn-circle-exclamation::before {
+  content: "\e598"; }
+
+.fa-snowman::before {
+  content: "\f7d0"; }
+
+.fa-mortar-pestle::before {
+  content: "\f5a7"; }
+
+.fa-road-barrier::before {
+  content: "\e562"; }
+
+.fa-school::before {
+  content: "\f549"; }
+
+.fa-igloo::before {
+  content: "\f7ae"; }
+
+.fa-joint::before {
+  content: "\f595"; }
+
+.fa-angle-right::before {
+  content: "\f105"; }
+
+.fa-horse::before {
+  content: "\f6f0"; }
+
+.fa-q::before {
+  content: "\51"; }
+
+.fa-g::before {
+  content: "\47"; }
+
+.fa-notes-medical::before {
+  content: "\f481"; }
+
+.fa-temperature-half::before {
+  content: "\f2c9"; }
+
+.fa-temperature-2::before {
+  content: "\f2c9"; }
+
+.fa-thermometer-2::before {
+  content: "\f2c9"; }
+
+.fa-thermometer-half::before {
+  content: "\f2c9"; }
+
+.fa-dong-sign::before {
+  content: "\e169"; }
+
+.fa-capsules::before {
+  content: "\f46b"; }
+
+.fa-poo-storm::before {
+  content: "\f75a"; }
+
+.fa-poo-bolt::before {
+  content: "\f75a"; }
+
+.fa-face-frown-open::before {
+  content: "\f57a"; }
+
+.fa-frown-open::before {
+  content: "\f57a"; }
+
+.fa-hand-point-up::before {
+  content: "\f0a6"; }
+
+.fa-money-bill::before {
+  content: "\f0d6"; }
+
+.fa-bookmark::before {
+  content: "\f02e"; }
+
+.fa-align-justify::before {
+  content: "\f039"; }
+
+.fa-umbrella-beach::before {
+  content: "\f5ca"; }
+
+.fa-helmet-un::before {
+  content: "\e503"; }
+
+.fa-bullseye::before {
+  content: "\f140"; }
+
+.fa-bacon::before {
+  content: "\f7e5"; }
+
+.fa-hand-point-down::before {
+  content: "\f0a7"; }
+
+.fa-arrow-up-from-bracket::before {
+  content: "\e09a"; }
+
+.fa-folder::before {
+  content: "\f07b"; }
+
+.fa-folder-blank::before {
+  content: "\f07b"; }
+
+.fa-file-waveform::before {
+  content: "\f478"; }
+
+.fa-file-medical-alt::before {
+  content: "\f478"; }
+
+.fa-radiation::before {
+  content: "\f7b9"; }
+
+.fa-chart-simple::before {
+  content: "\e473"; }
+
+.fa-mars-stroke::before {
+  content: "\f229"; }
+
+.fa-vial::before {
+  content: "\f492"; }
+
+.fa-gauge::before {
+  content: "\f624"; }
+
+.fa-dashboard::before {
+  content: "\f624"; }
+
+.fa-gauge-med::before {
+  content: "\f624"; }
+
+.fa-tachometer-alt-average::before {
+  content: "\f624"; }
+
+.fa-wand-magic-sparkles::before {
+  content: "\e2ca"; }
+
+.fa-magic-wand-sparkles::before {
+  content: "\e2ca"; }
+
+.fa-e::before {
+  content: "\45"; }
+
+.fa-pen-clip::before {
+  content: "\f305"; }
+
+.fa-pen-alt::before {
+  content: "\f305"; }
+
+.fa-bridge-circle-exclamation::before {
+  content: "\e4ca"; }
+
+.fa-user::before {
+  content: "\f007"; }
+
+.fa-school-circle-check::before {
+  content: "\e56b"; }
+
+.fa-dumpster::before {
+  content: "\f793"; }
+
+.fa-van-shuttle::before {
+  content: "\f5b6"; }
+
+.fa-shuttle-van::before {
+  content: "\f5b6"; }
+
+.fa-building-user::before {
+  content: "\e4da"; }
+
+.fa-square-caret-left::before {
+  content: "\f191"; }
+
+.fa-caret-square-left::before {
+  content: "\f191"; }
+
+.fa-highlighter::before {
+  content: "\f591"; }
+
+.fa-key::before {
+  content: "\f084"; }
+
+.fa-bullhorn::before {
+  content: "\f0a1"; }
+
+.fa-globe::before {
+  content: "\f0ac"; }
+
+.fa-synagogue::before {
+  content: "\f69b"; }
+
+.fa-person-half-dress::before {
+  content: "\e548"; }
+
+.fa-road-bridge::before {
+  content: "\e563"; }
+
+.fa-location-arrow::before {
+  content: "\f124"; }
+
+.fa-c::before {
+  content: "\43"; }
+
+.fa-tablet-button::before {
+  content: "\f10a"; }
+
+.fa-building-lock::before {
+  content: "\e4d6"; }
+
+.fa-pizza-slice::before {
+  content: "\f818"; }
+
+.fa-money-bill-wave::before {
+  content: "\f53a"; }
+
+.fa-chart-area::before {
+  content: "\f1fe"; }
+
+.fa-area-chart::before {
+  content: "\f1fe"; }
+
+.fa-house-flag::before {
+  content: "\e50d"; }
+
+.fa-person-circle-minus::before {
+  content: "\e540"; }
+
+.fa-ban::before {
+  content: "\f05e"; }
+
+.fa-cancel::before {
+  content: "\f05e"; }
+
+.fa-camera-rotate::before {
+  content: "\e0d8"; }
+
+.fa-spray-can-sparkles::before {
+  content: "\f5d0"; }
+
+.fa-air-freshener::before {
+  content: "\f5d0"; }
+
+.fa-star::before {
+  content: "\f005"; }
+
+.fa-repeat::before {
+  content: "\f363"; }
+
+.fa-cross::before {
+  content: "\f654"; }
+
+.fa-box::before {
+  content: "\f466"; }
+
+.fa-venus-mars::before {
+  content: "\f228"; }
+
+.fa-arrow-pointer::before {
+  content: "\f245"; }
+
+.fa-mouse-pointer::before {
+  content: "\f245"; }
+
+.fa-maximize::before {
+  content: "\f31e"; }
+
+.fa-expand-arrows-alt::before {
+  content: "\f31e"; }
+
+.fa-charging-station::before {
+  content: "\f5e7"; }
+
+.fa-shapes::before {
+  content: "\f61f"; }
+
+.fa-triangle-circle-square::before {
+  content: "\f61f"; }
+
+.fa-shuffle::before {
+  content: "\f074"; }
+
+.fa-random::before {
+  content: "\f074"; }
+
+.fa-person-running::before {
+  content: "\f70c"; }
+
+.fa-running::before {
+  content: "\f70c"; }
+
+.fa-mobile-retro::before {
+  content: "\e527"; }
+
+.fa-grip-lines-vertical::before {
+  content: "\f7a5"; }
+
+.fa-spider::before {
+  content: "\f717"; }
+
+.fa-hands-bound::before {
+  content: "\e4f9"; }
+
+.fa-file-invoice-dollar::before {
+  content: "\f571"; }
+
+.fa-plane-circle-exclamation::before {
+  content: "\e556"; }
+
+.fa-x-ray::before {
+  content: "\f497"; }
+
+.fa-spell-check::before {
+  content: "\f891"; }
+
+.fa-slash::before {
+  content: "\f715"; }
+
+.fa-computer-mouse::before {
+  content: "\f8cc"; }
+
+.fa-mouse::before {
+  content: "\f8cc"; }
+
+.fa-arrow-right-to-bracket::before {
+  content: "\f090"; }
+
+.fa-sign-in::before {
+  content: "\f090"; }
+
+.fa-shop-slash::before {
+  content: "\e070"; }
+
+.fa-store-alt-slash::before {
+  content: "\e070"; }
+
+.fa-server::before {
+  content: "\f233"; }
+
+.fa-virus-covid-slash::before {
+  content: "\e4a9"; }
+
+.fa-shop-lock::before {
+  content: "\e4a5"; }
+
+.fa-hourglass-start::before {
+  content: "\f251"; }
+
+.fa-hourglass-1::before {
+  content: "\f251"; }
+
+.fa-blender-phone::before {
+  content: "\f6b6"; }
+
+.fa-building-wheat::before {
+  content: "\e4db"; }
+
+.fa-person-breastfeeding::before {
+  content: "\e53a"; }
+
+.fa-right-to-bracket::before {
+  content: "\f2f6"; }
+
+.fa-sign-in-alt::before {
+  content: "\f2f6"; }
+
+.fa-venus::before {
+  content: "\f221"; }
+
+.fa-passport::before {
+  content: "\f5ab"; }
+
+.fa-heart-pulse::before {
+  content: "\f21e"; }
+
+.fa-heartbeat::before {
+  content: "\f21e"; }
+
+.fa-people-carry-box::before {
+  content: "\f4ce"; }
+
+.fa-people-carry::before {
+  content: "\f4ce"; }
+
+.fa-temperature-high::before {
+  content: "\f769"; }
+
+.fa-microchip::before {
+  content: "\f2db"; }
+
+.fa-crown::before {
+  content: "\f521"; }
+
+.fa-weight-hanging::before {
+  content: "\f5cd"; }
+
+.fa-xmarks-lines::before {
+  content: "\e59a"; }
+
+.fa-file-prescription::before {
+  content: "\f572"; }
+
+.fa-weight-scale::before {
+  content: "\f496"; }
+
+.fa-weight::before {
+  content: "\f496"; }
+
+.fa-user-group::before {
+  content: "\f500"; }
+
+.fa-user-friends::before {
+  content: "\f500"; }
+
+.fa-arrow-up-a-z::before {
+  content: "\f15e"; }
+
+.fa-sort-alpha-up::before {
+  content: "\f15e"; }
+
+.fa-chess-knight::before {
+  content: "\f441"; }
+
+.fa-face-laugh-squint::before {
+  content: "\f59b"; }
+
+.fa-laugh-squint::before {
+  content: "\f59b"; }
+
+.fa-wheelchair::before {
+  content: "\f193"; }
+
+.fa-circle-arrow-up::before {
+  content: "\f0aa"; }
+
+.fa-arrow-circle-up::before {
+  content: "\f0aa"; }
+
+.fa-toggle-on::before {
+  content: "\f205"; }
+
+.fa-person-walking::before {
+  content: "\f554"; }
+
+.fa-walking::before {
+  content: "\f554"; }
+
+.fa-l::before {
+  content: "\4c"; }
+
+.fa-fire::before {
+  content: "\f06d"; }
+
+.fa-bed-pulse::before {
+  content: "\f487"; }
+
+.fa-procedures::before {
+  content: "\f487"; }
+
+.fa-shuttle-space::before {
+  content: "\f197"; }
+
+.fa-space-shuttle::before {
+  content: "\f197"; }
+
+.fa-face-laugh::before {
+  content: "\f599"; }
+
+.fa-laugh::before {
+  content: "\f599"; }
+
+.fa-folder-open::before {
+  content: "\f07c"; }
+
+.fa-heart-circle-plus::before {
+  content: "\e500"; }
+
+.fa-code-fork::before {
+  content: "\e13b"; }
+
+.fa-city::before {
+  content: "\f64f"; }
+
+.fa-microphone-lines::before {
+  content: "\f3c9"; }
+
+.fa-microphone-alt::before {
+  content: "\f3c9"; }
+
+.fa-pepper-hot::before {
+  content: "\f816"; }
+
+.fa-unlock::before {
+  content: "\f09c"; }
+
+.fa-colon-sign::before {
+  content: "\e140"; }
+
+.fa-headset::before {
+  content: "\f590"; }
+
+.fa-store-slash::before {
+  content: "\e071"; }
+
+.fa-road-circle-xmark::before {
+  content: "\e566"; }
+
+.fa-user-minus::before {
+  content: "\f503"; }
+
+.fa-mars-stroke-up::before {
+  content: "\f22a"; }
+
+.fa-mars-stroke-v::before {
+  content: "\f22a"; }
+
+.fa-champagne-glasses::before {
+  content: "\f79f"; }
+
+.fa-glass-cheers::before {
+  content: "\f79f"; }
+
+.fa-clipboard::before {
+  content: "\f328"; }
+
+.fa-house-circle-exclamation::before {
+  content: "\e50a"; }
+
+.fa-file-arrow-up::before {
+  content: "\f574"; }
+
+.fa-file-upload::before {
+  content: "\f574"; }
+
+.fa-wifi::before {
+  content: "\f1eb"; }
+
+.fa-wifi-3::before {
+  content: "\f1eb"; }
+
+.fa-wifi-strong::before {
+  content: "\f1eb"; }
+
+.fa-bath::before {
+  content: "\f2cd"; }
+
+.fa-bathtub::before {
+  content: "\f2cd"; }
+
+.fa-underline::before {
+  content: "\f0cd"; }
+
+.fa-user-pen::before {
+  content: "\f4ff"; }
+
+.fa-user-edit::before {
+  content: "\f4ff"; }
+
+.fa-signature::before {
+  content: "\f5b7"; }
+
+.fa-stroopwafel::before {
+  content: "\f551"; }
+
+.fa-bold::before {
+  content: "\f032"; }
+
+.fa-anchor-lock::before {
+  content: "\e4ad"; }
+
+.fa-building-ngo::before {
+  content: "\e4d7"; }
+
+.fa-manat-sign::before {
+  content: "\e1d5"; }
+
+.fa-not-equal::before {
+  content: "\f53e"; }
+
+.fa-border-top-left::before {
+  content: "\f853"; }
+
+.fa-border-style::before {
+  content: "\f853"; }
+
+.fa-map-location-dot::before {
+  content: "\f5a0"; }
+
+.fa-map-marked-alt::before {
+  content: "\f5a0"; }
+
+.fa-jedi::before {
+  content: "\f669"; }
+
+.fa-square-poll-vertical::before {
+  content: "\f681"; }
+
+.fa-poll::before {
+  content: "\f681"; }
+
+.fa-mug-hot::before {
+  content: "\f7b6"; }
+
+.fa-car-battery::before {
+  content: "\f5df"; }
+
+.fa-battery-car::before {
+  content: "\f5df"; }
+
+.fa-gift::before {
+  content: "\f06b"; }
+
+.fa-dice-two::before {
+  content: "\f528"; }
+
+.fa-chess-queen::before {
+  content: "\f445"; }
+
+.fa-glasses::before {
+  content: "\f530"; }
+
+.fa-chess-board::before {
+  content: "\f43c"; }
+
+.fa-building-circle-check::before {
+  content: "\e4d2"; }
+
+.fa-person-chalkboard::before {
+  content: "\e53d"; }
+
+.fa-mars-stroke-right::before {
+  content: "\f22b"; }
+
+.fa-mars-stroke-h::before {
+  content: "\f22b"; }
+
+.fa-hand-back-fist::before {
+  content: "\f255"; }
+
+.fa-hand-rock::before {
+  content: "\f255"; }
+
+.fa-square-caret-up::before {
+  content: "\f151"; }
+
+.fa-caret-square-up::before {
+  content: "\f151"; }
+
+.fa-cloud-showers-water::before {
+  content: "\e4e4"; }
+
+.fa-chart-bar::before {
+  content: "\f080"; }
+
+.fa-bar-chart::before {
+  content: "\f080"; }
+
+.fa-hands-bubbles::before {
+  content: "\e05e"; }
+
+.fa-hands-wash::before {
+  content: "\e05e"; }
+
+.fa-less-than-equal::before {
+  content: "\f537"; }
+
+.fa-train::before {
+  content: "\f238"; }
+
+.fa-eye-low-vision::before {
+  content: "\f2a8"; }
+
+.fa-low-vision::before {
+  content: "\f2a8"; }
+
+.fa-crow::before {
+  content: "\f520"; }
+
+.fa-sailboat::before {
+  content: "\e445"; }
+
+.fa-window-restore::before {
+  content: "\f2d2"; }
+
+.fa-square-plus::before {
+  content: "\f0fe"; }
+
+.fa-plus-square::before {
+  content: "\f0fe"; }
+
+.fa-torii-gate::before {
+  content: "\f6a1"; }
+
+.fa-frog::before {
+  content: "\f52e"; }
+
+.fa-bucket::before {
+  content: "\e4cf"; }
+
+.fa-image::before {
+  content: "\f03e"; }
+
+.fa-microphone::before {
+  content: "\f130"; }
+
+.fa-cow::before {
+  content: "\f6c8"; }
+
+.fa-caret-up::before {
+  content: "\f0d8"; }
+
+.fa-screwdriver::before {
+  content: "\f54a"; }
+
+.fa-folder-closed::before {
+  content: "\e185"; }
+
+.fa-house-tsunami::before {
+  content: "\e515"; }
+
+.fa-square-nfi::before {
+  content: "\e576"; }
+
+.fa-arrow-up-from-ground-water::before {
+  content: "\e4b5"; }
+
+.fa-martini-glass::before {
+  content: "\f57b"; }
+
+.fa-glass-martini-alt::before {
+  content: "\f57b"; }
+
+.fa-rotate-left::before {
+  content: "\f2ea"; }
+
+.fa-rotate-back::before {
+  content: "\f2ea"; }
+
+.fa-rotate-backward::before {
+  content: "\f2ea"; }
+
+.fa-undo-alt::before {
+  content: "\f2ea"; }
+
+.fa-table-columns::before {
+  content: "\f0db"; }
+
+.fa-columns::before {
+  content: "\f0db"; }
+
+.fa-lemon::before {
+  content: "\f094"; }
+
+.fa-head-side-mask::before {
+  content: "\e063"; }
+
+.fa-handshake::before {
+  content: "\f2b5"; }
+
+.fa-gem::before {
+  content: "\f3a5"; }
+
+.fa-dolly::before {
+  content: "\f472"; }
+
+.fa-dolly-box::before {
+  content: "\f472"; }
+
+.fa-smoking::before {
+  content: "\f48d"; }
+
+.fa-minimize::before {
+  content: "\f78c"; }
+
+.fa-compress-arrows-alt::before {
+  content: "\f78c"; }
+
+.fa-monument::before {
+  content: "\f5a6"; }
+
+.fa-snowplow::before {
+  content: "\f7d2"; }
+
+.fa-angles-right::before {
+  content: "\f101"; }
+
+.fa-angle-double-right::before {
+  content: "\f101"; }
+
+.fa-cannabis::before {
+  content: "\f55f"; }
+
+.fa-circle-play::before {
+  content: "\f144"; }
+
+.fa-play-circle::before {
+  content: "\f144"; }
+
+.fa-tablets::before {
+  content: "\f490"; }
+
+.fa-ethernet::before {
+  content: "\f796"; }
+
+.fa-euro-sign::before {
+  content: "\f153"; }
+
+.fa-eur::before {
+  content: "\f153"; }
+
+.fa-euro::before {
+  content: "\f153"; }
+
+.fa-chair::before {
+  content: "\f6c0"; }
+
+.fa-circle-check::before {
+  content: "\f058"; }
+
+.fa-check-circle::before {
+  content: "\f058"; }
+
+.fa-circle-stop::before {
+  content: "\f28d"; }
+
+.fa-stop-circle::before {
+  content: "\f28d"; }
+
+.fa-compass-drafting::before {
+  content: "\f568"; }
+
+.fa-drafting-compass::before {
+  content: "\f568"; }
+
+.fa-plate-wheat::before {
+  content: "\e55a"; }
+
+.fa-icicles::before {
+  content: "\f7ad"; }
+
+.fa-person-shelter::before {
+  content: "\e54f"; }
+
+.fa-neuter::before {
+  content: "\f22c"; }
+
+.fa-id-badge::before {
+  content: "\f2c1"; }
+
+.fa-marker::before {
+  content: "\f5a1"; }
+
+.fa-face-laugh-beam::before {
+  content: "\f59a"; }
+
+.fa-laugh-beam::before {
+  content: "\f59a"; }
+
+.fa-helicopter-symbol::before {
+  content: "\e502"; }
+
+.fa-universal-access::before {
+  content: "\f29a"; }
+
+.fa-circle-chevron-up::before {
+  content: "\f139"; }
+
+.fa-chevron-circle-up::before {
+  content: "\f139"; }
+
+.fa-lari-sign::before {
+  content: "\e1c8"; }
+
+.fa-volcano::before {
+  content: "\f770"; }
+
+.fa-person-walking-dashed-line-arrow-right::before {
+  content: "\e553"; }
+
+.fa-sterling-sign::before {
+  content: "\f154"; }
+
+.fa-gbp::before {
+  content: "\f154"; }
+
+.fa-pound-sign::before {
+  content: "\f154"; }
+
+.fa-viruses::before {
+  content: "\e076"; }
+
+.fa-square-person-confined::before {
+  content: "\e577"; }
+
+.fa-user-tie::before {
+  content: "\f508"; }
+
+.fa-arrow-down-long::before {
+  content: "\f175"; }
+
+.fa-long-arrow-down::before {
+  content: "\f175"; }
+
+.fa-tent-arrow-down-to-line::before {
+  content: "\e57e"; }
+
+.fa-certificate::before {
+  content: "\f0a3"; }
+
+.fa-reply-all::before {
+  content: "\f122"; }
+
+.fa-mail-reply-all::before {
+  content: "\f122"; }
+
+.fa-suitcase::before {
+  content: "\f0f2"; }
+
+.fa-person-skating::before {
+  content: "\f7c5"; }
+
+.fa-skating::before {
+  content: "\f7c5"; }
+
+.fa-filter-circle-dollar::before {
+  content: "\f662"; }
+
+.fa-funnel-dollar::before {
+  content: "\f662"; }
+
+.fa-camera-retro::before {
+  content: "\f083"; }
+
+.fa-circle-arrow-down::before {
+  content: "\f0ab"; }
+
+.fa-arrow-circle-down::before {
+  content: "\f0ab"; }
+
+.fa-file-import::before {
+  content: "\f56f"; }
+
+.fa-arrow-right-to-file::before {
+  content: "\f56f"; }
+
+.fa-square-arrow-up-right::before {
+  content: "\f14c"; }
+
+.fa-external-link-square::before {
+  content: "\f14c"; }
+
+.fa-box-open::before {
+  content: "\f49e"; }
+
+.fa-scroll::before {
+  content: "\f70e"; }
+
+.fa-spa::before {
+  content: "\f5bb"; }
+
+.fa-location-pin-lock::before {
+  content: "\e51f"; }
+
+.fa-pause::before {
+  content: "\f04c"; }
+
+.fa-hill-avalanche::before {
+  content: "\e507"; }
+
+.fa-temperature-empty::before {
+  content: "\f2cb"; }
+
+.fa-temperature-0::before {
+  content: "\f2cb"; }
+
+.fa-thermometer-0::before {
+  content: "\f2cb"; }
+
+.fa-thermometer-empty::before {
+  content: "\f2cb"; }
+
+.fa-bomb::before {
+  content: "\f1e2"; }
+
+.fa-registered::before {
+  content: "\f25d"; }
+
+.fa-address-card::before {
+  content: "\f2bb"; }
+
+.fa-contact-card::before {
+  content: "\f2bb"; }
+
+.fa-vcard::before {
+  content: "\f2bb"; }
+
+.fa-scale-unbalanced-flip::before {
+  content: "\f516"; }
+
+.fa-balance-scale-right::before {
+  content: "\f516"; }
+
+.fa-subscript::before {
+  content: "\f12c"; }
+
+.fa-diamond-turn-right::before {
+  content: "\f5eb"; }
+
+.fa-directions::before {
+  content: "\f5eb"; }
+
+.fa-burst::before {
+  content: "\e4dc"; }
+
+.fa-house-laptop::before {
+  content: "\e066"; }
+
+.fa-laptop-house::before {
+  content: "\e066"; }
+
+.fa-face-tired::before {
+  content: "\f5c8"; }
+
+.fa-tired::before {
+  content: "\f5c8"; }
+
+.fa-money-bills::before {
+  content: "\e1f3"; }
+
+.fa-smog::before {
+  content: "\f75f"; }
+
+.fa-crutch::before {
+  content: "\f7f7"; }
+
+.fa-cloud-arrow-up::before {
+  content: "\f0ee"; }
+
+.fa-cloud-upload::before {
+  content: "\f0ee"; }
+
+.fa-cloud-upload-alt::before {
+  content: "\f0ee"; }
+
+.fa-palette::before {
+  content: "\f53f"; }
+
+.fa-arrows-turn-right::before {
+  content: "\e4c0"; }
+
+.fa-vest::before {
+  content: "\e085"; }
+
+.fa-ferry::before {
+  content: "\e4ea"; }
+
+.fa-arrows-down-to-people::before {
+  content: "\e4b9"; }
+
+.fa-seedling::before {
+  content: "\f4d8"; }
+
+.fa-sprout::before {
+  content: "\f4d8"; }
+
+.fa-left-right::before {
+  content: "\f337"; }
+
+.fa-arrows-alt-h::before {
+  content: "\f337"; }
+
+.fa-boxes-packing::before {
+  content: "\e4c7"; }
+
+.fa-circle-arrow-left::before {
+  content: "\f0a8"; }
+
+.fa-arrow-circle-left::before {
+  content: "\f0a8"; }
+
+.fa-group-arrows-rotate::before {
+  content: "\e4f6"; }
+
+.fa-bowl-food::before {
+  content: "\e4c6"; }
+
+.fa-candy-cane::before {
+  content: "\f786"; }
+
+.fa-arrow-down-wide-short::before {
+  content: "\f160"; }
+
+.fa-sort-amount-asc::before {
+  content: "\f160"; }
+
+.fa-sort-amount-down::before {
+  content: "\f160"; }
+
+.fa-cloud-bolt::before {
+  content: "\f76c"; }
+
+.fa-thunderstorm::before {
+  content: "\f76c"; }
+
+.fa-text-slash::before {
+  content: "\f87d"; }
+
+.fa-remove-format::before {
+  content: "\f87d"; }
+
+.fa-face-smile-wink::before {
+  content: "\f4da"; }
+
+.fa-smile-wink::before {
+  content: "\f4da"; }
+
+.fa-file-word::before {
+  content: "\f1c2"; }
+
+.fa-file-powerpoint::before {
+  content: "\f1c4"; }
+
+.fa-arrows-left-right::before {
+  content: "\f07e"; }
+
+.fa-arrows-h::before {
+  content: "\f07e"; }
+
+.fa-house-lock::before {
+  content: "\e510"; }
+
+.fa-cloud-arrow-down::before {
+  content: "\f0ed"; }
+
+.fa-cloud-download::before {
+  content: "\f0ed"; }
+
+.fa-cloud-download-alt::before {
+  content: "\f0ed"; }
+
+.fa-children::before {
+  content: "\e4e1"; }
+
+.fa-chalkboard::before {
+  content: "\f51b"; }
+
+.fa-blackboard::before {
+  content: "\f51b"; }
+
+.fa-user-large-slash::before {
+  content: "\f4fa"; }
+
+.fa-user-alt-slash::before {
+  content: "\f4fa"; }
+
+.fa-envelope-open::before {
+  content: "\f2b6"; }
+
+.fa-handshake-simple-slash::before {
+  content: "\e05f"; }
+
+.fa-handshake-alt-slash::before {
+  content: "\e05f"; }
+
+.fa-mattress-pillow::before {
+  content: "\e525"; }
+
+.fa-guarani-sign::before {
+  content: "\e19a"; }
+
+.fa-arrows-rotate::before {
+  content: "\f021"; }
+
+.fa-refresh::before {
+  content: "\f021"; }
+
+.fa-sync::before {
+  content: "\f021"; }
+
+.fa-fire-extinguisher::before {
+  content: "\f134"; }
+
+.fa-cruzeiro-sign::before {
+  content: "\e152"; }
+
+.fa-greater-than-equal::before {
+  content: "\f532"; }
+
+.fa-shield-halved::before {
+  content: "\f3ed"; }
+
+.fa-shield-alt::before {
+  content: "\f3ed"; }
+
+.fa-book-atlas::before {
+  content: "\f558"; }
+
+.fa-atlas::before {
+  content: "\f558"; }
+
+.fa-virus::before {
+  content: "\e074"; }
+
+.fa-envelope-circle-check::before {
+  content: "\e4e8"; }
+
+.fa-layer-group::before {
+  content: "\f5fd"; }
+
+.fa-arrows-to-dot::before {
+  content: "\e4be"; }
+
+.fa-archway::before {
+  content: "\f557"; }
+
+.fa-heart-circle-check::before {
+  content: "\e4fd"; }
+
+.fa-house-chimney-crack::before {
+  content: "\f6f1"; }
+
+.fa-house-damage::before {
+  content: "\f6f1"; }
+
+.fa-file-zipper::before {
+  content: "\f1c6"; }
+
+.fa-file-archive::before {
+  content: "\f1c6"; }
+
+.fa-square::before {
+  content: "\f0c8"; }
+
+.fa-martini-glass-empty::before {
+  content: "\f000"; }
+
+.fa-glass-martini::before {
+  content: "\f000"; }
+
+.fa-couch::before {
+  content: "\f4b8"; }
+
+.fa-cedi-sign::before {
+  content: "\e0df"; }
+
+.fa-italic::before {
+  content: "\f033"; }
+
+.fa-table-cells-column-lock::before {
+  content: "\e678"; }
+
+.fa-church::before {
+  content: "\f51d"; }
+
+.fa-comments-dollar::before {
+  content: "\f653"; }
+
+.fa-democrat::before {
+  content: "\f747"; }
+
+.fa-z::before {
+  content: "\5a"; }
+
+.fa-person-skiing::before {
+  content: "\f7c9"; }
+
+.fa-skiing::before {
+  content: "\f7c9"; }
+
+.fa-road-lock::before {
+  content: "\e567"; }
+
+.fa-a::before {
+  content: "\41"; }
+
+.fa-temperature-arrow-down::before {
+  content: "\e03f"; }
+
+.fa-temperature-down::before {
+  content: "\e03f"; }
+
+.fa-feather-pointed::before {
+  content: "\f56b"; }
+
+.fa-feather-alt::before {
+  content: "\f56b"; }
+
+.fa-p::before {
+  content: "\50"; }
+
+.fa-snowflake::before {
+  content: "\f2dc"; }
+
+.fa-newspaper::before {
+  content: "\f1ea"; }
+
+.fa-rectangle-ad::before {
+  content: "\f641"; }
+
+.fa-ad::before {
+  content: "\f641"; }
+
+.fa-circle-arrow-right::before {
+  content: "\f0a9"; }
+
+.fa-arrow-circle-right::before {
+  content: "\f0a9"; }
+
+.fa-filter-circle-xmark::before {
+  content: "\e17b"; }
+
+.fa-locust::before {
+  content: "\e520"; }
+
+.fa-sort::before {
+  content: "\f0dc"; }
+
+.fa-unsorted::before {
+  content: "\f0dc"; }
+
+.fa-list-ol::before {
+  content: "\f0cb"; }
+
+.fa-list-1-2::before {
+  content: "\f0cb"; }
+
+.fa-list-numeric::before {
+  content: "\f0cb"; }
+
+.fa-person-dress-burst::before {
+  content: "\e544"; }
+
+.fa-money-check-dollar::before {
+  content: "\f53d"; }
+
+.fa-money-check-alt::before {
+  content: "\f53d"; }
+
+.fa-vector-square::before {
+  content: "\f5cb"; }
+
+.fa-bread-slice::before {
+  content: "\f7ec"; }
+
+.fa-language::before {
+  content: "\f1ab"; }
+
+.fa-face-kiss-wink-heart::before {
+  content: "\f598"; }
+
+.fa-kiss-wink-heart::before {
+  content: "\f598"; }
+
+.fa-filter::before {
+  content: "\f0b0"; }
+
+.fa-question::before {
+  content: "\3f"; }
+
+.fa-file-signature::before {
+  content: "\f573"; }
+
+.fa-up-down-left-right::before {
+  content: "\f0b2"; }
+
+.fa-arrows-alt::before {
+  content: "\f0b2"; }
+
+.fa-house-chimney-user::before {
+  content: "\e065"; }
+
+.fa-hand-holding-heart::before {
+  content: "\f4be"; }
+
+.fa-puzzle-piece::before {
+  content: "\f12e"; }
+
+.fa-money-check::before {
+  content: "\f53c"; }
+
+.fa-star-half-stroke::before {
+  content: "\f5c0"; }
+
+.fa-star-half-alt::before {
+  content: "\f5c0"; }
+
+.fa-code::before {
+  content: "\f121"; }
+
+.fa-whiskey-glass::before {
+  content: "\f7a0"; }
+
+.fa-glass-whiskey::before {
+  content: "\f7a0"; }
+
+.fa-building-circle-exclamation::before {
+  content: "\e4d3"; }
+
+.fa-magnifying-glass-chart::before {
+  content: "\e522"; }
+
+.fa-arrow-up-right-from-square::before {
+  content: "\f08e"; }
+
+.fa-external-link::before {
+  content: "\f08e"; }
+
+.fa-cubes-stacked::before {
+  content: "\e4e6"; }
+
+.fa-won-sign::before {
+  content: "\f159"; }
+
+.fa-krw::before {
+  content: "\f159"; }
+
+.fa-won::before {
+  content: "\f159"; }
+
+.fa-virus-covid::before {
+  content: "\e4a8"; }
+
+.fa-austral-sign::before {
+  content: "\e0a9"; }
+
+.fa-f::before {
+  content: "\46"; }
+
+.fa-leaf::before {
+  content: "\f06c"; }
+
+.fa-road::before {
+  content: "\f018"; }
+
+.fa-taxi::before {
+  content: "\f1ba"; }
+
+.fa-cab::before {
+  content: "\f1ba"; }
+
+.fa-person-circle-plus::before {
+  content: "\e541"; }
+
+.fa-chart-pie::before {
+  content: "\f200"; }
+
+.fa-pie-chart::before {
+  content: "\f200"; }
+
+.fa-bolt-lightning::before {
+  content: "\e0b7"; }
+
+.fa-sack-xmark::before {
+  content: "\e56a"; }
+
+.fa-file-excel::before {
+  content: "\f1c3"; }
+
+.fa-file-contract::before {
+  content: "\f56c"; }
+
+.fa-fish-fins::before {
+  content: "\e4f2"; }
+
+.fa-building-flag::before {
+  content: "\e4d5"; }
+
+.fa-face-grin-beam::before {
+  content: "\f582"; }
+
+.fa-grin-beam::before {
+  content: "\f582"; }
+
+.fa-object-ungroup::before {
+  content: "\f248"; }
+
+.fa-poop::before {
+  content: "\f619"; }
+
+.fa-location-pin::before {
+  content: "\f041"; }
+
+.fa-map-marker::before {
+  content: "\f041"; }
+
+.fa-kaaba::before {
+  content: "\f66b"; }
+
+.fa-toilet-paper::before {
+  content: "\f71e"; }
+
+.fa-helmet-safety::before {
+  content: "\f807"; }
+
+.fa-hard-hat::before {
+  content: "\f807"; }
+
+.fa-hat-hard::before {
+  content: "\f807"; }
+
+.fa-eject::before {
+  content: "\f052"; }
+
+.fa-circle-right::before {
+  content: "\f35a"; }
+
+.fa-arrow-alt-circle-right::before {
+  content: "\f35a"; }
+
+.fa-plane-circle-check::before {
+  content: "\e555"; }
+
+.fa-face-rolling-eyes::before {
+  content: "\f5a5"; }
+
+.fa-meh-rolling-eyes::before {
+  content: "\f5a5"; }
+
+.fa-object-group::before {
+  content: "\f247"; }
+
+.fa-chart-line::before {
+  content: "\f201"; }
+
+.fa-line-chart::before {
+  content: "\f201"; }
+
+.fa-mask-ventilator::before {
+  content: "\e524"; }
+
+.fa-arrow-right::before {
+  content: "\f061"; }
+
+.fa-signs-post::before {
+  content: "\f277"; }
+
+.fa-map-signs::before {
+  content: "\f277"; }
+
+.fa-cash-register::before {
+  content: "\f788"; }
+
+.fa-person-circle-question::before {
+  content: "\e542"; }
+
+.fa-h::before {
+  content: "\48"; }
+
+.fa-tarp::before {
+  content: "\e57b"; }
+
+.fa-screwdriver-wrench::before {
+  content: "\f7d9"; }
+
+.fa-tools::before {
+  content: "\f7d9"; }
+
+.fa-arrows-to-eye::before {
+  content: "\e4bf"; }
+
+.fa-plug-circle-bolt::before {
+  content: "\e55b"; }
+
+.fa-heart::before {
+  content: "\f004"; }
+
+.fa-mars-and-venus::before {
+  content: "\f224"; }
+
+.fa-house-user::before {
+  content: "\e1b0"; }
+
+.fa-home-user::before {
+  content: "\e1b0"; }
+
+.fa-dumpster-fire::before {
+  content: "\f794"; }
+
+.fa-house-crack::before {
+  content: "\e3b1"; }
+
+.fa-martini-glass-citrus::before {
+  content: "\f561"; }
+
+.fa-cocktail::before {
+  content: "\f561"; }
+
+.fa-face-surprise::before {
+  content: "\f5c2"; }
+
+.fa-surprise::before {
+  content: "\f5c2"; }
+
+.fa-bottle-water::before {
+  content: "\e4c5"; }
+
+.fa-circle-pause::before {
+  content: "\f28b"; }
+
+.fa-pause-circle::before {
+  content: "\f28b"; }
+
+.fa-toilet-paper-slash::before {
+  content: "\e072"; }
+
+.fa-apple-whole::before {
+  content: "\f5d1"; }
+
+.fa-apple-alt::before {
+  content: "\f5d1"; }
+
+.fa-kitchen-set::before {
+  content: "\e51a"; }
+
+.fa-r::before {
+  content: "\52"; }
+
+.fa-temperature-quarter::before {
+  content: "\f2ca"; }
+
+.fa-temperature-1::before {
+  content: "\f2ca"; }
+
+.fa-thermometer-1::before {
+  content: "\f2ca"; }
+
+.fa-thermometer-quarter::before {
+  content: "\f2ca"; }
+
+.fa-cube::before {
+  content: "\f1b2"; }
+
+.fa-bitcoin-sign::before {
+  content: "\e0b4"; }
+
+.fa-shield-dog::before {
+  content: "\e573"; }
+
+.fa-solar-panel::before {
+  content: "\f5ba"; }
+
+.fa-lock-open::before {
+  content: "\f3c1"; }
+
+.fa-elevator::before {
+  content: "\e16d"; }
+
+.fa-money-bill-transfer::before {
+  content: "\e528"; }
+
+.fa-money-bill-trend-up::before {
+  content: "\e529"; }
+
+.fa-house-flood-water-circle-arrow-right::before {
+  content: "\e50f"; }
+
+.fa-square-poll-horizontal::before {
+  content: "\f682"; }
+
+.fa-poll-h::before {
+  content: "\f682"; }
+
+.fa-circle::before {
+  content: "\f111"; }
+
+.fa-backward-fast::before {
+  content: "\f049"; }
+
+.fa-fast-backward::before {
+  content: "\f049"; }
+
+.fa-recycle::before {
+  content: "\f1b8"; }
+
+.fa-user-astronaut::before {
+  content: "\f4fb"; }
+
+.fa-plane-slash::before {
+  content: "\e069"; }
+
+.fa-trademark::before {
+  content: "\f25c"; }
+
+.fa-basketball::before {
+  content: "\f434"; }
+
+.fa-basketball-ball::before {
+  content: "\f434"; }
+
+.fa-satellite-dish::before {
+  content: "\f7c0"; }
+
+.fa-circle-up::before {
+  content: "\f35b"; }
+
+.fa-arrow-alt-circle-up::before {
+  content: "\f35b"; }
+
+.fa-mobile-screen-button::before {
+  content: "\f3cd"; }
+
+.fa-mobile-alt::before {
+  content: "\f3cd"; }
+
+.fa-volume-high::before {
+  content: "\f028"; }
+
+.fa-volume-up::before {
+  content: "\f028"; }
+
+.fa-users-rays::before {
+  content: "\e593"; }
+
+.fa-wallet::before {
+  content: "\f555"; }
+
+.fa-clipboard-check::before {
+  content: "\f46c"; }
+
+.fa-file-audio::before {
+  content: "\f1c7"; }
+
+.fa-burger::before {
+  content: "\f805"; }
+
+.fa-hamburger::before {
+  content: "\f805"; }
+
+.fa-wrench::before {
+  content: "\f0ad"; }
+
+.fa-bugs::before {
+  content: "\e4d0"; }
+
+.fa-rupee-sign::before {
+  content: "\f156"; }
+
+.fa-rupee::before {
+  content: "\f156"; }
+
+.fa-file-image::before {
+  content: "\f1c5"; }
+
+.fa-circle-question::before {
+  content: "\f059"; }
+
+.fa-question-circle::before {
+  content: "\f059"; }
+
+.fa-plane-departure::before {
+  content: "\f5b0"; }
+
+.fa-handshake-slash::before {
+  content: "\e060"; }
+
+.fa-book-bookmark::before {
+  content: "\e0bb"; }
+
+.fa-code-branch::before {
+  content: "\f126"; }
+
+.fa-hat-cowboy::before {
+  content: "\f8c0"; }
+
+.fa-bridge::before {
+  content: "\e4c8"; }
+
+.fa-phone-flip::before {
+  content: "\f879"; }
+
+.fa-phone-alt::before {
+  content: "\f879"; }
+
+.fa-truck-front::before {
+  content: "\e2b7"; }
+
+.fa-cat::before {
+  content: "\f6be"; }
+
+.fa-anchor-circle-exclamation::before {
+  content: "\e4ab"; }
+
+.fa-truck-field::before {
+  content: "\e58d"; }
+
+.fa-route::before {
+  content: "\f4d7"; }
+
+.fa-clipboard-question::before {
+  content: "\e4e3"; }
+
+.fa-panorama::before {
+  content: "\e209"; }
+
+.fa-comment-medical::before {
+  content: "\f7f5"; }
+
+.fa-teeth-open::before {
+  content: "\f62f"; }
+
+.fa-file-circle-minus::before {
+  content: "\e4ed"; }
+
+.fa-tags::before {
+  content: "\f02c"; }
+
+.fa-wine-glass::before {
+  content: "\f4e3"; }
+
+.fa-forward-fast::before {
+  content: "\f050"; }
+
+.fa-fast-forward::before {
+  content: "\f050"; }
+
+.fa-face-meh-blank::before {
+  content: "\f5a4"; }
+
+.fa-meh-blank::before {
+  content: "\f5a4"; }
+
+.fa-square-parking::before {
+  content: "\f540"; }
+
+.fa-parking::before {
+  content: "\f540"; }
+
+.fa-house-signal::before {
+  content: "\e012"; }
+
+.fa-bars-progress::before {
+  content: "\f828"; }
+
+.fa-tasks-alt::before {
+  content: "\f828"; }
+
+.fa-faucet-drip::before {
+  content: "\e006"; }
+
+.fa-cart-flatbed::before {
+  content: "\f474"; }
+
+.fa-dolly-flatbed::before {
+  content: "\f474"; }
+
+.fa-ban-smoking::before {
+  content: "\f54d"; }
+
+.fa-smoking-ban::before {
+  content: "\f54d"; }
+
+.fa-terminal::before {
+  content: "\f120"; }
+
+.fa-mobile-button::before {
+  content: "\f10b"; }
+
+.fa-house-medical-flag::before {
+  content: "\e514"; }
+
+.fa-basket-shopping::before {
+  content: "\f291"; }
+
+.fa-shopping-basket::before {
+  content: "\f291"; }
+
+.fa-tape::before {
+  content: "\f4db"; }
+
+.fa-bus-simple::before {
+  content: "\f55e"; }
+
+.fa-bus-alt::before {
+  content: "\f55e"; }
+
+.fa-eye::before {
+  content: "\f06e"; }
+
+.fa-face-sad-cry::before {
+  content: "\f5b3"; }
+
+.fa-sad-cry::before {
+  content: "\f5b3"; }
+
+.fa-audio-description::before {
+  content: "\f29e"; }
+
+.fa-person-military-to-person::before {
+  content: "\e54c"; }
+
+.fa-file-shield::before {
+  content: "\e4f0"; }
+
+.fa-user-slash::before {
+  content: "\f506"; }
+
+.fa-pen::before {
+  content: "\f304"; }
+
+.fa-tower-observation::before {
+  content: "\e586"; }
+
+.fa-file-code::before {
+  content: "\f1c9"; }
+
+.fa-signal::before {
+  content: "\f012"; }
+
+.fa-signal-5::before {
+  content: "\f012"; }
+
+.fa-signal-perfect::before {
+  content: "\f012"; }
+
+.fa-bus::before {
+  content: "\f207"; }
+
+.fa-heart-circle-xmark::before {
+  content: "\e501"; }
+
+.fa-house-chimney::before {
+  content: "\e3af"; }
+
+.fa-home-lg::before {
+  content: "\e3af"; }
+
+.fa-window-maximize::before {
+  content: "\f2d0"; }
+
+.fa-face-frown::before {
+  content: "\f119"; }
+
+.fa-frown::before {
+  content: "\f119"; }
+
+.fa-prescription::before {
+  content: "\f5b1"; }
+
+.fa-shop::before {
+  content: "\f54f"; }
+
+.fa-store-alt::before {
+  content: "\f54f"; }
+
+.fa-floppy-disk::before {
+  content: "\f0c7"; }
+
+.fa-save::before {
+  content: "\f0c7"; }
+
+.fa-vihara::before {
+  content: "\f6a7"; }
+
+.fa-scale-unbalanced::before {
+  content: "\f515"; }
+
+.fa-balance-scale-left::before {
+  content: "\f515"; }
+
+.fa-sort-up::before {
+  content: "\f0de"; }
+
+.fa-sort-asc::before {
+  content: "\f0de"; }
+
+.fa-comment-dots::before {
+  content: "\f4ad"; }
+
+.fa-commenting::before {
+  content: "\f4ad"; }
+
+.fa-plant-wilt::before {
+  content: "\e5aa"; }
+
+.fa-diamond::before {
+  content: "\f219"; }
+
+.fa-face-grin-squint::before {
+  content: "\f585"; }
+
+.fa-grin-squint::before {
+  content: "\f585"; }
+
+.fa-hand-holding-dollar::before {
+  content: "\f4c0"; }
+
+.fa-hand-holding-usd::before {
+  content: "\f4c0"; }
+
+.fa-bacterium::before {
+  content: "\e05a"; }
+
+.fa-hand-pointer::before {
+  content: "\f25a"; }
+
+.fa-drum-steelpan::before {
+  content: "\f56a"; }
+
+.fa-hand-scissors::before {
+  content: "\f257"; }
+
+.fa-hands-praying::before {
+  content: "\f684"; }
+
+.fa-praying-hands::before {
+  content: "\f684"; }
+
+.fa-arrow-rotate-right::before {
+  content: "\f01e"; }
+
+.fa-arrow-right-rotate::before {
+  content: "\f01e"; }
+
+.fa-arrow-rotate-forward::before {
+  content: "\f01e"; }
+
+.fa-redo::before {
+  content: "\f01e"; }
+
+.fa-biohazard::before {
+  content: "\f780"; }
+
+.fa-location-crosshairs::before {
+  content: "\f601"; }
+
+.fa-location::before {
+  content: "\f601"; }
+
+.fa-mars-double::before {
+  content: "\f227"; }
+
+.fa-child-dress::before {
+  content: "\e59c"; }
+
+.fa-users-between-lines::before {
+  content: "\e591"; }
+
+.fa-lungs-virus::before {
+  content: "\e067"; }
+
+.fa-face-grin-tears::before {
+  content: "\f588"; }
+
+.fa-grin-tears::before {
+  content: "\f588"; }
+
+.fa-phone::before {
+  content: "\f095"; }
+
+.fa-calendar-xmark::before {
+  content: "\f273"; }
+
+.fa-calendar-times::before {
+  content: "\f273"; }
+
+.fa-child-reaching::before {
+  content: "\e59d"; }
+
+.fa-head-side-virus::before {
+  content: "\e064"; }
+
+.fa-user-gear::before {
+  content: "\f4fe"; }
+
+.fa-user-cog::before {
+  content: "\f4fe"; }
+
+.fa-arrow-up-1-9::before {
+  content: "\f163"; }
+
+.fa-sort-numeric-up::before {
+  content: "\f163"; }
+
+.fa-door-closed::before {
+  content: "\f52a"; }
+
+.fa-shield-virus::before {
+  content: "\e06c"; }
+
+.fa-dice-six::before {
+  content: "\f526"; }
+
+.fa-mosquito-net::before {
+  content: "\e52c"; }
+
+.fa-bridge-water::before {
+  content: "\e4ce"; }
+
+.fa-person-booth::before {
+  content: "\f756"; }
+
+.fa-text-width::before {
+  content: "\f035"; }
+
+.fa-hat-wizard::before {
+  content: "\f6e8"; }
+
+.fa-pen-fancy::before {
+  content: "\f5ac"; }
+
+.fa-person-digging::before {
+  content: "\f85e"; }
+
+.fa-digging::before {
+  content: "\f85e"; }
+
+.fa-trash::before {
+  content: "\f1f8"; }
+
+.fa-gauge-simple::before {
+  content: "\f629"; }
+
+.fa-gauge-simple-med::before {
+  content: "\f629"; }
+
+.fa-tachometer-average::before {
+  content: "\f629"; }
+
+.fa-book-medical::before {
+  content: "\f7e6"; }
+
+.fa-poo::before {
+  content: "\f2fe"; }
+
+.fa-quote-right::before {
+  content: "\f10e"; }
+
+.fa-quote-right-alt::before {
+  content: "\f10e"; }
+
+.fa-shirt::before {
+  content: "\f553"; }
+
+.fa-t-shirt::before {
+  content: "\f553"; }
+
+.fa-tshirt::before {
+  content: "\f553"; }
+
+.fa-cubes::before {
+  content: "\f1b3"; }
+
+.fa-divide::before {
+  content: "\f529"; }
+
+.fa-tenge-sign::before {
+  content: "\f7d7"; }
+
+.fa-tenge::before {
+  content: "\f7d7"; }
+
+.fa-headphones::before {
+  content: "\f025"; }
+
+.fa-hands-holding::before {
+  content: "\f4c2"; }
+
+.fa-hands-clapping::before {
+  content: "\e1a8"; }
+
+.fa-republican::before {
+  content: "\f75e"; }
+
+.fa-arrow-left::before {
+  content: "\f060"; }
+
+.fa-person-circle-xmark::before {
+  content: "\e543"; }
+
+.fa-ruler::before {
+  content: "\f545"; }
+
+.fa-align-left::before {
+  content: "\f036"; }
+
+.fa-dice-d6::before {
+  content: "\f6d1"; }
+
+.fa-restroom::before {
+  content: "\f7bd"; }
+
+.fa-j::before {
+  content: "\4a"; }
+
+.fa-users-viewfinder::before {
+  content: "\e595"; }
+
+.fa-file-video::before {
+  content: "\f1c8"; }
+
+.fa-up-right-from-square::before {
+  content: "\f35d"; }
+
+.fa-external-link-alt::before {
+  content: "\f35d"; }
+
+.fa-table-cells::before {
+  content: "\f00a"; }
+
+.fa-th::before {
+  content: "\f00a"; }
+
+.fa-file-pdf::before {
+  content: "\f1c1"; }
+
+.fa-book-bible::before {
+  content: "\f647"; }
+
+.fa-bible::before {
+  content: "\f647"; }
+
+.fa-o::before {
+  content: "\4f"; }
+
+.fa-suitcase-medical::before {
+  content: "\f0fa"; }
+
+.fa-medkit::before {
+  content: "\f0fa"; }
+
+.fa-user-secret::before {
+  content: "\f21b"; }
+
+.fa-otter::before {
+  content: "\f700"; }
+
+.fa-person-dress::before {
+  content: "\f182"; }
+
+.fa-female::before {
+  content: "\f182"; }
+
+.fa-comment-dollar::before {
+  content: "\f651"; }
+
+.fa-business-time::before {
+  content: "\f64a"; }
+
+.fa-briefcase-clock::before {
+  content: "\f64a"; }
+
+.fa-table-cells-large::before {
+  content: "\f009"; }
+
+.fa-th-large::before {
+  content: "\f009"; }
+
+.fa-book-tanakh::before {
+  content: "\f827"; }
+
+.fa-tanakh::before {
+  content: "\f827"; }
+
+.fa-phone-volume::before {
+  content: "\f2a0"; }
+
+.fa-volume-control-phone::before {
+  content: "\f2a0"; }
+
+.fa-hat-cowboy-side::before {
+  content: "\f8c1"; }
+
+.fa-clipboard-user::before {
+  content: "\f7f3"; }
+
+.fa-child::before {
+  content: "\f1ae"; }
+
+.fa-lira-sign::before {
+  content: "\f195"; }
+
+.fa-satellite::before {
+  content: "\f7bf"; }
+
+.fa-plane-lock::before {
+  content: "\e558"; }
+
+.fa-tag::before {
+  content: "\f02b"; }
+
+.fa-comment::before {
+  content: "\f075"; }
+
+.fa-cake-candles::before {
+  content: "\f1fd"; }
+
+.fa-birthday-cake::before {
+  content: "\f1fd"; }
+
+.fa-cake::before {
+  content: "\f1fd"; }
+
+.fa-envelope::before {
+  content: "\f0e0"; }
+
+.fa-angles-up::before {
+  content: "\f102"; }
+
+.fa-angle-double-up::before {
+  content: "\f102"; }
+
+.fa-paperclip::before {
+  content: "\f0c6"; }
+
+.fa-arrow-right-to-city::before {
+  content: "\e4b3"; }
+
+.fa-ribbon::before {
+  content: "\f4d6"; }
+
+.fa-lungs::before {
+  content: "\f604"; }
+
+.fa-arrow-up-9-1::before {
+  content: "\f887"; }
+
+.fa-sort-numeric-up-alt::before {
+  content: "\f887"; }
+
+.fa-litecoin-sign::before {
+  content: "\e1d3"; }
+
+.fa-border-none::before {
+  content: "\f850"; }
+
+.fa-circle-nodes::before {
+  content: "\e4e2"; }
+
+.fa-parachute-box::before {
+  content: "\f4cd"; }
+
+.fa-indent::before {
+  content: "\f03c"; }
+
+.fa-truck-field-un::before {
+  content: "\e58e"; }
+
+.fa-hourglass::before {
+  content: "\f254"; }
+
+.fa-hourglass-empty::before {
+  content: "\f254"; }
+
+.fa-mountain::before {
+  content: "\f6fc"; }
+
+.fa-user-doctor::before {
+  content: "\f0f0"; }
+
+.fa-user-md::before {
+  content: "\f0f0"; }
+
+.fa-circle-info::before {
+  content: "\f05a"; }
+
+.fa-info-circle::before {
+  content: "\f05a"; }
+
+.fa-cloud-meatball::before {
+  content: "\f73b"; }
+
+.fa-camera::before {
+  content: "\f030"; }
+
+.fa-camera-alt::before {
+  content: "\f030"; }
+
+.fa-square-virus::before {
+  content: "\e578"; }
+
+.fa-meteor::before {
+  content: "\f753"; }
+
+.fa-car-on::before {
+  content: "\e4dd"; }
+
+.fa-sleigh::before {
+  content: "\f7cc"; }
+
+.fa-arrow-down-1-9::before {
+  content: "\f162"; }
+
+.fa-sort-numeric-asc::before {
+  content: "\f162"; }
+
+.fa-sort-numeric-down::before {
+  content: "\f162"; }
+
+.fa-hand-holding-droplet::before {
+  content: "\f4c1"; }
+
+.fa-hand-holding-water::before {
+  content: "\f4c1"; }
+
+.fa-water::before {
+  content: "\f773"; }
+
+.fa-calendar-check::before {
+  content: "\f274"; }
+
+.fa-braille::before {
+  content: "\f2a1"; }
+
+.fa-prescription-bottle-medical::before {
+  content: "\f486"; }
+
+.fa-prescription-bottle-alt::before {
+  content: "\f486"; }
+
+.fa-landmark::before {
+  content: "\f66f"; }
+
+.fa-truck::before {
+  content: "\f0d1"; }
+
+.fa-crosshairs::before {
+  content: "\f05b"; }
+
+.fa-person-cane::before {
+  content: "\e53c"; }
+
+.fa-tent::before {
+  content: "\e57d"; }
+
+.fa-vest-patches::before {
+  content: "\e086"; }
+
+.fa-check-double::before {
+  content: "\f560"; }
+
+.fa-arrow-down-a-z::before {
+  content: "\f15d"; }
+
+.fa-sort-alpha-asc::before {
+  content: "\f15d"; }
+
+.fa-sort-alpha-down::before {
+  content: "\f15d"; }
+
+.fa-money-bill-wheat::before {
+  content: "\e52a"; }
+
+.fa-cookie::before {
+  content: "\f563"; }
+
+.fa-arrow-rotate-left::before {
+  content: "\f0e2"; }
+
+.fa-arrow-left-rotate::before {
+  content: "\f0e2"; }
+
+.fa-arrow-rotate-back::before {
+  content: "\f0e2"; }
+
+.fa-arrow-rotate-backward::before {
+  content: "\f0e2"; }
+
+.fa-undo::before {
+  content: "\f0e2"; }
+
+.fa-hard-drive::before {
+  content: "\f0a0"; }
+
+.fa-hdd::before {
+  content: "\f0a0"; }
+
+.fa-face-grin-squint-tears::before {
+  content: "\f586"; }
+
+.fa-grin-squint-tears::before {
+  content: "\f586"; }
+
+.fa-dumbbell::before {
+  content: "\f44b"; }
+
+.fa-rectangle-list::before {
+  content: "\f022"; }
+
+.fa-list-alt::before {
+  content: "\f022"; }
+
+.fa-tarp-droplet::before {
+  content: "\e57c"; }
+
+.fa-house-medical-circle-check::before {
+  content: "\e511"; }
+
+.fa-person-skiing-nordic::before {
+  content: "\f7ca"; }
+
+.fa-skiing-nordic::before {
+  content: "\f7ca"; }
+
+.fa-calendar-plus::before {
+  content: "\f271"; }
+
+.fa-plane-arrival::before {
+  content: "\f5af"; }
+
+.fa-circle-left::before {
+  content: "\f359"; }
+
+.fa-arrow-alt-circle-left::before {
+  content: "\f359"; }
+
+.fa-train-subway::before {
+  content: "\f239"; }
+
+.fa-subway::before {
+  content: "\f239"; }
+
+.fa-chart-gantt::before {
+  content: "\e0e4"; }
+
+.fa-indian-rupee-sign::before {
+  content: "\e1bc"; }
+
+.fa-indian-rupee::before {
+  content: "\e1bc"; }
+
+.fa-inr::before {
+  content: "\e1bc"; }
+
+.fa-crop-simple::before {
+  content: "\f565"; }
+
+.fa-crop-alt::before {
+  content: "\f565"; }
+
+.fa-money-bill-1::before {
+  content: "\f3d1"; }
+
+.fa-money-bill-alt::before {
+  content: "\f3d1"; }
+
+.fa-left-long::before {
+  content: "\f30a"; }
+
+.fa-long-arrow-alt-left::before {
+  content: "\f30a"; }
+
+.fa-dna::before {
+  content: "\f471"; }
+
+.fa-virus-slash::before {
+  content: "\e075"; }
+
+.fa-minus::before {
+  content: "\f068"; }
+
+.fa-subtract::before {
+  content: "\f068"; }
+
+.fa-chess::before {
+  content: "\f439"; }
+
+.fa-arrow-left-long::before {
+  content: "\f177"; }
+
+.fa-long-arrow-left::before {
+  content: "\f177"; }
+
+.fa-plug-circle-check::before {
+  content: "\e55c"; }
+
+.fa-street-view::before {
+  content: "\f21d"; }
+
+.fa-franc-sign::before {
+  content: "\e18f"; }
+
+.fa-volume-off::before {
+  content: "\f026"; }
+
+.fa-hands-asl-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-american-sign-language-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-asl-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-hands-american-sign-language-interpreting::before {
+  content: "\f2a3"; }
+
+.fa-gear::before {
+  content: "\f013"; }
+
+.fa-cog::before {
+  content: "\f013"; }
+
+.fa-droplet-slash::before {
+  content: "\f5c7"; }
+
+.fa-tint-slash::before {
+  content: "\f5c7"; }
+
+.fa-mosque::before {
+  content: "\f678"; }
+
+.fa-mosquito::before {
+  content: "\e52b"; }
+
+.fa-star-of-david::before {
+  content: "\f69a"; }
+
+.fa-person-military-rifle::before {
+  content: "\e54b"; }
+
+.fa-cart-shopping::before {
+  content: "\f07a"; }
+
+.fa-shopping-cart::before {
+  content: "\f07a"; }
+
+.fa-vials::before {
+  content: "\f493"; }
+
+.fa-plug-circle-plus::before {
+  content: "\e55f"; }
+
+.fa-place-of-worship::before {
+  content: "\f67f"; }
+
+.fa-grip-vertical::before {
+  content: "\f58e"; }
+
+.fa-arrow-turn-up::before {
+  content: "\f148"; }
+
+.fa-level-up::before {
+  content: "\f148"; }
+
+.fa-u::before {
+  content: "\55"; }
+
+.fa-square-root-variable::before {
+  content: "\f698"; }
+
+.fa-square-root-alt::before {
+  content: "\f698"; }
+
+.fa-clock::before {
+  content: "\f017"; }
+
+.fa-clock-four::before {
+  content: "\f017"; }
+
+.fa-backward-step::before {
+  content: "\f048"; }
+
+.fa-step-backward::before {
+  content: "\f048"; }
+
+.fa-pallet::before {
+  content: "\f482"; }
+
+.fa-faucet::before {
+  content: "\e005"; }
+
+.fa-baseball-bat-ball::before {
+  content: "\f432"; }
+
+.fa-s::before {
+  content: "\53"; }
+
+.fa-timeline::before {
+  content: "\e29c"; }
+
+.fa-keyboard::before {
+  content: "\f11c"; }
+
+.fa-caret-down::before {
+  content: "\f0d7"; }
+
+.fa-house-chimney-medical::before {
+  content: "\f7f2"; }
+
+.fa-clinic-medical::before {
+  content: "\f7f2"; }
+
+.fa-temperature-three-quarters::before {
+  content: "\f2c8"; }
+
+.fa-temperature-3::before {
+  content: "\f2c8"; }
+
+.fa-thermometer-3::before {
+  content: "\f2c8"; }
+
+.fa-thermometer-three-quarters::before {
+  content: "\f2c8"; }
+
+.fa-mobile-screen::before {
+  content: "\f3cf"; }
+
+.fa-mobile-android-alt::before {
+  content: "\f3cf"; }
+
+.fa-plane-up::before {
+  content: "\e22d"; }
+
+.fa-piggy-bank::before {
+  content: "\f4d3"; }
+
+.fa-battery-half::before {
+  content: "\f242"; }
+
+.fa-battery-3::before {
+  content: "\f242"; }
+
+.fa-mountain-city::before {
+  content: "\e52e"; }
+
+.fa-coins::before {
+  content: "\f51e"; }
+
+.fa-khanda::before {
+  content: "\f66d"; }
+
+.fa-sliders::before {
+  content: "\f1de"; }
+
+.fa-sliders-h::before {
+  content: "\f1de"; }
+
+.fa-folder-tree::before {
+  content: "\f802"; }
+
+.fa-network-wired::before {
+  content: "\f6ff"; }
+
+.fa-map-pin::before {
+  content: "\f276"; }
+
+.fa-hamsa::before {
+  content: "\f665"; }
+
+.fa-cent-sign::before {
+  content: "\e3f5"; }
+
+.fa-flask::before {
+  content: "\f0c3"; }
+
+.fa-person-pregnant::before {
+  content: "\e31e"; }
+
+.fa-wand-sparkles::before {
+  content: "\f72b"; }
+
+.fa-ellipsis-vertical::before {
+  content: "\f142"; }
+
+.fa-ellipsis-v::before {
+  content: "\f142"; }
+
+.fa-ticket::before {
+  content: "\f145"; }
+
+.fa-power-off::before {
+  content: "\f011"; }
+
+.fa-right-long::before {
+  content: "\f30b"; }
+
+.fa-long-arrow-alt-right::before {
+  content: "\f30b"; }
+
+.fa-flag-usa::before {
+  content: "\f74d"; }
+
+.fa-laptop-file::before {
+  content: "\e51d"; }
+
+.fa-tty::before {
+  content: "\f1e4"; }
+
+.fa-teletype::before {
+  content: "\f1e4"; }
+
+.fa-diagram-next::before {
+  content: "\e476"; }
+
+.fa-person-rifle::before {
+  content: "\e54e"; }
+
+.fa-house-medical-circle-exclamation::before {
+  content: "\e512"; }
+
+.fa-closed-captioning::before {
+  content: "\f20a"; }
+
+.fa-person-hiking::before {
+  content: "\f6ec"; }
+
+.fa-hiking::before {
+  content: "\f6ec"; }
+
+.fa-venus-double::before {
+  content: "\f226"; }
+
+.fa-images::before {
+  content: "\f302"; }
+
+.fa-calculator::before {
+  content: "\f1ec"; }
+
+.fa-people-pulling::before {
+  content: "\e535"; }
+
+.fa-n::before {
+  content: "\4e"; }
+
+.fa-cable-car::before {
+  content: "\f7da"; }
+
+.fa-tram::before {
+  content: "\f7da"; }
+
+.fa-cloud-rain::before {
+  content: "\f73d"; }
+
+.fa-building-circle-xmark::before {
+  content: "\e4d4"; }
+
+.fa-ship::before {
+  content: "\f21a"; }
+
+.fa-arrows-down-to-line::before {
+  content: "\e4b8"; }
+
+.fa-download::before {
+  content: "\f019"; }
+
+.fa-face-grin::before {
+  content: "\f580"; }
+
+.fa-grin::before {
+  content: "\f580"; }
+
+.fa-delete-left::before {
+  content: "\f55a"; }
+
+.fa-backspace::before {
+  content: "\f55a"; }
+
+.fa-eye-dropper::before {
+  content: "\f1fb"; }
+
+.fa-eye-dropper-empty::before {
+  content: "\f1fb"; }
+
+.fa-eyedropper::before {
+  content: "\f1fb"; }
+
+.fa-file-circle-check::before {
+  content: "\e5a0"; }
+
+.fa-forward::before {
+  content: "\f04e"; }
+
+.fa-mobile::before {
+  content: "\f3ce"; }
+
+.fa-mobile-android::before {
+  content: "\f3ce"; }
+
+.fa-mobile-phone::before {
+  content: "\f3ce"; }
+
+.fa-face-meh::before {
+  content: "\f11a"; }
+
+.fa-meh::before {
+  content: "\f11a"; }
+
+.fa-align-center::before {
+  content: "\f037"; }
+
+.fa-book-skull::before {
+  content: "\f6b7"; }
+
+.fa-book-dead::before {
+  content: "\f6b7"; }
+
+.fa-id-card::before {
+  content: "\f2c2"; }
+
+.fa-drivers-license::before {
+  content: "\f2c2"; }
+
+.fa-outdent::before {
+  content: "\f03b"; }
+
+.fa-dedent::before {
+  content: "\f03b"; }
+
+.fa-heart-circle-exclamation::before {
+  content: "\e4fe"; }
+
+.fa-house::before {
+  content: "\f015"; }
+
+.fa-home::before {
+  content: "\f015"; }
+
+.fa-home-alt::before {
+  content: "\f015"; }
+
+.fa-home-lg-alt::before {
+  content: "\f015"; }
+
+.fa-calendar-week::before {
+  content: "\f784"; }
+
+.fa-laptop-medical::before {
+  content: "\f812"; }
+
+.fa-b::before {
+  content: "\42"; }
+
+.fa-file-medical::before {
+  content: "\f477"; }
+
+.fa-dice-one::before {
+  content: "\f525"; }
+
+.fa-kiwi-bird::before {
+  content: "\f535"; }
+
+.fa-arrow-right-arrow-left::before {
+  content: "\f0ec"; }
+
+.fa-exchange::before {
+  content: "\f0ec"; }
+
+.fa-rotate-right::before {
+  content: "\f2f9"; }
+
+.fa-redo-alt::before {
+  content: "\f2f9"; }
+
+.fa-rotate-forward::before {
+  content: "\f2f9"; }
+
+.fa-utensils::before {
+  content: "\f2e7"; }
+
+.fa-cutlery::before {
+  content: "\f2e7"; }
+
+.fa-arrow-up-wide-short::before {
+  content: "\f161"; }
+
+.fa-sort-amount-up::before {
+  content: "\f161"; }
+
+.fa-mill-sign::before {
+  content: "\e1ed"; }
+
+.fa-bowl-rice::before {
+  content: "\e2eb"; }
+
+.fa-skull::before {
+  content: "\f54c"; }
+
+.fa-tower-broadcast::before {
+  content: "\f519"; }
+
+.fa-broadcast-tower::before {
+  content: "\f519"; }
+
+.fa-truck-pickup::before {
+  content: "\f63c"; }
+
+.fa-up-long::before {
+  content: "\f30c"; }
+
+.fa-long-arrow-alt-up::before {
+  content: "\f30c"; }
+
+.fa-stop::before {
+  content: "\f04d"; }
+
+.fa-code-merge::before {
+  content: "\f387"; }
+
+.fa-upload::before {
+  content: "\f093"; }
+
+.fa-hurricane::before {
+  content: "\f751"; }
+
+.fa-mound::before {
+  content: "\e52d"; }
+
+.fa-toilet-portable::before {
+  content: "\e583"; }
+
+.fa-compact-disc::before {
+  content: "\f51f"; }
+
+.fa-file-arrow-down::before {
+  content: "\f56d"; }
+
+.fa-file-download::before {
+  content: "\f56d"; }
+
+.fa-caravan::before {
+  content: "\f8ff"; }
+
+.fa-shield-cat::before {
+  content: "\e572"; }
+
+.fa-bolt::before {
+  content: "\f0e7"; }
+
+.fa-zap::before {
+  content: "\f0e7"; }
+
+.fa-glass-water::before {
+  content: "\e4f4"; }
+
+.fa-oil-well::before {
+  content: "\e532"; }
+
+.fa-vault::before {
+  content: "\e2c5"; }
+
+.fa-mars::before {
+  content: "\f222"; }
+
+.fa-toilet::before {
+  content: "\f7d8"; }
+
+.fa-plane-circle-xmark::before {
+  content: "\e557"; }
+
+.fa-yen-sign::before {
+  content: "\f157"; }
+
+.fa-cny::before {
+  content: "\f157"; }
+
+.fa-jpy::before {
+  content: "\f157"; }
+
+.fa-rmb::before {
+  content: "\f157"; }
+
+.fa-yen::before {
+  content: "\f157"; }
+
+.fa-ruble-sign::before {
+  content: "\f158"; }
+
+.fa-rouble::before {
+  content: "\f158"; }
+
+.fa-rub::before {
+  content: "\f158"; }
+
+.fa-ruble::before {
+  content: "\f158"; }
+
+.fa-sun::before {
+  content: "\f185"; }
+
+.fa-guitar::before {
+  content: "\f7a6"; }
+
+.fa-face-laugh-wink::before {
+  content: "\f59c"; }
+
+.fa-laugh-wink::before {
+  content: "\f59c"; }
+
+.fa-horse-head::before {
+  content: "\f7ab"; }
+
+.fa-bore-hole::before {
+  content: "\e4c3"; }
+
+.fa-industry::before {
+  content: "\f275"; }
+
+.fa-circle-down::before {
+  content: "\f358"; }
+
+.fa-arrow-alt-circle-down::before {
+  content: "\f358"; }
+
+.fa-arrows-turn-to-dots::before {
+  content: "\e4c1"; }
+
+.fa-florin-sign::before {
+  content: "\e184"; }
+
+.fa-arrow-down-short-wide::before {
+  content: "\f884"; }
+
+.fa-sort-amount-desc::before {
+  content: "\f884"; }
+
+.fa-sort-amount-down-alt::before {
+  content: "\f884"; }
+
+.fa-less-than::before {
+  content: "\3c"; }
+
+.fa-angle-down::before {
+  content: "\f107"; }
+
+.fa-car-tunnel::before {
+  content: "\e4de"; }
+
+.fa-head-side-cough::before {
+  content: "\e061"; }
+
+.fa-grip-lines::before {
+  content: "\f7a4"; }
+
+.fa-thumbs-down::before {
+  content: "\f165"; }
+
+.fa-user-lock::before {
+  content: "\f502"; }
+
+.fa-arrow-right-long::before {
+  content: "\f178"; }
+
+.fa-long-arrow-right::before {
+  content: "\f178"; }
+
+.fa-anchor-circle-xmark::before {
+  content: "\e4ac"; }
+
+.fa-ellipsis::before {
+  content: "\f141"; }
+
+.fa-ellipsis-h::before {
+  content: "\f141"; }
+
+.fa-chess-pawn::before {
+  content: "\f443"; }
+
+.fa-kit-medical::before {
+  content: "\f479"; }
+
+.fa-first-aid::before {
+  content: "\f479"; }
+
+.fa-person-through-window::before {
+  content: "\e5a9"; }
+
+.fa-toolbox::before {
+  content: "\f552"; }
+
+.fa-hands-holding-circle::before {
+  content: "\e4fb"; }
+
+.fa-bug::before {
+  content: "\f188"; }
+
+.fa-credit-card::before {
+  content: "\f09d"; }
+
+.fa-credit-card-alt::before {
+  content: "\f09d"; }
+
+.fa-car::before {
+  content: "\f1b9"; }
+
+.fa-automobile::before {
+  content: "\f1b9"; }
+
+.fa-hand-holding-hand::before {
+  content: "\e4f7"; }
+
+.fa-book-open-reader::before {
+  content: "\f5da"; }
+
+.fa-book-reader::before {
+  content: "\f5da"; }
+
+.fa-mountain-sun::before {
+  content: "\e52f"; }
+
+.fa-arrows-left-right-to-line::before {
+  content: "\e4ba"; }
+
+.fa-dice-d20::before {
+  content: "\f6cf"; }
+
+.fa-truck-droplet::before {
+  content: "\e58c"; }
+
+.fa-file-circle-xmark::before {
+  content: "\e5a1"; }
+
+.fa-temperature-arrow-up::before {
+  content: "\e040"; }
+
+.fa-temperature-up::before {
+  content: "\e040"; }
+
+.fa-medal::before {
+  content: "\f5a2"; }
+
+.fa-bed::before {
+  content: "\f236"; }
+
+.fa-square-h::before {
+  content: "\f0fd"; }
+
+.fa-h-square::before {
+  content: "\f0fd"; }
+
+.fa-podcast::before {
+  content: "\f2ce"; }
+
+.fa-temperature-full::before {
+  content: "\f2c7"; }
+
+.fa-temperature-4::before {
+  content: "\f2c7"; }
+
+.fa-thermometer-4::before {
+  content: "\f2c7"; }
+
+.fa-thermometer-full::before {
+  content: "\f2c7"; }
+
+.fa-bell::before {
+  content: "\f0f3"; }
+
+.fa-superscript::before {
+  content: "\f12b"; }
+
+.fa-plug-circle-xmark::before {
+  content: "\e560"; }
+
+.fa-star-of-life::before {
+  content: "\f621"; }
+
+.fa-phone-slash::before {
+  content: "\f3dd"; }
+
+.fa-paint-roller::before {
+  content: "\f5aa"; }
+
+.fa-handshake-angle::before {
+  content: "\f4c4"; }
+
+.fa-hands-helping::before {
+  content: "\f4c4"; }
+
+.fa-location-dot::before {
+  content: "\f3c5"; }
+
+.fa-map-marker-alt::before {
+  content: "\f3c5"; }
+
+.fa-file::before {
+  content: "\f15b"; }
+
+.fa-greater-than::before {
+  content: "\3e"; }
+
+.fa-person-swimming::before {
+  content: "\f5c4"; }
+
+.fa-swimmer::before {
+  content: "\f5c4"; }
+
+.fa-arrow-down::before {
+  content: "\f063"; }
+
+.fa-droplet::before {
+  content: "\f043"; }
+
+.fa-tint::before {
+  content: "\f043"; }
+
+.fa-eraser::before {
+  content: "\f12d"; }
+
+.fa-earth-americas::before {
+  content: "\f57d"; }
+
+.fa-earth::before {
+  content: "\f57d"; }
+
+.fa-earth-america::before {
+  content: "\f57d"; }
+
+.fa-globe-americas::before {
+  content: "\f57d"; }
+
+.fa-person-burst::before {
+  content: "\e53b"; }
+
+.fa-dove::before {
+  content: "\f4ba"; }
+
+.fa-battery-empty::before {
+  content: "\f244"; }
+
+.fa-battery-0::before {
+  content: "\f244"; }
+
+.fa-socks::before {
+  content: "\f696"; }
+
+.fa-inbox::before {
+  content: "\f01c"; }
+
+.fa-section::before {
+  content: "\e447"; }
+
+.fa-gauge-high::before {
+  content: "\f625"; }
+
+.fa-tachometer-alt::before {
+  content: "\f625"; }
+
+.fa-tachometer-alt-fast::before {
+  content: "\f625"; }
+
+.fa-envelope-open-text::before {
+  content: "\f658"; }
+
+.fa-hospital::before {
+  content: "\f0f8"; }
+
+.fa-hospital-alt::before {
+  content: "\f0f8"; }
+
+.fa-hospital-wide::before {
+  content: "\f0f8"; }
+
+.fa-wine-bottle::before {
+  content: "\f72f"; }
+
+.fa-chess-rook::before {
+  content: "\f447"; }
+
+.fa-bars-staggered::before {
+  content: "\f550"; }
+
+.fa-reorder::before {
+  content: "\f550"; }
+
+.fa-stream::before {
+  content: "\f550"; }
+
+.fa-dharmachakra::before {
+  content: "\f655"; }
+
+.fa-hotdog::before {
+  content: "\f80f"; }
+
+.fa-person-walking-with-cane::before {
+  content: "\f29d"; }
+
+.fa-blind::before {
+  content: "\f29d"; }
+
+.fa-drum::before {
+  content: "\f569"; }
+
+.fa-ice-cream::before {
+  content: "\f810"; }
+
+.fa-heart-circle-bolt::before {
+  content: "\e4fc"; }
+
+.fa-fax::before {
+  content: "\f1ac"; }
+
+.fa-paragraph::before {
+  content: "\f1dd"; }
+
+.fa-check-to-slot::before {
+  content: "\f772"; }
+
+.fa-vote-yea::before {
+  content: "\f772"; }
+
+.fa-star-half::before {
+  content: "\f089"; }
+
+.fa-boxes-stacked::before {
+  content: "\f468"; }
+
+.fa-boxes::before {
+  content: "\f468"; }
+
+.fa-boxes-alt::before {
+  content: "\f468"; }
+
+.fa-link::before {
+  content: "\f0c1"; }
+
+.fa-chain::before {
+  content: "\f0c1"; }
+
+.fa-ear-listen::before {
+  content: "\f2a2"; }
+
+.fa-assistive-listening-systems::before {
+  content: "\f2a2"; }
+
+.fa-tree-city::before {
+  content: "\e587"; }
+
+.fa-play::before {
+  content: "\f04b"; }
+
+.fa-font::before {
+  content: "\f031"; }
+
+.fa-table-cells-row-lock::before {
+  content: "\e67a"; }
+
+.fa-rupiah-sign::before {
+  content: "\e23d"; }
+
+.fa-magnifying-glass::before {
+  content: "\f002"; }
+
+.fa-search::before {
+  content: "\f002"; }
+
+.fa-table-tennis-paddle-ball::before {
+  content: "\f45d"; }
+
+.fa-ping-pong-paddle-ball::before {
+  content: "\f45d"; }
+
+.fa-table-tennis::before {
+  content: "\f45d"; }
+
+.fa-person-dots-from-line::before {
+  content: "\f470"; }
+
+.fa-diagnoses::before {
+  content: "\f470"; }
+
+.fa-trash-can-arrow-up::before {
+  content: "\f82a"; }
+
+.fa-trash-restore-alt::before {
+  content: "\f82a"; }
+
+.fa-naira-sign::before {
+  content: "\e1f6"; }
+
+.fa-cart-arrow-down::before {
+  content: "\f218"; }
+
+.fa-walkie-talkie::before {
+  content: "\f8ef"; }
+
+.fa-file-pen::before {
+  content: "\f31c"; }
+
+.fa-file-edit::before {
+  content: "\f31c"; }
+
+.fa-receipt::before {
+  content: "\f543"; }
+
+.fa-square-pen::before {
+  content: "\f14b"; }
+
+.fa-pen-square::before {
+  content: "\f14b"; }
+
+.fa-pencil-square::before {
+  content: "\f14b"; }
+
+.fa-suitcase-rolling::before {
+  content: "\f5c1"; }
+
+.fa-person-circle-exclamation::before {
+  content: "\e53f"; }
+
+.fa-chevron-down::before {
+  content: "\f078"; }
+
+.fa-battery-full::before {
+  content: "\f240"; }
+
+.fa-battery::before {
+  content: "\f240"; }
+
+.fa-battery-5::before {
+  content: "\f240"; }
+
+.fa-skull-crossbones::before {
+  content: "\f714"; }
+
+.fa-code-compare::before {
+  content: "\e13a"; }
+
+.fa-list-ul::before {
+  content: "\f0ca"; }
+
+.fa-list-dots::before {
+  content: "\f0ca"; }
+
+.fa-school-lock::before {
+  content: "\e56f"; }
+
+.fa-tower-cell::before {
+  content: "\e585"; }
+
+.fa-down-long::before {
+  content: "\f309"; }
+
+.fa-long-arrow-alt-down::before {
+  content: "\f309"; }
+
+.fa-ranking-star::before {
+  content: "\e561"; }
+
+.fa-chess-king::before {
+  content: "\f43f"; }
+
+.fa-person-harassing::before {
+  content: "\e549"; }
+
+.fa-brazilian-real-sign::before {
+  content: "\e46c"; }
+
+.fa-landmark-dome::before {
+  content: "\f752"; }
+
+.fa-landmark-alt::before {
+  content: "\f752"; }
+
+.fa-arrow-up::before {
+  content: "\f062"; }
+
+.fa-tv::before {
+  content: "\f26c"; }
+
+.fa-television::before {
+  content: "\f26c"; }
+
+.fa-tv-alt::before {
+  content: "\f26c"; }
+
+.fa-shrimp::before {
+  content: "\e448"; }
+
+.fa-list-check::before {
+  content: "\f0ae"; }
+
+.fa-tasks::before {
+  content: "\f0ae"; }
+
+.fa-jug-detergent::before {
+  content: "\e519"; }
+
+.fa-circle-user::before {
+  content: "\f2bd"; }
+
+.fa-user-circle::before {
+  content: "\f2bd"; }
+
+.fa-user-shield::before {
+  content: "\f505"; }
+
+.fa-wind::before {
+  content: "\f72e"; }
+
+.fa-car-burst::before {
+  content: "\f5e1"; }
+
+.fa-car-crash::before {
+  content: "\f5e1"; }
+
+.fa-y::before {
+  content: "\59"; }
+
+.fa-person-snowboarding::before {
+  content: "\f7ce"; }
+
+.fa-snowboarding::before {
+  content: "\f7ce"; }
+
+.fa-truck-fast::before {
+  content: "\f48b"; }
+
+.fa-shipping-fast::before {
+  content: "\f48b"; }
+
+.fa-fish::before {
+  content: "\f578"; }
+
+.fa-user-graduate::before {
+  content: "\f501"; }
+
+.fa-circle-half-stroke::before {
+  content: "\f042"; }
+
+.fa-adjust::before {
+  content: "\f042"; }
+
+.fa-clapperboard::before {
+  content: "\e131"; }
+
+.fa-circle-radiation::before {
+  content: "\f7ba"; }
+
+.fa-radiation-alt::before {
+  content: "\f7ba"; }
+
+.fa-baseball::before {
+  content: "\f433"; }
+
+.fa-baseball-ball::before {
+  content: "\f433"; }
+
+.fa-jet-fighter-up::before {
+  content: "\e518"; }
+
+.fa-diagram-project::before {
+  content: "\f542"; }
+
+.fa-project-diagram::before {
+  content: "\f542"; }
+
+.fa-copy::before {
+  content: "\f0c5"; }
+
+.fa-volume-xmark::before {
+  content: "\f6a9"; }
+
+.fa-volume-mute::before {
+  content: "\f6a9"; }
+
+.fa-volume-times::before {
+  content: "\f6a9"; }
+
+.fa-hand-sparkles::before {
+  content: "\e05d"; }
+
+.fa-grip::before {
+  content: "\f58d"; }
+
+.fa-grip-horizontal::before {
+  content: "\f58d"; }
+
+.fa-share-from-square::before {
+  content: "\f14d"; }
+
+.fa-share-square::before {
+  content: "\f14d"; }
+
+.fa-child-combatant::before {
+  content: "\e4e0"; }
+
+.fa-child-rifle::before {
+  content: "\e4e0"; }
+
+.fa-gun::before {
+  content: "\e19b"; }
+
+.fa-square-phone::before {
+  content: "\f098"; }
+
+.fa-phone-square::before {
+  content: "\f098"; }
+
+.fa-plus::before {
+  content: "\2b"; }
+
+.fa-add::before {
+  content: "\2b"; }
+
+.fa-expand::before {
+  content: "\f065"; }
+
+.fa-computer::before {
+  content: "\e4e5"; }
+
+.fa-xmark::before {
+  content: "\f00d"; }
+
+.fa-close::before {
+  content: "\f00d"; }
+
+.fa-multiply::before {
+  content: "\f00d"; }
+
+.fa-remove::before {
+  content: "\f00d"; }
+
+.fa-times::before {
+  content: "\f00d"; }
+
+.fa-arrows-up-down-left-right::before {
+  content: "\f047"; }
+
+.fa-arrows::before {
+  content: "\f047"; }
+
+.fa-chalkboard-user::before {
+  content: "\f51c"; }
+
+.fa-chalkboard-teacher::before {
+  content: "\f51c"; }
+
+.fa-peso-sign::before {
+  content: "\e222"; }
+
+.fa-building-shield::before {
+  content: "\e4d8"; }
+
+.fa-baby::before {
+  content: "\f77c"; }
+
+.fa-users-line::before {
+  content: "\e592"; }
+
+.fa-quote-left::before {
+  content: "\f10d"; }
+
+.fa-quote-left-alt::before {
+  content: "\f10d"; }
+
+.fa-tractor::before {
+  content: "\f722"; }
+
+.fa-trash-arrow-up::before {
+  content: "\f829"; }
+
+.fa-trash-restore::before {
+  content: "\f829"; }
+
+.fa-arrow-down-up-lock::before {
+  content: "\e4b0"; }
+
+.fa-lines-leaning::before {
+  content: "\e51e"; }
+
+.fa-ruler-combined::before {
+  content: "\f546"; }
+
+.fa-copyright::before {
+  content: "\f1f9"; }
+
+.fa-equals::before {
+  content: "\3d"; }
+
+.fa-blender::before {
+  content: "\f517"; }
+
+.fa-teeth::before {
+  content: "\f62e"; }
+
+.fa-shekel-sign::before {
+  content: "\f20b"; }
+
+.fa-ils::before {
+  content: "\f20b"; }
+
+.fa-shekel::before {
+  content: "\f20b"; }
+
+.fa-sheqel::before {
+  content: "\f20b"; }
+
+.fa-sheqel-sign::before {
+  content: "\f20b"; }
+
+.fa-map::before {
+  content: "\f279"; }
+
+.fa-rocket::before {
+  content: "\f135"; }
+
+.fa-photo-film::before {
+  content: "\f87c"; }
+
+.fa-photo-video::before {
+  content: "\f87c"; }
+
+.fa-folder-minus::before {
+  content: "\f65d"; }
+
+.fa-store::before {
+  content: "\f54e"; }
+
+.fa-arrow-trend-up::before {
+  content: "\e098"; }
+
+.fa-plug-circle-minus::before {
+  content: "\e55e"; }
+
+.fa-sign-hanging::before {
+  content: "\f4d9"; }
+
+.fa-sign::before {
+  content: "\f4d9"; }
+
+.fa-bezier-curve::before {
+  content: "\f55b"; }
+
+.fa-bell-slash::before {
+  content: "\f1f6"; }
+
+.fa-tablet::before {
+  content: "\f3fb"; }
+
+.fa-tablet-android::before {
+  content: "\f3fb"; }
+
+.fa-school-flag::before {
+  content: "\e56e"; }
+
+.fa-fill::before {
+  content: "\f575"; }
+
+.fa-angle-up::before {
+  content: "\f106"; }
+
+.fa-drumstick-bite::before {
+  content: "\f6d7"; }
+
+.fa-holly-berry::before {
+  content: "\f7aa"; }
+
+.fa-chevron-left::before {
+  content: "\f053"; }
+
+.fa-bacteria::before {
+  content: "\e059"; }
+
+.fa-hand-lizard::before {
+  content: "\f258"; }
+
+.fa-notdef::before {
+  content: "\e1fe"; }
+
+.fa-disease::before {
+  content: "\f7fa"; }
+
+.fa-briefcase-medical::before {
+  content: "\f469"; }
+
+.fa-genderless::before {
+  content: "\f22d"; }
+
+.fa-chevron-right::before {
+  content: "\f054"; }
+
+.fa-retweet::before {
+  content: "\f079"; }
+
+.fa-car-rear::before {
+  content: "\f5de"; }
+
+.fa-car-alt::before {
+  content: "\f5de"; }
+
+.fa-pump-soap::before {
+  content: "\e06b"; }
+
+.fa-video-slash::before {
+  content: "\f4e2"; }
+
+.fa-battery-quarter::before {
+  content: "\f243"; }
+
+.fa-battery-2::before {
+  content: "\f243"; }
+
+.fa-radio::before {
+  content: "\f8d7"; }
+
+.fa-baby-carriage::before {
+  content: "\f77d"; }
+
+.fa-carriage-baby::before {
+  content: "\f77d"; }
+
+.fa-traffic-light::before {
+  content: "\f637"; }
+
+.fa-thermometer::before {
+  content: "\f491"; }
+
+.fa-vr-cardboard::before {
+  content: "\f729"; }
+
+.fa-hand-middle-finger::before {
+  content: "\f806"; }
+
+.fa-percent::before {
+  content: "\25"; }
+
+.fa-percentage::before {
+  content: "\25"; }
+
+.fa-truck-moving::before {
+  content: "\f4df"; }
+
+.fa-glass-water-droplet::before {
+  content: "\e4f5"; }
+
+.fa-display::before {
+  content: "\e163"; }
+
+.fa-face-smile::before {
+  content: "\f118"; }
+
+.fa-smile::before {
+  content: "\f118"; }
+
+.fa-thumbtack::before {
+  content: "\f08d"; }
+
+.fa-thumb-tack::before {
+  content: "\f08d"; }
+
+.fa-trophy::before {
+  content: "\f091"; }
+
+.fa-person-praying::before {
+  content: "\f683"; }
+
+.fa-pray::before {
+  content: "\f683"; }
+
+.fa-hammer::before {
+  content: "\f6e3"; }
+
+.fa-hand-peace::before {
+  content: "\f25b"; }
+
+.fa-rotate::before {
+  content: "\f2f1"; }
+
+.fa-sync-alt::before {
+  content: "\f2f1"; }
+
+.fa-spinner::before {
+  content: "\f110"; }
+
+.fa-robot::before {
+  content: "\f544"; }
+
+.fa-peace::before {
+  content: "\f67c"; }
+
+.fa-gears::before {
+  content: "\f085"; }
+
+.fa-cogs::before {
+  content: "\f085"; }
+
+.fa-warehouse::before {
+  content: "\f494"; }
+
+.fa-arrow-up-right-dots::before {
+  content: "\e4b7"; }
+
+.fa-splotch::before {
+  content: "\f5bc"; }
+
+.fa-face-grin-hearts::before {
+  content: "\f584"; }
+
+.fa-grin-hearts::before {
+  content: "\f584"; }
+
+.fa-dice-four::before {
+  content: "\f524"; }
+
+.fa-sim-card::before {
+  content: "\f7c4"; }
+
+.fa-transgender::before {
+  content: "\f225"; }
+
+.fa-transgender-alt::before {
+  content: "\f225"; }
+
+.fa-mercury::before {
+  content: "\f223"; }
+
+.fa-arrow-turn-down::before {
+  content: "\f149"; }
+
+.fa-level-down::before {
+  content: "\f149"; }
+
+.fa-person-falling-burst::before {
+  content: "\e547"; }
+
+.fa-award::before {
+  content: "\f559"; }
+
+.fa-ticket-simple::before {
+  content: "\f3ff"; }
+
+.fa-ticket-alt::before {
+  content: "\f3ff"; }
+
+.fa-building::before {
+  content: "\f1ad"; }
+
+.fa-angles-left::before {
+  content: "\f100"; }
+
+.fa-angle-double-left::before {
+  content: "\f100"; }
+
+.fa-qrcode::before {
+  content: "\f029"; }
+
+.fa-clock-rotate-left::before {
+  content: "\f1da"; }
+
+.fa-history::before {
+  content: "\f1da"; }
+
+.fa-face-grin-beam-sweat::before {
+  content: "\f583"; }
+
+.fa-grin-beam-sweat::before {
+  content: "\f583"; }
+
+.fa-file-export::before {
+  content: "\f56e"; }
+
+.fa-arrow-right-from-file::before {
+  content: "\f56e"; }
+
+.fa-shield::before {
+  content: "\f132"; }
+
+.fa-shield-blank::before {
+  content: "\f132"; }
+
+.fa-arrow-up-short-wide::before {
+  content: "\f885"; }
+
+.fa-sort-amount-up-alt::before {
+  content: "\f885"; }
+
+.fa-house-medical::before {
+  content: "\e3b2"; }
+
+.fa-golf-ball-tee::before {
+  content: "\f450"; }
+
+.fa-golf-ball::before {
+  content: "\f450"; }
+
+.fa-circle-chevron-left::before {
+  content: "\f137"; }
+
+.fa-chevron-circle-left::before {
+  content: "\f137"; }
+
+.fa-house-chimney-window::before {
+  content: "\e00d"; }
+
+.fa-pen-nib::before {
+  content: "\f5ad"; }
+
+.fa-tent-arrow-turn-left::before {
+  content: "\e580"; }
+
+.fa-tents::before {
+  content: "\e582"; }
+
+.fa-wand-magic::before {
+  content: "\f0d0"; }
+
+.fa-magic::before {
+  content: "\f0d0"; }
+
+.fa-dog::before {
+  content: "\f6d3"; }
+
+.fa-carrot::before {
+  content: "\f787"; }
+
+.fa-moon::before {
+  content: "\f186"; }
+
+.fa-wine-glass-empty::before {
+  content: "\f5ce"; }
+
+.fa-wine-glass-alt::before {
+  content: "\f5ce"; }
+
+.fa-cheese::before {
+  content: "\f7ef"; }
+
+.fa-yin-yang::before {
+  content: "\f6ad"; }
+
+.fa-music::before {
+  content: "\f001"; }
+
+.fa-code-commit::before {
+  content: "\f386"; }
+
+.fa-temperature-low::before {
+  content: "\f76b"; }
+
+.fa-person-biking::before {
+  content: "\f84a"; }
+
+.fa-biking::before {
+  content: "\f84a"; }
+
+.fa-broom::before {
+  content: "\f51a"; }
+
+.fa-shield-heart::before {
+  content: "\e574"; }
+
+.fa-gopuram::before {
+  content: "\f664"; }
+
+.fa-earth-oceania::before {
+  content: "\e47b"; }
+
+.fa-globe-oceania::before {
+  content: "\e47b"; }
+
+.fa-square-xmark::before {
+  content: "\f2d3"; }
+
+.fa-times-square::before {
+  content: "\f2d3"; }
+
+.fa-xmark-square::before {
+  content: "\f2d3"; }
+
+.fa-hashtag::before {
+  content: "\23"; }
+
+.fa-up-right-and-down-left-from-center::before {
+  content: "\f424"; }
+
+.fa-expand-alt::before {
+  content: "\f424"; }
+
+.fa-oil-can::before {
+  content: "\f613"; }
+
+.fa-t::before {
+  content: "\54"; }
+
+.fa-hippo::before {
+  content: "\f6ed"; }
+
+.fa-chart-column::before {
+  content: "\e0e3"; }
+
+.fa-infinity::before {
+  content: "\f534"; }
+
+.fa-vial-circle-check::before {
+  content: "\e596"; }
+
+.fa-person-arrow-down-to-line::before {
+  content: "\e538"; }
+
+.fa-voicemail::before {
+  content: "\f897"; }
+
+.fa-fan::before {
+  content: "\f863"; }
+
+.fa-person-walking-luggage::before {
+  content: "\e554"; }
+
+.fa-up-down::before {
+  content: "\f338"; }
+
+.fa-arrows-alt-v::before {
+  content: "\f338"; }
+
+.fa-cloud-moon-rain::before {
+  content: "\f73c"; }
+
+.fa-calendar::before {
+  content: "\f133"; }
+
+.fa-trailer::before {
+  content: "\e041"; }
+
+.fa-bahai::before {
+  content: "\f666"; }
+
+.fa-haykal::before {
+  content: "\f666"; }
+
+.fa-sd-card::before {
+  content: "\f7c2"; }
+
+.fa-dragon::before {
+  content: "\f6d5"; }
+
+.fa-shoe-prints::before {
+  content: "\f54b"; }
+
+.fa-circle-plus::before {
+  content: "\f055"; }
+
+.fa-plus-circle::before {
+  content: "\f055"; }
+
+.fa-face-grin-tongue-wink::before {
+  content: "\f58b"; }
+
+.fa-grin-tongue-wink::before {
+  content: "\f58b"; }
+
+.fa-hand-holding::before {
+  content: "\f4bd"; }
+
+.fa-plug-circle-exclamation::before {
+  content: "\e55d"; }
+
+.fa-link-slash::before {
+  content: "\f127"; }
+
+.fa-chain-broken::before {
+  content: "\f127"; }
+
+.fa-chain-slash::before {
+  content: "\f127"; }
+
+.fa-unlink::before {
+  content: "\f127"; }
+
+.fa-clone::before {
+  content: "\f24d"; }
+
+.fa-person-walking-arrow-loop-left::before {
+  content: "\e551"; }
+
+.fa-arrow-up-z-a::before {
+  content: "\f882"; }
+
+.fa-sort-alpha-up-alt::before {
+  content: "\f882"; }
+
+.fa-fire-flame-curved::before {
+  content: "\f7e4"; }
+
+.fa-fire-alt::before {
+  content: "\f7e4"; }
+
+.fa-tornado::before {
+  content: "\f76f"; }
+
+.fa-file-circle-plus::before {
+  content: "\e494"; }
+
+.fa-book-quran::before {
+  content: "\f687"; }
+
+.fa-quran::before {
+  content: "\f687"; }
+
+.fa-anchor::before {
+  content: "\f13d"; }
+
+.fa-border-all::before {
+  content: "\f84c"; }
+
+.fa-face-angry::before {
+  content: "\f556"; }
+
+.fa-angry::before {
+  content: "\f556"; }
+
+.fa-cookie-bite::before {
+  content: "\f564"; }
+
+.fa-arrow-trend-down::before {
+  content: "\e097"; }
+
+.fa-rss::before {
+  content: "\f09e"; }
+
+.fa-feed::before {
+  content: "\f09e"; }
+
+.fa-draw-polygon::before {
+  content: "\f5ee"; }
+
+.fa-scale-balanced::before {
+  content: "\f24e"; }
+
+.fa-balance-scale::before {
+  content: "\f24e"; }
+
+.fa-gauge-simple-high::before {
+  content: "\f62a"; }
+
+.fa-tachometer::before {
+  content: "\f62a"; }
+
+.fa-tachometer-fast::before {
+  content: "\f62a"; }
+
+.fa-shower::before {
+  content: "\f2cc"; }
+
+.fa-desktop::before {
+  content: "\f390"; }
+
+.fa-desktop-alt::before {
+  content: "\f390"; }
+
+.fa-m::before {
+  content: "\4d"; }
+
+.fa-table-list::before {
+  content: "\f00b"; }
+
+.fa-th-list::before {
+  content: "\f00b"; }
+
+.fa-comment-sms::before {
+  content: "\f7cd"; }
+
+.fa-sms::before {
+  content: "\f7cd"; }
+
+.fa-book::before {
+  content: "\f02d"; }
+
+.fa-user-plus::before {
+  content: "\f234"; }
+
+.fa-check::before {
+  content: "\f00c"; }
+
+.fa-battery-three-quarters::before {
+  content: "\f241"; }
+
+.fa-battery-4::before {
+  content: "\f241"; }
+
+.fa-house-circle-check::before {
+  content: "\e509"; }
+
+.fa-angle-left::before {
+  content: "\f104"; }
+
+.fa-diagram-successor::before {
+  content: "\e47a"; }
+
+.fa-truck-arrow-right::before {
+  content: "\e58b"; }
+
+.fa-arrows-split-up-and-left::before {
+  content: "\e4bc"; }
+
+.fa-hand-fist::before {
+  content: "\f6de"; }
+
+.fa-fist-raised::before {
+  content: "\f6de"; }
+
+.fa-cloud-moon::before {
+  content: "\f6c3"; }
+
+.fa-briefcase::before {
+  content: "\f0b1"; }
+
+.fa-person-falling::before {
+  content: "\e546"; }
+
+.fa-image-portrait::before {
+  content: "\f3e0"; }
+
+.fa-portrait::before {
+  content: "\f3e0"; }
+
+.fa-user-tag::before {
+  content: "\f507"; }
+
+.fa-rug::before {
+  content: "\e569"; }
+
+.fa-earth-europe::before {
+  content: "\f7a2"; }
+
+.fa-globe-europe::before {
+  content: "\f7a2"; }
+
+.fa-cart-flatbed-suitcase::before {
+  content: "\f59d"; }
+
+.fa-luggage-cart::before {
+  content: "\f59d"; }
+
+.fa-rectangle-xmark::before {
+  content: "\f410"; }
+
+.fa-rectangle-times::before {
+  content: "\f410"; }
+
+.fa-times-rectangle::before {
+  content: "\f410"; }
+
+.fa-window-close::before {
+  content: "\f410"; }
+
+.fa-baht-sign::before {
+  content: "\e0ac"; }
+
+.fa-book-open::before {
+  content: "\f518"; }
+
+.fa-book-journal-whills::before {
+  content: "\f66a"; }
+
+.fa-journal-whills::before {
+  content: "\f66a"; }
+
+.fa-handcuffs::before {
+  content: "\e4f8"; }
+
+.fa-triangle-exclamation::before {
+  content: "\f071"; }
+
+.fa-exclamation-triangle::before {
+  content: "\f071"; }
+
+.fa-warning::before {
+  content: "\f071"; }
+
+.fa-database::before {
+  content: "\f1c0"; }
+
+.fa-share::before {
+  content: "\f064"; }
+
+.fa-mail-forward::before {
+  content: "\f064"; }
+
+.fa-bottle-droplet::before {
+  content: "\e4c4"; }
+
+.fa-mask-face::before {
+  content: "\e1d7"; }
+
+.fa-hill-rockslide::before {
+  content: "\e508"; }
+
+.fa-right-left::before {
+  content: "\f362"; }
+
+.fa-exchange-alt::before {
+  content: "\f362"; }
+
+.fa-paper-plane::before {
+  content: "\f1d8"; }
+
+.fa-road-circle-exclamation::before {
+  content: "\e565"; }
+
+.fa-dungeon::before {
+  content: "\f6d9"; }
+
+.fa-align-right::before {
+  content: "\f038"; }
+
+.fa-money-bill-1-wave::before {
+  content: "\f53b"; }
+
+.fa-money-bill-wave-alt::before {
+  content: "\f53b"; }
+
+.fa-life-ring::before {
+  content: "\f1cd"; }
+
+.fa-hands::before {
+  content: "\f2a7"; }
+
+.fa-sign-language::before {
+  content: "\f2a7"; }
+
+.fa-signing::before {
+  content: "\f2a7"; }
+
+.fa-calendar-day::before {
+  content: "\f783"; }
+
+.fa-water-ladder::before {
+  content: "\f5c5"; }
+
+.fa-ladder-water::before {
+  content: "\f5c5"; }
+
+.fa-swimming-pool::before {
+  content: "\f5c5"; }
+
+.fa-arrows-up-down::before {
+  content: "\f07d"; }
+
+.fa-arrows-v::before {
+  content: "\f07d"; }
+
+.fa-face-grimace::before {
+  content: "\f57f"; }
+
+.fa-grimace::before {
+  content: "\f57f"; }
+
+.fa-wheelchair-move::before {
+  content: "\e2ce"; }
+
+.fa-wheelchair-alt::before {
+  content: "\e2ce"; }
+
+.fa-turn-down::before {
+  content: "\f3be"; }
+
+.fa-level-down-alt::before {
+  content: "\f3be"; }
+
+.fa-person-walking-arrow-right::before {
+  content: "\e552"; }
+
+.fa-square-envelope::before {
+  content: "\f199"; }
+
+.fa-envelope-square::before {
+  content: "\f199"; }
+
+.fa-dice::before {
+  content: "\f522"; }
+
+.fa-bowling-ball::before {
+  content: "\f436"; }
+
+.fa-brain::before {
+  content: "\f5dc"; }
+
+.fa-bandage::before {
+  content: "\f462"; }
+
+.fa-band-aid::before {
+  content: "\f462"; }
+
+.fa-calendar-minus::before {
+  content: "\f272"; }
+
+.fa-circle-xmark::before {
+  content: "\f057"; }
+
+.fa-times-circle::before {
+  content: "\f057"; }
+
+.fa-xmark-circle::before {
+  content: "\f057"; }
+
+.fa-gifts::before {
+  content: "\f79c"; }
+
+.fa-hotel::before {
+  content: "\f594"; }
+
+.fa-earth-asia::before {
+  content: "\f57e"; }
+
+.fa-globe-asia::before {
+  content: "\f57e"; }
+
+.fa-id-card-clip::before {
+  content: "\f47f"; }
+
+.fa-id-card-alt::before {
+  content: "\f47f"; }
+
+.fa-magnifying-glass-plus::before {
+  content: "\f00e"; }
+
+.fa-search-plus::before {
+  content: "\f00e"; }
+
+.fa-thumbs-up::before {
+  content: "\f164"; }
+
+.fa-user-clock::before {
+  content: "\f4fd"; }
+
+.fa-hand-dots::before {
+  content: "\f461"; }
+
+.fa-allergies::before {
+  content: "\f461"; }
+
+.fa-file-invoice::before {
+  content: "\f570"; }
+
+.fa-window-minimize::before {
+  content: "\f2d1"; }
+
+.fa-mug-saucer::before {
+  content: "\f0f4"; }
+
+.fa-coffee::before {
+  content: "\f0f4"; }
+
+.fa-brush::before {
+  content: "\f55d"; }
+
+.fa-mask::before {
+  content: "\f6fa"; }
+
+.fa-magnifying-glass-minus::before {
+  content: "\f010"; }
+
+.fa-search-minus::before {
+  content: "\f010"; }
+
+.fa-ruler-vertical::before {
+  content: "\f548"; }
+
+.fa-user-large::before {
+  content: "\f406"; }
+
+.fa-user-alt::before {
+  content: "\f406"; }
+
+.fa-train-tram::before {
+  content: "\e5b4"; }
+
+.fa-user-nurse::before {
+  content: "\f82f"; }
+
+.fa-syringe::before {
+  content: "\f48e"; }
+
+.fa-cloud-sun::before {
+  content: "\f6c4"; }
+
+.fa-stopwatch-20::before {
+  content: "\e06f"; }
+
+.fa-square-full::before {
+  content: "\f45c"; }
+
+.fa-magnet::before {
+  content: "\f076"; }
+
+.fa-jar::before {
+  content: "\e516"; }
+
+.fa-note-sticky::before {
+  content: "\f249"; }
+
+.fa-sticky-note::before {
+  content: "\f249"; }
+
+.fa-bug-slash::before {
+  content: "\e490"; }
+
+.fa-arrow-up-from-water-pump::before {
+  content: "\e4b6"; }
+
+.fa-bone::before {
+  content: "\f5d7"; }
+
+.fa-user-injured::before {
+  content: "\f728"; }
+
+.fa-face-sad-tear::before {
+  content: "\f5b4"; }
+
+.fa-sad-tear::before {
+  content: "\f5b4"; }
+
+.fa-plane::before {
+  content: "\f072"; }
+
+.fa-tent-arrows-down::before {
+  content: "\e581"; }
+
+.fa-exclamation::before {
+  content: "\21"; }
+
+.fa-arrows-spin::before {
+  content: "\e4bb"; }
+
+.fa-print::before {
+  content: "\f02f"; }
+
+.fa-turkish-lira-sign::before {
+  content: "\e2bb"; }
+
+.fa-try::before {
+  content: "\e2bb"; }
+
+.fa-turkish-lira::before {
+  content: "\e2bb"; }
+
+.fa-dollar-sign::before {
+  content: "\24"; }
+
+.fa-dollar::before {
+  content: "\24"; }
+
+.fa-usd::before {
+  content: "\24"; }
+
+.fa-x::before {
+  content: "\58"; }
+
+.fa-magnifying-glass-dollar::before {
+  content: "\f688"; }
+
+.fa-search-dollar::before {
+  content: "\f688"; }
+
+.fa-users-gear::before {
+  content: "\f509"; }
+
+.fa-users-cog::before {
+  content: "\f509"; }
+
+.fa-person-military-pointing::before {
+  content: "\e54a"; }
+
+.fa-building-columns::before {
+  content: "\f19c"; }
+
+.fa-bank::before {
+  content: "\f19c"; }
+
+.fa-institution::before {
+  content: "\f19c"; }
+
+.fa-museum::before {
+  content: "\f19c"; }
+
+.fa-university::before {
+  content: "\f19c"; }
+
+.fa-umbrella::before {
+  content: "\f0e9"; }
+
+.fa-trowel::before {
+  content: "\e589"; }
+
+.fa-d::before {
+  content: "\44"; }
+
+.fa-stapler::before {
+  content: "\e5af"; }
+
+.fa-masks-theater::before {
+  content: "\f630"; }
+
+.fa-theater-masks::before {
+  content: "\f630"; }
+
+.fa-kip-sign::before {
+  content: "\e1c4"; }
+
+.fa-hand-point-left::before {
+  content: "\f0a5"; }
+
+.fa-handshake-simple::before {
+  content: "\f4c6"; }
+
+.fa-handshake-alt::before {
+  content: "\f4c6"; }
+
+.fa-jet-fighter::before {
+  content: "\f0fb"; }
+
+.fa-fighter-jet::before {
+  content: "\f0fb"; }
+
+.fa-square-share-nodes::before {
+  content: "\f1e1"; }
+
+.fa-share-alt-square::before {
+  content: "\f1e1"; }
+
+.fa-barcode::before {
+  content: "\f02a"; }
+
+.fa-plus-minus::before {
+  content: "\e43c"; }
+
+.fa-video::before {
+  content: "\f03d"; }
+
+.fa-video-camera::before {
+  content: "\f03d"; }
+
+.fa-graduation-cap::before {
+  content: "\f19d"; }
+
+.fa-mortar-board::before {
+  content: "\f19d"; }
+
+.fa-hand-holding-medical::before {
+  content: "\e05c"; }
+
+.fa-person-circle-check::before {
+  content: "\e53e"; }
+
+.fa-turn-up::before {
+  content: "\f3bf"; }
+
+.fa-level-up-alt::before {
+  content: "\f3bf"; }
+
+.sr-only,
+.fa-sr-only {
+  position: absolute;
+  width: 1px;
+  height: 1px;
+  padding: 0;
+  margin: -1px;
+  overflow: hidden;
+  clip: rect(0, 0, 0, 0);
+  white-space: nowrap;
+  border-width: 0; }
+
+.sr-only-focusable:not(:focus),
+.fa-sr-only-focusable:not(:focus) {
+  position: absolute;
+  width: 1px;
+  height: 1px;
+  padding: 0;
+  margin: -1px;
+  overflow: hidden;
+  clip: rect(0, 0, 0, 0);
+  white-space: nowrap;
+  border-width: 0; }
+:root, :host {
+  --fa-style-family-brands: 'Font Awesome 6 Brands';
+  --fa-font-brands: normal 400 1em/1 'Font Awesome 6 Brands'; }
+
+@font-face {
+  font-family: 'Font Awesome 6 Brands';
+  font-style: normal;
+  font-weight: 400;
+  font-display: block;
+  src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); }
+
+.fab,
+.fa-brands {
+  font-weight: 400; }
+
+.fa-monero:before {
+  content: "\f3d0"; }
+
+.fa-hooli:before {
+  content: "\f427"; }
+
+.fa-yelp:before {
+  content: "\f1e9"; }
+
+.fa-cc-visa:before {
+  content: "\f1f0"; }
+
+.fa-lastfm:before {
+  content: "\f202"; }
+
+.fa-shopware:before {
+  content: "\f5b5"; }
+
+.fa-creative-commons-nc:before {
+  content: "\f4e8"; }
+
+.fa-aws:before {
+  content: "\f375"; }
+
+.fa-redhat:before {
+  content: "\f7bc"; }
+
+.fa-yoast:before {
+  content: "\f2b1"; }
+
+.fa-cloudflare:before {
+  content: "\e07d"; }
+
+.fa-ups:before {
+  content: "\f7e0"; }
+
+.fa-pixiv:before {
+  content: "\e640"; }
+
+.fa-wpexplorer:before {
+  content: "\f2de"; }
+
+.fa-dyalog:before {
+  content: "\f399"; }
+
+.fa-bity:before {
+  content: "\f37a"; }
+
+.fa-stackpath:before {
+  content: "\f842"; }
+
+.fa-buysellads:before {
+  content: "\f20d"; }
+
+.fa-first-order:before {
+  content: "\f2b0"; }
+
+.fa-modx:before {
+  content: "\f285"; }
+
+.fa-guilded:before {
+  content: "\e07e"; }
+
+.fa-vnv:before {
+  content: "\f40b"; }
+
+.fa-square-js:before {
+  content: "\f3b9"; }
+
+.fa-js-square:before {
+  content: "\f3b9"; }
+
+.fa-microsoft:before {
+  content: "\f3ca"; }
+
+.fa-qq:before {
+  content: "\f1d6"; }
+
+.fa-orcid:before {
+  content: "\f8d2"; }
+
+.fa-java:before {
+  content: "\f4e4"; }
+
+.fa-invision:before {
+  content: "\f7b0"; }
+
+.fa-creative-commons-pd-alt:before {
+  content: "\f4ed"; }
+
+.fa-centercode:before {
+  content: "\f380"; }
+
+.fa-glide-g:before {
+  content: "\f2a6"; }
+
+.fa-drupal:before {
+  content: "\f1a9"; }
+
+.fa-jxl:before {
+  content: "\e67b"; }
+
+.fa-hire-a-helper:before {
+  content: "\f3b0"; }
+
+.fa-creative-commons-by:before {
+  content: "\f4e7"; }
+
+.fa-unity:before {
+  content: "\e049"; }
+
+.fa-whmcs:before {
+  content: "\f40d"; }
+
+.fa-rocketchat:before {
+  content: "\f3e8"; }
+
+.fa-vk:before {
+  content: "\f189"; }
+
+.fa-untappd:before {
+  content: "\f405"; }
+
+.fa-mailchimp:before {
+  content: "\f59e"; }
+
+.fa-css3-alt:before {
+  content: "\f38b"; }
+
+.fa-square-reddit:before {
+  content: "\f1a2"; }
+
+.fa-reddit-square:before {
+  content: "\f1a2"; }
+
+.fa-vimeo-v:before {
+  content: "\f27d"; }
+
+.fa-contao:before {
+  content: "\f26d"; }
+
+.fa-square-font-awesome:before {
+  content: "\e5ad"; }
+
+.fa-deskpro:before {
+  content: "\f38f"; }
+
+.fa-brave:before {
+  content: "\e63c"; }
+
+.fa-sistrix:before {
+  content: "\f3ee"; }
+
+.fa-square-instagram:before {
+  content: "\e055"; }
+
+.fa-instagram-square:before {
+  content: "\e055"; }
+
+.fa-battle-net:before {
+  content: "\f835"; }
+
+.fa-the-red-yeti:before {
+  content: "\f69d"; }
+
+.fa-square-hacker-news:before {
+  content: "\f3af"; }
+
+.fa-hacker-news-square:before {
+  content: "\f3af"; }
+
+.fa-edge:before {
+  content: "\f282"; }
+
+.fa-threads:before {
+  content: "\e618"; }
+
+.fa-napster:before {
+  content: "\f3d2"; }
+
+.fa-square-snapchat:before {
+  content: "\f2ad"; }
+
+.fa-snapchat-square:before {
+  content: "\f2ad"; }
+
+.fa-google-plus-g:before {
+  content: "\f0d5"; }
+
+.fa-artstation:before {
+  content: "\f77a"; }
+
+.fa-markdown:before {
+  content: "\f60f"; }
+
+.fa-sourcetree:before {
+  content: "\f7d3"; }
+
+.fa-google-plus:before {
+  content: "\f2b3"; }
+
+.fa-diaspora:before {
+  content: "\f791"; }
+
+.fa-foursquare:before {
+  content: "\f180"; }
+
+.fa-stack-overflow:before {
+  content: "\f16c"; }
+
+.fa-github-alt:before {
+  content: "\f113"; }
+
+.fa-phoenix-squadron:before {
+  content: "\f511"; }
+
+.fa-pagelines:before {
+  content: "\f18c"; }
+
+.fa-algolia:before {
+  content: "\f36c"; }
+
+.fa-red-river:before {
+  content: "\f3e3"; }
+
+.fa-creative-commons-sa:before {
+  content: "\f4ef"; }
+
+.fa-safari:before {
+  content: "\f267"; }
+
+.fa-google:before {
+  content: "\f1a0"; }
+
+.fa-square-font-awesome-stroke:before {
+  content: "\f35c"; }
+
+.fa-font-awesome-alt:before {
+  content: "\f35c"; }
+
+.fa-atlassian:before {
+  content: "\f77b"; }
+
+.fa-linkedin-in:before {
+  content: "\f0e1"; }
+
+.fa-digital-ocean:before {
+  content: "\f391"; }
+
+.fa-nimblr:before {
+  content: "\f5a8"; }
+
+.fa-chromecast:before {
+  content: "\f838"; }
+
+.fa-evernote:before {
+  content: "\f839"; }
+
+.fa-hacker-news:before {
+  content: "\f1d4"; }
+
+.fa-creative-commons-sampling:before {
+  content: "\f4f0"; }
+
+.fa-adversal:before {
+  content: "\f36a"; }
+
+.fa-creative-commons:before {
+  content: "\f25e"; }
+
+.fa-watchman-monitoring:before {
+  content: "\e087"; }
+
+.fa-fonticons:before {
+  content: "\f280"; }
+
+.fa-weixin:before {
+  content: "\f1d7"; }
+
+.fa-shirtsinbulk:before {
+  content: "\f214"; }
+
+.fa-codepen:before {
+  content: "\f1cb"; }
+
+.fa-git-alt:before {
+  content: "\f841"; }
+
+.fa-lyft:before {
+  content: "\f3c3"; }
+
+.fa-rev:before {
+  content: "\f5b2"; }
+
+.fa-windows:before {
+  content: "\f17a"; }
+
+.fa-wizards-of-the-coast:before {
+  content: "\f730"; }
+
+.fa-square-viadeo:before {
+  content: "\f2aa"; }
+
+.fa-viadeo-square:before {
+  content: "\f2aa"; }
+
+.fa-meetup:before {
+  content: "\f2e0"; }
+
+.fa-centos:before {
+  content: "\f789"; }
+
+.fa-adn:before {
+  content: "\f170"; }
+
+.fa-cloudsmith:before {
+  content: "\f384"; }
+
+.fa-opensuse:before {
+  content: "\e62b"; }
+
+.fa-pied-piper-alt:before {
+  content: "\f1a8"; }
+
+.fa-square-dribbble:before {
+  content: "\f397"; }
+
+.fa-dribbble-square:before {
+  content: "\f397"; }
+
+.fa-codiepie:before {
+  content: "\f284"; }
+
+.fa-node:before {
+  content: "\f419"; }
+
+.fa-mix:before {
+  content: "\f3cb"; }
+
+.fa-steam:before {
+  content: "\f1b6"; }
+
+.fa-cc-apple-pay:before {
+  content: "\f416"; }
+
+.fa-scribd:before {
+  content: "\f28a"; }
+
+.fa-debian:before {
+  content: "\e60b"; }
+
+.fa-openid:before {
+  content: "\f19b"; }
+
+.fa-instalod:before {
+  content: "\e081"; }
+
+.fa-expeditedssl:before {
+  content: "\f23e"; }
+
+.fa-sellcast:before {
+  content: "\f2da"; }
+
+.fa-square-twitter:before {
+  content: "\f081"; }
+
+.fa-twitter-square:before {
+  content: "\f081"; }
+
+.fa-r-project:before {
+  content: "\f4f7"; }
+
+.fa-delicious:before {
+  content: "\f1a5"; }
+
+.fa-freebsd:before {
+  content: "\f3a4"; }
+
+.fa-vuejs:before {
+  content: "\f41f"; }
+
+.fa-accusoft:before {
+  content: "\f369"; }
+
+.fa-ioxhost:before {
+  content: "\f208"; }
+
+.fa-fonticons-fi:before {
+  content: "\f3a2"; }
+
+.fa-app-store:before {
+  content: "\f36f"; }
+
+.fa-cc-mastercard:before {
+  content: "\f1f1"; }
+
+.fa-itunes-note:before {
+  content: "\f3b5"; }
+
+.fa-golang:before {
+  content: "\e40f"; }
+
+.fa-kickstarter:before {
+  content: "\f3bb"; }
+
+.fa-square-kickstarter:before {
+  content: "\f3bb"; }
+
+.fa-grav:before {
+  content: "\f2d6"; }
+
+.fa-weibo:before {
+  content: "\f18a"; }
+
+.fa-uncharted:before {
+  content: "\e084"; }
+
+.fa-firstdraft:before {
+  content: "\f3a1"; }
+
+.fa-square-youtube:before {
+  content: "\f431"; }
+
+.fa-youtube-square:before {
+  content: "\f431"; }
+
+.fa-wikipedia-w:before {
+  content: "\f266"; }
+
+.fa-wpressr:before {
+  content: "\f3e4"; }
+
+.fa-rendact:before {
+  content: "\f3e4"; }
+
+.fa-angellist:before {
+  content: "\f209"; }
+
+.fa-galactic-republic:before {
+  content: "\f50c"; }
+
+.fa-nfc-directional:before {
+  content: "\e530"; }
+
+.fa-skype:before {
+  content: "\f17e"; }
+
+.fa-joget:before {
+  content: "\f3b7"; }
+
+.fa-fedora:before {
+  content: "\f798"; }
+
+.fa-stripe-s:before {
+  content: "\f42a"; }
+
+.fa-meta:before {
+  content: "\e49b"; }
+
+.fa-laravel:before {
+  content: "\f3bd"; }
+
+.fa-hotjar:before {
+  content: "\f3b1"; }
+
+.fa-bluetooth-b:before {
+  content: "\f294"; }
+
+.fa-square-letterboxd:before {
+  content: "\e62e"; }
+
+.fa-sticker-mule:before {
+  content: "\f3f7"; }
+
+.fa-creative-commons-zero:before {
+  content: "\f4f3"; }
+
+.fa-hips:before {
+  content: "\f452"; }
+
+.fa-behance:before {
+  content: "\f1b4"; }
+
+.fa-reddit:before {
+  content: "\f1a1"; }
+
+.fa-discord:before {
+  content: "\f392"; }
+
+.fa-chrome:before {
+  content: "\f268"; }
+
+.fa-app-store-ios:before {
+  content: "\f370"; }
+
+.fa-cc-discover:before {
+  content: "\f1f2"; }
+
+.fa-wpbeginner:before {
+  content: "\f297"; }
+
+.fa-confluence:before {
+  content: "\f78d"; }
+
+.fa-shoelace:before {
+  content: "\e60c"; }
+
+.fa-mdb:before {
+  content: "\f8ca"; }
+
+.fa-dochub:before {
+  content: "\f394"; }
+
+.fa-accessible-icon:before {
+  content: "\f368"; }
+
+.fa-ebay:before {
+  content: "\f4f4"; }
+
+.fa-amazon:before {
+  content: "\f270"; }
+
+.fa-unsplash:before {
+  content: "\e07c"; }
+
+.fa-yarn:before {
+  content: "\f7e3"; }
+
+.fa-square-steam:before {
+  content: "\f1b7"; }
+
+.fa-steam-square:before {
+  content: "\f1b7"; }
+
+.fa-500px:before {
+  content: "\f26e"; }
+
+.fa-square-vimeo:before {
+  content: "\f194"; }
+
+.fa-vimeo-square:before {
+  content: "\f194"; }
+
+.fa-asymmetrik:before {
+  content: "\f372"; }
+
+.fa-font-awesome:before {
+  content: "\f2b4"; }
+
+.fa-font-awesome-flag:before {
+  content: "\f2b4"; }
+
+.fa-font-awesome-logo-full:before {
+  content: "\f2b4"; }
+
+.fa-gratipay:before {
+  content: "\f184"; }
+
+.fa-apple:before {
+  content: "\f179"; }
+
+.fa-hive:before {
+  content: "\e07f"; }
+
+.fa-gitkraken:before {
+  content: "\f3a6"; }
+
+.fa-keybase:before {
+  content: "\f4f5"; }
+
+.fa-apple-pay:before {
+  content: "\f415"; }
+
+.fa-padlet:before {
+  content: "\e4a0"; }
+
+.fa-amazon-pay:before {
+  content: "\f42c"; }
+
+.fa-square-github:before {
+  content: "\f092"; }
+
+.fa-github-square:before {
+  content: "\f092"; }
+
+.fa-stumbleupon:before {
+  content: "\f1a4"; }
+
+.fa-fedex:before {
+  content: "\f797"; }
+
+.fa-phoenix-framework:before {
+  content: "\f3dc"; }
+
+.fa-shopify:before {
+  content: "\e057"; }
+
+.fa-neos:before {
+  content: "\f612"; }
+
+.fa-square-threads:before {
+  content: "\e619"; }
+
+.fa-hackerrank:before {
+  content: "\f5f7"; }
+
+.fa-researchgate:before {
+  content: "\f4f8"; }
+
+.fa-swift:before {
+  content: "\f8e1"; }
+
+.fa-angular:before {
+  content: "\f420"; }
+
+.fa-speakap:before {
+  content: "\f3f3"; }
+
+.fa-angrycreative:before {
+  content: "\f36e"; }
+
+.fa-y-combinator:before {
+  content: "\f23b"; }
+
+.fa-empire:before {
+  content: "\f1d1"; }
+
+.fa-envira:before {
+  content: "\f299"; }
+
+.fa-google-scholar:before {
+  content: "\e63b"; }
+
+.fa-square-gitlab:before {
+  content: "\e5ae"; }
+
+.fa-gitlab-square:before {
+  content: "\e5ae"; }
+
+.fa-studiovinari:before {
+  content: "\f3f8"; }
+
+.fa-pied-piper:before {
+  content: "\f2ae"; }
+
+.fa-wordpress:before {
+  content: "\f19a"; }
+
+.fa-product-hunt:before {
+  content: "\f288"; }
+
+.fa-firefox:before {
+  content: "\f269"; }
+
+.fa-linode:before {
+  content: "\f2b8"; }
+
+.fa-goodreads:before {
+  content: "\f3a8"; }
+
+.fa-square-odnoklassniki:before {
+  content: "\f264"; }
+
+.fa-odnoklassniki-square:before {
+  content: "\f264"; }
+
+.fa-jsfiddle:before {
+  content: "\f1cc"; }
+
+.fa-sith:before {
+  content: "\f512"; }
+
+.fa-themeisle:before {
+  content: "\f2b2"; }
+
+.fa-page4:before {
+  content: "\f3d7"; }
+
+.fa-hashnode:before {
+  content: "\e499"; }
+
+.fa-react:before {
+  content: "\f41b"; }
+
+.fa-cc-paypal:before {
+  content: "\f1f4"; }
+
+.fa-squarespace:before {
+  content: "\f5be"; }
+
+.fa-cc-stripe:before {
+  content: "\f1f5"; }
+
+.fa-creative-commons-share:before {
+  content: "\f4f2"; }
+
+.fa-bitcoin:before {
+  content: "\f379"; }
+
+.fa-keycdn:before {
+  content: "\f3ba"; }
+
+.fa-opera:before {
+  content: "\f26a"; }
+
+.fa-itch-io:before {
+  content: "\f83a"; }
+
+.fa-umbraco:before {
+  content: "\f8e8"; }
+
+.fa-galactic-senate:before {
+  content: "\f50d"; }
+
+.fa-ubuntu:before {
+  content: "\f7df"; }
+
+.fa-draft2digital:before {
+  content: "\f396"; }
+
+.fa-stripe:before {
+  content: "\f429"; }
+
+.fa-houzz:before {
+  content: "\f27c"; }
+
+.fa-gg:before {
+  content: "\f260"; }
+
+.fa-dhl:before {
+  content: "\f790"; }
+
+.fa-square-pinterest:before {
+  content: "\f0d3"; }
+
+.fa-pinterest-square:before {
+  content: "\f0d3"; }
+
+.fa-xing:before {
+  content: "\f168"; }
+
+.fa-blackberry:before {
+  content: "\f37b"; }
+
+.fa-creative-commons-pd:before {
+  content: "\f4ec"; }
+
+.fa-playstation:before {
+  content: "\f3df"; }
+
+.fa-quinscape:before {
+  content: "\f459"; }
+
+.fa-less:before {
+  content: "\f41d"; }
+
+.fa-blogger-b:before {
+  content: "\f37d"; }
+
+.fa-opencart:before {
+  content: "\f23d"; }
+
+.fa-vine:before {
+  content: "\f1ca"; }
+
+.fa-signal-messenger:before {
+  content: "\e663"; }
+
+.fa-paypal:before {
+  content: "\f1ed"; }
+
+.fa-gitlab:before {
+  content: "\f296"; }
+
+.fa-typo3:before {
+  content: "\f42b"; }
+
+.fa-reddit-alien:before {
+  content: "\f281"; }
+
+.fa-yahoo:before {
+  content: "\f19e"; }
+
+.fa-dailymotion:before {
+  content: "\e052"; }
+
+.fa-affiliatetheme:before {
+  content: "\f36b"; }
+
+.fa-pied-piper-pp:before {
+  content: "\f1a7"; }
+
+.fa-bootstrap:before {
+  content: "\f836"; }
+
+.fa-odnoklassniki:before {
+  content: "\f263"; }
+
+.fa-nfc-symbol:before {
+  content: "\e531"; }
+
+.fa-mintbit:before {
+  content: "\e62f"; }
+
+.fa-ethereum:before {
+  content: "\f42e"; }
+
+.fa-speaker-deck:before {
+  content: "\f83c"; }
+
+.fa-creative-commons-nc-eu:before {
+  content: "\f4e9"; }
+
+.fa-patreon:before {
+  content: "\f3d9"; }
+
+.fa-avianex:before {
+  content: "\f374"; }
+
+.fa-ello:before {
+  content: "\f5f1"; }
+
+.fa-gofore:before {
+  content: "\f3a7"; }
+
+.fa-bimobject:before {
+  content: "\f378"; }
+
+.fa-brave-reverse:before {
+  content: "\e63d"; }
+
+.fa-facebook-f:before {
+  content: "\f39e"; }
+
+.fa-square-google-plus:before {
+  content: "\f0d4"; }
+
+.fa-google-plus-square:before {
+  content: "\f0d4"; }
+
+.fa-web-awesome:before {
+  content: "\e682"; }
+
+.fa-mandalorian:before {
+  content: "\f50f"; }
+
+.fa-first-order-alt:before {
+  content: "\f50a"; }
+
+.fa-osi:before {
+  content: "\f41a"; }
+
+.fa-google-wallet:before {
+  content: "\f1ee"; }
+
+.fa-d-and-d-beyond:before {
+  content: "\f6ca"; }
+
+.fa-periscope:before {
+  content: "\f3da"; }
+
+.fa-fulcrum:before {
+  content: "\f50b"; }
+
+.fa-cloudscale:before {
+  content: "\f383"; }
+
+.fa-forumbee:before {
+  content: "\f211"; }
+
+.fa-mizuni:before {
+  content: "\f3cc"; }
+
+.fa-schlix:before {
+  content: "\f3ea"; }
+
+.fa-square-xing:before {
+  content: "\f169"; }
+
+.fa-xing-square:before {
+  content: "\f169"; }
+
+.fa-bandcamp:before {
+  content: "\f2d5"; }
+
+.fa-wpforms:before {
+  content: "\f298"; }
+
+.fa-cloudversify:before {
+  content: "\f385"; }
+
+.fa-usps:before {
+  content: "\f7e1"; }
+
+.fa-megaport:before {
+  content: "\f5a3"; }
+
+.fa-magento:before {
+  content: "\f3c4"; }
+
+.fa-spotify:before {
+  content: "\f1bc"; }
+
+.fa-optin-monster:before {
+  content: "\f23c"; }
+
+.fa-fly:before {
+  content: "\f417"; }
+
+.fa-aviato:before {
+  content: "\f421"; }
+
+.fa-itunes:before {
+  content: "\f3b4"; }
+
+.fa-cuttlefish:before {
+  content: "\f38c"; }
+
+.fa-blogger:before {
+  content: "\f37c"; }
+
+.fa-flickr:before {
+  content: "\f16e"; }
+
+.fa-viber:before {
+  content: "\f409"; }
+
+.fa-soundcloud:before {
+  content: "\f1be"; }
+
+.fa-digg:before {
+  content: "\f1a6"; }
+
+.fa-tencent-weibo:before {
+  content: "\f1d5"; }
+
+.fa-letterboxd:before {
+  content: "\e62d"; }
+
+.fa-symfony:before {
+  content: "\f83d"; }
+
+.fa-maxcdn:before {
+  content: "\f136"; }
+
+.fa-etsy:before {
+  content: "\f2d7"; }
+
+.fa-facebook-messenger:before {
+  content: "\f39f"; }
+
+.fa-audible:before {
+  content: "\f373"; }
+
+.fa-think-peaks:before {
+  content: "\f731"; }
+
+.fa-bilibili:before {
+  content: "\e3d9"; }
+
+.fa-erlang:before {
+  content: "\f39d"; }
+
+.fa-x-twitter:before {
+  content: "\e61b"; }
+
+.fa-cotton-bureau:before {
+  content: "\f89e"; }
+
+.fa-dashcube:before {
+  content: "\f210"; }
+
+.fa-42-group:before {
+  content: "\e080"; }
+
+.fa-innosoft:before {
+  content: "\e080"; }
+
+.fa-stack-exchange:before {
+  content: "\f18d"; }
+
+.fa-elementor:before {
+  content: "\f430"; }
+
+.fa-square-pied-piper:before {
+  content: "\e01e"; }
+
+.fa-pied-piper-square:before {
+  content: "\e01e"; }
+
+.fa-creative-commons-nd:before {
+  content: "\f4eb"; }
+
+.fa-palfed:before {
+  content: "\f3d8"; }
+
+.fa-superpowers:before {
+  content: "\f2dd"; }
+
+.fa-resolving:before {
+  content: "\f3e7"; }
+
+.fa-xbox:before {
+  content: "\f412"; }
+
+.fa-square-web-awesome-stroke:before {
+  content: "\e684"; }
+
+.fa-searchengin:before {
+  content: "\f3eb"; }
+
+.fa-tiktok:before {
+  content: "\e07b"; }
+
+.fa-square-facebook:before {
+  content: "\f082"; }
+
+.fa-facebook-square:before {
+  content: "\f082"; }
+
+.fa-renren:before {
+  content: "\f18b"; }
+
+.fa-linux:before {
+  content: "\f17c"; }
+
+.fa-glide:before {
+  content: "\f2a5"; }
+
+.fa-linkedin:before {
+  content: "\f08c"; }
+
+.fa-hubspot:before {
+  content: "\f3b2"; }
+
+.fa-deploydog:before {
+  content: "\f38e"; }
+
+.fa-twitch:before {
+  content: "\f1e8"; }
+
+.fa-ravelry:before {
+  content: "\f2d9"; }
+
+.fa-mixer:before {
+  content: "\e056"; }
+
+.fa-square-lastfm:before {
+  content: "\f203"; }
+
+.fa-lastfm-square:before {
+  content: "\f203"; }
+
+.fa-vimeo:before {
+  content: "\f40a"; }
+
+.fa-mendeley:before {
+  content: "\f7b3"; }
+
+.fa-uniregistry:before {
+  content: "\f404"; }
+
+.fa-figma:before {
+  content: "\f799"; }
+
+.fa-creative-commons-remix:before {
+  content: "\f4ee"; }
+
+.fa-cc-amazon-pay:before {
+  content: "\f42d"; }
+
+.fa-dropbox:before {
+  content: "\f16b"; }
+
+.fa-instagram:before {
+  content: "\f16d"; }
+
+.fa-cmplid:before {
+  content: "\e360"; }
+
+.fa-upwork:before {
+  content: "\e641"; }
+
+.fa-facebook:before {
+  content: "\f09a"; }
+
+.fa-gripfire:before {
+  content: "\f3ac"; }
+
+.fa-jedi-order:before {
+  content: "\f50e"; }
+
+.fa-uikit:before {
+  content: "\f403"; }
+
+.fa-fort-awesome-alt:before {
+  content: "\f3a3"; }
+
+.fa-phabricator:before {
+  content: "\f3db"; }
+
+.fa-ussunnah:before {
+  content: "\f407"; }
+
+.fa-earlybirds:before {
+  content: "\f39a"; }
+
+.fa-trade-federation:before {
+  content: "\f513"; }
+
+.fa-autoprefixer:before {
+  content: "\f41c"; }
+
+.fa-whatsapp:before {
+  content: "\f232"; }
+
+.fa-square-upwork:before {
+  content: "\e67c"; }
+
+.fa-slideshare:before {
+  content: "\f1e7"; }
+
+.fa-google-play:before {
+  content: "\f3ab"; }
+
+.fa-viadeo:before {
+  content: "\f2a9"; }
+
+.fa-line:before {
+  content: "\f3c0"; }
+
+.fa-google-drive:before {
+  content: "\f3aa"; }
+
+.fa-servicestack:before {
+  content: "\f3ec"; }
+
+.fa-simplybuilt:before {
+  content: "\f215"; }
+
+.fa-bitbucket:before {
+  content: "\f171"; }
+
+.fa-imdb:before {
+  content: "\f2d8"; }
+
+.fa-deezer:before {
+  content: "\e077"; }
+
+.fa-raspberry-pi:before {
+  content: "\f7bb"; }
+
+.fa-jira:before {
+  content: "\f7b1"; }
+
+.fa-docker:before {
+  content: "\f395"; }
+
+.fa-screenpal:before {
+  content: "\e570"; }
+
+.fa-bluetooth:before {
+  content: "\f293"; }
+
+.fa-gitter:before {
+  content: "\f426"; }
+
+.fa-d-and-d:before {
+  content: "\f38d"; }
+
+.fa-microblog:before {
+  content: "\e01a"; }
+
+.fa-cc-diners-club:before {
+  content: "\f24c"; }
+
+.fa-gg-circle:before {
+  content: "\f261"; }
+
+.fa-pied-piper-hat:before {
+  content: "\f4e5"; }
+
+.fa-kickstarter-k:before {
+  content: "\f3bc"; }
+
+.fa-yandex:before {
+  content: "\f413"; }
+
+.fa-readme:before {
+  content: "\f4d5"; }
+
+.fa-html5:before {
+  content: "\f13b"; }
+
+.fa-sellsy:before {
+  content: "\f213"; }
+
+.fa-square-web-awesome:before {
+  content: "\e683"; }
+
+.fa-sass:before {
+  content: "\f41e"; }
+
+.fa-wirsindhandwerk:before {
+  content: "\e2d0"; }
+
+.fa-wsh:before {
+  content: "\e2d0"; }
+
+.fa-buromobelexperte:before {
+  content: "\f37f"; }
+
+.fa-salesforce:before {
+  content: "\f83b"; }
+
+.fa-octopus-deploy:before {
+  content: "\e082"; }
+
+.fa-medapps:before {
+  content: "\f3c6"; }
+
+.fa-ns8:before {
+  content: "\f3d5"; }
+
+.fa-pinterest-p:before {
+  content: "\f231"; }
+
+.fa-apper:before {
+  content: "\f371"; }
+
+.fa-fort-awesome:before {
+  content: "\f286"; }
+
+.fa-waze:before {
+  content: "\f83f"; }
+
+.fa-bluesky:before {
+  content: "\e671"; }
+
+.fa-cc-jcb:before {
+  content: "\f24b"; }
+
+.fa-snapchat:before {
+  content: "\f2ab"; }
+
+.fa-snapchat-ghost:before {
+  content: "\f2ab"; }
+
+.fa-fantasy-flight-games:before {
+  content: "\f6dc"; }
+
+.fa-rust:before {
+  content: "\e07a"; }
+
+.fa-wix:before {
+  content: "\f5cf"; }
+
+.fa-square-behance:before {
+  content: "\f1b5"; }
+
+.fa-behance-square:before {
+  content: "\f1b5"; }
+
+.fa-supple:before {
+  content: "\f3f9"; }
+
+.fa-webflow:before {
+  content: "\e65c"; }
+
+.fa-rebel:before {
+  content: "\f1d0"; }
+
+.fa-css3:before {
+  content: "\f13c"; }
+
+.fa-staylinked:before {
+  content: "\f3f5"; }
+
+.fa-kaggle:before {
+  content: "\f5fa"; }
+
+.fa-space-awesome:before {
+  content: "\e5ac"; }
+
+.fa-deviantart:before {
+  content: "\f1bd"; }
+
+.fa-cpanel:before {
+  content: "\f388"; }
+
+.fa-goodreads-g:before {
+  content: "\f3a9"; }
+
+.fa-square-git:before {
+  content: "\f1d2"; }
+
+.fa-git-square:before {
+  content: "\f1d2"; }
+
+.fa-square-tumblr:before {
+  content: "\f174"; }
+
+.fa-tumblr-square:before {
+  content: "\f174"; }
+
+.fa-trello:before {
+  content: "\f181"; }
+
+.fa-creative-commons-nc-jp:before {
+  content: "\f4ea"; }
+
+.fa-get-pocket:before {
+  content: "\f265"; }
+
+.fa-perbyte:before {
+  content: "\e083"; }
+
+.fa-grunt:before {
+  content: "\f3ad"; }
+
+.fa-weebly:before {
+  content: "\f5cc"; }
+
+.fa-connectdevelop:before {
+  content: "\f20e"; }
+
+.fa-leanpub:before {
+  content: "\f212"; }
+
+.fa-black-tie:before {
+  content: "\f27e"; }
+
+.fa-themeco:before {
+  content: "\f5c6"; }
+
+.fa-python:before {
+  content: "\f3e2"; }
+
+.fa-android:before {
+  content: "\f17b"; }
+
+.fa-bots:before {
+  content: "\e340"; }
+
+.fa-free-code-camp:before {
+  content: "\f2c5"; }
+
+.fa-hornbill:before {
+  content: "\f592"; }
+
+.fa-js:before {
+  content: "\f3b8"; }
+
+.fa-ideal:before {
+  content: "\e013"; }
+
+.fa-git:before {
+  content: "\f1d3"; }
+
+.fa-dev:before {
+  content: "\f6cc"; }
+
+.fa-sketch:before {
+  content: "\f7c6"; }
+
+.fa-yandex-international:before {
+  content: "\f414"; }
+
+.fa-cc-amex:before {
+  content: "\f1f3"; }
+
+.fa-uber:before {
+  content: "\f402"; }
+
+.fa-github:before {
+  content: "\f09b"; }
+
+.fa-php:before {
+  content: "\f457"; }
+
+.fa-alipay:before {
+  content: "\f642"; }
+
+.fa-youtube:before {
+  content: "\f167"; }
+
+.fa-skyatlas:before {
+  content: "\f216"; }
+
+.fa-firefox-browser:before {
+  content: "\e007"; }
+
+.fa-replyd:before {
+  content: "\f3e6"; }
+
+.fa-suse:before {
+  content: "\f7d6"; }
+
+.fa-jenkins:before {
+  content: "\f3b6"; }
+
+.fa-twitter:before {
+  content: "\f099"; }
+
+.fa-rockrms:before {
+  content: "\f3e9"; }
+
+.fa-pinterest:before {
+  content: "\f0d2"; }
+
+.fa-buffer:before {
+  content: "\f837"; }
+
+.fa-npm:before {
+  content: "\f3d4"; }
+
+.fa-yammer:before {
+  content: "\f840"; }
+
+.fa-btc:before {
+  content: "\f15a"; }
+
+.fa-dribbble:before {
+  content: "\f17d"; }
+
+.fa-stumbleupon-circle:before {
+  content: "\f1a3"; }
+
+.fa-internet-explorer:before {
+  content: "\f26b"; }
+
+.fa-stubber:before {
+  content: "\e5c7"; }
+
+.fa-telegram:before {
+  content: "\f2c6"; }
+
+.fa-telegram-plane:before {
+  content: "\f2c6"; }
+
+.fa-old-republic:before {
+  content: "\f510"; }
+
+.fa-odysee:before {
+  content: "\e5c6"; }
+
+.fa-square-whatsapp:before {
+  content: "\f40c"; }
+
+.fa-whatsapp-square:before {
+  content: "\f40c"; }
+
+.fa-node-js:before {
+  content: "\f3d3"; }
+
+.fa-edge-legacy:before {
+  content: "\e078"; }
+
+.fa-slack:before {
+  content: "\f198"; }
+
+.fa-slack-hash:before {
+  content: "\f198"; }
+
+.fa-medrt:before {
+  content: "\f3c8"; }
+
+.fa-usb:before {
+  content: "\f287"; }
+
+.fa-tumblr:before {
+  content: "\f173"; }
+
+.fa-vaadin:before {
+  content: "\f408"; }
+
+.fa-quora:before {
+  content: "\f2c4"; }
+
+.fa-square-x-twitter:before {
+  content: "\e61a"; }
+
+.fa-reacteurope:before {
+  content: "\f75d"; }
+
+.fa-medium:before {
+  content: "\f23a"; }
+
+.fa-medium-m:before {
+  content: "\f23a"; }
+
+.fa-amilia:before {
+  content: "\f36d"; }
+
+.fa-mixcloud:before {
+  content: "\f289"; }
+
+.fa-flipboard:before {
+  content: "\f44d"; }
+
+.fa-viacoin:before {
+  content: "\f237"; }
+
+.fa-critical-role:before {
+  content: "\f6c9"; }
+
+.fa-sitrox:before {
+  content: "\e44a"; }
+
+.fa-discourse:before {
+  content: "\f393"; }
+
+.fa-joomla:before {
+  content: "\f1aa"; }
+
+.fa-mastodon:before {
+  content: "\f4f6"; }
+
+.fa-airbnb:before {
+  content: "\f834"; }
+
+.fa-wolf-pack-battalion:before {
+  content: "\f514"; }
+
+.fa-buy-n-large:before {
+  content: "\f8a6"; }
+
+.fa-gulp:before {
+  content: "\f3ae"; }
+
+.fa-creative-commons-sampling-plus:before {
+  content: "\f4f1"; }
+
+.fa-strava:before {
+  content: "\f428"; }
+
+.fa-ember:before {
+  content: "\f423"; }
+
+.fa-canadian-maple-leaf:before {
+  content: "\f785"; }
+
+.fa-teamspeak:before {
+  content: "\f4f9"; }
+
+.fa-pushed:before {
+  content: "\f3e1"; }
+
+.fa-wordpress-simple:before {
+  content: "\f411"; }
+
+.fa-nutritionix:before {
+  content: "\f3d6"; }
+
+.fa-wodu:before {
+  content: "\e088"; }
+
+.fa-google-pay:before {
+  content: "\e079"; }
+
+.fa-intercom:before {
+  content: "\f7af"; }
+
+.fa-zhihu:before {
+  content: "\f63f"; }
+
+.fa-korvue:before {
+  content: "\f42f"; }
+
+.fa-pix:before {
+  content: "\e43a"; }
+
+.fa-steam-symbol:before {
+  content: "\f3f6"; }
+:root, :host {
+  --fa-style-family-classic: 'Font Awesome 6 Free';
+  --fa-font-regular: normal 400 1em/1 'Font Awesome 6 Free'; }
+
+@font-face {
+  font-family: 'Font Awesome 6 Free';
+  font-style: normal;
+  font-weight: 400;
+  font-display: block;
+  src: url("../webfonts/fa-regular-400.woff2") format("woff2"), url("../webfonts/fa-regular-400.ttf") format("truetype"); }
+
+.far,
+.fa-regular {
+  font-weight: 400; }
+:root, :host {
+  --fa-style-family-classic: 'Font Awesome 6 Free';
+  --fa-font-solid: normal 900 1em/1 'Font Awesome 6 Free'; }
+
+@font-face {
+  font-family: 'Font Awesome 6 Free';
+  font-style: normal;
+  font-weight: 900;
+  font-display: block;
+  src: url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.ttf") format("truetype"); }
+
+.fas,
+.fa-solid {
+  font-weight: 900; }
+@font-face {
+  font-family: 'Font Awesome 5 Brands';
+  font-display: block;
+  font-weight: 400;
+  src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'Font Awesome 5 Free';
+  font-display: block;
+  font-weight: 900;
+  src: url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'Font Awesome 5 Free';
+  font-display: block;
+  font-weight: 400;
+  src: url("../webfonts/fa-regular-400.woff2") format("woff2"), url("../webfonts/fa-regular-400.ttf") format("truetype"); }
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-solid-900.woff2") format("woff2"), url("../webfonts/fa-solid-900.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-brands-400.woff2") format("woff2"), url("../webfonts/fa-brands-400.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-regular-400.woff2") format("woff2"), url("../webfonts/fa-regular-400.ttf") format("truetype"); }
+
+@font-face {
+  font-family: 'FontAwesome';
+  font-display: block;
+  src: url("../webfonts/fa-v4compatibility.woff2") format("woff2"), url("../webfonts/fa-v4compatibility.ttf") format("truetype"); }
diff --git a/docs/deps/font-awesome-6.5.2/css/all.min.css b/docs/deps/font-awesome-6.5.2/css/all.min.css
new file mode 100644
index 00000000..269bceea
--- /dev/null
+++ b/docs/deps/font-awesome-6.5.2/css/all.min.css
@@ -0,0 +1,9 @@
+/*!
+ * Font Awesome Free 6.5.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2024 Fonticons, Inc.
+ */
+.fa{font-family:var(--fa-style-family,"Font Awesome 6 Free");font-weight:var(--fa-style,900)}.fa,.fa-brands,.fa-classic,.fa-regular,.fa-sharp,.fa-solid,.fab,.far,.fas{-moz-osx-font-smoothing:grayscale;-webkit-font-smoothing:antialiased;display:var(--fa-display,inline-block);font-style:normal;font-variant:normal;line-height:1;text-rendering:auto}.fa-classic,.fa-regular,.fa-solid,.far,.fas{font-family:"Font Awesome 6 Free"}.fa-brands,.fab{font-family:"Font Awesome 6 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diff --git a/docs/deps/font-awesome-6.5.2/css/v4-shims.css b/docs/deps/font-awesome-6.5.2/css/v4-shims.css
new file mode 100644
index 00000000..ea60ea4d
--- /dev/null
+++ b/docs/deps/font-awesome-6.5.2/css/v4-shims.css
@@ -0,0 +1,2194 @@
+/*!
+ * Font Awesome Free 6.5.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2024 Fonticons, Inc.
+ */
+.fa.fa-glass:before {
+  content: "\f000"; }
+
+.fa.fa-envelope-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-envelope-o:before {
+  content: "\f0e0"; }
+
+.fa.fa-star-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-star-o:before {
+  content: "\f005"; }
+
+.fa.fa-remove:before {
+  content: "\f00d"; }
+
+.fa.fa-close:before {
+  content: "\f00d"; }
+
+.fa.fa-gear:before {
+  content: "\f013"; }
+
+.fa.fa-trash-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-trash-o:before {
+  content: "\f2ed"; }
+
+.fa.fa-home:before {
+  content: "\f015"; }
+
+.fa.fa-file-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-file-o:before {
+  content: "\f15b"; }
+
+.fa.fa-clock-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-clock-o:before {
+  content: "\f017"; }
+
+.fa.fa-arrow-circle-o-down {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-arrow-circle-o-down:before {
+  content: "\f358"; }
+
+.fa.fa-arrow-circle-o-up {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-arrow-circle-o-up:before {
+  content: "\f35b"; }
+
+.fa.fa-play-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-play-circle-o:before {
+  content: "\f144"; }
+
+.fa.fa-repeat:before {
+  content: "\f01e"; }
+
+.fa.fa-rotate-right:before {
+  content: "\f01e"; }
+
+.fa.fa-refresh:before {
+  content: "\f021"; }
+
+.fa.fa-list-alt {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-list-alt:before {
+  content: "\f022"; }
+
+.fa.fa-dedent:before {
+  content: "\f03b"; }
+
+.fa.fa-video-camera:before {
+  content: "\f03d"; }
+
+.fa.fa-picture-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-picture-o:before {
+  content: "\f03e"; }
+
+.fa.fa-photo {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-photo:before {
+  content: "\f03e"; }
+
+.fa.fa-image {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-image:before {
+  content: "\f03e"; }
+
+.fa.fa-map-marker:before {
+  content: "\f3c5"; }
+
+.fa.fa-pencil-square-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-pencil-square-o:before {
+  content: "\f044"; }
+
+.fa.fa-edit {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-edit:before {
+  content: "\f044"; }
+
+.fa.fa-share-square-o:before {
+  content: "\f14d"; }
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+.fa.fa-check-square-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-check-square-o:before {
+  content: "\f14a"; }
+
+.fa.fa-arrows:before {
+  content: "\f0b2"; }
+
+.fa.fa-times-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
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+.fa.fa-times-circle-o:before {
+  content: "\f057"; }
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+.fa.fa-check-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
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+.fa.fa-check-circle-o:before {
+  content: "\f058"; }
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+.fa.fa-mail-forward:before {
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+  font-weight: 400; }
+
+.fa.fa-modx {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fort-awesome {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-usb {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-product-hunt {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-mixcloud {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-scribd {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-pause-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-pause-circle-o:before {
+  content: "\f28b"; }
+
+.fa.fa-stop-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-stop-circle-o:before {
+  content: "\f28d"; }
+
+.fa.fa-bluetooth {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-bluetooth-b {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-gitlab {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wpbeginner {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wpforms {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-envira {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wheelchair-alt {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wheelchair-alt:before {
+  content: "\f368"; }
+
+.fa.fa-question-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-question-circle-o:before {
+  content: "\f059"; }
+
+.fa.fa-volume-control-phone:before {
+  content: "\f2a0"; }
+
+.fa.fa-asl-interpreting:before {
+  content: "\f2a3"; }
+
+.fa.fa-deafness:before {
+  content: "\f2a4"; }
+
+.fa.fa-hard-of-hearing:before {
+  content: "\f2a4"; }
+
+.fa.fa-glide {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-glide-g {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-signing:before {
+  content: "\f2a7"; }
+
+.fa.fa-viadeo {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-viadeo-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-viadeo-square:before {
+  content: "\f2aa"; }
+
+.fa.fa-snapchat {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-snapchat-ghost {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-snapchat-ghost:before {
+  content: "\f2ab"; }
+
+.fa.fa-snapchat-square {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-snapchat-square:before {
+  content: "\f2ad"; }
+
+.fa.fa-pied-piper {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-first-order {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-yoast {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-themeisle {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-official {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-official:before {
+  content: "\f2b3"; }
+
+.fa.fa-google-plus-circle {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-google-plus-circle:before {
+  content: "\f2b3"; }
+
+.fa.fa-font-awesome {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fa {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-fa:before {
+  content: "\f2b4"; }
+
+.fa.fa-handshake-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-handshake-o:before {
+  content: "\f2b5"; }
+
+.fa.fa-envelope-open-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-envelope-open-o:before {
+  content: "\f2b6"; }
+
+.fa.fa-linode {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-address-book-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-address-book-o:before {
+  content: "\f2b9"; }
+
+.fa.fa-vcard:before {
+  content: "\f2bb"; }
+
+.fa.fa-address-card-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-address-card-o:before {
+  content: "\f2bb"; }
+
+.fa.fa-vcard-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-vcard-o:before {
+  content: "\f2bb"; }
+
+.fa.fa-user-circle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-user-circle-o:before {
+  content: "\f2bd"; }
+
+.fa.fa-user-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-user-o:before {
+  content: "\f007"; }
+
+.fa.fa-id-badge {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-drivers-license:before {
+  content: "\f2c2"; }
+
+.fa.fa-id-card-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-id-card-o:before {
+  content: "\f2c2"; }
+
+.fa.fa-drivers-license-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-drivers-license-o:before {
+  content: "\f2c2"; }
+
+.fa.fa-quora {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-free-code-camp {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-telegram {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-thermometer-4:before {
+  content: "\f2c7"; }
+
+.fa.fa-thermometer:before {
+  content: "\f2c7"; }
+
+.fa.fa-thermometer-3:before {
+  content: "\f2c8"; }
+
+.fa.fa-thermometer-2:before {
+  content: "\f2c9"; }
+
+.fa.fa-thermometer-1:before {
+  content: "\f2ca"; }
+
+.fa.fa-thermometer-0:before {
+  content: "\f2cb"; }
+
+.fa.fa-bathtub:before {
+  content: "\f2cd"; }
+
+.fa.fa-s15:before {
+  content: "\f2cd"; }
+
+.fa.fa-window-maximize {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-window-restore {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-times-rectangle:before {
+  content: "\f410"; }
+
+.fa.fa-window-close-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-window-close-o:before {
+  content: "\f410"; }
+
+.fa.fa-times-rectangle-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-times-rectangle-o:before {
+  content: "\f410"; }
+
+.fa.fa-bandcamp {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-grav {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-etsy {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-imdb {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-ravelry {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-eercast {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-eercast:before {
+  content: "\f2da"; }
+
+.fa.fa-snowflake-o {
+  font-family: 'Font Awesome 6 Free';
+  font-weight: 400; }
+
+.fa.fa-snowflake-o:before {
+  content: "\f2dc"; }
+
+.fa.fa-superpowers {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-wpexplorer {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
+
+.fa.fa-meetup {
+  font-family: 'Font Awesome 6 Brands';
+  font-weight: 400; }
diff --git a/docs/deps/font-awesome-6.5.2/css/v4-shims.min.css b/docs/deps/font-awesome-6.5.2/css/v4-shims.min.css
new file mode 100644
index 00000000..09baf5fc
--- /dev/null
+++ b/docs/deps/font-awesome-6.5.2/css/v4-shims.min.css
@@ -0,0 +1,6 @@
+/*!
+ * Font Awesome Free 6.5.2 by @fontawesome - https://fontawesome.com
+ * License - https://fontawesome.com/license/free (Icons: CC BY 4.0, Fonts: SIL OFL 1.1, Code: MIT License)
+ * Copyright 2024 Fonticons, Inc.
+ */
+.fa.fa-glass:before{content:"\f000"}.fa.fa-envelope-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-envelope-o:before{content:"\f0e0"}.fa.fa-star-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-star-o:before{content:"\f005"}.fa.fa-close:before,.fa.fa-remove:before{content:"\f00d"}.fa.fa-gear:before{content:"\f013"}.fa.fa-trash-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-trash-o:before{content:"\f2ed"}.fa.fa-home:before{content:"\f015"}.fa.fa-file-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-file-o:before{content:"\f15b"}.fa.fa-clock-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-clock-o:before{content:"\f017"}.fa.fa-arrow-circle-o-down{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-arrow-circle-o-down:before{content:"\f358"}.fa.fa-arrow-circle-o-up{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-arrow-circle-o-up:before{content:"\f35b"}.fa.fa-play-circle-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-play-circle-o:before{content:"\f144"}.fa.fa-repeat:before,.fa.fa-rotate-right:before{content:"\f01e"}.fa.fa-refresh:before{content:"\f021"}.fa.fa-list-alt{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-list-alt:before{content:"\f022"}.fa.fa-dedent:before{content:"\f03b"}.fa.fa-video-camera:before{content:"\f03d"}.fa.fa-picture-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-picture-o:before{content:"\f03e"}.fa.fa-photo{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-photo:before{content:"\f03e"}.fa.fa-image{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-image:before{content:"\f03e"}.fa.fa-map-marker:before{content:"\f3c5"}.fa.fa-pencil-square-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-pencil-square-o:before{content:"\f044"}.fa.fa-edit{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-edit:before{content:"\f044"}.fa.fa-share-square-o:before{content:"\f14d"}.fa.fa-check-square-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-check-square-o:before{content:"\f14a"}.fa.fa-arrows:before{content:"\f0b2"}.fa.fa-times-circle-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-times-circle-o:before{content:"\f057"}.fa.fa-check-circle-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-check-circle-o:before{content:"\f058"}.fa.fa-mail-forward:before{content:"\f064"}.fa.fa-expand:before{content:"\f424"}.fa.fa-compress:before{content:"\f422"}.fa.fa-eye,.fa.fa-eye-slash{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-warning:before{content:"\f071"}.fa.fa-calendar:before{content:"\f073"}.fa.fa-arrows-v:before{content:"\f338"}.fa.fa-arrows-h:before{content:"\f337"}.fa.fa-bar-chart-o:before,.fa.fa-bar-chart:before{content:"\e0e3"}.fa.fa-twitter-square{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-twitter-square:before{content:"\f081"}.fa.fa-facebook-square{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-facebook-square:before{content:"\f082"}.fa.fa-gears:before{content:"\f085"}.fa.fa-thumbs-o-up{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-thumbs-o-up:before{content:"\f164"}.fa.fa-thumbs-o-down{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-thumbs-o-down:before{content:"\f165"}.fa.fa-heart-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-heart-o:before{content:"\f004"}.fa.fa-sign-out:before{content:"\f2f5"}.fa.fa-linkedin-square{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-linkedin-square:before{content:"\f08c"}.fa.fa-thumb-tack:before{content:"\f08d"}.fa.fa-external-link:before{content:"\f35d"}.fa.fa-sign-in:before{content:"\f2f6"}.fa.fa-github-square{font-family:"Font Awesome 6 Brands";font-weight:400}.fa.fa-github-square:before{content:"\f092"}.fa.fa-lemon-o{font-family:"Font Awesome 6 Free";font-weight:400}.fa.fa-lemon-o:before{content:"\f094"}.fa.fa-square-o{font-family:"Font Awesome 6 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@@ -0,0 +1,7 @@
+/*!
+ * headroom.js v0.11.0 - Give your page some headroom. Hide your header until you need it
+ * Copyright (c) 2020 Nick Williams - http://wicky.nillia.ms/headroom.js
+ * License: MIT
+ */
+
+!function(t,n){"object"==typeof exports&&"undefined"!=typeof module?module.exports=n():"function"==typeof define&&define.amd?define(n):(t=t||self).Headroom=n()}(this,function(){"use strict";function t(){return"undefined"!=typeof window}function d(t){return function(t){return t&&t.document&&function(t){return 9===t.nodeType}(t.document)}(t)?function(t){var n=t.document,o=n.body,s=n.documentElement;return{scrollHeight:function(){return Math.max(o.scrollHeight,s.scrollHeight,o.offsetHeight,s.offsetHeight,o.clientHeight,s.clientHeight)},height:function(){return t.innerHeight||s.clientHeight||o.clientHeight},scrollY:function(){return void 0!==t.pageYOffset?t.pageYOffset:(s||o.parentNode||o).scrollTop}}}(t):function(t){return{scrollHeight:function(){return Math.max(t.scrollHeight,t.offsetHeight,t.clientHeight)},height:function(){return Math.max(t.offsetHeight,t.clientHeight)},scrollY:function(){return t.scrollTop}}}(t)}function n(t,s,e){var n,o=function(){var n=!1;try{var t={get passive(){n=!0}};window.addEventListener("test",t,t),window.removeEventListener("test",t,t)}catch(t){n=!1}return n}(),i=!1,r=d(t),l=r.scrollY(),a={};function c(){var t=Math.round(r.scrollY()),n=r.height(),o=r.scrollHeight();a.scrollY=t,a.lastScrollY=l,a.direction=ls.tolerance[a.direction],e(a),l=t,i=!1}function h(){i||(i=!0,n=requestAnimationFrame(c))}var u=!!o&&{passive:!0,capture:!1};return t.addEventListener("scroll",h,u),c(),{destroy:function(){cancelAnimationFrame(n),t.removeEventListener("scroll",h,u)}}}function o(t,n){n=n||{},Object.assign(this,o.options,n),this.classes=Object.assign({},o.options.classes,n.classes),this.elem=t,this.tolerance=function(t){return t===Object(t)?t:{down:t,up:t}}(this.tolerance),this.initialised=!1,this.frozen=!1}return o.prototype={constructor:o,init:function(){return o.cutsTheMustard&&!this.initialised&&(this.addClass("initial"),this.initialised=!0,setTimeout(function(t){t.scrollTracker=n(t.scroller,{offset:t.offset,tolerance:t.tolerance},t.update.bind(t))},100,this)),this},destroy:function(){this.initialised=!1,Object.keys(this.classes).forEach(this.removeClass,this),this.scrollTracker.destroy()},unpin:function(){!this.hasClass("pinned")&&this.hasClass("unpinned")||(this.addClass("unpinned"),this.removeClass("pinned"),this.onUnpin&&this.onUnpin.call(this))},pin:function(){this.hasClass("unpinned")&&(this.addClass("pinned"),this.removeClass("unpinned"),this.onPin&&this.onPin.call(this))},freeze:function(){this.frozen=!0,this.addClass("frozen")},unfreeze:function(){this.frozen=!1,this.removeClass("frozen")},top:function(){this.hasClass("top")||(this.addClass("top"),this.removeClass("notTop"),this.onTop&&this.onTop.call(this))},notTop:function(){this.hasClass("notTop")||(this.addClass("notTop"),this.removeClass("top"),this.onNotTop&&this.onNotTop.call(this))},bottom:function(){this.hasClass("bottom")||(this.addClass("bottom"),this.removeClass("notBottom"),this.onBottom&&this.onBottom.call(this))},notBottom:function(){this.hasClass("notBottom")||(this.addClass("notBottom"),this.removeClass("bottom"),this.onNotBottom&&this.onNotBottom.call(this))},shouldUnpin:function(t){return"down"===t.direction&&!t.top&&t.toleranceExceeded},shouldPin:function(t){return"up"===t.direction&&t.toleranceExceeded||t.top},addClass:function(t){this.elem.classList.add.apply(this.elem.classList,this.classes[t].split(" "))},removeClass:function(t){this.elem.classList.remove.apply(this.elem.classList,this.classes[t].split(" "))},hasClass:function(t){return this.classes[t].split(" ").every(function(t){return this.classList.contains(t)},this.elem)},update:function(t){t.isOutOfBounds||!0!==this.frozen&&(t.top?this.top():this.notTop(),t.bottom?this.bottom():this.notBottom(),this.shouldUnpin(t)?this.unpin():this.shouldPin(t)&&this.pin())}},o.options={tolerance:{up:0,down:0},offset:0,scroller:t()?window:null,classes:{frozen:"headroom--frozen",pinned:"headroom--pinned",unpinned:"headroom--unpinned",top:"headroom--top",notTop:"headroom--not-top",bottom:"headroom--bottom",notBottom:"headroom--not-bottom",initial:"headroom"}},o.cutsTheMustard=!!(t()&&function(){}.bind&&"classList"in document.documentElement&&Object.assign&&Object.keys&&requestAnimationFrame),o});
\ No newline at end of file
diff --git a/docs/deps/headroom-0.11.0/jQuery.headroom.min.js b/docs/deps/headroom-0.11.0/jQuery.headroom.min.js
new file mode 100644
index 00000000..17f70c9e
--- /dev/null
+++ b/docs/deps/headroom-0.11.0/jQuery.headroom.min.js
@@ -0,0 +1,7 @@
+/*!
+ * headroom.js v0.9.4 - Give your page some headroom. Hide your header until you need it
+ * Copyright (c) 2017 Nick Williams - http://wicky.nillia.ms/headroom.js
+ * License: MIT
+ */
+
+!function(a){a&&(a.fn.headroom=function(b){return this.each(function(){var c=a(this),d=c.data("headroom"),e="object"==typeof b&&b;e=a.extend(!0,{},Headroom.options,e),d||(d=new Headroom(this,e),d.init(),c.data("headroom",d)),"string"==typeof b&&(d[b](),"destroy"===b&&c.removeData("headroom"))})},a("[data-headroom]").each(function(){var b=a(this);b.headroom(b.data())}))}(window.Zepto||window.jQuery);
\ No newline at end of file
diff --git a/docs/deps/search-1.0.0/autocomplete.jquery.min.js b/docs/deps/search-1.0.0/autocomplete.jquery.min.js
new file mode 100644
index 00000000..fb63a6a2
--- /dev/null
+++ b/docs/deps/search-1.0.0/autocomplete.jquery.min.js
@@ -0,0 +1,7 @@
+/*!
+ * autocomplete.js 0.38.0
+ * https://github.com/algolia/autocomplete.js
+ * Copyright 2020 Algolia, Inc. and other contributors; Licensed MIT
+ */
+!function(a){function b(d){if(c[d])return c[d].exports;var e=c[d]={exports:{},id:d,loaded:!1};return a[d].call(e.exports,e,e.exports,b),e.loaded=!0,e.exports}var c={};b.m=a,b.c=c,b.p="",b(0)}([function(a,b,c){"use strict";a.exports=c(1)},function(a,b,c){"use strict";var d=c(2),e=c(3);d.element=e;var f=c(4);f.isArray=e.isArray,f.isFunction=e.isFunction,f.isObject=e.isPlainObject,f.bind=e.proxy,f.each=function(a,b){function c(a,c){return b(c,a)}e.each(a,c)},f.map=e.map,f.mixin=e.extend,f.Event=e.Event;var g,h,i,j=c(5),k=c(6);g=e.fn.autocomplete,h="aaAutocomplete",i={initialize:function(a,b){function c(){var c,d=e(this),f=new k({el:d});c=new j({input:d,eventBus:f,dropdownMenuContainer:a.dropdownMenuContainer,hint:void 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i[a]&&"initialize"!==a?(b=this.filter(function(){return!!e(this).data(h)}),i[a].apply(b,[].slice.call(arguments,1))):i.initialize.apply(this,arguments)},e.fn.autocomplete.noConflict=function(){return e.fn.autocomplete=g,this},e.fn.autocomplete.sources=j.sources,e.fn.autocomplete.escapeHighlightedString=f.escapeHighlightedString,a.exports=e.fn.autocomplete},function(a,b){"use strict";a.exports={element:null}},function(a,b){a.exports=jQuery},function(a,b,c){"use strict";function d(a){return a.replace(/[\-\[\]\/\{\}\(\)\*\+\?\.\\\^\$\|]/g,"\\$&")}var e=c(2);a.exports={isArray:null,isFunction:null,isObject:null,bind:null,each:null,map:null,mixin:null,isMsie:function(a){if(void 0===a&&(a=navigator.userAgent),/(msie|trident)/i.test(a)){var b=a.match(/(msie |rv:)(\d+(.\d+)?)/i);if(b)return b[2]}return!1},escapeRegExChars:function(a){return a.replace(/[\-\[\]\/\{\}\(\)\*\+\?\.\\\^\$\|]/g,"\\$&")},isNumber:function(a){return"number"==typeof a},toStr:function(a){return void 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f=document.createElement("div");f.appendChild(document.createTextNode(c));var g=document.createElement("div");return g.appendChild(document.createTextNode(a)),g.innerHTML.replace(RegExp(d(e.innerHTML),"g"),b).replace(RegExp(d(f.innerHTML),"g"),c)}}},function(a,b,c){"use strict";function d(a){var b,c;if(a=a||{},a.input||i.error("missing input"),this.isActivated=!1,this.debug=!!a.debug,this.autoselect=!!a.autoselect,this.autoselectOnBlur=!!a.autoselectOnBlur,this.openOnFocus=!!a.openOnFocus,this.minLength=i.isNumber(a.minLength)?a.minLength:1,this.autoWidth=void 0===a.autoWidth||!!a.autoWidth,this.clearOnSelected=!!a.clearOnSelected,this.tabAutocomplete=void 0===a.tabAutocomplete||!!a.tabAutocomplete,a.hint=!!a.hint,a.hint&&a.appendTo)throw new Error("[autocomplete.js] hint and appendTo options can't be used at the same 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d.Dropdown({appendTo:a.appendTo,wrapper:this.$node,menu:b,datasets:a.datasets,templates:a.templates,cssClasses:a.cssClasses,minLength:this.minLength}).onSync("suggestionClicked",this._onSuggestionClicked,this).onSync("cursorMoved",this._onCursorMoved,this).onSync("cursorRemoved",this._onCursorRemoved,this).onSync("opened",this._onOpened,this).onSync("closed",this._onClosed,this).onSync("shown",this._onShown,this).onSync("empty",this._onEmpty,this).onSync("redrawn",this._onRedrawn,this).onAsync("datasetRendered",this._onDatasetRendered,this),this.input=new 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required").prop("readonly",!0).attr({"aria-hidden":"true",autocomplete:"off",spellcheck:"false",tabindex:-1}),e.removeData&&e.removeData(),b.data(h,{"aria-autocomplete":b.attr("aria-autocomplete"),"aria-expanded":b.attr("aria-expanded"),"aria-owns":b.attr("aria-owns"),autocomplete:b.attr("autocomplete"),dir:b.attr("dir"),role:b.attr("role"),spellcheck:b.attr("spellcheck"),style:b.attr("style"),type:b.attr("type")}),b.addClass(i.className(a.cssClasses.prefix,a.cssClasses.input,!0)).attr({autocomplete:"off",spellcheck:!1,role:"combobox","aria-autocomplete":a.datasets&&a.datasets[0]&&a.datasets[0].displayKey?"both":"list","aria-expanded":"false","aria-label":a.ariaLabel,"aria-owns":a.listboxId}).css(a.hint?a.css.input:a.css.inputWithNoHint);try{b.attr("dir")||b.attr("dir","auto")}catch(a){}return c=a.appendTo?c.appendTo(j.element(a.appendTo).eq(0)).eq(0):b.wrap(c).parent(),c.prepend(a.hint?e:null).append(d),{wrapper:c,input:b,hint:e,menu:d}}function f(a){return{backgroundAttachment:a.css("background-attachment"),backgroundClip:a.css("background-clip"),backgroundColor:a.css("background-color"),backgroundImage:a.css("background-image"),backgroundOrigin:a.css("background-origin"),backgroundPosition:a.css("background-position"),backgroundRepeat:a.css("background-repeat"),backgroundSize:a.css("background-size")}}function g(a,b){var c=a.find(i.className(b.prefix,b.input));i.each(c.data(h),function(a,b){void 0===a?c.removeAttr(b):c.attr(b,a)}),c.detach().removeClass(i.className(b.prefix,b.input,!0)).insertAfter(a),c.removeData&&c.removeData(h),a.remove()}var h="aaAttrs",i=c(4),j=c(2),k=c(6),l=c(7),m=c(16),n=c(18),o=c(19);i.mixin(d.prototype,{_bindKeyboardShortcuts:function(a){if(a.keyboardShortcuts){var b=this.$input,c=[];i.each(a.keyboardShortcuts,function(a){"string"==typeof a&&(a=a.toUpperCase().charCodeAt(0)),c.push(a)}),j.element(document).keydown(function(a){var 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c=this.dropdown.getDatumForCursor(),d=this.dropdown.getCurrentCursor().attr("id");this.input.setActiveDescendant(d),c&&(b&&this.input.setInputValue(c.value,!0),this.eventBus.trigger("cursorchanged",c.raw,c.datasetName))},_onCursorRemoved:function(){this.input.resetInputValue(),this._updateHint(),this.eventBus.trigger("cursorremoved")},_onDatasetRendered:function(){this._updateHint(),this.eventBus.trigger("updated")},_onOpened:function(){this._updateHint(),this.input.expand(),this.eventBus.trigger("opened")},_onEmpty:function(){this.eventBus.trigger("empty")},_onRedrawn:function(){this.$node.css("top","0px"),this.$node.css("left","0px");var a=this.$input[0].getBoundingClientRect();this.autoWidth&&this.$node.css("width",a.width+"px");var b=this.$node[0].getBoundingClientRect(),c=a.bottom-b.top;this.$node.css("top",c+"px");var d=a.left-b.left;this.$node.css("left",d+"px"),this.eventBus.trigger("redrawn")},_onShown:function(){this.eventBus.trigger("shown"),this.autoselect&&this.dropdown.cursorTopSuggestion()},_onClosed:function(){this.input.clearHint(),this.input.removeActiveDescendant(),this.input.collapse(),this.eventBus.trigger("closed")},_onFocused:function(){if(this.isActivated=!0,this.openOnFocus){var a=this.input.getQuery();a.length>=this.minLength?this.dropdown.update(a):this.dropdown.empty(),this.dropdown.open()}},_onBlurred:function(){var a,b;a=this.dropdown.getDatumForCursor(),b=this.dropdown.getDatumForTopSuggestion();var c={selectionMethod:"blur"};this.debug||(this.autoselectOnBlur&&a?this._select(a,c):this.autoselectOnBlur&&b?this._select(b,c):(this.isActivated=!1,this.dropdown.empty(),this.dropdown.close()))},_onEnterKeyed:function(a,b){var c,d;c=this.dropdown.getDatumForCursor(),d=this.dropdown.getDatumForTopSuggestion();var 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a=this.input.getInputValue();a.length>=this.minLength?this.dropdown.update(a):this.dropdown.empty()}this.dropdown.open()},close:function(){this.dropdown.close()},setVal:function(a){a=i.toStr(a),this.isActivated?this.input.setInputValue(a):(this.input.setQuery(a),this.input.setInputValue(a,!0)),this._setLanguageDirection()},getVal:function(){return this.input.getQuery()},destroy:function(){this.input.destroy(),this.dropdown.destroy(),g(this.$node,this.cssClasses),this.$node=null},getWrapper:function(){return this.dropdown.$container[0]}}),d.Dropdown=m,d.Input=l,d.sources=c(20),a.exports=d},function(a,b,c){"use strict";function d(a){a&&a.el||e.error("EventBus initialized without el"),this.$el=f.element(a.el)}var e=c(4),f=c(2);e.mixin(d.prototype,{trigger:function(a,b,c,d){var f=e.Event("autocomplete:"+a);return this.$el.trigger(f,[b,c,d]),f}}),a.exports=d},function(a,b,c){"use strict";function d(a){var b,c,d,f,g=this;a=a||{},a.input||i.error("input is 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\ No newline at end of file
diff --git a/docs/deps/search-1.0.0/fuse.min.js b/docs/deps/search-1.0.0/fuse.min.js
new file mode 100644
index 00000000..7def5985
--- /dev/null
+++ b/docs/deps/search-1.0.0/fuse.min.js
@@ -0,0 +1,9 @@
+/**
+ * Fuse.js v6.4.6 - Lightweight fuzzy-search (http://fusejs.io)
+ *
+ * Copyright (c) 2021 Kiro Risk (http://kiro.me)
+ * All Rights Reserved. Apache Software License 2.0
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ */
+var e,t;e=this,t=function(){"use strict";function e(t){return(e="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(e){return typeof e}:function(e){return e&&"function"==typeof Symbol&&e.constructor===Symbol&&e!==Symbol.prototype?"symbol":typeof e})(t)}function t(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")}function n(e,t){for(var n=0;ne.length)&&(t=e.length);for(var n=0,r=new Array(t);n0&&void 0!==arguments[0]?arguments[0]:3,t=new Map,n=Math.pow(10,e);return{get:function(e){var r=e.match(I).length;if(t.has(r))return t.get(r);var i=1/Math.sqrt(r),o=parseFloat(Math.round(i*n)/n);return t.set(r,o),o},clear:function(){t.clear()}}}var E=function(){function e(){var n=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{},r=n.getFn,i=void 0===r?A.getFn:r;t(this,e),this.norm=C(3),this.getFn=i,this.isCreated=!1,this.setIndexRecords()}return r(e,[{key:"setSources",value:function(){var e=arguments.length>0&&void 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diff --git a/docs/deps/search-1.0.0/mark.min.js b/docs/deps/search-1.0.0/mark.min.js
new file mode 100644
index 00000000..1eea0533
--- /dev/null
+++ b/docs/deps/search-1.0.0/mark.min.js
@@ -0,0 +1,7 @@
+/*!***************************************************
+* mark.js v8.11.1
+* https://markjs.io/
+* Copyright (c) 2014–2018, Julian Kühnel
+* Released under the MIT license https://git.io/vwTVl
+*****************************************************/
+!function(e,t){"object"==typeof exports&&"undefined"!=typeof module?module.exports=t():"function"==typeof define&&define.amd?define(t):e.Mark=t()}(this,function(){"use strict";var e="function"==typeof Symbol&&"symbol"==typeof Symbol.iterator?function(e){return typeof e}:function(e){return e&&"function"==typeof Symbol&&e.constructor===Symbol&&e!==Symbol.prototype?"symbol":typeof e},t=function(e,t){if(!(e instanceof t))throw new TypeError("Cannot call a class as a function")},n=function(){function e(e,t){for(var n=0;n1&&void 0!==arguments[1])||arguments[1],i=arguments.length>2&&void 0!==arguments[2]?arguments[2]:[],o=arguments.length>3&&void 0!==arguments[3]?arguments[3]:5e3;t(this,e),this.ctx=n,this.iframes=r,this.exclude=i,this.iframesTimeout=o}return n(e,[{key:"getContexts",value:function(){var e=[];return(void 0!==this.ctx&&this.ctx?NodeList.prototype.isPrototypeOf(this.ctx)?Array.prototype.slice.call(this.ctx):Array.isArray(this.ctx)?this.ctx:"string"==typeof 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-Page not found (404) • mkin
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-Content not found. Please use links in the navbar.
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    Developed by Johannes Ranke.
    
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    Site built with pkgdown 1.6.1.
    
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-Work package 1.1: Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P • mkin
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    Work package 1.1: Testing hierarchical parent
-degradation kinetics with residue data on dimethenamid and
-dimethenamid-P
    
-                        
    Johannes
-Ranke
    
-            
-            
    Last change on 5 January
-2022, last compiled on 5 Januar 2023
    
-      
-      Source: vignettes/2022_wp_1.1_dmta_parent.rmd
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    Introduction
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    The purpose of this document is to demonstrate how nonlinear
-hierarchical models (NLHM) based on the parent degradation models SFO,
-FOMC, DFOP and HS can be fitted with the mkin package.
    
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    The mkin package is used in version 1.2.2. It contains the test data
-and the functions used in the evaluations. The saemix
-package is used as a backend for fitting the NLHM, but is also loaded to
-make the convergence plot function available.
    
-
    This document is processed with the knitr package, which
-also provides the kable function that is used to improve
-the display of tabular data in R markdown documents. For parallel
-processing, the parallel package is used.
    
-
    -library(mkin)
-library(knitr)
-library(saemix)
-library(parallel)
-n_cores <- detectCores()
-if (Sys.info()["sysname"] == "Windows") {
-  cl <- makePSOCKcluster(n_cores)
-} else {
-  cl <- makeForkCluster(n_cores)
-}
    
-
    
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    Preprocessing of test data
-
    
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    The test data are available in the mkin package as an object of class
-mkindsg (mkin dataset group) under the identifier
-dimethenamid_2018. The following preprocessing steps are
-still necessary:
    
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    • The data available for the enantiomer dimethenamid-P (DMTAP) are
-renamed to have the same substance name as the data for the racemic
-mixture dimethenamid (DMTA). The reason for this is that no difference
-between their degradation behaviour was identified in the EU risk
-assessment.
      • 
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    • The data for transformation products and unnecessary columns are
-discarded
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    • The observation times of each dataset are multiplied with the
-corresponding normalisation factor also available in the dataset, in
-order to make it possible to describe all datasets with a single set of
-parameters that are independent of temperature
      • 
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    • Finally, datasets observed in the same soil (Elliot 1
-and Elliot 2) are combined, resulting in dimethenamid
-(DMTA) data from six soils.
      • 
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    The following commented R code performs this preprocessing.
    
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    -# Apply a function to each of the seven datasets in the mkindsg object to create a list
-dmta_ds <- lapply(1:7, function(i) {
-  ds_i <- dimethenamid_2018$ds[[i]]$data                     # Get a dataset
-  ds_i[ds_i$name == "DMTAP", "name"] <-  "DMTA"              # Rename DMTAP to DMTA
-  ds_i <- subset(ds_i, name == "DMTA", c("name", "time", "value")) # Select data
-  ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i]  # Normalise time
-  ds_i                                                       # Return the dataset
-})
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-# Use dataset titles as names for the list elements
-names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title)
-
-# Combine data for Elliot soil to obtain a named list with six elements
-dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]]) #
-dmta_ds[["Elliot 1"]] <- NULL
-dmta_ds[["Elliot 2"]] <- NULL
    
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    The following tables show the 6 datasets.
    
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    -for (ds_name in names(dmta_ds)) {
-    print(kable(mkin_long_to_wide(dmta_ds[[ds_name]]),
-      caption = paste("Dataset", ds_name),
-      label = paste0("tab:", ds_name), booktabs = TRUE))
-    cat("\n\\clearpage\n")
-}
    
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    Dataset Calke
    timeDMTA
    095.8
    098.7
    1460.5
    3039.1
    5915.2
    1204.8
    1204.6
    
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    Dataset Borstel
    timeDMTA
    0.000000100.5
    0.00000099.6
    1.94129591.9
    1.94129591.3
    6.79453481.8
    6.79453482.1
    13.58906769.1
    13.58906768.0
    27.17813551.4
    27.17813551.4
    56.29756527.6
    56.29756526.8
    86.38764315.7
    86.38764315.3
    115.5070737.9
    115.5070738.1
    
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    Dataset Flaach
    timeDMTA
    0.000000096.5
    0.000000096.8
    0.000000097.0
    0.623385682.9
    0.623385686.7
    0.623385687.4
    1.870156772.8
    1.870156769.9
    1.870156771.9
    4.363698951.4
    4.363698952.9
    4.363698948.6
    8.727397928.5
    8.727397927.3
    8.727397927.5
    13.091096814.8
    13.091096813.4
    13.091096814.4
    17.45479577.7
    17.45479577.3
    17.45479578.1
    26.18219362.0
    26.18219361.5
    26.18219361.9
    34.90959151.3
    34.90959151.0
    34.90959151.1
    43.63698930.9
    43.63698930.7
    43.63698930.7
    52.36438720.6
    52.36438720.4
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    74.80626740.4
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    Dataset BBA 2.2
    timeDMTA
    0.000000098.09
    0.000000098.77
    0.767892293.52
    0.767892292.03
    2.303676588.39
    2.303676587.18
    5.375245269.38
    5.375245271.06
    10.750490445.21
    10.750490446.81
    16.125735530.54
    16.125735530.07
    21.500980721.60
    21.500980720.41
    32.25147119.10
    32.25147119.70
    43.00196146.58
    43.00196146.31
    53.75245183.47
    53.75245183.52
    64.50294213.40
    64.50294213.67
    91.37916801.62
    91.37916801.62
    
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    Dataset BBA 2.3
    timeDMTA
    0.000000099.33
    0.000000097.44
    0.673393893.73
    0.673393893.77
    2.020181487.84
    2.020181489.82
    4.713756571.61
    4.713756571.42
    9.427513145.60
    9.427513145.42
    14.141269631.12
    14.141269631.68
    18.855026223.20
    18.855026224.13
    28.28253939.43
    28.28253939.82
    37.71005237.08
    37.71005238.64
    47.13756544.41
    47.13756544.78
    56.56507854.92
    56.56507855.08
    80.13386122.13
    80.13386122.23
    
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    Dataset Elliot
    timeDMTA
    0.00000097.5
    0.000000100.7
    1.22847886.4
    1.22847888.5
    3.68543569.8
    3.68543577.1
    8.59934959.0
    8.59934954.2
    17.19869731.3
    17.19869733.5
    25.79804619.6
    25.79804620.9
    34.39739513.3
    34.39739515.8
    51.5960926.7
    51.5960928.7
    68.7947898.8
    68.7947898.7
    103.1921846.0
    103.1921844.4
    146.1889283.3
    146.1889282.8
    223.5830661.4
    223.5830661.8
    0.00000093.4
    0.000000103.2
    1.22847889.2
    1.22847886.6
    3.68543578.2
    3.68543578.1
    8.59934955.6
    8.59934953.0
    17.19869733.7
    17.19869733.2
    25.79804620.9
    25.79804619.9
    34.39739518.2
    34.39739512.7
    51.5960927.8
    51.5960929.0
    68.79478911.4
    68.7947899.0
    103.1921843.9
    103.1921844.4
    146.1889282.6
    146.1889283.4
    223.5830662.0
    223.5830661.7
    
-
    
-
    
-
    
-
    Separate evaluations
-
    
-
    In order to obtain suitable starting parameters for the NLHM fits,
-separate fits of the four models to the data for each soil are generated
-using the mmkin function from the mkin
-package. In a first step, constant variance is assumed. Convergence is
-checked with the status function.
    
-
    -deg_mods <- c("SFO", "FOMC", "DFOP", "HS")
-f_sep_const <- mmkin(
-  deg_mods,
-  dmta_ds,
-  error_model = "const",
-  quiet = TRUE)
-
-status(f_sep_const) |> kable()
    
-
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    CalkeBorstelFlaachBBA 2.2BBA 2.3Elliot
    SFOOKOKOKOKOKOK
    FOMCOKOKOKOKOKOK
    DFOPOKOKOKOKOKOK
    HSOKOKOKCOKOK
    
-
    In the table above, OK indicates convergence, and C indicates failure
-to converge. All separate fits with constant variance converged, with
-the sole exception of the HS fit to the BBA 2.2 data. To prepare for
-fitting NLHM using the two-component error model, the separate fits are
-updated assuming two-component error.
    
-
    -f_sep_tc <- update(f_sep_const, error_model = "tc")
-status(f_sep_tc) |> kable()
    
-
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    CalkeBorstelFlaachBBA 2.2BBA 2.3Elliot
    SFOOKOKOKOKOKOK
    FOMCOKOKOKOKCOK
    DFOPOKOKCOKCOK
    HSOKCOKOKOKOK
    
-
    Using the two-component error model, the one fit that did not
-converge with constant variance did converge, but other non-SFO fits
-failed to converge.
    
-
    
-
    
-
    Hierarchichal model fits
-
    
-
    The following code fits eight versions of hierarchical models to the
-data, using SFO, FOMC, DFOP and HS for the parent compound, and using
-either constant variance or two-component error for the error model. The
-default parameter distribution model in mkin allows for variation of all
-degradation parameters across the assumed population of soils. In other
-words, each degradation parameter is associated with a random effect as
-a first step. The mhmkin function makes it possible to fit
-all eight versions in parallel (given a sufficient number of computing
-cores being available) to save execution time.
    
-
    Convergence plots and summaries for these fits are shown in the
-appendix.
    
-
    -f_saem <- mhmkin(list(f_sep_const, f_sep_tc), transformations = "saemix")
    
-
    The output of the status function shows that all fits
-terminated successfully.
    
-
    -status(f_saem) |> kable()
    
-
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    consttc
    SFOOKOK
    FOMCOKOK
    DFOPOKOK
    HSOKOK
    
-
    The AIC and BIC values show that the biphasic models DFOP and HS give
-the best fits.
    
-
    -anova(f_saem) |> kable(digits = 1)
    
-
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    nparAICBICLik
    SFO const5796.3795.3-393.2
    SFO tc6798.3797.1-393.2
    FOMC const7734.2732.7-360.1
    FOMC tc8720.4718.8-352.2
    DFOP const9711.8710.0-346.9
    HS const9714.0712.1-348.0
    DFOP tc10665.5663.4-322.8
    HS tc10667.1665.0-323.6
    
-
    The DFOP model is preferred here, as it has a better mechanistic
-basis for batch experiments with constant incubation conditions. Also,
-it shows the lowest AIC and BIC values in the first set of fits when
-combined with the two-component error model. Therefore, the DFOP model
-was selected for further refinements of the fits with the aim to make
-the model fully identifiable.
    
-
    
-
    Parameter identifiability based on the Fisher Information
-Matrix
-
    
-
    Using the illparms function, ill-defined statistical
-model parameters such as standard deviations of the degradation
-parameters in the population and error model parameters can be
-found.
    
-
    -illparms(f_saem) |> kable()
    
-
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    consttc
    SFOb.1
    FOMCsd(DMTA_0)
    DFOPsd(k2)sd(k2)
    HSsd(tb)
    
-
    According to the illparms function, the fitted standard
-deviation of the second kinetic rate constant k2 is
-ill-defined in both DFOP fits. This suggests that different values would
-be obtained for this standard deviation when using different starting
-values.
    
-
    The thus identified overparameterisation is addressed by removing the
-random effect for k2 from the parameter model.
    
-
    -f_saem_dfop_tc_no_ranef_k2 <- update(f_saem[["DFOP", "tc"]],
-  no_random_effect = "k2")
    
-
    For the resulting fit, it is checked whether there are still
-ill-defined parameters,
    
-
    -illparms(f_saem_dfop_tc_no_ranef_k2)
    
-
    which is not the case. Below, the refined model is compared with the
-previous best model. The model without random effect for k2
-is a reduced version of the previous model. Therefore, the models are
-nested and can be compared using the likelihood ratio test. This is
-achieved with the argument test = TRUE to the
-anova function.
    
-
    -anova(f_saem[["DFOP", "tc"]], f_saem_dfop_tc_no_ranef_k2, test = TRUE) |>
-  kable(format.args = list(digits = 4))
    
-
----------
-
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-
    









    nparAICBICLikChisqDfPr(>Chisq)
    f_saem_dfop_tc_no_ranef_k29663.8661.9-322.9NANANA
    f_saem[[“DFOP”, “tc”]]10665.5663.4-322.80.280910.5961
    
-
    The AIC and BIC criteria are lower after removal of the ill-defined
-random effect for k2. The p value of the likelihood ratio
-test is much greater than 0.05, indicating that the model with the
-higher likelihood (here the model with random effects for all
-degradation parameters f_saem[["DFOP", "tc"]]) does not fit
-significantly better than the model with the lower likelihood (the
-reduced model f_saem_dfop_tc_no_ranef_k2).
    
-
    Therefore, AIC, BIC and likelihood ratio test suggest the use of the
-reduced model.
    
-
    The convergence of the fit is checked visually.
    
-
    
-Convergence plot for the NLHM DFOP fit with two-component error and without a random effect on 'k2'
    
-Convergence plot for the NLHM DFOP fit with two-component error and
-without a random effect on ‘k2’
-
    
-
    
-
    All parameters appear to have converged to a satisfactory degree. The
-final fit is plotted using the plot method from the mkin package.
    
-
    -plot(f_saem_dfop_tc_no_ranef_k2)
    
-
    
-Plot of the final NLHM DFOP fit
    
-Plot of the final NLHM DFOP fit
-
    
-
    
-
    Finally, a summary report of the fit is produced.
    
-
    -summary(f_saem_dfop_tc_no_ranef_k2)
    
-
    saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Thu Jan  5 08:19:13 2023 
-Date of summary: Thu Jan  5 08:19:13 2023 
-
-Equations:
-d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-           time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-           * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 4.075 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-   DMTA_0        k1        k2         g 
-98.759266  0.087034  0.009933  0.930827 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 k1 k2 g
-DMTA_0  98.76  0  0 0
-k1       0.00  1  0 0
-k2       0.00  0  1 0
-g        0.00  0  0 1
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC   BIC logLik
-  663.8 661.9 -322.9
-
-Optimised parameters:
-               est.     lower     upper
-DMTA_0    98.228939 96.285869 100.17201
-k1         0.064063  0.033477   0.09465
-k2         0.008297  0.005824   0.01077
-g          0.953821  0.914328   0.99331
-a.1        1.068479  0.869538   1.26742
-b.1        0.029424  0.022406   0.03644
-SD.DMTA_0  2.030437  0.404824   3.65605
-SD.k1      0.594692  0.256660   0.93272
-SD.g       1.006754  0.361327   1.65218
-
-Correlation: 
-   DMTA_0  k1      k2     
-k1  0.0218                
-k2  0.0556  0.0355        
-g  -0.0516 -0.0284 -0.2800
-
-Random effects:
-            est.  lower  upper
-SD.DMTA_0 2.0304 0.4048 3.6560
-SD.k1     0.5947 0.2567 0.9327
-SD.g      1.0068 0.3613 1.6522
-
-Variance model:
-       est.   lower   upper
-a.1 1.06848 0.86954 1.26742
-b.1 0.02942 0.02241 0.03644
-
-Estimated disappearance times:
-      DT50 DT90 DT50back DT50_k1 DT50_k2
-DMTA 11.45 41.4    12.46   10.82   83.54
    
-
    
-
    
-
    Alternative check of parameter identifiability
-
    
-
    The parameter check used in the illparms function is
-based on a quadratic approximation of the likelihood surface near its
-optimum, which is calculated using the Fisher Information Matrix (FIM).
-An alternative way to check parameter identifiability based on a
-multistart approach has recently been implemented in mkin.
    
-
    The graph below shows boxplots of the parameters obtained in 50 runs
-of the saem algorithm with different parameter combinations, sampled
-from the range of the parameters obtained for the individual datasets
-fitted separately using nonlinear regression.
    
-
    -f_saem_dfop_tc_multi <- multistart(f_saem[["DFOP", "tc"]], n = 50, cores = 15)
    
-
    -par(mar = c(6.1, 4.1, 2.1, 2.1))
-parplot(f_saem_dfop_tc_multi, lpos = "bottomright", ylim = c(0.3, 10), las = 2)
    
-
    
-Scaled parameters from the multistart runs, full model
    
-Scaled parameters from the multistart runs, full model
-
    
-
    
-
    The graph clearly confirms the lack of identifiability of the
-variance of k2 in the full model. The overparameterisation
-of the model also indicates a lack of identifiability of the variance of
-parameter g.
    
-
    The parameter boxplots of the multistart runs with the reduced model
-shown below indicate that all runs give similar results, regardless of
-the starting parameters.
    
-
    -f_saem_dfop_tc_no_ranef_k2_multi <- multistart(f_saem_dfop_tc_no_ranef_k2,
-  n = 50, cores = 15)
    
-
    -par(mar = c(6.1, 4.1, 2.1, 2.1))
-parplot(f_saem_dfop_tc_no_ranef_k2_multi, ylim = c(0.5, 2), las = 2,
-  lpos = "bottomright")
    
-
    
-Scaled parameters from the multistart runs, reduced model
    
-Scaled parameters from the multistart runs, reduced model
-
    
-
    
-
    When only the parameters of the top 25% of the fits are shown (based
-on a feature introduced in mkin 1.2.2 currently under development), the
-scatter is even less as shown below.
    
-
    -par(mar = c(6.1, 4.1, 2.1, 2.1))
-parplot(f_saem_dfop_tc_no_ranef_k2_multi, ylim = c(0.5, 2), las = 2, llquant = 0.25,
-  lpos = "bottomright")
    
-
    
-Scaled parameters from the multistart runs, reduced model, fits with the top 25\% likelihood values
    
-Scaled parameters from the multistart runs, reduced model, fits with the
-top 25% likelihood values
-
    
-
    
-
    
-
    
-
    
-
    Conclusions
-
    
-
    Fitting the four parent degradation models SFO, FOMC, DFOP and HS as
-part of hierarchical model fits with two different error models and
-normal distributions of the transformed degradation parameters works
-without technical problems. The biphasic models DFOP and HS gave the
-best fit to the data, but the default parameter distribution model was
-not fully identifiable. Removing the random effect for the second
-kinetic rate constant of the DFOP model resulted in a reduced model that
-was fully identifiable and showed the lowest values for the model
-selection criteria AIC and BIC. The reliability of the identification of
-all model parameters was confirmed using multiple starting values.
    
-
    
-
    
-
    Appendix
-
    
-
    
-
    Hierarchical model fit listings
-
    
-
-Hierarchical mkin fit of the SFO model with error model const
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Thu Jan  5 08:19:06 2023 
-Date of summary: Thu Jan  5 08:20:11 2023 
-
-Equations:
-d_DMTA/dt = - k_DMTA * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 1.09 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
- DMTA_0  k_DMTA 
-97.2953  0.0566 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 k_DMTA
-DMTA_0   97.3      0
-k_DMTA    0.0      1
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC   BIC logLik
-  796.3 795.3 -393.2
-
-Optimised parameters:
-              est.    lower   upper
-DMTA_0    97.28130 95.71113 98.8515
-k_DMTA     0.05665  0.02909  0.0842
-a.1        2.66442  2.35579  2.9731
-SD.DMTA_0  1.54776  0.15447  2.9411
-SD.k_DMTA  0.60690  0.26248  0.9513
-
-Correlation: 
-       DMTA_0
-k_DMTA 0.0168
-
-Random effects:
-            est.  lower  upper
-SD.DMTA_0 1.5478 0.1545 2.9411
-SD.k_DMTA 0.6069 0.2625 0.9513
-
-Variance model:
-     est. lower upper
-a.1 2.664 2.356 2.973
-
-Estimated disappearance times:
-      DT50  DT90
-DMTA 12.24 40.65
-
-
    
-
    
-
-Hierarchical mkin fit of the SFO model with error model tc
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Thu Jan  5 08:19:07 2023 
-Date of summary: Thu Jan  5 08:20:11 2023 
-
-Equations:
-d_DMTA/dt = - k_DMTA * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 2.441 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-  DMTA_0   k_DMTA 
-96.99175  0.05603 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 k_DMTA
-DMTA_0  96.99      0
-k_DMTA   0.00      1
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC   BIC logLik
-  798.3 797.1 -393.2
-
-Optimised parameters:
-               est.     lower    upper
-DMTA_0    97.271822 95.703157 98.84049
-k_DMTA     0.056638  0.029110  0.08417
-a.1        2.660081  2.230398  3.08976
-b.1        0.001665 -0.006911  0.01024
-SD.DMTA_0  1.545520  0.145035  2.94601
-SD.k_DMTA  0.606422  0.262274  0.95057
-
-Correlation: 
-       DMTA_0
-k_DMTA 0.0169
-
-Random effects:
-            est.  lower  upper
-SD.DMTA_0 1.5455 0.1450 2.9460
-SD.k_DMTA 0.6064 0.2623 0.9506
-
-Variance model:
-        est.     lower   upper
-a.1 2.660081  2.230398 3.08976
-b.1 0.001665 -0.006911 0.01024
-
-Estimated disappearance times:
-      DT50  DT90
-DMTA 12.24 40.65
-
-
    
-
    
-
-Hierarchical mkin fit of the FOMC model with error model const
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Thu Jan  5 08:19:06 2023 
-Date of summary: Thu Jan  5 08:20:11 2023 
-
-Equations:
-d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 1.156 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
- DMTA_0   alpha    beta 
- 98.292   9.909 156.341 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 alpha beta
-DMTA_0  98.29     0    0
-alpha    0.00     1    0
-beta     0.00     0    1
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC   BIC logLik
-  734.2 732.7 -360.1
-
-Optimised parameters:
-              est.   lower   upper
-DMTA_0     98.3435 96.9033  99.784
-alpha       7.2007  2.5889  11.812
-beta      112.8746 34.8816 190.868
-a.1         2.0459  1.8054   2.286
-SD.DMTA_0   1.4795  0.2717   2.687
-SD.alpha    0.6396  0.1509   1.128
-SD.beta     0.6874  0.1587   1.216
-
-Correlation: 
-      DMTA_0  alpha  
-alpha -0.1125        
-beta  -0.1227  0.3632
-
-Random effects:
-            est.  lower upper
-SD.DMTA_0 1.4795 0.2717 2.687
-SD.alpha  0.6396 0.1509 1.128
-SD.beta   0.6874 0.1587 1.216
-
-Variance model:
-     est. lower upper
-a.1 2.046 1.805 2.286
-
-Estimated disappearance times:
-      DT50  DT90 DT50back
-DMTA 11.41 42.53     12.8
-
-
    
-
    
-
-Hierarchical mkin fit of the FOMC model with error model tc
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Thu Jan  5 08:19:07 2023 
-Date of summary: Thu Jan  5 08:20:11 2023 
-
-Equations:
-d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 2.729 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-DMTA_0  alpha   beta 
-98.772  4.663 92.597 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 alpha beta
-DMTA_0  98.77     0    0
-alpha    0.00     1    0
-beta     0.00     0    1
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC   BIC logLik
-  720.4 718.8 -352.2
-
-Optimised parameters:
-              est.    lower     upper
-DMTA_0    98.99136 97.26011 100.72261
-alpha      5.86312  2.57485   9.15138
-beta      88.55571 29.20889 147.90254
-a.1        1.51063  1.24384   1.77741
-b.1        0.02824  0.02040   0.03609
-SD.DMTA_0  1.57436 -0.04867   3.19739
-SD.alpha   0.59871  0.17132   1.02611
-SD.beta    0.72994  0.22849   1.23139
-
-Correlation: 
-      DMTA_0  alpha  
-alpha -0.1363        
-beta  -0.1414  0.2542
-
-Random effects:
-            est.    lower upper
-SD.DMTA_0 1.5744 -0.04867 3.197
-SD.alpha  0.5987  0.17132 1.026
-SD.beta   0.7299  0.22849 1.231
-
-Variance model:
-       est.  lower   upper
-a.1 1.51063 1.2438 1.77741
-b.1 0.02824 0.0204 0.03609
-
-Estimated disappearance times:
-      DT50 DT90 DT50back
-DMTA 11.11 42.6    12.82
-
-
    
-
    
-
-Hierarchical mkin fit of the DFOP model with error model const
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Thu Jan  5 08:19:07 2023 
-Date of summary: Thu Jan  5 08:20:11 2023 
-
-Equations:
-d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-           time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-           * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 2.007 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
-  DMTA_0       k1       k2        g 
-98.64383  0.09211  0.02999  0.76814 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 k1 k2 g
-DMTA_0  98.64  0  0 0
-k1       0.00  1  0 0
-k2       0.00  0  1 0
-g        0.00  0  0 1
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC BIC logLik
-  711.8 710 -346.9
-
-Optimised parameters:
-               est.     lower    upper
-DMTA_0    98.092481 96.573898 99.61106
-k1         0.062499  0.030336  0.09466
-k2         0.009065 -0.005133  0.02326
-g          0.948967  0.862079  1.03586
-a.1        1.821671  1.604774  2.03857
-SD.DMTA_0  1.677785  0.472066  2.88350
-SD.k1      0.634962  0.270788  0.99914
-SD.k2      1.033498 -0.205994  2.27299
-SD.g       1.710046  0.428642  2.99145
-
-Correlation: 
-   DMTA_0  k1      k2     
-k1  0.0246                
-k2  0.0491  0.0953        
-g  -0.0552 -0.0889 -0.4795
-
-Random effects:
-           est.   lower  upper
-SD.DMTA_0 1.678  0.4721 2.8835
-SD.k1     0.635  0.2708 0.9991
-SD.k2     1.033 -0.2060 2.2730
-SD.g      1.710  0.4286 2.9914
-
-Variance model:
-     est. lower upper
-a.1 1.822 1.605 2.039
-
-Estimated disappearance times:
-      DT50 DT90 DT50back DT50_k1 DT50_k2
-DMTA 11.79 42.8    12.88   11.09   76.46
-
-
    
-
    
-
-Hierarchical mkin fit of the DFOP model with error model tc
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Thu Jan  5 08:19:08 2023 
-Date of summary: Thu Jan  5 08:20:11 2023 
-
-Equations:
-d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-           time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-           * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 3.033 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-   DMTA_0        k1        k2         g 
-98.759266  0.087034  0.009933  0.930827 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 k1 k2 g
-DMTA_0  98.76  0  0 0
-k1       0.00  1  0 0
-k2       0.00  0  1 0
-g        0.00  0  0 1
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC   BIC logLik
-  665.5 663.4 -322.8
-
-Optimised parameters:
-               est.     lower     upper
-DMTA_0    98.377019 96.447952 100.30609
-k1         0.064843  0.034607   0.09508
-k2         0.008895  0.006368   0.01142
-g          0.949696  0.903815   0.99558
-a.1        1.065241  0.865754   1.26473
-b.1        0.029340  0.022336   0.03634
-SD.DMTA_0  2.007754  0.387982   3.62753
-SD.k1      0.580473  0.250286   0.91066
-SD.k2      0.006105 -4.920337   4.93255
-SD.g       1.097149  0.412779   1.78152
-
-Correlation: 
-   DMTA_0  k1      k2     
-k1  0.0235                
-k2  0.0595  0.0424        
-g  -0.0470 -0.0278 -0.2731
-
-Random effects:
-              est.   lower  upper
-SD.DMTA_0 2.007754  0.3880 3.6275
-SD.k1     0.580473  0.2503 0.9107
-SD.k2     0.006105 -4.9203 4.9325
-SD.g      1.097149  0.4128 1.7815
-
-Variance model:
-       est.   lower   upper
-a.1 1.06524 0.86575 1.26473
-b.1 0.02934 0.02234 0.03634
-
-Estimated disappearance times:
-      DT50  DT90 DT50back DT50_k1 DT50_k2
-DMTA 11.36 41.32    12.44   10.69   77.92
-
-
    
-
    
-
-Hierarchical mkin fit of the HS model with error model const
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Thu Jan  5 08:19:07 2023 
-Date of summary: Thu Jan  5 08:20:11 2023 
-
-Equations:
-d_DMTA/dt = - ifelse(time <= tb, k1, k2) * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 2.004 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
-  DMTA_0       k1       k2       tb 
-97.82176  0.06931  0.02997 11.13945 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 k1 k2 tb
-DMTA_0  97.82  0  0  0
-k1       0.00  1  0  0
-k2       0.00  0  1  0
-tb       0.00  0  0  1
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-  AIC   BIC logLik
-  714 712.1   -348
-
-Optimised parameters:
-              est.    lower    upper
-DMTA_0    98.16102 96.47747 99.84456
-k1         0.07876  0.05261  0.10491
-k2         0.02227  0.01706  0.02747
-tb        13.99089 -7.40049 35.38228
-a.1        1.82305  1.60700  2.03910
-SD.DMTA_0  1.88413  0.56204  3.20622
-SD.k1      0.34292  0.10482  0.58102
-SD.k2      0.19851  0.01718  0.37985
-SD.tb      1.68168  0.58064  2.78272
-
-Correlation: 
-   DMTA_0  k1      k2     
-k1  0.0142                
-k2  0.0001 -0.0025        
-tb  0.0165 -0.1256 -0.0301
-
-Random effects:
-            est.   lower  upper
-SD.DMTA_0 1.8841 0.56204 3.2062
-SD.k1     0.3429 0.10482 0.5810
-SD.k2     0.1985 0.01718 0.3798
-SD.tb     1.6817 0.58064 2.7827
-
-Variance model:
-     est. lower upper
-a.1 1.823 1.607 2.039
-
-Estimated disappearance times:
-      DT50  DT90 DT50back DT50_k1 DT50_k2
-DMTA 8.801 67.91    20.44   8.801   31.13
-
-
    
-
    
-
-Hierarchical mkin fit of the HS model with error model tc
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Thu Jan  5 08:19:08 2023 
-Date of summary: Thu Jan  5 08:20:11 2023 
-
-Equations:
-d_DMTA/dt = - ifelse(time <= tb, k1, k2) * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 3.287 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-  DMTA_0       k1       k2       tb 
-98.45190  0.07525  0.02576 19.19375 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 k1 k2 tb
-DMTA_0  98.45  0  0  0
-k1       0.00  1  0  0
-k2       0.00  0  1  0
-tb       0.00  0  0  1
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC BIC logLik
-  667.1 665 -323.6
-
-Optimised parameters:
-              est.    lower    upper
-DMTA_0    97.76570 95.81350 99.71791
-k1         0.05855  0.03080  0.08630
-k2         0.02337  0.01664  0.03010
-tb        31.09638 29.38289 32.80987
-a.1        1.08835  0.88590  1.29080
-b.1        0.02964  0.02257  0.03671
-SD.DMTA_0  2.04877  0.42607  3.67147
-SD.k1      0.59166  0.25621  0.92711
-SD.k2      0.30698  0.09561  0.51835
-SD.tb      0.01274 -0.10914  0.13462
-
-Correlation: 
-   DMTA_0  k1      k2     
-k1  0.0160                
-k2 -0.0070 -0.0024        
-tb -0.0668 -0.0103 -0.2013
-
-Random effects:
-             est.    lower  upper
-SD.DMTA_0 2.04877  0.42607 3.6715
-SD.k1     0.59166  0.25621 0.9271
-SD.k2     0.30698  0.09561 0.5183
-SD.tb     0.01274 -0.10914 0.1346
-
-Variance model:
-       est.   lower   upper
-a.1 1.08835 0.88590 1.29080
-b.1 0.02964 0.02257 0.03671
-
-Estimated disappearance times:
-      DT50  DT90 DT50back DT50_k1 DT50_k2
-DMTA 11.84 51.71    15.57   11.84   29.66
-
-
    
-
    
-
    
-
    
-
    Hierarchical model convergence plots
-
    
-
    
-Convergence plot for the NLHM SFO fit with constant variance
    
-Convergence plot for the NLHM SFO fit with constant variance
-
    
-
    
-
    
-Convergence plot for the NLHM SFO fit with two-component error
    
-Convergence plot for the NLHM SFO fit with two-component error
-
    
-
    
-
    
-Convergence plot for the NLHM FOMC fit with constant variance
    
-Convergence plot for the NLHM FOMC fit with constant variance
-
    
-
    
-
    
-Convergence plot for the NLHM FOMC fit with two-component error
    
-Convergence plot for the NLHM FOMC fit with two-component error
-
    
-
    
-
    
-Convergence plot for the NLHM DFOP fit with constant variance
    
-Convergence plot for the NLHM DFOP fit with constant variance
-
    
-
    
-
    
-Convergence plot for the NLHM DFOP fit with two-component error
    
-Convergence plot for the NLHM DFOP fit with two-component error
-
    
-
    
-
    
-Convergence plot for the NLHM HS fit with constant variance
    
-Convergence plot for the NLHM HS fit with constant variance
-
    
-
    
-
    
-Convergence plot for the NLHM HS fit with two-component error
    
-Convergence plot for the NLHM HS fit with two-component error
-
    
-
    
-
    
-
    
-
    Session info
-
    
-
    R version 4.2.2 Patched (2022-11-10 r83330)
-Platform: x86_64-pc-linux-gnu (64-bit)
-Running under: Debian GNU/Linux bookworm/sid
-
-Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/openblas-serial/libblas.so.3
-LAPACK: /usr/lib/x86_64-linux-gnu/openblas-serial/libopenblas-r0.3.21.so
-
-locale:
- [1] LC_CTYPE=de_DE.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=de_DE.UTF-8        LC_COLLATE=de_DE.UTF-8    
- [5] LC_MONETARY=de_DE.UTF-8    LC_MESSAGES=de_DE.UTF-8   
- [7] LC_PAPER=de_DE.UTF-8       LC_NAME=C                 
- [9] LC_ADDRESS=C               LC_TELEPHONE=C            
-[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C       
-
-attached base packages:
-[1] parallel  stats     graphics  grDevices utils     datasets  methods  
-[8] base     
-
-other attached packages:
-[1] saemix_3.2 npde_3.3   knitr_1.41 mkin_1.2.2
-
-loaded via a namespace (and not attached):
- [1] deSolve_1.34      zoo_1.8-11        tidyselect_1.2.0  xfun_0.35        
- [5] bslib_0.4.2       purrr_1.0.0       lattice_0.20-45   colorspace_2.0-3 
- [9] vctrs_0.5.1       generics_0.1.3    htmltools_0.5.4   yaml_2.3.6       
-[13] utf8_1.2.2        rlang_1.0.6       pkgdown_2.0.7     jquerylib_0.1.4  
-[17] pillar_1.8.1      glue_1.6.2        DBI_1.1.3         lifecycle_1.0.3  
-[21] stringr_1.5.0     munsell_0.5.0     gtable_0.3.1      ragg_1.2.4       
-[25] codetools_0.2-18  memoise_2.0.1     evaluate_0.19     fastmap_1.1.0    
-[29] lmtest_0.9-40     fansi_1.0.3       highr_0.9         scales_1.2.1     
-[33] cachem_1.0.6      desc_1.4.2        jsonlite_1.8.4    systemfonts_1.0.4
-[37] fs_1.5.2          textshaping_0.3.6 gridExtra_2.3     ggplot2_3.4.0    
-[41] digest_0.6.31     stringi_1.7.8     dplyr_1.0.10      grid_4.2.2       
-[45] rprojroot_2.0.3   cli_3.5.0         tools_4.2.2       magrittr_2.0.3   
-[49] sass_0.4.4        tibble_3.1.8      pkgconfig_2.0.3   assertthat_0.2.1 
-[53] rmarkdown_2.19    R6_2.5.1          mclust_6.0.0      nlme_3.1-161     
-[57] compiler_4.2.2   
    
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-
-      
    
-  
    
-
    Developed by Johannes Ranke.
    
-
    
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-  
    
-
    Site built with pkgdown 2.0.7.
    
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-Example evaluation of FOCUS Example Dataset D • mkin
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    Example evaluation of FOCUS Example Dataset
-D
    
-                        
    Johannes
-Ranke
    
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    Last change 31 January 2019
-(rebuilt 2023-04-16)
    
-      
-      Source: vignettes/FOCUS_D.rmd
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    This is just a very simple vignette showing how to fit a degradation
-model for a parent compound with one transformation product using
-mkin. After loading the library we look at the data. We
-have observed concentrations in the column named value at
-the times specified in column time for the two observed
-variables named parent and m1.
    
-
    -library(mkin, quietly = TRUE)
-print(FOCUS_2006_D)
    
-
    ##      name time  value
-## 1  parent    0  99.46
-## 2  parent    0 102.04
-## 3  parent    1  93.50
-## 4  parent    1  92.50
-## 5  parent    3  63.23
-## 6  parent    3  68.99
-## 7  parent    7  52.32
-## 8  parent    7  55.13
-## 9  parent   14  27.27
-## 10 parent   14  26.64
-## 11 parent   21  11.50
-## 12 parent   21  11.64
-## 13 parent   35   2.85
-## 14 parent   35   2.91
-## 15 parent   50   0.69
-## 16 parent   50   0.63
-## 17 parent   75   0.05
-## 18 parent   75   0.06
-## 19 parent  100     NA
-## 20 parent  100     NA
-## 21 parent  120     NA
-## 22 parent  120     NA
-## 23     m1    0   0.00
-## 24     m1    0   0.00
-## 25     m1    1   4.84
-## 26     m1    1   5.64
-## 27     m1    3  12.91
-## 28     m1    3  12.96
-## 29     m1    7  22.97
-## 30     m1    7  24.47
-## 31     m1   14  41.69
-## 32     m1   14  33.21
-## 33     m1   21  44.37
-## 34     m1   21  46.44
-## 35     m1   35  41.22
-## 36     m1   35  37.95
-## 37     m1   50  41.19
-## 38     m1   50  40.01
-## 39     m1   75  40.09
-## 40     m1   75  33.85
-## 41     m1  100  31.04
-## 42     m1  100  33.13
-## 43     m1  120  25.15
-## 44     m1  120  33.31
    
-
    Next we specify the degradation model: The parent compound degrades
-with simple first-order kinetics (SFO) to one metabolite named m1, which
-also degrades with SFO kinetics.
    
-
    The call to mkinmod returns a degradation model. The differential
-equations represented in R code can be found in the character vector
-$diffs of the mkinmod object. If a C compiler
-(gcc) is installed and functional, the differential equation model will
-be compiled from auto-generated C code.
    
-
    -SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
    
-
    ## Temporary DLL for differentials generated and loaded
    
-
    -print(SFO_SFO$diffs)
    
-
    ##                                                    parent 
-##                          "d_parent = - k_parent * parent" 
-##                                                        m1 
-## "d_m1 = + f_parent_to_m1 * k_parent * parent - k_m1 * m1"
    
-
    We do the fitting without progress report
-(quiet = TRUE).
    
-
    -fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
    
-
    ## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE): Observations with
-## value of zero were removed from the data
    
-
    A plot of the fit including a residual plot for both observed
-variables is obtained using the plot_sep method for
-mkinfit objects, which shows separate graphs for all
-compounds and their residuals.
    
-
    -plot_sep(fit, lpos = c("topright", "bottomright"))
    
-
    
-
    Confidence intervals for the parameter estimates are obtained using
-the mkinparplot function.
    
-
-
    
-
    A comprehensive report of the results is obtained using the
-summary method for mkinfit objects.
    
-
    -summary(fit)
    
-
    ## mkin version used for fitting:    1.2.3 
-## R version used for fitting:       4.2.3 
-## Date of fit:     Sun Apr 16 08:35:12 2023 
-## Date of summary: Sun Apr 16 08:35:12 2023 
-## 
-## Equations:
-## d_parent/dt = - k_parent * parent
-## d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
-## 
-## Model predictions using solution type analytical 
-## 
-## Fitted using 401 model solutions performed in 0.05 s
-## 
-## Error model: Constant variance 
-## 
-## Error model algorithm: OLS 
-## 
-## Starting values for parameters to be optimised:
-##                   value   type
-## parent_0       100.7500  state
-## k_parent         0.1000 deparm
-## k_m1             0.1001 deparm
-## f_parent_to_m1   0.5000 deparm
-## 
-## Starting values for the transformed parameters actually optimised:
-##                      value lower upper
-## parent_0        100.750000  -Inf   Inf
-## log_k_parent     -2.302585  -Inf   Inf
-## log_k_m1         -2.301586  -Inf   Inf
-## f_parent_qlogis   0.000000  -Inf   Inf
-## 
-## Fixed parameter values:
-##      value  type
-## m1_0     0 state
-## 
-## 
-## Warning(s): 
-## Observations with value of zero were removed from the data
-## 
-## Results:
-## 
-##        AIC      BIC    logLik
-##   204.4486 212.6365 -97.22429
-## 
-## Optimised, transformed parameters with symmetric confidence intervals:
-##                 Estimate Std. Error   Lower    Upper
-## parent_0        99.60000    1.57000 96.4000 102.8000
-## log_k_parent    -2.31600    0.04087 -2.3990  -2.2330
-## log_k_m1        -5.24700    0.13320 -5.5180  -4.9770
-## f_parent_qlogis  0.05792    0.08926 -0.1237   0.2395
-## sigma            3.12600    0.35850  2.3960   3.8550
-## 
-## Parameter correlation:
-##                   parent_0 log_k_parent   log_k_m1 f_parent_qlogis      sigma
-## parent_0         1.000e+00    5.174e-01 -1.688e-01      -5.471e-01 -1.172e-06
-## log_k_parent     5.174e-01    1.000e+00 -3.263e-01      -5.426e-01 -8.483e-07
-## log_k_m1        -1.688e-01   -3.263e-01  1.000e+00       7.478e-01  8.205e-07
-## f_parent_qlogis -5.471e-01   -5.426e-01  7.478e-01       1.000e+00  1.305e-06
-## sigma           -1.172e-06   -8.483e-07  8.205e-07       1.305e-06  1.000e+00
-## 
-## Backtransformed parameters:
-## Confidence intervals for internally transformed parameters are asymmetric.
-## t-test (unrealistically) based on the assumption of normal distribution
-## for estimators of untransformed parameters.
-##                 Estimate t value    Pr(>t)     Lower     Upper
-## parent_0       99.600000  63.430 2.298e-36 96.400000 1.028e+02
-## k_parent        0.098700  24.470 4.955e-23  0.090820 1.073e-01
-## k_m1            0.005261   7.510 6.165e-09  0.004012 6.898e-03
-## f_parent_to_m1  0.514500  23.070 3.104e-22  0.469100 5.596e-01
-## sigma           3.126000   8.718 2.235e-10  2.396000 3.855e+00
-## 
-## FOCUS Chi2 error levels in percent:
-##          err.min n.optim df
-## All data   6.398       4 15
-## parent     6.459       2  7
-## m1         4.690       2  8
-## 
-## Resulting formation fractions:
-##                 ff
-## parent_m1   0.5145
-## parent_sink 0.4855
-## 
-## Estimated disappearance times:
-##           DT50   DT90
-## parent   7.023  23.33
-## m1     131.761 437.70
-## 
-## Data:
-##  time variable observed predicted   residual
-##     0   parent    99.46  99.59848 -1.385e-01
-##     0   parent   102.04  99.59848  2.442e+00
-##     1   parent    93.50  90.23787  3.262e+00
-##     1   parent    92.50  90.23787  2.262e+00
-##     3   parent    63.23  74.07319 -1.084e+01
-##     3   parent    68.99  74.07319 -5.083e+00
-##     7   parent    52.32  49.91207  2.408e+00
-##     7   parent    55.13  49.91207  5.218e+00
-##    14   parent    27.27  25.01258  2.257e+00
-##    14   parent    26.64  25.01258  1.627e+00
-##    21   parent    11.50  12.53462 -1.035e+00
-##    21   parent    11.64  12.53462 -8.946e-01
-##    35   parent     2.85   3.14787 -2.979e-01
-##    35   parent     2.91   3.14787 -2.379e-01
-##    50   parent     0.69   0.71624 -2.624e-02
-##    50   parent     0.63   0.71624 -8.624e-02
-##    75   parent     0.05   0.06074 -1.074e-02
-##    75   parent     0.06   0.06074 -7.382e-04
-##     1       m1     4.84   4.80296  3.704e-02
-##     1       m1     5.64   4.80296  8.370e-01
-##     3       m1    12.91  13.02400 -1.140e-01
-##     3       m1    12.96  13.02400 -6.400e-02
-##     7       m1    22.97  25.04476 -2.075e+00
-##     7       m1    24.47  25.04476 -5.748e-01
-##    14       m1    41.69  36.69003  5.000e+00
-##    14       m1    33.21  36.69003 -3.480e+00
-##    21       m1    44.37  41.65310  2.717e+00
-##    21       m1    46.44  41.65310  4.787e+00
-##    35       m1    41.22  43.31313 -2.093e+00
-##    35       m1    37.95  43.31313 -5.363e+00
-##    50       m1    41.19  41.21832 -2.832e-02
-##    50       m1    40.01  41.21832 -1.208e+00
-##    75       m1    40.09  36.44704  3.643e+00
-##    75       m1    33.85  36.44704 -2.597e+00
-##   100       m1    31.04  31.98162 -9.416e-01
-##   100       m1    33.13  31.98162  1.148e+00
-##   120       m1    25.15  28.78984 -3.640e+00
-##   120       m1    33.31  28.78984  4.520e+00
    
-  
    
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-      
    
-  
    
-
    Developed by Johannes Ranke.
    
-
    
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-
    
-  
    
-
    Site built with pkgdown 2.0.7.
    
-
    
-
-      
    
-
    
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-  
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diff --git a/docs/dev/articles/FOCUS_D_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/dev/articles/FOCUS_D_files/accessible-code-block-0.0.1/empty-anchor.js
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-// Hide empty  tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
-// v0.0.1
-// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
-
-document.addEventListener('DOMContentLoaded', function() {
-  const codeList = document.getElementsByClassName("sourceCode");
-  for (var i = 0; i < codeList.length; i++) {
-    var linkList = codeList[i].getElementsByTagName('a');
-    for (var j = 0; j < linkList.length; j++) {
-      if (linkList[j].innerHTML === "") {
-        linkList[j].setAttribute('aria-hidden', 'true');
-      }
-    }
-  }
-});
diff --git a/docs/dev/articles/FOCUS_D_files/anchor-sections-1.0/anchor-sections.css b/docs/dev/articles/FOCUS_D_files/anchor-sections-1.0/anchor-sections.css
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-/* Styles for section anchors */
-a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
-a.anchor-section::before {content: '#';}
-.hasAnchor:hover a.anchor-section {visibility: visible;}
diff --git a/docs/dev/articles/FOCUS_D_files/anchor-sections-1.0/anchor-sections.js b/docs/dev/articles/FOCUS_D_files/anchor-sections-1.0/anchor-sections.js
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-// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
-document.addEventListener('DOMContentLoaded', function() {
-  // Do nothing if AnchorJS is used
-  if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
-    return;
-  }
-
-  const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
-
-  // Do nothing if sections are already anchored
-  if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
-    return null;
-  }
-
-  // Use section id when pandoc runs with --section-divs
-  const section_id = function(x) {
-    return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
-            ? x.id : '');
-  };
-
-  // Add anchors
-  h.forEach(function(x) {
-    const id = x.id || section_id(x.parentElement);
-    if (id === '') {
-      return null;
-    }
-    let anchor = document.createElement('a');
-    anchor.href = '#' + id;
-    anchor.classList = ['anchor-section'];
-    x.classList.add('hasAnchor');
-    x.appendChild(anchor);
-  });
-});
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-// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
-// be compatible with the behavior of Pandoc < 2.8).
-document.addEventListener('DOMContentLoaded', function(e) {
-  var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
-  var i, h, a;
-  for (i = 0; i < hs.length; i++) {
-    h = hs[i];
-    if (!/^h[1-6]$/i.test(h.tagName)) continue;  // it should be a header h1-h6
-    a = h.attributes;
-    while (a.length > 0) h.removeAttribute(a[0].name);
-  }
-});
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-
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-
-
-Example evaluation of FOCUS Laboratory Data L1 to L3 • mkin
-
-
-
-
-
-
-
-
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-    
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-    
    
-      
    
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-  
    
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-      
    Example evaluation of FOCUS Laboratory Data L1
-to L3
    
-                        
    Johannes
-Ranke
    
-            
-            
    Last change 18 May 2022
-(rebuilt 2023-04-16)
    
-      
-      Source: vignettes/FOCUS_L.rmd
-      
-
-    
    
-
-    
-    
-
    
-
    Laboratory Data L1
-
    
-
    The following code defines example dataset L1 from the FOCUS kinetics
-report, p. 284:
    
-
    -library("mkin", quietly = TRUE)
-FOCUS_2006_L1 = data.frame(
-  t = rep(c(0, 1, 2, 3, 5, 7, 14, 21, 30), each = 2),
-  parent = c(88.3, 91.4, 85.6, 84.5, 78.9, 77.6,
-             72.0, 71.9, 50.3, 59.4, 47.0, 45.1,
-             27.7, 27.3, 10.0, 10.4, 2.9, 4.0))
-FOCUS_2006_L1_mkin <- mkin_wide_to_long(FOCUS_2006_L1)
    
-
    Here we use the assumptions of simple first order (SFO), the case of
-declining rate constant over time (FOMC) and the case of two different
-phases of the kinetics (DFOP). For a more detailed discussion of the
-models, please see the FOCUS kinetics report.
    
-
    Since mkin version 0.9-32 (July 2014), we can use shorthand notation
-like "SFO" for parent only degradation models. The
-following two lines fit the model and produce the summary report of the
-model fit. This covers the numerical analysis given in the FOCUS
-report.
    
-
    -m.L1.SFO <- mkinfit("SFO", FOCUS_2006_L1_mkin, quiet = TRUE)
-summary(m.L1.SFO)
    
-
    ## mkin version used for fitting:    1.2.3 
-## R version used for fitting:       4.2.3 
-## Date of fit:     Sun Apr 16 08:35:14 2023 
-## Date of summary: Sun Apr 16 08:35:14 2023 
-## 
-## Equations:
-## d_parent/dt = - k_parent * parent
-## 
-## Model predictions using solution type analytical 
-## 
-## Fitted using 133 model solutions performed in 0.011 s
-## 
-## Error model: Constant variance 
-## 
-## Error model algorithm: OLS 
-## 
-## Starting values for parameters to be optimised:
-##          value   type
-## parent_0 89.85  state
-## k_parent  0.10 deparm
-## 
-## Starting values for the transformed parameters actually optimised:
-##                  value lower upper
-## parent_0     89.850000  -Inf   Inf
-## log_k_parent -2.302585  -Inf   Inf
-## 
-## Fixed parameter values:
-## None
-## 
-## Results:
-## 
-##        AIC     BIC    logLik
-##   93.88778 96.5589 -43.94389
-## 
-## Optimised, transformed parameters with symmetric confidence intervals:
-##              Estimate Std. Error  Lower  Upper
-## parent_0       92.470    1.28200 89.740 95.200
-## log_k_parent   -2.347    0.03763 -2.428 -2.267
-## sigma           2.780    0.46330  1.792  3.767
-## 
-## Parameter correlation:
-##                parent_0 log_k_parent      sigma
-## parent_0      1.000e+00    6.186e-01 -1.516e-09
-## log_k_parent  6.186e-01    1.000e+00 -3.124e-09
-## sigma        -1.516e-09   -3.124e-09  1.000e+00
-## 
-## Backtransformed parameters:
-## Confidence intervals for internally transformed parameters are asymmetric.
-## t-test (unrealistically) based on the assumption of normal distribution
-## for estimators of untransformed parameters.
-##          Estimate t value    Pr(>t)    Lower   Upper
-## parent_0 92.47000   72.13 8.824e-21 89.74000 95.2000
-## k_parent  0.09561   26.57 2.487e-14  0.08824  0.1036
-## sigma     2.78000    6.00 1.216e-05  1.79200  3.7670
-## 
-## FOCUS Chi2 error levels in percent:
-##          err.min n.optim df
-## All data   3.424       2  7
-## parent     3.424       2  7
-## 
-## Estimated disappearance times:
-##         DT50  DT90
-## parent 7.249 24.08
-## 
-## Data:
-##  time variable observed predicted residual
-##     0   parent     88.3    92.471  -4.1710
-##     0   parent     91.4    92.471  -1.0710
-##     1   parent     85.6    84.039   1.5610
-##     1   parent     84.5    84.039   0.4610
-##     2   parent     78.9    76.376   2.5241
-##     2   parent     77.6    76.376   1.2241
-##     3   parent     72.0    69.412   2.5884
-##     3   parent     71.9    69.412   2.4884
-##     5   parent     50.3    57.330  -7.0301
-##     5   parent     59.4    57.330   2.0699
-##     7   parent     47.0    47.352  -0.3515
-##     7   parent     45.1    47.352  -2.2515
-##    14   parent     27.7    24.247   3.4528
-##    14   parent     27.3    24.247   3.0528
-##    21   parent     10.0    12.416  -2.4163
-##    21   parent     10.4    12.416  -2.0163
-##    30   parent      2.9     5.251  -2.3513
-##    30   parent      4.0     5.251  -1.2513
    
-
    A plot of the fit is obtained with the plot function for mkinfit
-objects.
    
-
    -plot(m.L1.SFO, show_errmin = TRUE, main = "FOCUS L1 - SFO")
    
-
    
-
    The residual plot can be easily obtained by
    
-
    -mkinresplot(m.L1.SFO, ylab = "Observed", xlab = "Time")
    
-
    
-
    For comparison, the FOMC model is fitted as well, and the \(\chi^2\) error level is checked.
    
-
    -m.L1.FOMC <- mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet=TRUE)
    
-
    ## Warning in mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet = TRUE): Optimisation did not converge:
-## false convergence (8)
    
-
    -plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")
    
-
    
-
    -summary(m.L1.FOMC, data = FALSE)
    
-
    ## Warning in sqrt(diag(covar)): NaNs produced
    
-
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
-
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result
-## is doubtful
    
-
    ## mkin version used for fitting:    1.2.3 
-## R version used for fitting:       4.2.3 
-## Date of fit:     Sun Apr 16 08:35:14 2023 
-## Date of summary: Sun Apr 16 08:35:14 2023 
-## 
-## Equations:
-## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
-## 
-## Model predictions using solution type analytical 
-## 
-## Fitted using 369 model solutions performed in 0.025 s
-## 
-## Error model: Constant variance 
-## 
-## Error model algorithm: OLS 
-## 
-## Starting values for parameters to be optimised:
-##          value   type
-## parent_0 89.85  state
-## alpha     1.00 deparm
-## beta     10.00 deparm
-## 
-## Starting values for the transformed parameters actually optimised:
-##               value lower upper
-## parent_0  89.850000  -Inf   Inf
-## log_alpha  0.000000  -Inf   Inf
-## log_beta   2.302585  -Inf   Inf
-## 
-## Fixed parameter values:
-## None
-## 
-## 
-## Warning(s): 
-## Optimisation did not converge:
-## false convergence (8)
-## 
-## Results:
-## 
-##        AIC      BIC   logLik
-##   95.88781 99.44929 -43.9439
-## 
-## Optimised, transformed parameters with symmetric confidence intervals:
-##           Estimate Std. Error  Lower  Upper
-## parent_0     92.47     1.2820 89.720 95.220
-## log_alpha    13.78        NaN    NaN    NaN
-## log_beta     16.13        NaN    NaN    NaN
-## sigma         2.78     0.4598  1.794  3.766
-## 
-## Parameter correlation:
-##            parent_0 log_alpha log_beta     sigma
-## parent_0  1.0000000       NaN      NaN 0.0001671
-## log_alpha       NaN         1      NaN       NaN
-## log_beta        NaN       NaN        1       NaN
-## sigma     0.0001671       NaN      NaN 1.0000000
-## 
-## Backtransformed parameters:
-## Confidence intervals for internally transformed parameters are asymmetric.
-## t-test (unrealistically) based on the assumption of normal distribution
-## for estimators of untransformed parameters.
-##           Estimate t value Pr(>t)  Lower  Upper
-## parent_0 9.247e+01      NA     NA 89.720 95.220
-## alpha    9.658e+05      NA     NA     NA     NA
-## beta     1.010e+07      NA     NA     NA     NA
-## sigma    2.780e+00      NA     NA  1.794  3.766
-## 
-## FOCUS Chi2 error levels in percent:
-##          err.min n.optim df
-## All data   3.619       3  6
-## parent     3.619       3  6
-## 
-## Estimated disappearance times:
-##        DT50  DT90 DT50back
-## parent 7.25 24.08     7.25
    
-
    We get a warning that the default optimisation algorithm
-Port did not converge, which is an indication that the
-model is overparameterised, i.e. contains too many parameters
-that are ill-defined as a consequence.
    
-
    And in fact, due to the higher number of parameters, and the lower
-number of degrees of freedom of the fit, the \(\chi^2\) error level is actually higher for
-the FOMC model (3.6%) than for the SFO model (3.4%). Additionally, the
-parameters log_alpha and log_beta internally
-fitted in the model have excessive confidence intervals, that span more
-than 25 orders of magnitude (!) when backtransformed to the scale of
-alpha and beta. Also, the t-test for
-significant difference from zero does not indicate such a significant
-difference, with p-values greater than 0.1, and finally, the parameter
-correlation of log_alpha and log_beta is
-1.000, clearly indicating that the model is overparameterised.
    
-
    The \(\chi^2\) error levels reported
-in Appendix 3 and Appendix 7 to the FOCUS kinetics report are rounded to
-integer percentages and partly deviate by one percentage point from the
-results calculated by mkin. The reason for this is not known. However,
-mkin gives the same \(\chi^2\) error
-levels as the kinfit package and the calculation routines of the kinfit
-package have been extensively compared to the results obtained by the
-KinGUI software, as documented in the kinfit package vignette. KinGUI
-was the first widely used standard package in this field. Also, the
-calculation of \(\chi^2\) error levels
-was compared with KinGUII, CAKE and DegKin manager in a project
-sponsored by the German Umweltbundesamt (Ranke
-2014).
    
-
    
-
    
-
    Laboratory Data L2
-
    
-
    The following code defines example dataset L2 from the FOCUS kinetics
-report, p. 287:
    
-
    -FOCUS_2006_L2 = data.frame(
-  t = rep(c(0, 1, 3, 7, 14, 28), each = 2),
-  parent = c(96.1, 91.8, 41.4, 38.7,
-             19.3, 22.3, 4.6, 4.6,
-             2.6, 1.2, 0.3, 0.6))
-FOCUS_2006_L2_mkin <- mkin_wide_to_long(FOCUS_2006_L2)
    
-
    
-
    SFO fit for L2
-
    
-
    Again, the SFO model is fitted and the result is plotted. The
-residual plot can be obtained simply by adding the argument
-show_residuals to the plot command.
    
-
    -m.L2.SFO <- mkinfit("SFO", FOCUS_2006_L2_mkin, quiet=TRUE)
-plot(m.L2.SFO, show_residuals = TRUE, show_errmin = TRUE,
-     main = "FOCUS L2 - SFO")
    
-
    
-
    The \(\chi^2\) error level of 14%
-suggests that the model does not fit very well. This is also obvious
-from the plots of the fit, in which we have included the residual
-plot.
    
-
    In the FOCUS kinetics report, it is stated that there is no apparent
-systematic error observed from the residual plot up to the measured DT90
-(approximately at day 5), and there is an underestimation beyond that
-point.
    
-
    We may add that it is difficult to judge the random nature of the
-residuals just from the three samplings at days 0, 1 and 3. Also, it is
-not clear a priori why a consistent underestimation after the
-approximate DT90 should be irrelevant. However, this can be rationalised
-by the fact that the FOCUS fate models generally only implement SFO
-kinetics.
    
-
    
-
    
-
    FOMC fit for L2
-
    
-
    For comparison, the FOMC model is fitted as well, and the \(\chi^2\) error level is checked.
    
-
    -m.L2.FOMC <- mkinfit("FOMC", FOCUS_2006_L2_mkin, quiet = TRUE)
-plot(m.L2.FOMC, show_residuals = TRUE,
-     main = "FOCUS L2 - FOMC")
    
-
    
-
    -summary(m.L2.FOMC, data = FALSE)
    
-
    ## mkin version used for fitting:    1.2.3 
-## R version used for fitting:       4.2.3 
-## Date of fit:     Sun Apr 16 08:35:14 2023 
-## Date of summary: Sun Apr 16 08:35:14 2023 
-## 
-## Equations:
-## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
-## 
-## Model predictions using solution type analytical 
-## 
-## Fitted using 239 model solutions performed in 0.015 s
-## 
-## Error model: Constant variance 
-## 
-## Error model algorithm: OLS 
-## 
-## Starting values for parameters to be optimised:
-##          value   type
-## parent_0 93.95  state
-## alpha     1.00 deparm
-## beta     10.00 deparm
-## 
-## Starting values for the transformed parameters actually optimised:
-##               value lower upper
-## parent_0  93.950000  -Inf   Inf
-## log_alpha  0.000000  -Inf   Inf
-## log_beta   2.302585  -Inf   Inf
-## 
-## Fixed parameter values:
-## None
-## 
-## Results:
-## 
-##        AIC      BIC    logLik
-##   61.78966 63.72928 -26.89483
-## 
-## Optimised, transformed parameters with symmetric confidence intervals:
-##           Estimate Std. Error    Lower   Upper
-## parent_0   93.7700     1.6130 90.05000 97.4900
-## log_alpha   0.3180     0.1559 -0.04149  0.6776
-## log_beta    0.2102     0.2493 -0.36460  0.7850
-## sigma       2.2760     0.4645  1.20500  3.3470
-## 
-## Parameter correlation:
-##             parent_0  log_alpha   log_beta      sigma
-## parent_0   1.000e+00 -1.151e-01 -2.085e-01 -7.828e-09
-## log_alpha -1.151e-01  1.000e+00  9.741e-01 -1.602e-07
-## log_beta  -2.085e-01  9.741e-01  1.000e+00 -1.372e-07
-## sigma     -7.828e-09 -1.602e-07 -1.372e-07  1.000e+00
-## 
-## Backtransformed parameters:
-## Confidence intervals for internally transformed parameters are asymmetric.
-## t-test (unrealistically) based on the assumption of normal distribution
-## for estimators of untransformed parameters.
-##          Estimate t value    Pr(>t)   Lower  Upper
-## parent_0   93.770  58.120 4.267e-12 90.0500 97.490
-## alpha       1.374   6.414 1.030e-04  0.9594  1.969
-## beta        1.234   4.012 1.942e-03  0.6945  2.192
-## sigma       2.276   4.899 5.977e-04  1.2050  3.347
-## 
-## FOCUS Chi2 error levels in percent:
-##          err.min n.optim df
-## All data   6.205       3  3
-## parent     6.205       3  3
-## 
-## Estimated disappearance times:
-##          DT50  DT90 DT50back
-## parent 0.8092 5.356    1.612
    
-
    The error level at which the \(\chi^2\) test passes is much lower in this
-case. Therefore, the FOMC model provides a better description of the
-data, as less experimental error has to be assumed in order to explain
-the data.
    
-
    
-
    
-
    DFOP fit for L2
-
    
-
    Fitting the four parameter DFOP model further reduces the \(\chi^2\) error level.
    
-
    -m.L2.DFOP <- mkinfit("DFOP", FOCUS_2006_L2_mkin, quiet = TRUE)
-plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE,
-     main = "FOCUS L2 - DFOP")
    
-
    
-
    -summary(m.L2.DFOP, data = FALSE)
    
-
    ## mkin version used for fitting:    1.2.3 
-## R version used for fitting:       4.2.3 
-## Date of fit:     Sun Apr 16 08:35:15 2023 
-## Date of summary: Sun Apr 16 08:35:15 2023 
-## 
-## Equations:
-## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-##            time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-##            * parent
-## 
-## Model predictions using solution type analytical 
-## 
-## Fitted using 581 model solutions performed in 0.04 s
-## 
-## Error model: Constant variance 
-## 
-## Error model algorithm: OLS 
-## 
-## Starting values for parameters to be optimised:
-##          value   type
-## parent_0 93.95  state
-## k1        0.10 deparm
-## k2        0.01 deparm
-## g         0.50 deparm
-## 
-## Starting values for the transformed parameters actually optimised:
-##              value lower upper
-## parent_0 93.950000  -Inf   Inf
-## log_k1   -2.302585  -Inf   Inf
-## log_k2   -4.605170  -Inf   Inf
-## g_qlogis  0.000000  -Inf   Inf
-## 
-## Fixed parameter values:
-## None
-## 
-## Results:
-## 
-##        AIC      BIC    logLik
-##   52.36695 54.79148 -21.18347
-## 
-## Optimised, transformed parameters with symmetric confidence intervals:
-##          Estimate Std. Error      Lower     Upper
-## parent_0   93.950  9.998e-01    91.5900   96.3100
-## log_k1      3.112  1.842e+03 -4353.0000 4359.0000
-## log_k2     -1.088  6.285e-02    -1.2370   -0.9394
-## g_qlogis   -0.399  9.946e-02    -0.6342   -0.1638
-## sigma       1.414  2.886e-01     0.7314    2.0960
-## 
-## Parameter correlation:
-##            parent_0     log_k1     log_k2   g_qlogis      sigma
-## parent_0  1.000e+00  6.783e-07 -3.390e-10  2.665e-01 -2.967e-10
-## log_k1    6.783e-07  1.000e+00  1.116e-04 -2.196e-04 -1.031e-05
-## log_k2   -3.390e-10  1.116e-04  1.000e+00 -7.903e-01  2.917e-09
-## g_qlogis  2.665e-01 -2.196e-04 -7.903e-01  1.000e+00 -4.408e-09
-## sigma    -2.967e-10 -1.031e-05  2.917e-09 -4.408e-09  1.000e+00
-## 
-## Backtransformed parameters:
-## Confidence intervals for internally transformed parameters are asymmetric.
-## t-test (unrealistically) based on the assumption of normal distribution
-## for estimators of untransformed parameters.
-##          Estimate   t value    Pr(>t)   Lower   Upper
-## parent_0  93.9500 9.397e+01 2.036e-12 91.5900 96.3100
-## k1        22.4800 5.553e-04 4.998e-01  0.0000     Inf
-## k2         0.3369 1.591e+01 4.697e-07  0.2904  0.3909
-## g          0.4016 1.680e+01 3.238e-07  0.3466  0.4591
-## sigma      1.4140 4.899e+00 8.776e-04  0.7314  2.0960
-## 
-## FOCUS Chi2 error levels in percent:
-##          err.min n.optim df
-## All data    2.53       4  2
-## parent      2.53       4  2
-## 
-## Estimated disappearance times:
-##          DT50  DT90 DT50back DT50_k1 DT50_k2
-## parent 0.5335 5.311    1.599 0.03084   2.058
    
-
    Here, the DFOP model is clearly the best-fit model for dataset L2
-based on the chi^2 error level criterion.
    
-
    
-
    
-
    
-
    Laboratory Data L3
-
    
-
    The following code defines example dataset L3 from the FOCUS kinetics
-report, p. 290.
    
-
    -FOCUS_2006_L3 = data.frame(
-  t = c(0, 3, 7, 14, 30, 60, 91, 120),
-  parent = c(97.8, 60, 51, 43, 35, 22, 15, 12))
-FOCUS_2006_L3_mkin <- mkin_wide_to_long(FOCUS_2006_L3)
    
-
    
-
    Fit multiple models
-
    
-
    As of mkin version 0.9-39 (June 2015), we can fit several models to
-one or more datasets in one call to the function mmkin. The
-datasets have to be passed in a list, in this case a named list holding
-only the L3 dataset prepared above.
    
-
    -# Only use one core here, not to offend the CRAN checks
-mm.L3 <- mmkin(c("SFO", "FOMC", "DFOP"), cores = 1,
-               list("FOCUS L3" = FOCUS_2006_L3_mkin), quiet = TRUE)
-plot(mm.L3)
    
-
    
-
    The \(\chi^2\) error level of 21% as
-well as the plot suggest that the SFO model does not fit very well. The
-FOMC model performs better, with an error level at which the \(\chi^2\) test passes of 7%. Fitting the
-four parameter DFOP model further reduces the \(\chi^2\) error level considerably.
    
-
    
-
    
-
    Accessing mmkin objects
-
    
-
    The objects returned by mmkin are arranged like a matrix, with models
-as a row index and datasets as a column index.
    
-
    We can extract the summary and plot for e.g. the DFOP fit,
-using square brackets for indexing which will result in the use of the
-summary and plot functions working on mkinfit objects.
    
-
    -summary(mm.L3[["DFOP", 1]])
    
-
    ## mkin version used for fitting:    1.2.3 
-## R version used for fitting:       4.2.3 
-## Date of fit:     Sun Apr 16 08:35:15 2023 
-## Date of summary: Sun Apr 16 08:35:15 2023 
-## 
-## Equations:
-## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-##            time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-##            * parent
-## 
-## Model predictions using solution type analytical 
-## 
-## Fitted using 376 model solutions performed in 0.024 s
-## 
-## Error model: Constant variance 
-## 
-## Error model algorithm: OLS 
-## 
-## Starting values for parameters to be optimised:
-##          value   type
-## parent_0 97.80  state
-## k1        0.10 deparm
-## k2        0.01 deparm
-## g         0.50 deparm
-## 
-## Starting values for the transformed parameters actually optimised:
-##              value lower upper
-## parent_0 97.800000  -Inf   Inf
-## log_k1   -2.302585  -Inf   Inf
-## log_k2   -4.605170  -Inf   Inf
-## g_qlogis  0.000000  -Inf   Inf
-## 
-## Fixed parameter values:
-## None
-## 
-## Results:
-## 
-##        AIC      BIC    logLik
-##   32.97732 33.37453 -11.48866
-## 
-## Optimised, transformed parameters with symmetric confidence intervals:
-##          Estimate Std. Error   Lower      Upper
-## parent_0  97.7500    1.01900 94.5000 101.000000
-## log_k1    -0.6612    0.10050 -0.9812  -0.341300
-## log_k2    -4.2860    0.04322 -4.4230  -4.148000
-## g_qlogis  -0.1739    0.05270 -0.3416  -0.006142
-## sigma      1.0170    0.25430  0.2079   1.827000
-## 
-## Parameter correlation:
-##            parent_0     log_k1     log_k2   g_qlogis      sigma
-## parent_0  1.000e+00  1.732e-01  2.282e-02  4.009e-01 -9.664e-08
-## log_k1    1.732e-01  1.000e+00  4.945e-01 -5.809e-01  7.147e-07
-## log_k2    2.282e-02  4.945e-01  1.000e+00 -6.812e-01  1.022e-06
-## g_qlogis  4.009e-01 -5.809e-01 -6.812e-01  1.000e+00 -7.926e-07
-## sigma    -9.664e-08  7.147e-07  1.022e-06 -7.926e-07  1.000e+00
-## 
-## Backtransformed parameters:
-## Confidence intervals for internally transformed parameters are asymmetric.
-## t-test (unrealistically) based on the assumption of normal distribution
-## for estimators of untransformed parameters.
-##          Estimate t value    Pr(>t)    Lower     Upper
-## parent_0 97.75000  95.960 1.248e-06 94.50000 101.00000
-## k1        0.51620   9.947 1.081e-03  0.37490   0.71090
-## k2        0.01376  23.140 8.840e-05  0.01199   0.01579
-## g         0.45660  34.920 2.581e-05  0.41540   0.49850
-## sigma     1.01700   4.000 1.400e-02  0.20790   1.82700
-## 
-## FOCUS Chi2 error levels in percent:
-##          err.min n.optim df
-## All data   2.225       4  4
-## parent     2.225       4  4
-## 
-## Estimated disappearance times:
-##         DT50 DT90 DT50back DT50_k1 DT50_k2
-## parent 7.464  123    37.03   1.343   50.37
-## 
-## Data:
-##  time variable observed predicted residual
-##     0   parent     97.8     97.75  0.05396
-##     3   parent     60.0     60.45 -0.44933
-##     7   parent     51.0     49.44  1.56338
-##    14   parent     43.0     43.84 -0.83632
-##    30   parent     35.0     35.15 -0.14707
-##    60   parent     22.0     23.26 -1.25919
-##    91   parent     15.0     15.18 -0.18181
-##   120   parent     12.0     10.19  1.81395
    
-
    -plot(mm.L3[["DFOP", 1]], show_errmin = TRUE)
    
-
    
-
    Here, a look to the model plot, the confidence intervals of the
-parameters and the correlation matrix suggest that the parameter
-estimates are reliable, and the DFOP model can be used as the best-fit
-model based on the \(\chi^2\) error
-level criterion for laboratory data L3.
    
-
    This is also an example where the standard t-test for the parameter
-g_ilr is misleading, as it tests for a significant
-difference from zero. In this case, zero appears to be the correct value
-for this parameter, and the confidence interval for the backtransformed
-parameter g is quite narrow.
    
-
    
-
    
-
    
-
    Laboratory Data L4
-
    
-
    The following code defines example dataset L4 from the FOCUS kinetics
-report, p. 293:
    
-
    -FOCUS_2006_L4 = data.frame(
-  t = c(0, 3, 7, 14, 30, 60, 91, 120),
-  parent = c(96.6, 96.3, 94.3, 88.8, 74.9, 59.9, 53.5, 49.0))
-FOCUS_2006_L4_mkin <- mkin_wide_to_long(FOCUS_2006_L4)
    
-
    Fits of the SFO and FOMC models, plots and summaries are produced
-below:
    
-
    -# Only use one core here, not to offend the CRAN checks
-mm.L4 <- mmkin(c("SFO", "FOMC"), cores = 1,
-               list("FOCUS L4" = FOCUS_2006_L4_mkin),
-               quiet = TRUE)
-plot(mm.L4)
    
-
    
-
    The \(\chi^2\) error level of 3.3%
-as well as the plot suggest that the SFO model fits very well. The error
-level at which the \(\chi^2\) test
-passes is slightly lower for the FOMC model. However, the difference
-appears negligible.
    
-
    -summary(mm.L4[["SFO", 1]], data = FALSE)
    
-
    ## mkin version used for fitting:    1.2.3 
-## R version used for fitting:       4.2.3 
-## Date of fit:     Sun Apr 16 08:35:15 2023 
-## Date of summary: Sun Apr 16 08:35:16 2023 
-## 
-## Equations:
-## d_parent/dt = - k_parent * parent
-## 
-## Model predictions using solution type analytical 
-## 
-## Fitted using 142 model solutions performed in 0.009 s
-## 
-## Error model: Constant variance 
-## 
-## Error model algorithm: OLS 
-## 
-## Starting values for parameters to be optimised:
-##          value   type
-## parent_0  96.6  state
-## k_parent   0.1 deparm
-## 
-## Starting values for the transformed parameters actually optimised:
-##                  value lower upper
-## parent_0     96.600000  -Inf   Inf
-## log_k_parent -2.302585  -Inf   Inf
-## 
-## Fixed parameter values:
-## None
-## 
-## Results:
-## 
-##        AIC      BIC    logLik
-##   47.12133 47.35966 -20.56067
-## 
-## Optimised, transformed parameters with symmetric confidence intervals:
-##              Estimate Std. Error  Lower   Upper
-## parent_0       96.440    1.69900 92.070 100.800
-## log_k_parent   -5.030    0.07059 -5.211  -4.848
-## sigma           3.162    0.79050  1.130   5.194
-## 
-## Parameter correlation:
-##               parent_0 log_k_parent     sigma
-## parent_0     1.000e+00    5.938e-01 3.387e-07
-## log_k_parent 5.938e-01    1.000e+00 5.830e-07
-## sigma        3.387e-07    5.830e-07 1.000e+00
-## 
-## Backtransformed parameters:
-## Confidence intervals for internally transformed parameters are asymmetric.
-## t-test (unrealistically) based on the assumption of normal distribution
-## for estimators of untransformed parameters.
-##           Estimate t value    Pr(>t)     Lower     Upper
-## parent_0 96.440000   56.77 1.604e-08 92.070000 1.008e+02
-## k_parent  0.006541   14.17 1.578e-05  0.005455 7.842e-03
-## sigma     3.162000    4.00 5.162e-03  1.130000 5.194e+00
-## 
-## FOCUS Chi2 error levels in percent:
-##          err.min n.optim df
-## All data   3.287       2  6
-## parent     3.287       2  6
-## 
-## Estimated disappearance times:
-##        DT50 DT90
-## parent  106  352
    
-
    -summary(mm.L4[["FOMC", 1]], data = FALSE)
    
-
    ## mkin version used for fitting:    1.2.3 
-## R version used for fitting:       4.2.3 
-## Date of fit:     Sun Apr 16 08:35:15 2023 
-## Date of summary: Sun Apr 16 08:35:16 2023 
-## 
-## Equations:
-## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
-## 
-## Model predictions using solution type analytical 
-## 
-## Fitted using 224 model solutions performed in 0.014 s
-## 
-## Error model: Constant variance 
-## 
-## Error model algorithm: OLS 
-## 
-## Starting values for parameters to be optimised:
-##          value   type
-## parent_0  96.6  state
-## alpha      1.0 deparm
-## beta      10.0 deparm
-## 
-## Starting values for the transformed parameters actually optimised:
-##               value lower upper
-## parent_0  96.600000  -Inf   Inf
-## log_alpha  0.000000  -Inf   Inf
-## log_beta   2.302585  -Inf   Inf
-## 
-## Fixed parameter values:
-## None
-## 
-## Results:
-## 
-##        AIC      BIC    logLik
-##   40.37255 40.69032 -16.18628
-## 
-## Optimised, transformed parameters with symmetric confidence intervals:
-##           Estimate Std. Error   Lower    Upper
-## parent_0   99.1400     1.2670 95.6300 102.7000
-## log_alpha  -0.3506     0.2616 -1.0770   0.3756
-## log_beta    4.1740     0.3938  3.0810   5.2670
-## sigma       1.8300     0.4575  0.5598   3.1000
-## 
-## Parameter correlation:
-##             parent_0  log_alpha   log_beta      sigma
-## parent_0   1.000e+00 -4.696e-01 -5.543e-01 -2.468e-07
-## log_alpha -4.696e-01  1.000e+00  9.889e-01  2.478e-08
-## log_beta  -5.543e-01  9.889e-01  1.000e+00  5.211e-08
-## sigma     -2.468e-07  2.478e-08  5.211e-08  1.000e+00
-## 
-## Backtransformed parameters:
-## Confidence intervals for internally transformed parameters are asymmetric.
-## t-test (unrealistically) based on the assumption of normal distribution
-## for estimators of untransformed parameters.
-##          Estimate t value    Pr(>t)   Lower   Upper
-## parent_0  99.1400  78.250 7.993e-08 95.6300 102.700
-## alpha      0.7042   3.823 9.365e-03  0.3407   1.456
-## beta      64.9800   2.540 3.201e-02 21.7800 193.900
-## sigma      1.8300   4.000 8.065e-03  0.5598   3.100
-## 
-## FOCUS Chi2 error levels in percent:
-##          err.min n.optim df
-## All data   2.029       3  5
-## parent     2.029       3  5
-## 
-## Estimated disappearance times:
-##         DT50 DT90 DT50back
-## parent 108.9 1644    494.9
    
-
    
-
    
-
    References
-
    
-
    
-
    
-Ranke, Johannes. 2014. “Prüfung und
-Validierung von Modellierungssoftware als Alternative zu ModelMaker
-4.0.” Umweltbundesamt Projektnummer 27452.
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-Articles • mkin
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    Articles
    
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    All vignettes
    
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    Example evaluation of FOCUS Example Dataset D
    
-        
    
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    Example evaluation of FOCUS Laboratory Data L1 to L3
    
-        
    
-        
    Introduction to mkin
    
-        
    
-        
    Testing hierarchical pathway kinetics with residue data on cyantraniliprole
    
-        
    
-        
    Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P
    
-        
    
-        
    Testing hierarchical pathway kinetics with residue data on dimethenamid and dimethenamid-P
    
-        
    
-        
    Calculation of time weighted average concentrations with mkin
    
-        
    
-        
    Example evaluation of FOCUS dataset Z
    
-        
    
-        
    Evaluation of example datasets from Attachment 1 to the US EPA SOP for the NAFTA guidance
    
-        
    
-        
    Benchmark timings for mkin
    
-        
    
-        
    Performance benefit by using compiled model definitions in mkin
    
-        
    
-        
    Example evaluations of the dimethenamid data from 2018
    
-        
    
-        
    Short demo of the multistart method
    
-        
    
-        
    Benchmark timings for saem.mmkin
    
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    Developed by Johannes Ranke.
    
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-Introduction to mkin • mkin
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    Introduction to mkin
    
-                        
    Johannes
-Ranke
    
-            
-            
    Last change 15 February 2021
-(rebuilt 2023-04-16)
    
-      
-      Source: vignettes/mkin.rmd
-      
-
-    
    
-
-    
-    
-
    Wissenschaftlicher Berater, Kronacher
-Str. 12, 79639 Grenzach-Wyhlen, Germany
     Privatdozent at the
-University of Freiburg
    
-
    
-
    Abstract
-
    
-
    In the regulatory evaluation of chemical substances like plant
-protection products (pesticides), biocides and other chemicals,
-degradation data play an important role. For the evaluation of pesticide
-degradation experiments, detailed guidance has been developed, based on
-nonlinear optimisation. The R add-on package
-mkin implements fitting some of the models recommended in
-this guidance from within R and calculates some statistical measures for
-data series within one or more compartments, for parent and
-metabolites.
    
-
    -library("mkin", quietly = TRUE)
-# Define the kinetic model
-m_SFO_SFO_SFO <- mkinmod(parent = mkinsub("SFO", "M1"),
-                         M1 = mkinsub("SFO", "M2"),
-                         M2 = mkinsub("SFO"),
-                         use_of_ff = "max", quiet = TRUE)
-
-
-# Produce model predictions using some arbitrary parameters
-sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-d_SFO_SFO_SFO <- mkinpredict(m_SFO_SFO_SFO,
-  c(k_parent = 0.03,
-    f_parent_to_M1 = 0.5, k_M1 = log(2)/100,
-    f_M1_to_M2 = 0.9, k_M2 = log(2)/50),
-  c(parent = 100, M1 = 0, M2 = 0),
-  sampling_times)
-
-# Generate a dataset by adding normally distributed errors with
-# standard deviation 3, for two replicates at each sampling time
-d_SFO_SFO_SFO_err <- add_err(d_SFO_SFO_SFO, reps = 2,
-                             sdfunc = function(x) 3,
-                             n = 1, seed = 123456789 )
-
-# Fit the model to the dataset
-f_SFO_SFO_SFO <- mkinfit(m_SFO_SFO_SFO, d_SFO_SFO_SFO_err[[1]], quiet = TRUE)
-
-# Plot the results separately for parent and metabolites
-plot_sep(f_SFO_SFO_SFO, lpos = c("topright", "bottomright", "bottomright"))
    
-
    
-
    
-
    
-
    Background
-
    
-
    The mkin package (J. Ranke
-2021) implements the approach to degradation kinetics recommended
-in the kinetics report provided by the FOrum for Co-ordination of
-pesticide fate models and their USe (FOCUS Work
-Group on Degradation Kinetics 2006, 2014). It covers data series
-describing the decline of one compound, data series with transformation
-products (commonly termed metabolites) and data series for more than one
-compartment. It is possible to include back reactions. Therefore,
-equilibrium reactions and equilibrium partitioning can be specified,
-although this often leads to an overparameterisation of the model.
    
-
    When the first mkin code was published in 2010, the most
-commonly used tools for fitting more complex kinetic degradation models
-to experimental data were KinGUI (Schäfer et al.
-2007), a MATLAB based tool with a graphical user interface that
-was specifically tailored to the task and included some output as
-proposed by the FOCUS Kinetics Workgroup, and ModelMaker, a general
-purpose compartment based tool providing infrastructure for fitting
-dynamic simulation models based on differential equations to data.
    
-
    The ‘mkin’ code was first uploaded to the BerliOS development
-platform. When this was taken down, the version control history was
-imported into the R-Forge site (see e.g. the
-initial commit on 11 May 2010), where the code is still being
-updated.
    
-
    At that time, the R package FME (Flexible Modelling
-Environment) (Soetaert and Petzoldt 2010)
-was already available, and provided a good basis for developing a
-package specifically tailored to the task. The remaining challenge was
-to make it as easy as possible for the users (including the author of
-this vignette) to specify the system of differential equations and to
-include the output requested by the FOCUS guidance, such as the \(\chi^2\) error level as defined in this
-guidance.
    
-
    Also, mkin introduced using analytical solutions for
-parent only kinetics for improved optimization speed. Later, Eigenvalue
-based solutions were introduced to mkin for the case of
-linear differential equations (i.e. where the FOMC or DFOP
-models were not used for the parent compound), greatly improving the
-optimization speed for these cases. This, has become somehow obsolete,
-as the use of compiled code described below gives even faster execution
-times.
    
-
    The possibility to specify back-reactions and a biphasic model
-(SFORB) for metabolites were present in mkin from the very
-beginning.
    
-
    
-
    Derived software tools
-
    
-
    Soon after the publication of mkin, two derived tools
-were published, namely KinGUII (developed at Bayer Crop Science) and
-CAKE (commissioned to Tessella by Syngenta), which added a graphical
-user interface (GUI), and added fitting by iteratively reweighted least
-squares (IRLS) and characterisation of likely parameter distributions by
-Markov Chain Monte Carlo (MCMC) sampling.
    
-
    CAKE focuses on a smooth use experience, sacrificing some flexibility
-in the model definition, originally allowing only two primary
-metabolites in parallel. The current version 3.4 of CAKE released in May
-2020 uses a scheme for up to six metabolites in a flexible arrangement
-and supports biphasic modelling of metabolites, but does not support
-back-reactions (non-instantaneous equilibria).
    
-
    KinGUI offers an even more flexible widget for specifying complex
-kinetic models. Back-reactions (non-instantaneous equilibria) were
-supported early on, but until 2014, only simple first-order models could
-be specified for transformation products. Starting with KinGUII version
-2.1, biphasic modelling of metabolites was also available in
-KinGUII.
    
-
    A further graphical user interface (GUI) that has recently been
-brought to a decent degree of maturity is the browser based GUI named
-gmkin. Please see its documentation page and manual
-for further information.
    
-
    A comparison of scope, usability and numerical results obtained with
-these tools has been recently been published by Johannes Ranke, Wöltjen, and Meinecke
-(2018).
    
-
    
-
    
-
    
-
    Unique features
-
    
-
    Currently, the main unique features available in mkin
-are
    
-
      
-
    • the speed
-increase by using compiled code when a compiler is present,
      • 
-
    • parallel model fitting on multicore machines using the mmkin
-function,
      • 
-
    • the estimation of parameter confidence intervals based on
-transformed parameters (see below) and
      • 
-
    • the possibility to use the two-component
-error model
-
      • 
-
    
-
    The iteratively reweighted least squares fitting of different
-variances for each variable as introduced by Gao
-et al. (2011) has been available in mkin since version
-0.9-22. With release
-0.9.49.5, the IRLS algorithm has been complemented by direct or
-step-wise maximisation of the likelihood function, which makes it
-possible not only to fit the variance by variable error model but also a
-two-component
-error model inspired by error models developed in analytical
-chemistry (Johannes Ranke and Meinecke
-2019).
    
-
    
-
    
-
    Internal parameter transformations
-
    
-
    For rate constants, the log transformation is used, as proposed by
-Bates and Watts (1988, 77, 149).
-Approximate intervals are constructed for the transformed rate constants
-(compare Bates and Watts 1988, 135),
-i.e. for their logarithms. Confidence intervals for the rate
-constants are then obtained using the appropriate backtransformation
-using the exponential function.
    
-
    In the first version of mkin allowing for specifying
-models using formation fractions, a home-made reparameterisation was
-used in order to ensure that the sum of formation fractions would not
-exceed unity.
    
-
    This method is still used in the current version of KinGUII (v2.1
-from April 2014), with a modification that allows for fixing the pathway
-to sink to zero. CAKE uses penalties in the objective function in order
-to enforce this constraint.
    
-
    In 2012, an alternative reparameterisation of the formation fractions
-was proposed together with René Lehmann (J. Ranke
-and Lehmann 2012), based on isometric logratio transformation
-(ILR). The aim was to improve the validity of the linear approximation
-of the objective function during the parameter estimation procedure as
-well as in the subsequent calculation of parameter confidence intervals.
-In the current version of mkin, a logit transformation is used for
-parameters that are bound between 0 and 1, such as the g parameter of
-the DFOP model.
    
-
    
-
    Confidence intervals based on transformed parameters
-
    
-
    In the first attempt at providing improved parameter confidence
-intervals introduced to mkin in 2013, confidence intervals
-obtained from FME on the transformed parameters were simply all
-backtransformed one by one to yield asymmetric confidence intervals for
-the backtransformed parameters.
    
-
    However, while there is a 1:1 relation between the rate constants in
-the model and the transformed parameters fitted in the model, the
-parameters obtained by the isometric logratio transformation are
-calculated from the set of formation fractions that quantify the paths
-to each of the compounds formed from a specific parent compound, and no
-such 1:1 relation exists.
    
-
    Therefore, parameter confidence intervals for formation fractions
-obtained with this method only appear valid for the case of a single
-transformation product, where currently the logit transformation is used
-for the formation fraction.
    
-
    The confidence intervals obtained by backtransformation for the cases
-where a 1:1 relation between transformed and original parameter exist
-are considered by the author of this vignette to be more accurate than
-those obtained using a re-estimation of the Hessian matrix after
-backtransformation, as implemented in the FME package.
    
-
    
-
    
-
    Parameter t-test based on untransformed parameters
-
    
-
    The standard output of many nonlinear regression software packages
-includes the results from a test for significant difference from zero
-for all parameters. Such a test is also recommended to check the
-validity of rate constants in the FOCUS guidance (FOCUS Work Group on Degradation Kinetics 2014,
-96ff).
    
-
    It has been argued that the precondition for this test, i.e.
-normal distribution of the estimator for the parameters, is not
-fulfilled in the case of nonlinear regression (J.
-Ranke and Lehmann 2015). However, this test is commonly used by
-industry, consultants and national authorities in order to decide on the
-reliability of parameter estimates, based on the FOCUS guidance
-mentioned above. Therefore, the results of this one-sided t-test are
-included in the summary output from mkin.
    
-
    As it is not reasonable to test for significant difference of the
-transformed parameters (e.g. \(log(k)\)) from zero, the t-test is
-calculated based on the model definition before parameter
-transformation, i.e. in a similar way as in packages that do
-not apply such an internal parameter transformation. A note is included
-in the mkin output, pointing to the fact that the t-test is
-based on the unjustified assumption of normal distribution of the
-parameter estimators.
    
-
    
-
    
-
    
-
    References
-
    
-
-
    
-
    
-Bates, D., and D. Watts. 1988. Nonlinear Regression and Its
-Applications. Wiley-Interscience.
-
    
-
    
-FOCUS Work Group on Degradation Kinetics. 2006. Guidance Document on
-Estimating Persistence and Degradation Kinetics from Environmental Fate
-Studies on Pesticides in EU Registration. Report of the FOCUS Work Group
-on Degradation Kinetics. http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics.
-
    
-
    
-———. 2014. Generic Guidance for Estimating Persistence and
-Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
-Registration. 1.1 ed. http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics.
-
    
-
    
-Gao, Z., J. W. Green, J. Vanderborght, and W. Schmitt. 2011.
-“Improving Uncertainty Analysis in Kinetic Evaluations Using
-Iteratively Reweighted Least Squares.” Journal. Environmental
-Science and Technology 45: 4429–37.
-
    
-
    
-Ranke, J. 2021. ‘mkin‘:
-Kinetic Evaluation of Chemical Degradation Data. https://CRAN.R-project.org/package=mkin.
-
    
-
    
-Ranke, J., and R. Lehmann. 2012. “Parameter Reliability in Kinetic
-Evaluation of Environmental Metabolism Data - Assessment and the
-Influence of Model Specification.” In SETAC World 20-24
-May. Berlin. https://jrwb.de/posters/Poster_SETAC_2012_Kinetic_parameter_uncertainty_model_parameterization_Lehmann_Ranke.pdf.
-
    
-
    
-———. 2015. “To t-Test or Not to t-Test, That Is the
-Question.” In XV Symposium on Pesticide Chemistry 2-4
-September 2015. Piacenza. https://jrwb.de/posters/piacenza_2015.pdf.
-
    
-
    
-Ranke, Johannes, and Stefan Meinecke. 2019. “Error Models for the
-Kinetic Evaluation of Chemical Degradation Data.”
-Environments 6 (12). https://doi.org/10.3390/environments6120124.
-
    
-
    
-Ranke, Johannes, Janina Wöltjen, and Stefan Meinecke. 2018.
-“Comparison of Software Tools for Kinetic Evaluation of Chemical
-Degradation Data.” Environmental Sciences Europe 30 (1):
-17. https://doi.org/10.1186/s12302-018-0145-1.
-
    
-
    
-Schäfer, D., B. Mikolasch, P. Rainbird, and B. Harvey. 2007.
-“KinGUI: A New Kinetic Software Tool for Evaluations
-According to FOCUS Degradation Kinetics.” In
-Proceedings of the XIII Symposium Pesticide Chemistry, edited
-by Del Re A. A. M., Capri E., Fragoulis G., and Trevisan M., 916–23.
-Piacenza.
-
    
-
    
-Soetaert, Karline, and Thomas Petzoldt. 2010. “Inverse Modelling,
-Sensitivity and Monte Carlo Analysis in R Using Package
-FME.” Journal of Statistical Software 33
-(3): 1–28. https://doi.org/10.18637/jss.v033.i03.
-
    
-
    
-
    
-  
    
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-  
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-      
    
-  
    
-
    Developed by Johannes Ranke.
    
-
    
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-  
    
-
    Site built with pkgdown 2.0.7.
    
-
    
-
-      
    
-
    
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-  
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-  
-
-  
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diff --git a/docs/dev/articles/mkin_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/dev/articles/mkin_files/accessible-code-block-0.0.1/empty-anchor.js
deleted file mode 100644
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+++ /dev/null
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-// Hide empty  tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
-// v0.0.1
-// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
-
-document.addEventListener('DOMContentLoaded', function() {
-  const codeList = document.getElementsByClassName("sourceCode");
-  for (var i = 0; i < codeList.length; i++) {
-    var linkList = codeList[i].getElementsByTagName('a');
-    for (var j = 0; j < linkList.length; j++) {
-      if (linkList[j].innerHTML === "") {
-        linkList[j].setAttribute('aria-hidden', 'true');
-      }
-    }
-  }
-});
diff --git a/docs/dev/articles/mkin_files/anchor-sections-1.0/anchor-sections.css b/docs/dev/articles/mkin_files/anchor-sections-1.0/anchor-sections.css
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-/* Styles for section anchors */
-a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
-a.anchor-section::before {content: '#';}
-.hasAnchor:hover a.anchor-section {visibility: visible;}
diff --git a/docs/dev/articles/mkin_files/anchor-sections-1.0/anchor-sections.js b/docs/dev/articles/mkin_files/anchor-sections-1.0/anchor-sections.js
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-// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
-document.addEventListener('DOMContentLoaded', function() {
-  // Do nothing if AnchorJS is used
-  if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
-    return;
-  }
-
-  const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
-
-  // Do nothing if sections are already anchored
-  if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
-    return null;
-  }
-
-  // Use section id when pandoc runs with --section-divs
-  const section_id = function(x) {
-    return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
-            ? x.id : '');
-  };
-
-  // Add anchors
-  h.forEach(function(x) {
-    const id = x.id || section_id(x.parentElement);
-    if (id === '') {
-      return null;
-    }
-    let anchor = document.createElement('a');
-    anchor.href = '#' + id;
-    anchor.classList = ['anchor-section'];
-    x.classList.add('hasAnchor');
-    x.appendChild(anchor);
-  });
-});
diff --git a/docs/dev/articles/mkin_files/figure-html/unnamed-chunk-2-1.png b/docs/dev/articles/mkin_files/figure-html/unnamed-chunk-2-1.png
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diff --git a/docs/dev/articles/mkin_files/header-attrs-2.6/header-attrs.js b/docs/dev/articles/mkin_files/header-attrs-2.6/header-attrs.js
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-// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
-// be compatible with the behavior of Pandoc < 2.8).
-document.addEventListener('DOMContentLoaded', function(e) {
-  var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
-  var i, h, a;
-  for (i = 0; i < hs.length; i++) {
-    h = hs[i];
-    if (!/^h[1-6]$/i.test(h.tagName)) continue;  // it should be a header h1-h6
-    a = h.attributes;
-    while (a.length > 0) h.removeAttribute(a[0].name);
-  }
-});
diff --git a/docs/dev/articles/prebuilt/2022_cyan_pathway.html b/docs/dev/articles/prebuilt/2022_cyan_pathway.html
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-
-Testing hierarchical pathway kinetics with residue data on cyantraniliprole • mkin
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    Testing hierarchical pathway kinetics with
-residue data on cyantraniliprole
    
-                        
    Johannes
-Ranke
    
-            
-            
    Last change on 20 April 2023,
-last compiled on 20 April 2023
    
-      
-      Source: vignettes/prebuilt/2022_cyan_pathway.rmd
-      
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-    
    
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-    
-    
-
    
-
    Introduction
-
    
-
    The purpose of this document is to test demonstrate how nonlinear
-hierarchical models (NLHM) based on the parent degradation models SFO,
-FOMC, DFOP and HS, with serial formation of two or more metabolites can
-be fitted with the mkin package.
    
-
    It was assembled in the course of work package 1.2 of Project Number
-173340 (Application of nonlinear hierarchical models to the kinetic
-evaluation of chemical degradation data) of the German Environment
-Agency carried out in 2022 and 2023.
    
-
    The mkin package is used in version 1.2.4 which is currently under
-development. The newly introduced functionality that is used here is a
-simplification of excluding random effects for a set of fits based on a
-related set of fits with a reduced model, and the documentation of the
-starting parameters of the fit, so that all starting parameters of
-saem fits are now listed in the summary. The
-saemix package is used as a backend for fitting the NLHM,
-but is also loaded to make the convergence plot function available.
    
-
    This document is processed with the knitr package, which
-also provides the kable function that is used to improve
-the display of tabular data in R markdown documents. For parallel
-processing, the parallel package is used.
    
-
    -library(mkin)
-library(knitr)
-library(saemix)
-library(parallel)
-n_cores <- detectCores()
-
-# We need to start a new cluster after defining a compiled model that is
-# saved as a DLL to the user directory, therefore we define a function
-# This is used again after defining the pathway model
-start_cluster <- function(n_cores) {
-  if (Sys.info()["sysname"] == "Windows") {
-    ret <- makePSOCKcluster(n_cores)
-  } else {
-    ret <- makeForkCluster(n_cores)
-  }
-  return(ret)
-}
-cl <- start_cluster(n_cores)
    
-
    
-
    Test data
-
    
-
    The example data are taken from the final addendum to the DAR from
-2014 and are distributed with the mkin package. Residue data and time
-step normalisation factors are read in using the function
-read_spreadsheet from the mkin package. This function also
-performs the time step normalisation.
    
-
    -data_file <- system.file(
-  "testdata", "cyantraniliprole_soil_efsa_2014.xlsx",
-  package = "mkin")
-cyan_ds <- read_spreadsheet(data_file, parent_only = FALSE)
    
-
    The following tables show the covariate data and the 5 datasets that
-were read in from the spreadsheet file.
    
-
    -pH <- attr(cyan_ds, "covariates")
-kable(pH, caption = "Covariate data")
    
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    Covariate data
    pH
    Nambsheim7.90
    Tama6.20
    Gross-Umstadt7.04
    Sassafras4.62
    Lleida8.05
    
-
    -for (ds_name in names(cyan_ds)) {
-  print(
-    kable(mkin_long_to_wide(cyan_ds[[ds_name]]),
-      caption = paste("Dataset", ds_name),
-      booktabs = TRUE, row.names = FALSE))
-    cat("\n\\clearpage\n")
-}
    
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    Dataset Nambsheim
    timecyanJCZ38J9C38JSE76J9Z38
    0.000000105.79NANANANA
    3.21042477.267.9211.945.589.12
    7.49098857.1315.4616.5812.5911.74
    17.12225937.7415.9813.3626.0510.77
    23.54310531.476.0514.4934.714.96
    43.87578816.746.077.5740.386.52
    67.4188938.8510.346.3930.718.90
    107.0141165.199.611.9520.4112.93
    129.4870803.456.181.3621.786.99
    195.8358322.159.130.9516.297.69
    254.6935961.926.920.2013.577.16
    321.0423482.267.02NA11.128.66
    383.110535NA5.05NA10.645.56
    0.000000105.57NANANANA
    3.21042478.8812.7711.945.479.12
    7.49098859.9415.2716.5813.6011.74
    17.12225939.6714.2613.3629.4410.77
    23.54310530.2116.0714.4935.904.96
    43.87578818.069.447.5742.306.52
    67.4188938.545.786.3934.708.90
    107.0141167.264.541.9523.3312.93
    129.4870803.604.221.3623.566.99
    195.8358322.843.050.9516.217.69
    254.6935962.002.900.2015.537.16
    321.0423481.790.94NA9.808.66
    383.110535NA1.82NA9.495.56
    
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    Dataset Tama
    timecyanJCZ38J9Z38JSE76
    0.000000106.14NANANA
    2.40083393.476.462.85NA
    5.60194388.3910.864.653.85
    12.80444272.2911.974.9111.24
    17.60610865.7913.116.6313.79
    32.81138253.1611.248.9023.40
    50.41749044.0111.349.9829.56
    80.02776133.238.8211.3135.63
    96.83359140.685.948.3229.09
    146.45080320.654.498.7236.88
    190.46607217.714.6611.1040.97
    240.08328414.862.2711.6240.11
    286.49938612.02NA10.7342.58
    0.000000109.11NANANA
    2.40083396.845.522.042.02
    5.60194385.299.652.994.39
    12.80444273.6812.485.0511.47
    17.60610864.8912.446.2915.00
    32.81138252.2710.867.6523.30
    50.41749042.6110.549.3731.06
    80.02776134.2910.029.0437.87
    96.83359130.506.348.1433.97
    146.45080319.216.298.5226.15
    190.46607217.555.819.8932.08
    240.08328413.225.9910.7940.66
    286.49938611.096.058.8242.90
    
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    Dataset Gross-Umstadt
    timecyanJCZ38J9Z38JSE76
    0.0000000103.03NANANA
    2.101468187.854.793.260.62
    4.903425577.358.059.891.32
    10.507340469.339.7412.324.74
    21.014680755.6514.5713.599.84
    31.522021149.0314.6616.7112.32
    42.029361541.8615.9713.6415.53
    63.044042234.8818.2014.1222.02
    84.058723028.2615.6414.0625.60
    0.0000000104.05NANANA
    2.101468185.252.687.320.69
    4.903425577.227.288.371.45
    10.507340465.2310.7310.934.74
    21.014680757.7812.2914.809.05
    31.522021154.8314.0512.0111.05
    42.029361545.1712.1217.8915.71
    63.044042234.8312.9015.8622.52
    84.058723026.5914.2814.9128.48
    0.0000000104.62NANANA
    0.814522597.21NA4.00NA
    1.900552589.643.595.24NA
    4.072612587.904.109.58NA
    8.145225186.905.969.45NA
    12.217837674.747.8315.035.33
    16.290450274.138.8414.415.10
    24.435675365.2611.8418.336.71
    32.580900457.7012.7419.939.74
    0.0000000101.94NANANA
    0.814522599.94NANANA
    1.900552594.87NA4.56NA
    4.072612586.966.756.90NA
    8.145225180.5110.687.432.58
    12.217837678.3810.359.463.69
    16.290450270.0513.739.277.18
    24.435675361.2812.5713.2813.19
    32.580900452.8512.6712.9513.69
    
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    Dataset Sassafras
    timecyanJCZ38J9Z38JSE76
    0.000000102.17NANANA
    2.21671995.491.110.100.83
    5.17234383.356.432.893.30
    11.08359378.1810.005.590.81
    22.16718670.4417.214.231.09
    33.25077968.0020.455.861.17
    44.33437159.6424.643.172.72
    66.50155750.7327.506.191.27
    88.66874245.6532.775.694.54
    0.000000100.43NANANA
    2.21671995.343.210.140.46
    5.17234384.385.734.750.62
    11.08359378.5011.893.990.73
    22.16718671.1717.284.390.66
    33.25077959.4118.7311.852.65
    44.33437164.5722.935.132.01
    66.50155749.0833.395.673.63
    88.66874240.4139.605.936.17
    
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    Dataset Lleida
    timecyanJCZ38J9Z38JSE76
    0.000000102.71NANANA
    2.82105179.115.708.070.97
    6.58245170.037.1711.314.72
    14.10525350.9310.2514.849.95
    28.21050533.4310.4014.8224.06
    42.31575824.699.7516.3829.38
    56.42101022.9910.0615.5129.25
    84.63151614.635.6314.7431.04
    112.84202112.434.1713.5333.28
    0.00000099.31NANANA
    2.82105182.076.555.601.12
    6.58245170.657.618.013.21
    14.10525353.5211.4810.8212.24
    28.21050535.6011.1915.4323.53
    42.31575834.2611.0913.2627.42
    56.42101021.794.8018.3030.20
    84.63151614.066.3016.3532.32
    112.84202111.515.5712.6432.51
    
-
    
-
    
-
    
-
    Parent only evaluations
-
    
-
    As the pathway fits have very long run times, evaluations of the
-parent data are performed first, in order to determine for each
-hierarchical parent degradation model which random effects on the
-degradation model parameters are ill-defined.
    
-
    -cyan_sep_const <- mmkin(c("SFO", "FOMC", "DFOP", "SFORB", "HS"),
-  cyan_ds, quiet = TRUE, cores = n_cores)
-cyan_sep_tc <- update(cyan_sep_const, error_model = "tc")
-cyan_saem_full <- mhmkin(list(cyan_sep_const, cyan_sep_tc))
-status(cyan_saem_full) |> kable()
    
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    consttc
    SFOOKOK
    FOMCOKOK
    DFOPOKOK
    SFORBOKOK
    HSOKOK
    
-
    All fits converged successfully.
    
-
    -illparms(cyan_saem_full) |> kable()
    
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    consttc
    SFOsd(cyan_0)sd(cyan_0)
    FOMCsd(log_beta)sd(cyan_0)
    DFOPsd(cyan_0)sd(cyan_0), sd(log_k1)
    SFORBsd(cyan_free_0)sd(cyan_free_0), sd(log_k_cyan_free_bound)
    HSsd(cyan_0)sd(cyan_0)
    
-
    In almost all models, the random effect for the initial concentration
-of the parent compound is ill-defined. For the biexponential models DFOP
-and SFORB, the random effect of one additional parameter is ill-defined
-when the two-component error model is used.
    
-
    -anova(cyan_saem_full) |> kable(digits = 1)
    
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    nparAICBICLik
    SFO const5833.9832.0-412.0
    SFO tc6831.6829.3-409.8
    FOMC const7709.1706.4-347.6
    FOMC tc8689.2686.1-336.6
    DFOP const9703.0699.5-342.5
    SFORB const9701.3697.8-341.7
    HS const9718.6715.1-350.3
    DFOP tc10703.1699.2-341.6
    SFORB tc10700.1696.2-340.1
    HS tc10716.7712.8-348.3
    
-
    Model comparison based on AIC and BIC indicates that the
-two-component error model is preferable for all parent models with the
-exception of DFOP. The lowest AIC and BIC values are are obtained with
-the FOMC model, followed by SFORB and DFOP.
    
-
-
    
-
    
-
    Pathway fits
-
    
-
    
-
    Evaluations with pathway established previously
-
    
-
    To test the technical feasibility of coupling the relevant parent
-degradation models with different transformation pathway models, a list
-of mkinmod models is set up below. As in the EU evaluation,
-parallel formation of metabolites JCZ38 and J9Z38 and secondary
-formation of metabolite JSE76 from JCZ38 is used.
    
-
    -if (!dir.exists("cyan_dlls")) dir.create("cyan_dlls")
-cyan_path_1 <- list(
-  sfo_path_1 = mkinmod(
-    cyan = mkinsub("SFO", c("JCZ38", "J9Z38")),
-    JCZ38 = mkinsub("SFO", "JSE76"),
-    J9Z38 = mkinsub("SFO"),
-    JSE76 = mkinsub("SFO"), quiet = TRUE,
-    name = "sfo_path_1", dll_dir = "cyan_dlls", overwrite = TRUE),
-  fomc_path_1 = mkinmod(
-    cyan = mkinsub("FOMC", c("JCZ38", "J9Z38")),
-    JCZ38 = mkinsub("SFO", "JSE76"),
-    J9Z38 = mkinsub("SFO"),
-    JSE76 = mkinsub("SFO"), quiet = TRUE,
-    name = "fomc_path_1", dll_dir = "cyan_dlls", overwrite = TRUE),
-  dfop_path_1 = mkinmod(
-    cyan = mkinsub("DFOP", c("JCZ38", "J9Z38")),
-    JCZ38 = mkinsub("SFO", "JSE76"),
-    J9Z38 = mkinsub("SFO"),
-    JSE76 = mkinsub("SFO"), quiet = TRUE,
-    name = "dfop_path_1", dll_dir = "cyan_dlls", overwrite = TRUE),
-  sforb_path_1 = mkinmod(
-    cyan = mkinsub("SFORB", c("JCZ38", "J9Z38")),
-    JCZ38 = mkinsub("SFO", "JSE76"),
-    J9Z38 = mkinsub("SFO"),
-    JSE76 = mkinsub("SFO"), quiet = TRUE,
-    name = "sforb_path_1", dll_dir = "cyan_dlls", overwrite = TRUE),
-  hs_path_1 = mkinmod(
-    cyan = mkinsub("HS", c("JCZ38", "J9Z38")),
-    JCZ38 = mkinsub("SFO", "JSE76"),
-    J9Z38 = mkinsub("SFO"),
-    JSE76 = mkinsub("SFO"), quiet = TRUE,
-    name = "hs_path_1", dll_dir = "cyan_dlls", overwrite = TRUE)
-)
-cl_path_1 <- start_cluster(n_cores)
    
-
    To obtain suitable starting values for the NLHM fits, separate
-pathway fits are performed for all datasets.
    
-
    -f_sep_1_const <- mmkin(
-  cyan_path_1,
-  cyan_ds,
-  error_model = "const",
-  cluster = cl_path_1,
-  quiet = TRUE)
-status(f_sep_1_const) |> kable()
    
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    NambsheimTamaGross-UmstadtSassafrasLleida
    sfo_path_1OKOKOKOKOK
    fomc_path_1OKOKOKOKOK
    dfop_path_1OKOKOKOKOK
    sforb_path_1OKOKOKOKOK
    hs_path_1CCCCC
    
-
    -f_sep_1_tc <- update(f_sep_1_const, error_model = "tc")
-status(f_sep_1_tc) |> kable()
    
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    NambsheimTamaGross-UmstadtSassafrasLleida
    sfo_path_1OKOKOKOKOK
    fomc_path_1OKOKOKOKC
    dfop_path_1OKOKOKOKOK
    sforb_path_1OKCOKOKOK
    hs_path_1COKCOKOK
    
-
    Most separate fits converged successfully. The biggest convergence
-problems are seen when using the HS model with constant variance.
    
-
    For the hierarchical pathway fits, those random effects that could
-not be quantified in the corresponding parent data analyses are
-excluded.
    
-
    In the code below, the output of the illparms function
-for the parent only fits is used as an argument
-no_random_effect to the mhmkin function. The
-possibility to do so was introduced in mkin version 1.2.2
-which is currently under development.
    
-
    -f_saem_1 <- mhmkin(list(f_sep_1_const, f_sep_1_tc),
-  no_random_effect = illparms(cyan_saem_full),
-  cluster = cl_path_1)
    
-
    -status(f_saem_1) |> kable()
    
-
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    consttc
    sfo_path_1Fth, FOFth, FO
    fomc_path_1OKFth, FO
    dfop_path_1Fth, FOFth, FO
    sforb_path_1Fth, FOFth, FO
    hs_path_1Fth, FOFth, FO
    
-
    The status information from the individual fits shows that all fits
-completed successfully. The matrix entries Fth and FO indicate that the
-Fisher Information Matrix could not be inverted for the fixed effects
-(theta) and the random effects (Omega), respectively. For the affected
-fits, ill-defined parameters cannot be determined using the
-illparms function, because it relies on the Fisher
-Information Matrix.
    
-
    -illparms(f_saem_1) |> kable()
    
-
-----
-
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-
    




    consttc
    sfo_path_1NANA
    fomc_path_1sd(log_k_J9Z38), sd(f_cyan_ilr_2),
-sd(f_JCZ38_qlogis)NA
    dfop_path_1NANA
    sforb_path_1NANA
    hs_path_1NANA
    
-
    The model comparison below suggests that the pathway fits using DFOP
-or SFORB for the parent compound provide the best fit.
    
-
    -anova(f_saem_1) |> kable(digits = 1)
    
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    nparAICBICLik
    sfo_path_1 const162692.82686.6-1330.4
    sfo_path_1 tc172657.72651.1-1311.9
    fomc_path_1 const182427.82420.8-1195.9
    fomc_path_1 tc192423.42416.0-1192.7
    dfop_path_1 const202403.22395.4-1181.6
    sforb_path_1 const202401.42393.6-1180.7
    hs_path_1 const202427.32419.5-1193.7
    dfop_path_1 tc202398.02390.2-1179.0
    sforb_path_1 tc202399.82392.0-1179.9
    hs_path_1 tc212422.32414.1-1190.2
    
-
    For these two parent model, successful fits are shown below. Plots of
-the fits with the other parent models are shown in the Appendix.
    
-
    -plot(f_saem_1[["dfop_path_1", "tc"]])
    
-
    
-DFOP pathway fit with two-component error
    
-DFOP pathway fit with two-component error
-
    
-
    
-
    -plot(f_saem_1[["sforb_path_1", "tc"]])
    
-
    
-SFORB pathway fit with two-component error
    
-SFORB pathway fit with two-component error
-
    
-
    
-
    A closer graphical analysis of these Figures shows that the residues
-of transformation product JCZ38 in the soils Tama and Nambsheim observed
-at later time points are strongly and systematically underestimated.
    
-
    -stopCluster(cl_path_1)
    
-
    
-
    
-
    Alternative pathway fits
-
    
-
    To improve the fit for JCZ38, a back-reaction from JSE76 to JCZ38 was
-introduced in an alternative version of the transformation pathway, in
-analogy to the back-reaction from K5A78 to K5A77. Both pairs of
-transformation products are pairs of an organic acid with its
-corresponding amide (Addendum 2014, p. 109). As FOMC provided the best
-fit for the parent, and the biexponential models DFOP and SFORB provided
-the best initial pathway fits, these three parent models are used in the
-alternative pathway fits.
    
-
    -cyan_path_2 <- list(
-  fomc_path_2 = mkinmod(
-    cyan = mkinsub("FOMC", c("JCZ38", "J9Z38")),
-    JCZ38 = mkinsub("SFO", "JSE76"),
-    J9Z38 = mkinsub("SFO"),
-    JSE76 = mkinsub("SFO", "JCZ38"),
-    name = "fomc_path_2", quiet = TRUE,
-    dll_dir = "cyan_dlls",
-    overwrite = TRUE
-  ),
-  dfop_path_2 = mkinmod(
-    cyan = mkinsub("DFOP", c("JCZ38", "J9Z38")),
-    JCZ38 = mkinsub("SFO", "JSE76"),
-    J9Z38 = mkinsub("SFO"),
-    JSE76 = mkinsub("SFO", "JCZ38"),
-    name = "dfop_path_2", quiet = TRUE,
-    dll_dir = "cyan_dlls",
-    overwrite = TRUE
-  ),
-  sforb_path_2 = mkinmod(
-    cyan = mkinsub("SFORB", c("JCZ38", "J9Z38")),
-    JCZ38 = mkinsub("SFO", "JSE76"),
-    J9Z38 = mkinsub("SFO"),
-    JSE76 = mkinsub("SFO", "JCZ38"),
-    name = "sforb_path_2", quiet = TRUE,
-    dll_dir = "cyan_dlls",
-    overwrite = TRUE
-  )
-)
-
-cl_path_2 <- start_cluster(n_cores)
-f_sep_2_const <- mmkin(
-  cyan_path_2,
-  cyan_ds,
-  error_model = "const",
-  cluster = cl_path_2,
-  quiet = TRUE)
-
-status(f_sep_2_const) |> kable()
    
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    NambsheimTamaGross-UmstadtSassafrasLleida
    fomc_path_2OKOKOKCOK
    dfop_path_2OKOKOKCOK
    sforb_path_2OKOKOKCOK
    
-
    Using constant variance, separate fits converge with the exception of
-the fits to the Sassafras soil data.
    
-
    -f_sep_2_tc <- update(f_sep_2_const, error_model = "tc")
-status(f_sep_2_tc) |> kable()
    
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    NambsheimTamaGross-UmstadtSassafrasLleida
    fomc_path_2OKCOKCOK
    dfop_path_2OKOKOKCOK
    sforb_path_2OKOKOKOKOK
    
-
    Using the two-component error model, all separate fits converge with
-the exception of the alternative pathway fit with DFOP used for the
-parent and the Sassafras dataset.
    
-
    -f_saem_2 <- mhmkin(list(f_sep_2_const, f_sep_2_tc),
-  no_random_effect = illparms(cyan_saem_full[2:4, ]),
-  cluster = cl_path_2)
    
-
    -status(f_saem_2) |> kable()
    
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    consttc
    fomc_path_2OKFO
    dfop_path_2OKOK
    sforb_path_2OKOK
    
-
    The hierarchical fits for the alternative pathway completed
-successfully.
    
-
    -illparms(f_saem_2) |> kable()
    
-
-----
-
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-
    




    consttc
    fomc_path_2sd(f_JCZ38_qlogis), sd(f_JSE76_qlogis)NA
    dfop_path_2sd(f_JCZ38_qlogis), sd(f_JSE76_qlogis)sd(f_JCZ38_qlogis), sd(f_JSE76_qlogis)
    sforb_path_2sd(f_JCZ38_qlogis), sd(f_JSE76_qlogis)sd(f_JCZ38_qlogis), sd(f_JSE76_qlogis)
    
-
    In both fits, the random effects for the formation fractions for the
-pathways from JCZ38 to JSE76, and for the reverse pathway from JSE76 to
-JCZ38 are ill-defined.
    
-
    -anova(f_saem_2) |> kable(digits = 1)
    
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    nparAICBICLik
    fomc_path_2 const202308.32300.5-1134.2
    fomc_path_2 tc212248.32240.1-1103.2
    dfop_path_2 const222289.62281.0-1122.8
    sforb_path_2 const222284.12275.5-1120.0
    dfop_path_2 tc222234.42225.8-1095.2
    sforb_path_2 tc222240.42231.8-1098.2
    
-
    The variants using the biexponential models DFOP and SFORB for the
-parent compound and the two-component error model give the lowest AIC
-and BIC values and are plotted below. Compared with the original
-pathway, the AIC and BIC values indicate a large improvement. This is
-confirmed by the plots, which show that the metabolite JCZ38 is fitted
-much better with this model.
    
-
    -plot(f_saem_2[["fomc_path_2", "tc"]])
    
-
    
-FOMC pathway fit with two-component error, alternative pathway
    
-FOMC pathway fit with two-component error, alternative pathway
-
    
-
    
-
    -plot(f_saem_2[["dfop_path_2", "tc"]])
    
-
    
-DFOP pathway fit with two-component error, alternative pathway
    
-DFOP pathway fit with two-component error, alternative pathway
-
    
-
    
-
    -plot(f_saem_2[["sforb_path_2", "tc"]])
    
-
    
-SFORB pathway fit with two-component error, alternative pathway
    
-SFORB pathway fit with two-component error, alternative pathway
-
    
-
    
-
    
-
    
-
    Refinement of alternative pathway fits
-
    
-
    All ill-defined random effects that were identified in the parent
-only fits and in the above pathway fits, are excluded for the final
-evaluations below. For this purpose, a list of character vectors is
-created below that can be indexed by row and column indices, and which
-contains the degradation parameter names for which random effects should
-be excluded for each of the hierarchical fits contained in
-f_saem_2.
    
-
    -no_ranef <- matrix(list(), nrow = 3, ncol = 2, dimnames = dimnames(f_saem_2))
-no_ranef[["fomc_path_2", "const"]] <- c("log_beta", "f_JCZ38_qlogis", "f_JSE76_qlogis")
-no_ranef[["fomc_path_2", "tc"]] <- c("cyan_0", "f_JCZ38_qlogis", "f_JSE76_qlogis")
-no_ranef[["dfop_path_2", "const"]] <- c("cyan_0", "f_JCZ38_qlogis", "f_JSE76_qlogis")
-no_ranef[["dfop_path_2", "tc"]] <- c("cyan_0", "log_k1", "f_JCZ38_qlogis", "f_JSE76_qlogis")
-no_ranef[["sforb_path_2", "const"]] <- c("cyan_free_0",
-  "f_JCZ38_qlogis", "f_JSE76_qlogis")
-no_ranef[["sforb_path_2", "tc"]] <- c("cyan_free_0", "log_k_cyan_free_bound",
-  "f_JCZ38_qlogis", "f_JSE76_qlogis")
-clusterExport(cl_path_2, "no_ranef")
-
-f_saem_3 <- update(f_saem_2,
-  no_random_effect = no_ranef,
-  cluster = cl_path_2)
    
-
    -status(f_saem_3) |> kable()
    
-
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    consttc
    fomc_path_2EFth
    dfop_path_2FthFth
    sforb_path_2FthFth
    
-
    With the exception of the FOMC pathway fit with constant variance,
-all updated fits completed successfully. However, the Fisher Information
-Matrix for the fixed effects (Fth) could not be inverted, so no
-confidence intervals for the optimised parameters are available.
    
-
    -illparms(f_saem_3) |> kable()
    
-
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    consttc
    fomc_path_2E
    dfop_path_2
    sforb_path_2
    
-
    -anova(f_saem_3) |> kable(digits = 1)
    
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
    nparAICBICLik
    fomc_path_2 tc192250.92243.5-1106.5
    dfop_path_2 const202281.72273.9-1120.8
    sforb_path_2 const202279.52271.7-1119.7
    dfop_path_2 tc202231.52223.7-1095.8
    sforb_path_2 tc202235.72227.9-1097.9
    
-
    While the AIC and BIC values of the best fit (DFOP pathway fit with
-two-component error) are lower than in the previous fits with the
-alternative pathway, the practical value of these refined evaluations is
-limited as no confidence intervals are obtained.
    
-
    -stopCluster(cl_path_2)
    
-
    
-
    
-
    
-
    Conclusion
-
    
-
    It was demonstrated that a relatively complex transformation pathway
-with parallel formation of two primary metabolites and one secondary
-metabolite can be fitted even if the data in the individual datasets are
-quite different and partly only cover the formation phase.
    
-
    The run times of the pathway fits were several hours, limiting the
-practical feasibility of iterative refinements based on ill-defined
-parameters and of alternative checks of parameter identifiability based
-on multistart runs.
    
-
    
-
    
-
    Acknowledgements
-
    
-
    The helpful comments by Janina Wöltjen of the German Environment
-Agency are gratefully acknowledged.
    
-
    
-
    
-
    Appendix
-
    
-
    
-
    Plots of fits that were not refined further
-
    
-
    -plot(f_saem_1[["sfo_path_1", "tc"]])
    
-
    
-SFO pathway fit with two-component error
    
-SFO pathway fit with two-component error
-
    
-
    
-
    -plot(f_saem_1[["fomc_path_1", "tc"]])
    
-
    
-FOMC pathway fit with two-component error
    
-FOMC pathway fit with two-component error
-
    
-
    
-
    -plot(f_saem_1[["sforb_path_1", "tc"]])
    
-
    
-HS pathway fit with two-component error
    
-HS pathway fit with two-component error
-
    
-
    
-
    
-
    
-
    Hierarchical fit listings
-
    
-
    
-
    Pathway 1
-
    
-
-Hierarchical SFO path 1 fit with constant variance
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:33:05 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan/dt = - k_cyan * cyan
-d_JCZ38/dt = + f_cyan_to_JCZ38 * k_cyan * cyan - k_JCZ38 * JCZ38
-d_J9Z38/dt = + f_cyan_to_J9Z38 * k_cyan * cyan - k_J9Z38 * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 438.011 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
-        cyan_0     log_k_cyan    log_k_JCZ38    log_k_J9Z38    log_k_JSE76 
-       95.3304        -3.8459        -3.1305        -5.0678        -5.3196 
-  f_cyan_ilr_1   f_cyan_ilr_2 f_JCZ38_qlogis 
-        0.8158        22.5404        10.4289 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-               cyan_0 log_k_cyan log_k_JCZ38 log_k_J9Z38 log_k_JSE76
-cyan_0          4.797     0.0000       0.000       0.000      0.0000
-log_k_cyan      0.000     0.9619       0.000       0.000      0.0000
-log_k_JCZ38     0.000     0.0000       2.139       0.000      0.0000
-log_k_J9Z38     0.000     0.0000       0.000       1.639      0.0000
-log_k_JSE76     0.000     0.0000       0.000       0.000      0.7894
-f_cyan_ilr_1    0.000     0.0000       0.000       0.000      0.0000
-f_cyan_ilr_2    0.000     0.0000       0.000       0.000      0.0000
-f_JCZ38_qlogis  0.000     0.0000       0.000       0.000      0.0000
-               f_cyan_ilr_1 f_cyan_ilr_2 f_JCZ38_qlogis
-cyan_0               0.0000        0.000           0.00
-log_k_cyan           0.0000        0.000           0.00
-log_k_JCZ38          0.0000        0.000           0.00
-log_k_J9Z38          0.0000        0.000           0.00
-log_k_JSE76          0.0000        0.000           0.00
-f_cyan_ilr_1         0.7714        0.000           0.00
-f_cyan_ilr_2         0.0000        8.684           0.00
-f_JCZ38_qlogis       0.0000        0.000          13.48
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2693 2687  -1330
-
-Optimised parameters:
-                     est. lower upper
-cyan_0            95.0946    NA    NA
-log_k_cyan        -3.8544    NA    NA
-log_k_JCZ38       -3.0402    NA    NA
-log_k_J9Z38       -5.0109    NA    NA
-log_k_JSE76       -5.2857    NA    NA
-f_cyan_ilr_1       0.8069    NA    NA
-f_cyan_ilr_2      16.6623    NA    NA
-f_JCZ38_qlogis     1.3602    NA    NA
-a.1                4.8326    NA    NA
-SD.log_k_cyan      0.5842    NA    NA
-SD.log_k_JCZ38     1.2680    NA    NA
-SD.log_k_J9Z38     0.3626    NA    NA
-SD.log_k_JSE76     0.5244    NA    NA
-SD.f_cyan_ilr_1    0.2752    NA    NA
-SD.f_cyan_ilr_2    2.3556    NA    NA
-SD.f_JCZ38_qlogis  0.2400    NA    NA
-
-Correlation is not available
-
-Random effects:
-                    est. lower upper
-SD.log_k_cyan     0.5842    NA    NA
-SD.log_k_JCZ38    1.2680    NA    NA
-SD.log_k_J9Z38    0.3626    NA    NA
-SD.log_k_JSE76    0.5244    NA    NA
-SD.f_cyan_ilr_1   0.2752    NA    NA
-SD.f_cyan_ilr_2   2.3556    NA    NA
-SD.f_JCZ38_qlogis 0.2400    NA    NA
-
-Variance model:
-     est. lower upper
-a.1 4.833    NA    NA
-
-Backtransformed parameters:
-                      est. lower upper
-cyan_0           95.094581    NA    NA
-k_cyan            0.021186    NA    NA
-k_JCZ38           0.047825    NA    NA
-k_J9Z38           0.006665    NA    NA
-k_JSE76           0.005063    NA    NA
-f_cyan_to_JCZ38   0.757885    NA    NA
-f_cyan_to_J9Z38   0.242115    NA    NA
-f_JCZ38_to_JSE76  0.795792    NA    NA
-
-Resulting formation fractions:
-                   ff
-cyan_JCZ38  7.579e-01
-cyan_J9Z38  2.421e-01
-cyan_sink   5.877e-10
-JCZ38_JSE76 7.958e-01
-JCZ38_sink  2.042e-01
-
-Estimated disappearance times:
-        DT50   DT90
-cyan   32.72 108.68
-JCZ38  14.49  48.15
-J9Z38 103.99 345.46
-JSE76 136.90 454.76
-
-
    
-
    
-
-Hierarchical SFO path 1 fit with two-component error
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:32:55 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan/dt = - k_cyan * cyan
-d_JCZ38/dt = + f_cyan_to_JCZ38 * k_cyan * cyan - k_JCZ38 * JCZ38
-d_J9Z38/dt = + f_cyan_to_J9Z38 * k_cyan * cyan - k_J9Z38 * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 427.249 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-        cyan_0     log_k_cyan    log_k_JCZ38    log_k_J9Z38    log_k_JSE76 
-       96.0039        -3.8907        -3.1276        -5.0069        -4.9367 
-  f_cyan_ilr_1   f_cyan_ilr_2 f_JCZ38_qlogis 
-        0.7937        20.0030        15.1336 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-               cyan_0 log_k_cyan log_k_JCZ38 log_k_J9Z38 log_k_JSE76
-cyan_0          4.859      0.000        0.00        0.00      0.0000
-log_k_cyan      0.000      0.962        0.00        0.00      0.0000
-log_k_JCZ38     0.000      0.000        2.04        0.00      0.0000
-log_k_J9Z38     0.000      0.000        0.00        1.72      0.0000
-log_k_JSE76     0.000      0.000        0.00        0.00      0.9076
-f_cyan_ilr_1    0.000      0.000        0.00        0.00      0.0000
-f_cyan_ilr_2    0.000      0.000        0.00        0.00      0.0000
-f_JCZ38_qlogis  0.000      0.000        0.00        0.00      0.0000
-               f_cyan_ilr_1 f_cyan_ilr_2 f_JCZ38_qlogis
-cyan_0               0.0000        0.000           0.00
-log_k_cyan           0.0000        0.000           0.00
-log_k_JCZ38          0.0000        0.000           0.00
-log_k_J9Z38          0.0000        0.000           0.00
-log_k_JSE76          0.0000        0.000           0.00
-f_cyan_ilr_1         0.7598        0.000           0.00
-f_cyan_ilr_2         0.0000        7.334           0.00
-f_JCZ38_qlogis       0.0000        0.000          11.78
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2658 2651  -1312
-
-Optimised parameters:
-                      est. lower upper
-cyan_0            94.72923    NA    NA
-log_k_cyan        -3.91670    NA    NA
-log_k_JCZ38       -3.12917    NA    NA
-log_k_J9Z38       -5.06070    NA    NA
-log_k_JSE76       -5.09254    NA    NA
-f_cyan_ilr_1       0.81116    NA    NA
-f_cyan_ilr_2      39.97850    NA    NA
-f_JCZ38_qlogis     3.09728    NA    NA
-a.1                3.95044    NA    NA
-b.1                0.07998    NA    NA
-SD.log_k_cyan      0.58855    NA    NA
-SD.log_k_JCZ38     1.29753    NA    NA
-SD.log_k_J9Z38     0.62851    NA    NA
-SD.log_k_JSE76     0.37235    NA    NA
-SD.f_cyan_ilr_1    0.37346    NA    NA
-SD.f_cyan_ilr_2    1.41667    NA    NA
-SD.f_JCZ38_qlogis  1.81467    NA    NA
-
-Correlation is not available
-
-Random effects:
-                    est. lower upper
-SD.log_k_cyan     0.5886    NA    NA
-SD.log_k_JCZ38    1.2975    NA    NA
-SD.log_k_J9Z38    0.6285    NA    NA
-SD.log_k_JSE76    0.3724    NA    NA
-SD.f_cyan_ilr_1   0.3735    NA    NA
-SD.f_cyan_ilr_2   1.4167    NA    NA
-SD.f_JCZ38_qlogis 1.8147    NA    NA
-
-Variance model:
-       est. lower upper
-a.1 3.95044    NA    NA
-b.1 0.07998    NA    NA
-
-Backtransformed parameters:
-                      est. lower upper
-cyan_0           94.729229    NA    NA
-k_cyan            0.019907    NA    NA
-k_JCZ38           0.043754    NA    NA
-k_J9Z38           0.006341    NA    NA
-k_JSE76           0.006142    NA    NA
-f_cyan_to_JCZ38   0.758991    NA    NA
-f_cyan_to_J9Z38   0.241009    NA    NA
-f_JCZ38_to_JSE76  0.956781    NA    NA
-
-Resulting formation fractions:
-                 ff
-cyan_JCZ38  0.75899
-cyan_J9Z38  0.24101
-cyan_sink   0.00000
-JCZ38_JSE76 0.95678
-JCZ38_sink  0.04322
-
-Estimated disappearance times:
-        DT50   DT90
-cyan   34.82 115.67
-JCZ38  15.84  52.63
-J9Z38 109.31 363.12
-JSE76 112.85 374.87
-
-
    
-
    
-
-Hierarchical FOMC path 1 fit with constant variance
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:33:49 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan
-d_JCZ38/dt = + f_cyan_to_JCZ38 * (alpha/beta) * 1/((time/beta) + 1) *
-           cyan - k_JCZ38 * JCZ38
-d_J9Z38/dt = + f_cyan_to_J9Z38 * (alpha/beta) * 1/((time/beta) + 1) *
-           cyan - k_J9Z38 * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 481.497 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
-        cyan_0    log_k_JCZ38    log_k_J9Z38    log_k_JSE76   f_cyan_ilr_1 
-      101.2314        -3.3680        -5.1108        -5.9416         0.7144 
-  f_cyan_ilr_2 f_JCZ38_qlogis      log_alpha       log_beta 
-        7.3870        15.7604        -0.1791         2.9811 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-               cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1
-cyan_0          5.416       0.000         0.0       0.000       0.0000
-log_k_JCZ38     0.000       2.439         0.0       0.000       0.0000
-log_k_J9Z38     0.000       0.000         1.7       0.000       0.0000
-log_k_JSE76     0.000       0.000         0.0       1.856       0.0000
-f_cyan_ilr_1    0.000       0.000         0.0       0.000       0.7164
-f_cyan_ilr_2    0.000       0.000         0.0       0.000       0.0000
-f_JCZ38_qlogis  0.000       0.000         0.0       0.000       0.0000
-log_alpha       0.000       0.000         0.0       0.000       0.0000
-log_beta        0.000       0.000         0.0       0.000       0.0000
-               f_cyan_ilr_2 f_JCZ38_qlogis log_alpha log_beta
-cyan_0                 0.00           0.00    0.0000   0.0000
-log_k_JCZ38            0.00           0.00    0.0000   0.0000
-log_k_J9Z38            0.00           0.00    0.0000   0.0000
-log_k_JSE76            0.00           0.00    0.0000   0.0000
-f_cyan_ilr_1           0.00           0.00    0.0000   0.0000
-f_cyan_ilr_2          12.33           0.00    0.0000   0.0000
-f_JCZ38_qlogis         0.00          20.42    0.0000   0.0000
-log_alpha              0.00           0.00    0.4144   0.0000
-log_beta               0.00           0.00    0.0000   0.5077
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2428 2421  -1196
-
-Optimised parameters:
-                      est.     lower    upper
-cyan_0            101.0225 98.306270 103.7387
-log_k_JCZ38        -3.3786 -4.770657  -1.9866
-log_k_J9Z38        -5.2603 -5.902085  -4.6186
-log_k_JSE76        -6.1427 -7.318336  -4.9671
-f_cyan_ilr_1        0.7437  0.421215   1.0663
-f_cyan_ilr_2        0.9108  0.267977   1.5537
-f_JCZ38_qlogis      2.0487  0.524897   3.5724
-log_alpha          -0.2268 -0.618049   0.1644
-log_beta            2.8986  2.700701   3.0964
-a.1                 3.4058  3.169913   3.6416
-SD.cyan_0           2.5279  0.454190   4.6016
-SD.log_k_JCZ38      1.5636  0.572824   2.5543
-SD.log_k_J9Z38      0.5316 -0.004405   1.0677
-SD.log_k_JSE76      0.9903  0.106325   1.8742
-SD.f_cyan_ilr_1     0.3464  0.112066   0.5807
-SD.f_cyan_ilr_2     0.2804 -0.393900   0.9546
-SD.f_JCZ38_qlogis   0.9416 -0.152986   2.0362
-SD.log_alpha        0.4273  0.161044   0.6936
-
-Correlation: 
-               cyan_0  l__JCZ3 l__J9Z3 l__JSE7 f_cy__1 f_cy__2 f_JCZ38 log_lph
-log_k_JCZ38    -0.0156                                                        
-log_k_J9Z38    -0.0493  0.0073                                                
-log_k_JSE76    -0.0329  0.0018  0.0069                                        
-f_cyan_ilr_1   -0.0086  0.0180 -0.1406  0.0012                                
-f_cyan_ilr_2   -0.2629  0.0779  0.2826  0.0274  0.0099                        
-f_JCZ38_qlogis  0.0713 -0.0747 -0.0505  0.1169 -0.1022 -0.4893                
-log_alpha      -0.0556  0.0120  0.0336  0.0193  0.0036  0.0840 -0.0489        
-log_beta       -0.2898  0.0460  0.1305  0.0768  0.0190  0.4071 -0.1981  0.2772
-
-Random effects:
-                    est.     lower  upper
-SD.cyan_0         2.5279  0.454190 4.6016
-SD.log_k_JCZ38    1.5636  0.572824 2.5543
-SD.log_k_J9Z38    0.5316 -0.004405 1.0677
-SD.log_k_JSE76    0.9903  0.106325 1.8742
-SD.f_cyan_ilr_1   0.3464  0.112066 0.5807
-SD.f_cyan_ilr_2   0.2804 -0.393900 0.9546
-SD.f_JCZ38_qlogis 0.9416 -0.152986 2.0362
-SD.log_alpha      0.4273  0.161044 0.6936
-
-Variance model:
-     est. lower upper
-a.1 3.406  3.17 3.642
-
-Backtransformed parameters:
-                      est.     lower     upper
-cyan_0           1.010e+02 9.831e+01 1.037e+02
-k_JCZ38          3.409e-02 8.475e-03 1.372e-01
-k_J9Z38          5.194e-03 2.734e-03 9.867e-03
-k_JSE76          2.149e-03 6.633e-04 6.963e-03
-f_cyan_to_JCZ38  6.481e-01        NA        NA
-f_cyan_to_J9Z38  2.264e-01        NA        NA
-f_JCZ38_to_JSE76 8.858e-01 6.283e-01 9.727e-01
-alpha            7.971e-01 5.390e-01 1.179e+00
-beta             1.815e+01 1.489e+01 2.212e+01
-
-Resulting formation fractions:
-                ff
-cyan_JCZ38  0.6481
-cyan_J9Z38  0.2264
-cyan_sink   0.1255
-JCZ38_JSE76 0.8858
-JCZ38_sink  0.1142
-
-Estimated disappearance times:
-        DT50    DT90 DT50back
-cyan   25.15  308.01    92.72
-JCZ38  20.33   67.54       NA
-J9Z38 133.46  443.35       NA
-JSE76 322.53 1071.42       NA
-
-
    
-
    
-
-Hierarchical FOMC path 1 fit with two-component error
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:33:59 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan
-d_JCZ38/dt = + f_cyan_to_JCZ38 * (alpha/beta) * 1/((time/beta) + 1) *
-           cyan - k_JCZ38 * JCZ38
-d_J9Z38/dt = + f_cyan_to_J9Z38 * (alpha/beta) * 1/((time/beta) + 1) *
-           cyan - k_J9Z38 * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 491.071 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-        cyan_0    log_k_JCZ38    log_k_J9Z38    log_k_JSE76   f_cyan_ilr_1 
-     101.13827       -3.32493       -5.08921       -5.93478        0.71330 
-  f_cyan_ilr_2 f_JCZ38_qlogis      log_alpha       log_beta 
-      10.05989       12.79248       -0.09621        3.10646 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-               cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1
-cyan_0          5.643       0.000       0.000        0.00       0.0000
-log_k_JCZ38     0.000       2.319       0.000        0.00       0.0000
-log_k_J9Z38     0.000       0.000       1.731        0.00       0.0000
-log_k_JSE76     0.000       0.000       0.000        1.86       0.0000
-f_cyan_ilr_1    0.000       0.000       0.000        0.00       0.7186
-f_cyan_ilr_2    0.000       0.000       0.000        0.00       0.0000
-f_JCZ38_qlogis  0.000       0.000       0.000        0.00       0.0000
-log_alpha       0.000       0.000       0.000        0.00       0.0000
-log_beta        0.000       0.000       0.000        0.00       0.0000
-               f_cyan_ilr_2 f_JCZ38_qlogis log_alpha log_beta
-cyan_0                 0.00           0.00    0.0000   0.0000
-log_k_JCZ38            0.00           0.00    0.0000   0.0000
-log_k_J9Z38            0.00           0.00    0.0000   0.0000
-log_k_JSE76            0.00           0.00    0.0000   0.0000
-f_cyan_ilr_1           0.00           0.00    0.0000   0.0000
-f_cyan_ilr_2          12.49           0.00    0.0000   0.0000
-f_JCZ38_qlogis         0.00          20.19    0.0000   0.0000
-log_alpha              0.00           0.00    0.3142   0.0000
-log_beta               0.00           0.00    0.0000   0.7331
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2423 2416  -1193
-
-Optimised parameters:
-                       est. lower upper
-cyan_0            100.57649    NA    NA
-log_k_JCZ38        -3.46250    NA    NA
-log_k_J9Z38        -5.24442    NA    NA
-log_k_JSE76        -5.75229    NA    NA
-f_cyan_ilr_1        0.68480    NA    NA
-f_cyan_ilr_2        0.61670    NA    NA
-f_JCZ38_qlogis     87.97407    NA    NA
-log_alpha          -0.15699    NA    NA
-log_beta            3.01540    NA    NA
-a.1                 3.11518    NA    NA
-b.1                 0.04445    NA    NA
-SD.log_k_JCZ38      1.40732    NA    NA
-SD.log_k_J9Z38      0.56510    NA    NA
-SD.log_k_JSE76      0.72067    NA    NA
-SD.f_cyan_ilr_1     0.31199    NA    NA
-SD.f_cyan_ilr_2     0.36894    NA    NA
-SD.f_JCZ38_qlogis   6.92892    NA    NA
-SD.log_alpha        0.25662    NA    NA
-SD.log_beta         0.35845    NA    NA
-
-Correlation is not available
-
-Random effects:
-                    est. lower upper
-SD.log_k_JCZ38    1.4073    NA    NA
-SD.log_k_J9Z38    0.5651    NA    NA
-SD.log_k_JSE76    0.7207    NA    NA
-SD.f_cyan_ilr_1   0.3120    NA    NA
-SD.f_cyan_ilr_2   0.3689    NA    NA
-SD.f_JCZ38_qlogis 6.9289    NA    NA
-SD.log_alpha      0.2566    NA    NA
-SD.log_beta       0.3585    NA    NA
-
-Variance model:
-       est. lower upper
-a.1 3.11518    NA    NA
-b.1 0.04445    NA    NA
-
-Backtransformed parameters:
-                      est. lower upper
-cyan_0           1.006e+02    NA    NA
-k_JCZ38          3.135e-02    NA    NA
-k_J9Z38          5.277e-03    NA    NA
-k_JSE76          3.175e-03    NA    NA
-f_cyan_to_JCZ38  5.991e-01    NA    NA
-f_cyan_to_J9Z38  2.275e-01    NA    NA
-f_JCZ38_to_JSE76 1.000e+00    NA    NA
-alpha            8.547e-01    NA    NA
-beta             2.040e+01    NA    NA
-
-Resulting formation fractions:
-                ff
-cyan_JCZ38  0.5991
-cyan_J9Z38  0.2275
-cyan_sink   0.1734
-JCZ38_JSE76 1.0000
-JCZ38_sink  0.0000
-
-Estimated disappearance times:
-        DT50   DT90 DT50back
-cyan   25.50 281.29    84.68
-JCZ38  22.11  73.44       NA
-J9Z38 131.36 436.35       NA
-JSE76 218.28 725.11       NA
-
-
    
-
    
-
-Hierarchical DFOP path 1 fit with constant variance
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:34:33 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-           time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-           * cyan
-d_JCZ38/dt = + f_cyan_to_JCZ38 * ((k1 * g * exp(-k1 * time) + k2 * (1 -
-           g) * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-           exp(-k2 * time))) * cyan - k_JCZ38 * JCZ38
-d_J9Z38/dt = + f_cyan_to_J9Z38 * ((k1 * g * exp(-k1 * time) + k2 * (1 -
-           g) * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-           exp(-k2 * time))) * cyan - k_J9Z38 * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 525.551 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
-        cyan_0    log_k_JCZ38    log_k_J9Z38    log_k_JSE76   f_cyan_ilr_1 
-      102.0644        -3.4008        -5.0024        -5.8613         0.6855 
-  f_cyan_ilr_2 f_JCZ38_qlogis         log_k1         log_k2       g_qlogis 
-        1.2365        13.7245        -1.8641        -4.5063        -0.6468 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-               cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1
-cyan_0          4.466       0.000       0.000       0.000       0.0000
-log_k_JCZ38     0.000       2.382       0.000       0.000       0.0000
-log_k_J9Z38     0.000       0.000       1.595       0.000       0.0000
-log_k_JSE76     0.000       0.000       0.000       1.245       0.0000
-f_cyan_ilr_1    0.000       0.000       0.000       0.000       0.6852
-f_cyan_ilr_2    0.000       0.000       0.000       0.000       0.0000
-f_JCZ38_qlogis  0.000       0.000       0.000       0.000       0.0000
-log_k1          0.000       0.000       0.000       0.000       0.0000
-log_k2          0.000       0.000       0.000       0.000       0.0000
-g_qlogis        0.000       0.000       0.000       0.000       0.0000
-               f_cyan_ilr_2 f_JCZ38_qlogis log_k1 log_k2 g_qlogis
-cyan_0                 0.00           0.00 0.0000 0.0000    0.000
-log_k_JCZ38            0.00           0.00 0.0000 0.0000    0.000
-log_k_J9Z38            0.00           0.00 0.0000 0.0000    0.000
-log_k_JSE76            0.00           0.00 0.0000 0.0000    0.000
-f_cyan_ilr_1           0.00           0.00 0.0000 0.0000    0.000
-f_cyan_ilr_2           1.28           0.00 0.0000 0.0000    0.000
-f_JCZ38_qlogis         0.00          16.11 0.0000 0.0000    0.000
-log_k1                 0.00           0.00 0.9866 0.0000    0.000
-log_k2                 0.00           0.00 0.0000 0.5953    0.000
-g_qlogis               0.00           0.00 0.0000 0.0000    1.583
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2403 2395  -1182
-
-Optimised parameters:
-                      est. lower upper
-cyan_0            102.6079    NA    NA
-log_k_JCZ38        -3.4855    NA    NA
-log_k_J9Z38        -5.1686    NA    NA
-log_k_JSE76        -5.6697    NA    NA
-f_cyan_ilr_1        0.6714    NA    NA
-f_cyan_ilr_2        0.4986    NA    NA
-f_JCZ38_qlogis     55.4760    NA    NA
-log_k1             -1.8409    NA    NA
-log_k2             -4.4915    NA    NA
-g_qlogis           -0.6403    NA    NA
-a.1                 3.2387    NA    NA
-SD.log_k_JCZ38      1.4524    NA    NA
-SD.log_k_J9Z38      0.5151    NA    NA
-SD.log_k_JSE76      0.6514    NA    NA
-SD.f_cyan_ilr_1     0.3023    NA    NA
-SD.f_cyan_ilr_2     0.2959    NA    NA
-SD.f_JCZ38_qlogis   1.9984    NA    NA
-SD.log_k1           0.5188    NA    NA
-SD.log_k2           0.3894    NA    NA
-SD.g_qlogis         0.8579    NA    NA
-
-Correlation is not available
-
-Random effects:
-                    est. lower upper
-SD.log_k_JCZ38    1.4524    NA    NA
-SD.log_k_J9Z38    0.5151    NA    NA
-SD.log_k_JSE76    0.6514    NA    NA
-SD.f_cyan_ilr_1   0.3023    NA    NA
-SD.f_cyan_ilr_2   0.2959    NA    NA
-SD.f_JCZ38_qlogis 1.9984    NA    NA
-SD.log_k1         0.5188    NA    NA
-SD.log_k2         0.3894    NA    NA
-SD.g_qlogis       0.8579    NA    NA
-
-Variance model:
-     est. lower upper
-a.1 3.239    NA    NA
-
-Backtransformed parameters:
-                      est. lower upper
-cyan_0           1.026e+02    NA    NA
-k_JCZ38          3.064e-02    NA    NA
-k_J9Z38          5.692e-03    NA    NA
-k_JSE76          3.449e-03    NA    NA
-f_cyan_to_JCZ38  5.798e-01    NA    NA
-f_cyan_to_J9Z38  2.243e-01    NA    NA
-f_JCZ38_to_JSE76 1.000e+00    NA    NA
-k1               1.587e-01    NA    NA
-k2               1.120e-02    NA    NA
-g                3.452e-01    NA    NA
-
-Resulting formation fractions:
-                ff
-cyan_JCZ38  0.5798
-cyan_J9Z38  0.2243
-cyan_sink   0.1958
-JCZ38_JSE76 1.0000
-JCZ38_sink  0.0000
-
-Estimated disappearance times:
-        DT50   DT90 DT50back DT50_k1 DT50_k2
-cyan   25.21 167.73    50.49   4.368   61.87
-JCZ38  22.62  75.15       NA      NA      NA
-J9Z38 121.77 404.50       NA      NA      NA
-JSE76 200.98 667.64       NA      NA      NA
-
-
    
-
    
-
-Hierarchical DFOP path 1 fit with two-component error
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:37:03 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-           time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-           * cyan
-d_JCZ38/dt = + f_cyan_to_JCZ38 * ((k1 * g * exp(-k1 * time) + k2 * (1 -
-           g) * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-           exp(-k2 * time))) * cyan - k_JCZ38 * JCZ38
-d_J9Z38/dt = + f_cyan_to_J9Z38 * ((k1 * g * exp(-k1 * time) + k2 * (1 -
-           g) * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-           exp(-k2 * time))) * cyan - k_J9Z38 * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 675.804 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-        cyan_0    log_k_JCZ38    log_k_J9Z38    log_k_JSE76   f_cyan_ilr_1 
-      101.3964        -3.3626        -4.9792        -5.8727         0.6814 
-  f_cyan_ilr_2 f_JCZ38_qlogis         log_k1         log_k2       g_qlogis 
-        6.7799        13.7245        -1.9222        -4.5035        -0.7172 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-               cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1
-cyan_0          5.317       0.000       0.000       0.000       0.0000
-log_k_JCZ38     0.000       2.272       0.000       0.000       0.0000
-log_k_J9Z38     0.000       0.000       1.633       0.000       0.0000
-log_k_JSE76     0.000       0.000       0.000       1.271       0.0000
-f_cyan_ilr_1    0.000       0.000       0.000       0.000       0.6838
-f_cyan_ilr_2    0.000       0.000       0.000       0.000       0.0000
-f_JCZ38_qlogis  0.000       0.000       0.000       0.000       0.0000
-log_k1          0.000       0.000       0.000       0.000       0.0000
-log_k2          0.000       0.000       0.000       0.000       0.0000
-g_qlogis        0.000       0.000       0.000       0.000       0.0000
-               f_cyan_ilr_2 f_JCZ38_qlogis log_k1 log_k2 g_qlogis
-cyan_0                 0.00           0.00 0.0000 0.0000    0.000
-log_k_JCZ38            0.00           0.00 0.0000 0.0000    0.000
-log_k_J9Z38            0.00           0.00 0.0000 0.0000    0.000
-log_k_JSE76            0.00           0.00 0.0000 0.0000    0.000
-f_cyan_ilr_1           0.00           0.00 0.0000 0.0000    0.000
-f_cyan_ilr_2          11.77           0.00 0.0000 0.0000    0.000
-f_JCZ38_qlogis         0.00          16.11 0.0000 0.0000    0.000
-log_k1                 0.00           0.00 0.9496 0.0000    0.000
-log_k2                 0.00           0.00 0.0000 0.5846    0.000
-g_qlogis               0.00           0.00 0.0000 0.0000    1.719
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2398 2390  -1179
-
-Optimised parameters:
-                      est. lower upper
-cyan_0            100.8076    NA    NA
-log_k_JCZ38        -3.4684    NA    NA
-log_k_J9Z38        -5.0844    NA    NA
-log_k_JSE76        -5.5743    NA    NA
-f_cyan_ilr_1        0.6669    NA    NA
-f_cyan_ilr_2        0.7912    NA    NA
-f_JCZ38_qlogis     84.1825    NA    NA
-log_k1             -2.1671    NA    NA
-log_k2             -4.5447    NA    NA
-g_qlogis           -0.5631    NA    NA
-a.1                 2.9627    NA    NA
-b.1                 0.0444    NA    NA
-SD.log_k_JCZ38      1.4044    NA    NA
-SD.log_k_J9Z38      0.6410    NA    NA
-SD.log_k_JSE76      0.5391    NA    NA
-SD.f_cyan_ilr_1     0.3203    NA    NA
-SD.f_cyan_ilr_2     0.5038    NA    NA
-SD.f_JCZ38_qlogis   3.5865    NA    NA
-SD.log_k2           0.3119    NA    NA
-SD.g_qlogis         0.8276    NA    NA
-
-Correlation is not available
-
-Random effects:
-                    est. lower upper
-SD.log_k_JCZ38    1.4044    NA    NA
-SD.log_k_J9Z38    0.6410    NA    NA
-SD.log_k_JSE76    0.5391    NA    NA
-SD.f_cyan_ilr_1   0.3203    NA    NA
-SD.f_cyan_ilr_2   0.5038    NA    NA
-SD.f_JCZ38_qlogis 3.5865    NA    NA
-SD.log_k2         0.3119    NA    NA
-SD.g_qlogis       0.8276    NA    NA
-
-Variance model:
-      est. lower upper
-a.1 2.9627    NA    NA
-b.1 0.0444    NA    NA
-
-Backtransformed parameters:
-                      est. lower upper
-cyan_0           1.008e+02    NA    NA
-k_JCZ38          3.117e-02    NA    NA
-k_J9Z38          6.193e-03    NA    NA
-k_JSE76          3.794e-03    NA    NA
-f_cyan_to_JCZ38  6.149e-01    NA    NA
-f_cyan_to_J9Z38  2.395e-01    NA    NA
-f_JCZ38_to_JSE76 1.000e+00    NA    NA
-k1               1.145e-01    NA    NA
-k2               1.062e-02    NA    NA
-g                3.628e-01    NA    NA
-
-Resulting formation fractions:
-                ff
-cyan_JCZ38  0.6149
-cyan_J9Z38  0.2395
-cyan_sink   0.1456
-JCZ38_JSE76 1.0000
-JCZ38_sink  0.0000
-
-Estimated disappearance times:
-        DT50   DT90 DT50back DT50_k1 DT50_k2
-cyan   26.26 174.32    52.47   6.053   65.25
-JCZ38  22.24  73.88       NA      NA      NA
-J9Z38 111.93 371.82       NA      NA      NA
-JSE76 182.69 606.88       NA      NA      NA
-
-
    
-
    
-
-Hierarchical SFORB path 1 fit with constant variance
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:34:43 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound *
-           cyan_free + k_cyan_bound_free * cyan_bound
-d_cyan_bound/dt = + k_cyan_free_bound * cyan_free - k_cyan_bound_free *
-           cyan_bound
-d_JCZ38/dt = + f_cyan_free_to_JCZ38 * k_cyan_free * cyan_free - k_JCZ38
-           * JCZ38
-d_J9Z38/dt = + f_cyan_free_to_J9Z38 * k_cyan_free * cyan_free - k_J9Z38
-           * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 535.818 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
-          cyan_free_0       log_k_cyan_free log_k_cyan_free_bound 
-             102.0643               -2.8987               -2.7077 
-log_k_cyan_bound_free           log_k_JCZ38           log_k_J9Z38 
-              -3.4717               -3.4008               -5.0024 
-          log_k_JSE76          f_cyan_ilr_1          f_cyan_ilr_2 
-              -5.8613                0.6855                1.2366 
-       f_JCZ38_qlogis 
-              13.7418 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-                      cyan_free_0 log_k_cyan_free log_k_cyan_free_bound
-cyan_free_0                 4.466          0.0000                 0.000
-log_k_cyan_free             0.000          0.6158                 0.000
-log_k_cyan_free_bound       0.000          0.0000                 1.463
-log_k_cyan_bound_free       0.000          0.0000                 0.000
-log_k_JCZ38                 0.000          0.0000                 0.000
-log_k_J9Z38                 0.000          0.0000                 0.000
-log_k_JSE76                 0.000          0.0000                 0.000
-f_cyan_ilr_1                0.000          0.0000                 0.000
-f_cyan_ilr_2                0.000          0.0000                 0.000
-f_JCZ38_qlogis              0.000          0.0000                 0.000
-                      log_k_cyan_bound_free log_k_JCZ38 log_k_J9Z38 log_k_JSE76
-cyan_free_0                           0.000       0.000       0.000       0.000
-log_k_cyan_free                       0.000       0.000       0.000       0.000
-log_k_cyan_free_bound                 0.000       0.000       0.000       0.000
-log_k_cyan_bound_free                 1.058       0.000       0.000       0.000
-log_k_JCZ38                           0.000       2.382       0.000       0.000
-log_k_J9Z38                           0.000       0.000       1.595       0.000
-log_k_JSE76                           0.000       0.000       0.000       1.245
-f_cyan_ilr_1                          0.000       0.000       0.000       0.000
-f_cyan_ilr_2                          0.000       0.000       0.000       0.000
-f_JCZ38_qlogis                        0.000       0.000       0.000       0.000
-                      f_cyan_ilr_1 f_cyan_ilr_2 f_JCZ38_qlogis
-cyan_free_0                 0.0000         0.00           0.00
-log_k_cyan_free             0.0000         0.00           0.00
-log_k_cyan_free_bound       0.0000         0.00           0.00
-log_k_cyan_bound_free       0.0000         0.00           0.00
-log_k_JCZ38                 0.0000         0.00           0.00
-log_k_J9Z38                 0.0000         0.00           0.00
-log_k_JSE76                 0.0000         0.00           0.00
-f_cyan_ilr_1                0.6852         0.00           0.00
-f_cyan_ilr_2                0.0000         1.28           0.00
-f_JCZ38_qlogis              0.0000         0.00          16.14
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2401 2394  -1181
-
-Optimised parameters:
-                             est. lower upper
-cyan_free_0              102.7803    NA    NA
-log_k_cyan_free           -2.8068    NA    NA
-log_k_cyan_free_bound     -2.5714    NA    NA
-log_k_cyan_bound_free     -3.4426    NA    NA
-log_k_JCZ38               -3.4994    NA    NA
-log_k_J9Z38               -5.1148    NA    NA
-log_k_JSE76               -5.6335    NA    NA
-f_cyan_ilr_1               0.6597    NA    NA
-f_cyan_ilr_2               0.5132    NA    NA
-f_JCZ38_qlogis            37.2090    NA    NA
-a.1                        3.2367    NA    NA
-SD.log_k_cyan_free         0.3161    NA    NA
-SD.log_k_cyan_free_bound   0.8103    NA    NA
-SD.log_k_cyan_bound_free   0.5554    NA    NA
-SD.log_k_JCZ38             1.4858    NA    NA
-SD.log_k_J9Z38             0.5859    NA    NA
-SD.log_k_JSE76             0.6195    NA    NA
-SD.f_cyan_ilr_1            0.3118    NA    NA
-SD.f_cyan_ilr_2            0.3344    NA    NA
-SD.f_JCZ38_qlogis          0.5518    NA    NA
-
-Correlation is not available
-
-Random effects:
-                           est. lower upper
-SD.log_k_cyan_free       0.3161    NA    NA
-SD.log_k_cyan_free_bound 0.8103    NA    NA
-SD.log_k_cyan_bound_free 0.5554    NA    NA
-SD.log_k_JCZ38           1.4858    NA    NA
-SD.log_k_J9Z38           0.5859    NA    NA
-SD.log_k_JSE76           0.6195    NA    NA
-SD.f_cyan_ilr_1          0.3118    NA    NA
-SD.f_cyan_ilr_2          0.3344    NA    NA
-SD.f_JCZ38_qlogis        0.5518    NA    NA
-
-Variance model:
-     est. lower upper
-a.1 3.237    NA    NA
-
-Backtransformed parameters:
-                          est. lower upper
-cyan_free_0          1.028e+02    NA    NA
-k_cyan_free          6.040e-02    NA    NA
-k_cyan_free_bound    7.643e-02    NA    NA
-k_cyan_bound_free    3.198e-02    NA    NA
-k_JCZ38              3.022e-02    NA    NA
-k_J9Z38              6.007e-03    NA    NA
-k_JSE76              3.576e-03    NA    NA
-f_cyan_free_to_JCZ38 5.787e-01    NA    NA
-f_cyan_free_to_J9Z38 2.277e-01    NA    NA
-f_JCZ38_to_JSE76     1.000e+00    NA    NA
-
-Estimated Eigenvalues of SFORB model(s):
-cyan_b1 cyan_b2  cyan_g 
-0.15646 0.01235 0.33341 
-
-Resulting formation fractions:
-                    ff
-cyan_free_JCZ38 0.5787
-cyan_free_J9Z38 0.2277
-cyan_free_sink  0.1936
-cyan_free       1.0000
-JCZ38_JSE76     1.0000
-JCZ38_sink      0.0000
-
-Estimated disappearance times:
-        DT50  DT90 DT50back DT50_cyan_b1 DT50_cyan_b2
-cyan   24.48 153.7    46.26         4.43        56.15
-JCZ38  22.94  76.2       NA           NA           NA
-J9Z38 115.39 383.3       NA           NA           NA
-JSE76 193.84 643.9       NA           NA           NA
-
-
    
-
    
-
-Hierarchical SFORB path 1 fit with two-component error
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:37:02 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound *
-           cyan_free + k_cyan_bound_free * cyan_bound
-d_cyan_bound/dt = + k_cyan_free_bound * cyan_free - k_cyan_bound_free *
-           cyan_bound
-d_JCZ38/dt = + f_cyan_free_to_JCZ38 * k_cyan_free * cyan_free - k_JCZ38
-           * JCZ38
-d_J9Z38/dt = + f_cyan_free_to_J9Z38 * k_cyan_free * cyan_free - k_J9Z38
-           * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 674.859 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-          cyan_free_0       log_k_cyan_free log_k_cyan_free_bound 
-             101.3964               -2.9881               -2.7949 
-log_k_cyan_bound_free           log_k_JCZ38           log_k_J9Z38 
-              -3.4376               -3.3626               -4.9792 
-          log_k_JSE76          f_cyan_ilr_1          f_cyan_ilr_2 
-              -5.8727                0.6814                6.8139 
-       f_JCZ38_qlogis 
-              13.7419 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-                      cyan_free_0 log_k_cyan_free log_k_cyan_free_bound
-cyan_free_0                 5.317          0.0000                 0.000
-log_k_cyan_free             0.000          0.7301                 0.000
-log_k_cyan_free_bound       0.000          0.0000                 1.384
-log_k_cyan_bound_free       0.000          0.0000                 0.000
-log_k_JCZ38                 0.000          0.0000                 0.000
-log_k_J9Z38                 0.000          0.0000                 0.000
-log_k_JSE76                 0.000          0.0000                 0.000
-f_cyan_ilr_1                0.000          0.0000                 0.000
-f_cyan_ilr_2                0.000          0.0000                 0.000
-f_JCZ38_qlogis              0.000          0.0000                 0.000
-                      log_k_cyan_bound_free log_k_JCZ38 log_k_J9Z38 log_k_JSE76
-cyan_free_0                           0.000       0.000       0.000       0.000
-log_k_cyan_free                       0.000       0.000       0.000       0.000
-log_k_cyan_free_bound                 0.000       0.000       0.000       0.000
-log_k_cyan_bound_free                 1.109       0.000       0.000       0.000
-log_k_JCZ38                           0.000       2.272       0.000       0.000
-log_k_J9Z38                           0.000       0.000       1.633       0.000
-log_k_JSE76                           0.000       0.000       0.000       1.271
-f_cyan_ilr_1                          0.000       0.000       0.000       0.000
-f_cyan_ilr_2                          0.000       0.000       0.000       0.000
-f_JCZ38_qlogis                        0.000       0.000       0.000       0.000
-                      f_cyan_ilr_1 f_cyan_ilr_2 f_JCZ38_qlogis
-cyan_free_0                 0.0000         0.00           0.00
-log_k_cyan_free             0.0000         0.00           0.00
-log_k_cyan_free_bound       0.0000         0.00           0.00
-log_k_cyan_bound_free       0.0000         0.00           0.00
-log_k_JCZ38                 0.0000         0.00           0.00
-log_k_J9Z38                 0.0000         0.00           0.00
-log_k_JSE76                 0.0000         0.00           0.00
-f_cyan_ilr_1                0.6838         0.00           0.00
-f_cyan_ilr_2                0.0000        11.84           0.00
-f_JCZ38_qlogis              0.0000         0.00          16.14
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2400 2392  -1180
-
-Optimised parameters:
-                              est. lower upper
-cyan_free_0              100.69983    NA    NA
-log_k_cyan_free           -3.11584    NA    NA
-log_k_cyan_free_bound     -3.15216    NA    NA
-log_k_cyan_bound_free     -3.65986    NA    NA
-log_k_JCZ38               -3.47811    NA    NA
-log_k_J9Z38               -5.08835    NA    NA
-log_k_JSE76               -5.55514    NA    NA
-f_cyan_ilr_1               0.66764    NA    NA
-f_cyan_ilr_2               0.78329    NA    NA
-f_JCZ38_qlogis            25.35245    NA    NA
-a.1                        2.99088    NA    NA
-b.1                        0.04346    NA    NA
-SD.log_k_cyan_free         0.48797    NA    NA
-SD.log_k_cyan_bound_free   0.27243    NA    NA
-SD.log_k_JCZ38             1.42450    NA    NA
-SD.log_k_J9Z38             0.63496    NA    NA
-SD.log_k_JSE76             0.55951    NA    NA
-SD.f_cyan_ilr_1            0.32687    NA    NA
-SD.f_cyan_ilr_2            0.48056    NA    NA
-SD.f_JCZ38_qlogis          0.43818    NA    NA
-
-Correlation is not available
-
-Random effects:
-                           est. lower upper
-SD.log_k_cyan_free       0.4880    NA    NA
-SD.log_k_cyan_bound_free 0.2724    NA    NA
-SD.log_k_JCZ38           1.4245    NA    NA
-SD.log_k_J9Z38           0.6350    NA    NA
-SD.log_k_JSE76           0.5595    NA    NA
-SD.f_cyan_ilr_1          0.3269    NA    NA
-SD.f_cyan_ilr_2          0.4806    NA    NA
-SD.f_JCZ38_qlogis        0.4382    NA    NA
-
-Variance model:
-       est. lower upper
-a.1 2.99088    NA    NA
-b.1 0.04346    NA    NA
-
-Backtransformed parameters:
-                          est. lower upper
-cyan_free_0          1.007e+02    NA    NA
-k_cyan_free          4.434e-02    NA    NA
-k_cyan_free_bound    4.276e-02    NA    NA
-k_cyan_bound_free    2.574e-02    NA    NA
-k_JCZ38              3.087e-02    NA    NA
-k_J9Z38              6.168e-03    NA    NA
-k_JSE76              3.868e-03    NA    NA
-f_cyan_free_to_JCZ38 6.143e-01    NA    NA
-f_cyan_free_to_J9Z38 2.389e-01    NA    NA
-f_JCZ38_to_JSE76     1.000e+00    NA    NA
-
-Estimated Eigenvalues of SFORB model(s):
-cyan_b1 cyan_b2  cyan_g 
-0.10161 0.01123 0.36636 
-
-Resulting formation fractions:
-                       ff
-cyan_free_JCZ38 6.143e-01
-cyan_free_J9Z38 2.389e-01
-cyan_free_sink  1.468e-01
-cyan_free       1.000e+00
-JCZ38_JSE76     1.000e+00
-JCZ38_sink      9.763e-12
-
-Estimated disappearance times:
-        DT50  DT90 DT50back DT50_cyan_b1 DT50_cyan_b2
-cyan   25.91 164.4    49.49        6.822        61.72
-JCZ38  22.46  74.6       NA           NA           NA
-J9Z38 112.37 373.3       NA           NA           NA
-JSE76 179.22 595.4       NA           NA           NA
-
-
    
-
    
-
-Hierarchical HS path 1 fit with constant variance
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:34:41 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan/dt = - ifelse(time <= tb, k1, k2) * cyan
-d_JCZ38/dt = + f_cyan_to_JCZ38 * ifelse(time <= tb, k1, k2) * cyan -
-           k_JCZ38 * JCZ38
-d_J9Z38/dt = + f_cyan_to_J9Z38 * ifelse(time <= tb, k1, k2) * cyan -
-           k_J9Z38 * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 533.787 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
-        cyan_0    log_k_JCZ38    log_k_J9Z38    log_k_JSE76   f_cyan_ilr_1 
-      102.8738        -3.4490        -4.9348        -5.5989         0.6469 
-  f_cyan_ilr_2 f_JCZ38_qlogis         log_k1         log_k2         log_tb 
-        1.2854         9.7193        -2.9084        -4.1810         1.7813 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-               cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1
-cyan_0          5.409        0.00        0.00       0.000       0.0000
-log_k_JCZ38     0.000        2.33        0.00       0.000       0.0000
-log_k_J9Z38     0.000        0.00        1.59       0.000       0.0000
-log_k_JSE76     0.000        0.00        0.00       1.006       0.0000
-f_cyan_ilr_1    0.000        0.00        0.00       0.000       0.6371
-f_cyan_ilr_2    0.000        0.00        0.00       0.000       0.0000
-f_JCZ38_qlogis  0.000        0.00        0.00       0.000       0.0000
-log_k1          0.000        0.00        0.00       0.000       0.0000
-log_k2          0.000        0.00        0.00       0.000       0.0000
-log_tb          0.000        0.00        0.00       0.000       0.0000
-               f_cyan_ilr_2 f_JCZ38_qlogis log_k1 log_k2 log_tb
-cyan_0                0.000           0.00 0.0000 0.0000 0.0000
-log_k_JCZ38           0.000           0.00 0.0000 0.0000 0.0000
-log_k_J9Z38           0.000           0.00 0.0000 0.0000 0.0000
-log_k_JSE76           0.000           0.00 0.0000 0.0000 0.0000
-f_cyan_ilr_1          0.000           0.00 0.0000 0.0000 0.0000
-f_cyan_ilr_2          2.167           0.00 0.0000 0.0000 0.0000
-f_JCZ38_qlogis        0.000          10.22 0.0000 0.0000 0.0000
-log_k1                0.000           0.00 0.7003 0.0000 0.0000
-log_k2                0.000           0.00 0.0000 0.8928 0.0000
-log_tb                0.000           0.00 0.0000 0.0000 0.6774
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2427 2420  -1194
-
-Optimised parameters:
-                       est. lower upper
-cyan_0            101.84849    NA    NA
-log_k_JCZ38        -3.47365    NA    NA
-log_k_J9Z38        -5.10562    NA    NA
-log_k_JSE76        -5.60318    NA    NA
-f_cyan_ilr_1        0.66127    NA    NA
-f_cyan_ilr_2        0.60283    NA    NA
-f_JCZ38_qlogis     45.06408    NA    NA
-log_k1             -3.10124    NA    NA
-log_k2             -4.39028    NA    NA
-log_tb              2.32256    NA    NA
-a.1                 3.32683    NA    NA
-SD.log_k_JCZ38      1.41427    NA    NA
-SD.log_k_J9Z38      0.54767    NA    NA
-SD.log_k_JSE76      0.62147    NA    NA
-SD.f_cyan_ilr_1     0.30189    NA    NA
-SD.f_cyan_ilr_2     0.34960    NA    NA
-SD.f_JCZ38_qlogis   0.04644    NA    NA
-SD.log_k1           0.39534    NA    NA
-SD.log_k2           0.43468    NA    NA
-SD.log_tb           0.60781    NA    NA
-
-Correlation is not available
-
-Random effects:
-                     est. lower upper
-SD.log_k_JCZ38    1.41427    NA    NA
-SD.log_k_J9Z38    0.54767    NA    NA
-SD.log_k_JSE76    0.62147    NA    NA
-SD.f_cyan_ilr_1   0.30189    NA    NA
-SD.f_cyan_ilr_2   0.34960    NA    NA
-SD.f_JCZ38_qlogis 0.04644    NA    NA
-SD.log_k1         0.39534    NA    NA
-SD.log_k2         0.43468    NA    NA
-SD.log_tb         0.60781    NA    NA
-
-Variance model:
-     est. lower upper
-a.1 3.327    NA    NA
-
-Backtransformed parameters:
-                      est. lower upper
-cyan_0           1.018e+02    NA    NA
-k_JCZ38          3.100e-02    NA    NA
-k_J9Z38          6.063e-03    NA    NA
-k_JSE76          3.686e-03    NA    NA
-f_cyan_to_JCZ38  5.910e-01    NA    NA
-f_cyan_to_J9Z38  2.320e-01    NA    NA
-f_JCZ38_to_JSE76 1.000e+00    NA    NA
-k1               4.499e-02    NA    NA
-k2               1.240e-02    NA    NA
-tb               1.020e+01    NA    NA
-
-Resulting formation fractions:
-               ff
-cyan_JCZ38  0.591
-cyan_J9Z38  0.232
-cyan_sink   0.177
-JCZ38_JSE76 1.000
-JCZ38_sink  0.000
-
-Estimated disappearance times:
-        DT50   DT90 DT50back DT50_k1 DT50_k2
-cyan   29.09 158.91    47.84   15.41   55.91
-JCZ38  22.36  74.27       NA      NA      NA
-J9Z38 114.33 379.80       NA      NA      NA
-JSE76 188.04 624.66       NA      NA      NA
-
-
    
-
    
-
-Hierarchical HS path 1 fit with two-component error
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:34:39 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan/dt = - ifelse(time <= tb, k1, k2) * cyan
-d_JCZ38/dt = + f_cyan_to_JCZ38 * ifelse(time <= tb, k1, k2) * cyan -
-           k_JCZ38 * JCZ38
-d_J9Z38/dt = + f_cyan_to_J9Z38 * ifelse(time <= tb, k1, k2) * cyan -
-           k_J9Z38 * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 531.084 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-        cyan_0    log_k_JCZ38    log_k_J9Z38    log_k_JSE76   f_cyan_ilr_1 
-       101.168         -3.358         -4.941         -5.794          0.676 
-  f_cyan_ilr_2 f_JCZ38_qlogis         log_k1         log_k2         log_tb 
-         5.740         13.863         -3.147         -4.262          2.173 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-               cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1
-cyan_0           5.79       0.000       0.000       0.000       0.0000
-log_k_JCZ38      0.00       2.271       0.000       0.000       0.0000
-log_k_J9Z38      0.00       0.000       1.614       0.000       0.0000
-log_k_JSE76      0.00       0.000       0.000       1.264       0.0000
-f_cyan_ilr_1     0.00       0.000       0.000       0.000       0.6761
-f_cyan_ilr_2     0.00       0.000       0.000       0.000       0.0000
-f_JCZ38_qlogis   0.00       0.000       0.000       0.000       0.0000
-log_k1           0.00       0.000       0.000       0.000       0.0000
-log_k2           0.00       0.000       0.000       0.000       0.0000
-log_tb           0.00       0.000       0.000       0.000       0.0000
-               f_cyan_ilr_2 f_JCZ38_qlogis log_k1 log_k2 log_tb
-cyan_0                0.000           0.00 0.0000 0.0000  0.000
-log_k_JCZ38           0.000           0.00 0.0000 0.0000  0.000
-log_k_J9Z38           0.000           0.00 0.0000 0.0000  0.000
-log_k_JSE76           0.000           0.00 0.0000 0.0000  0.000
-f_cyan_ilr_1          0.000           0.00 0.0000 0.0000  0.000
-f_cyan_ilr_2          9.572           0.00 0.0000 0.0000  0.000
-f_JCZ38_qlogis        0.000          19.19 0.0000 0.0000  0.000
-log_k1                0.000           0.00 0.8705 0.0000  0.000
-log_k2                0.000           0.00 0.0000 0.9288  0.000
-log_tb                0.000           0.00 0.0000 0.0000  1.065
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2422 2414  -1190
-
-Optimised parameters:
-                      est. lower upper
-cyan_0            100.9521    NA    NA
-log_k_JCZ38        -3.4629    NA    NA
-log_k_J9Z38        -5.0346    NA    NA
-log_k_JSE76        -5.5722    NA    NA
-f_cyan_ilr_1        0.6560    NA    NA
-f_cyan_ilr_2        0.7983    NA    NA
-f_JCZ38_qlogis     42.7949    NA    NA
-log_k1             -3.1721    NA    NA
-log_k2             -4.4039    NA    NA
-log_tb              2.3994    NA    NA
-a.1                 3.0586    NA    NA
-b.1                 0.0380    NA    NA
-SD.log_k_JCZ38      1.3754    NA    NA
-SD.log_k_J9Z38      0.6703    NA    NA
-SD.log_k_JSE76      0.5876    NA    NA
-SD.f_cyan_ilr_1     0.3272    NA    NA
-SD.f_cyan_ilr_2     0.5300    NA    NA
-SD.f_JCZ38_qlogis   6.4465    NA    NA
-SD.log_k1           0.4135    NA    NA
-SD.log_k2           0.4182    NA    NA
-SD.log_tb           0.6035    NA    NA
-
-Correlation is not available
-
-Random effects:
-                    est. lower upper
-SD.log_k_JCZ38    1.3754    NA    NA
-SD.log_k_J9Z38    0.6703    NA    NA
-SD.log_k_JSE76    0.5876    NA    NA
-SD.f_cyan_ilr_1   0.3272    NA    NA
-SD.f_cyan_ilr_2   0.5300    NA    NA
-SD.f_JCZ38_qlogis 6.4465    NA    NA
-SD.log_k1         0.4135    NA    NA
-SD.log_k2         0.4182    NA    NA
-SD.log_tb         0.6035    NA    NA
-
-Variance model:
-     est. lower upper
-a.1 3.059    NA    NA
-b.1 0.038    NA    NA
-
-Backtransformed parameters:
-                      est. lower upper
-cyan_0           1.010e+02    NA    NA
-k_JCZ38          3.134e-02    NA    NA
-k_J9Z38          6.509e-03    NA    NA
-k_JSE76          3.802e-03    NA    NA
-f_cyan_to_JCZ38  6.127e-01    NA    NA
-f_cyan_to_J9Z38  2.423e-01    NA    NA
-f_JCZ38_to_JSE76 1.000e+00    NA    NA
-k1               4.191e-02    NA    NA
-k2               1.223e-02    NA    NA
-tb               1.102e+01    NA    NA
-
-Resulting formation fractions:
-                ff
-cyan_JCZ38  0.6127
-cyan_J9Z38  0.2423
-cyan_sink   0.1449
-JCZ38_JSE76 1.0000
-JCZ38_sink  0.0000
-
-Estimated disappearance times:
-        DT50   DT90 DT50back DT50_k1 DT50_k2
-cyan   29.94 161.54    48.63   16.54   56.68
-JCZ38  22.12  73.47       NA      NA      NA
-J9Z38 106.50 353.77       NA      NA      NA
-JSE76 182.30 605.60       NA      NA      NA
-
-
    
-
    
-
    
-
    
-
    Pathway 2
-
    
-
-Hierarchical FOMC path 2 fit with constant variance
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:45:51 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan
-d_JCZ38/dt = + f_cyan_to_JCZ38 * (alpha/beta) * 1/((time/beta) + 1) *
-           cyan - k_JCZ38 * JCZ38 + f_JSE76_to_JCZ38 * k_JSE76 * JSE76
-d_J9Z38/dt = + f_cyan_to_J9Z38 * (alpha/beta) * 1/((time/beta) + 1) *
-           cyan - k_J9Z38 * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 517.002 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
-        cyan_0    log_k_JCZ38    log_k_J9Z38    log_k_JSE76   f_cyan_ilr_1 
-      101.8173        -1.8998        -5.1449        -2.5415         0.6705 
-  f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis      log_alpha       log_beta 
-        4.4669        16.1281        13.3327        -0.2314         2.8738 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-               cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1
-cyan_0          5.742       0.000       0.000        0.00       0.0000
-log_k_JCZ38     0.000       1.402       0.000        0.00       0.0000
-log_k_J9Z38     0.000       0.000       1.718        0.00       0.0000
-log_k_JSE76     0.000       0.000       0.000        3.57       0.0000
-f_cyan_ilr_1    0.000       0.000       0.000        0.00       0.5926
-f_cyan_ilr_2    0.000       0.000       0.000        0.00       0.0000
-f_JCZ38_qlogis  0.000       0.000       0.000        0.00       0.0000
-f_JSE76_qlogis  0.000       0.000       0.000        0.00       0.0000
-log_alpha       0.000       0.000       0.000        0.00       0.0000
-log_beta        0.000       0.000       0.000        0.00       0.0000
-               f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_alpha log_beta
-cyan_0                 0.00           0.00           0.00    0.0000   0.0000
-log_k_JCZ38            0.00           0.00           0.00    0.0000   0.0000
-log_k_J9Z38            0.00           0.00           0.00    0.0000   0.0000
-log_k_JSE76            0.00           0.00           0.00    0.0000   0.0000
-f_cyan_ilr_1           0.00           0.00           0.00    0.0000   0.0000
-f_cyan_ilr_2          10.56           0.00           0.00    0.0000   0.0000
-f_JCZ38_qlogis         0.00          12.04           0.00    0.0000   0.0000
-f_JSE76_qlogis         0.00           0.00          15.26    0.0000   0.0000
-log_alpha              0.00           0.00           0.00    0.4708   0.0000
-log_beta               0.00           0.00           0.00    0.0000   0.4432
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2308 2301  -1134
-
-Optimised parameters:
-                      est.    lower     upper
-cyan_0            101.9586 99.22024 104.69700
-log_k_JCZ38        -2.4861 -3.17661  -1.79560
-log_k_J9Z38        -5.3926 -6.08842  -4.69684
-log_k_JSE76        -3.1193 -4.12904  -2.10962
-f_cyan_ilr_1        0.7368  0.42085   1.05276
-f_cyan_ilr_2        0.6196  0.06052   1.17861
-f_JCZ38_qlogis      4.8970 -4.68003  14.47398
-f_JSE76_qlogis      4.4066 -1.02087   9.83398
-log_alpha          -0.3021 -0.68264   0.07838
-log_beta            2.7438  2.57970   2.90786
-a.1                 2.9008  2.69920   3.10245
-SD.cyan_0           2.7081  0.64216   4.77401
-SD.log_k_JCZ38      0.7043  0.19951   1.20907
-SD.log_k_J9Z38      0.6248  0.05790   1.19180
-SD.log_k_JSE76      1.0750  0.33157   1.81839
-SD.f_cyan_ilr_1     0.3429  0.11688   0.56892
-SD.f_cyan_ilr_2     0.4774  0.09381   0.86097
-SD.f_JCZ38_qlogis   1.5565 -7.83970  10.95279
-SD.f_JSE76_qlogis   1.6871 -1.25577   4.63000
-SD.log_alpha        0.4216  0.15913   0.68405
-
-Correlation: 
-               cyan_0  l__JCZ3 l__J9Z3 l__JSE7 f_cy__1 f_cy__2 f_JCZ38 f_JSE76
-log_k_JCZ38    -0.0167                                                        
-log_k_J9Z38    -0.0307  0.0057                                                
-log_k_JSE76    -0.0032  0.1358  0.0009                                        
-f_cyan_ilr_1   -0.0087  0.0206 -0.1158 -0.0009                                
-f_cyan_ilr_2   -0.1598  0.0690  0.1770  0.0002 -0.0007                        
-f_JCZ38_qlogis  0.0966 -0.1132 -0.0440  0.0182 -0.1385 -0.4583                
-f_JSE76_qlogis -0.0647  0.1157  0.0333 -0.0026  0.1110  0.3620 -0.8586        
-log_alpha      -0.0389  0.0113  0.0209  0.0021  0.0041  0.0451 -0.0605  0.0412
-log_beta       -0.2508  0.0533  0.0977  0.0098  0.0220  0.2741 -0.2934  0.1999
-               log_lph
-log_k_JCZ38           
-log_k_J9Z38           
-log_k_JSE76           
-f_cyan_ilr_1          
-f_cyan_ilr_2          
-f_JCZ38_qlogis        
-f_JSE76_qlogis        
-log_alpha             
-log_beta        0.2281
-
-Random effects:
-                    est.    lower   upper
-SD.cyan_0         2.7081  0.64216  4.7740
-SD.log_k_JCZ38    0.7043  0.19951  1.2091
-SD.log_k_J9Z38    0.6248  0.05790  1.1918
-SD.log_k_JSE76    1.0750  0.33157  1.8184
-SD.f_cyan_ilr_1   0.3429  0.11688  0.5689
-SD.f_cyan_ilr_2   0.4774  0.09381  0.8610
-SD.f_JCZ38_qlogis 1.5565 -7.83970 10.9528
-SD.f_JSE76_qlogis 1.6871 -1.25577  4.6300
-SD.log_alpha      0.4216  0.15913  0.6840
-
-Variance model:
-     est. lower upper
-a.1 2.901 2.699 3.102
-
-Backtransformed parameters:
-                      est.     lower     upper
-cyan_0           101.95862 99.220240 1.047e+02
-k_JCZ38            0.08323  0.041727 1.660e-01
-k_J9Z38            0.00455  0.002269 9.124e-03
-k_JSE76            0.04419  0.016098 1.213e-01
-f_cyan_to_JCZ38    0.61318        NA        NA
-f_cyan_to_J9Z38    0.21630        NA        NA
-f_JCZ38_to_JSE76   0.99259  0.009193 1.000e+00
-f_JSE76_to_JCZ38   0.98795  0.264857 9.999e-01
-alpha              0.73924  0.505281 1.082e+00
-beta              15.54568 13.193194 1.832e+01
-
-Resulting formation fractions:
-                  ff
-cyan_JCZ38  0.613182
-cyan_J9Z38  0.216298
-cyan_sink   0.170519
-JCZ38_JSE76 0.992586
-JCZ38_sink  0.007414
-JSE76_JCZ38 0.987950
-JSE76_sink  0.012050
-
-Estimated disappearance times:
-         DT50   DT90 DT50back
-cyan   24.157 334.68    100.7
-JCZ38   8.328  27.66       NA
-J9Z38 152.341 506.06       NA
-JSE76  15.687  52.11       NA
-
-
    
-
    
-
-Hierarchical FOMC path 2 fit with two-component error
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:45:39 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan
-d_JCZ38/dt = + f_cyan_to_JCZ38 * (alpha/beta) * 1/((time/beta) + 1) *
-           cyan - k_JCZ38 * JCZ38 + f_JSE76_to_JCZ38 * k_JSE76 * JSE76
-d_J9Z38/dt = + f_cyan_to_J9Z38 * (alpha/beta) * 1/((time/beta) + 1) *
-           cyan - k_J9Z38 * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 505.619 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-        cyan_0    log_k_JCZ38    log_k_J9Z38    log_k_JSE76   f_cyan_ilr_1 
-      101.9028        -1.9055        -5.0249        -2.5646         0.6807 
-  f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis      log_alpha       log_beta 
-        4.8883        16.0676         9.3923        -0.1346         3.0364 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-               cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1
-cyan_0          6.321       0.000       0.000       0.000       0.0000
-log_k_JCZ38     0.000       1.392       0.000       0.000       0.0000
-log_k_J9Z38     0.000       0.000       1.561       0.000       0.0000
-log_k_JSE76     0.000       0.000       0.000       3.614       0.0000
-f_cyan_ilr_1    0.000       0.000       0.000       0.000       0.6339
-f_cyan_ilr_2    0.000       0.000       0.000       0.000       0.0000
-f_JCZ38_qlogis  0.000       0.000       0.000       0.000       0.0000
-f_JSE76_qlogis  0.000       0.000       0.000       0.000       0.0000
-log_alpha       0.000       0.000       0.000       0.000       0.0000
-log_beta        0.000       0.000       0.000       0.000       0.0000
-               f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_alpha log_beta
-cyan_0                 0.00           0.00           0.00    0.0000   0.0000
-log_k_JCZ38            0.00           0.00           0.00    0.0000   0.0000
-log_k_J9Z38            0.00           0.00           0.00    0.0000   0.0000
-log_k_JSE76            0.00           0.00           0.00    0.0000   0.0000
-f_cyan_ilr_1           0.00           0.00           0.00    0.0000   0.0000
-f_cyan_ilr_2          10.41           0.00           0.00    0.0000   0.0000
-f_JCZ38_qlogis         0.00          12.24           0.00    0.0000   0.0000
-f_JSE76_qlogis         0.00           0.00          15.13    0.0000   0.0000
-log_alpha              0.00           0.00           0.00    0.3701   0.0000
-log_beta               0.00           0.00           0.00    0.0000   0.5662
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2248 2240  -1103
-
-Optimised parameters:
-                       est.      lower      upper
-cyan_0            101.55545  9.920e+01  1.039e+02
-log_k_JCZ38        -2.37354 -2.928e+00 -1.819e+00
-log_k_J9Z38        -5.14736 -5.960e+00 -4.335e+00
-log_k_JSE76        -3.07802 -4.243e+00 -1.913e+00
-f_cyan_ilr_1        0.71263  3.655e-01  1.060e+00
-f_cyan_ilr_2        0.95202  2.701e-01  1.634e+00
-f_JCZ38_qlogis      3.58473  1.251e+00  5.919e+00
-f_JSE76_qlogis     19.03623 -1.037e+07  1.037e+07
-log_alpha          -0.15297 -4.490e-01  1.431e-01
-log_beta            2.99230  2.706e+00  3.278e+00
-a.1                 2.04816         NA         NA
-b.1                 0.06886         NA         NA
-SD.log_k_JCZ38      0.56174         NA         NA
-SD.log_k_J9Z38      0.86509         NA         NA
-SD.log_k_JSE76      1.28450         NA         NA
-SD.f_cyan_ilr_1     0.38705         NA         NA
-SD.f_cyan_ilr_2     0.54153         NA         NA
-SD.f_JCZ38_qlogis   1.65311         NA         NA
-SD.f_JSE76_qlogis   7.51468         NA         NA
-SD.log_alpha        0.31586         NA         NA
-SD.log_beta         0.24696         NA         NA
-
-Correlation is not available
-
-Random effects:
-                    est. lower upper
-SD.log_k_JCZ38    0.5617    NA    NA
-SD.log_k_J9Z38    0.8651    NA    NA
-SD.log_k_JSE76    1.2845    NA    NA
-SD.f_cyan_ilr_1   0.3870    NA    NA
-SD.f_cyan_ilr_2   0.5415    NA    NA
-SD.f_JCZ38_qlogis 1.6531    NA    NA
-SD.f_JSE76_qlogis 7.5147    NA    NA
-SD.log_alpha      0.3159    NA    NA
-SD.log_beta       0.2470    NA    NA
-
-Variance model:
-       est. lower upper
-a.1 2.04816    NA    NA
-b.1 0.06886    NA    NA
-
-Backtransformed parameters:
-                      est.    lower    upper
-cyan_0           1.016e+02 99.20301 103.9079
-k_JCZ38          9.315e-02  0.05349   0.1622
-k_J9Z38          5.815e-03  0.00258   0.0131
-k_JSE76          4.605e-02  0.01436   0.1477
-f_cyan_to_JCZ38  6.438e-01       NA       NA
-f_cyan_to_J9Z38  2.350e-01       NA       NA
-f_JCZ38_to_JSE76 9.730e-01  0.77745   0.9973
-f_JSE76_to_JCZ38 1.000e+00  0.00000   1.0000
-alpha            8.582e-01  0.63824   1.1538
-beta             1.993e+01 14.97621  26.5262
-
-Resulting formation fractions:
-                   ff
-cyan_JCZ38  6.438e-01
-cyan_J9Z38  2.350e-01
-cyan_sink   1.212e-01
-JCZ38_JSE76 9.730e-01
-JCZ38_sink  2.700e-02
-JSE76_JCZ38 1.000e+00
-JSE76_sink  5.403e-09
-
-Estimated disappearance times:
-         DT50   DT90 DT50back
-cyan   24.771 271.70    81.79
-JCZ38   7.441  24.72       NA
-J9Z38 119.205 395.99       NA
-JSE76  15.052  50.00       NA
-
-
    
-
    
-
-Hierarchical DFOP path 2 fit with constant variance
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:46:46 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-           time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-           * cyan
-d_JCZ38/dt = + f_cyan_to_JCZ38 * ((k1 * g * exp(-k1 * time) + k2 * (1 -
-           g) * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-           exp(-k2 * time))) * cyan - k_JCZ38 * JCZ38 +
-           f_JSE76_to_JCZ38 * k_JSE76 * JSE76
-d_J9Z38/dt = + f_cyan_to_J9Z38 * ((k1 * g * exp(-k1 * time) + k2 * (1 -
-           g) * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-           exp(-k2 * time))) * cyan - k_J9Z38 * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 572.382 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
-        cyan_0    log_k_JCZ38    log_k_J9Z38    log_k_JSE76   f_cyan_ilr_1 
-      102.4358        -2.3107        -5.3123        -3.7120         0.6753 
-  f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis         log_k1         log_k2 
-        1.1462        12.4095        12.3630        -1.9317        -4.4557 
-      g_qlogis 
-       -0.5648 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-               cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1
-cyan_0          4.594      0.0000       0.000         0.0       0.0000
-log_k_JCZ38     0.000      0.7966       0.000         0.0       0.0000
-log_k_J9Z38     0.000      0.0000       1.561         0.0       0.0000
-log_k_JSE76     0.000      0.0000       0.000         0.8       0.0000
-f_cyan_ilr_1    0.000      0.0000       0.000         0.0       0.6349
-f_cyan_ilr_2    0.000      0.0000       0.000         0.0       0.0000
-f_JCZ38_qlogis  0.000      0.0000       0.000         0.0       0.0000
-f_JSE76_qlogis  0.000      0.0000       0.000         0.0       0.0000
-log_k1          0.000      0.0000       0.000         0.0       0.0000
-log_k2          0.000      0.0000       0.000         0.0       0.0000
-g_qlogis        0.000      0.0000       0.000         0.0       0.0000
-               f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_k1 log_k2
-cyan_0                0.000           0.00            0.0  0.000 0.0000
-log_k_JCZ38           0.000           0.00            0.0  0.000 0.0000
-log_k_J9Z38           0.000           0.00            0.0  0.000 0.0000
-log_k_JSE76           0.000           0.00            0.0  0.000 0.0000
-f_cyan_ilr_1          0.000           0.00            0.0  0.000 0.0000
-f_cyan_ilr_2          1.797           0.00            0.0  0.000 0.0000
-f_JCZ38_qlogis        0.000          13.85            0.0  0.000 0.0000
-f_JSE76_qlogis        0.000           0.00           14.1  0.000 0.0000
-log_k1                0.000           0.00            0.0  1.106 0.0000
-log_k2                0.000           0.00            0.0  0.000 0.6141
-g_qlogis              0.000           0.00            0.0  0.000 0.0000
-               g_qlogis
-cyan_0            0.000
-log_k_JCZ38       0.000
-log_k_J9Z38       0.000
-log_k_JSE76       0.000
-f_cyan_ilr_1      0.000
-f_cyan_ilr_2      0.000
-f_JCZ38_qlogis    0.000
-f_JSE76_qlogis    0.000
-log_k1            0.000
-log_k2            0.000
-g_qlogis          1.595
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2290 2281  -1123
-
-Optimised parameters:
-                      est.     lower    upper
-cyan_0            102.6903 101.44420 103.9365
-log_k_JCZ38        -2.4018  -2.98058  -1.8230
-log_k_J9Z38        -5.1865  -5.92931  -4.4437
-log_k_JSE76        -3.0784  -4.25226  -1.9045
-f_cyan_ilr_1        0.7157   0.37625   1.0551
-f_cyan_ilr_2        0.7073   0.20136   1.2132
-f_JCZ38_qlogis      4.6797   0.43240   8.9269
-f_JSE76_qlogis      5.0080  -1.01380  11.0299
-log_k1             -1.9620  -2.62909  -1.2949
-log_k2             -4.4894  -4.94958  -4.0292
-g_qlogis           -0.4658  -1.34443   0.4129
-a.1                 2.7158   2.52576   2.9059
-SD.log_k_JCZ38      0.5818   0.15679   1.0067
-SD.log_k_J9Z38      0.7421   0.16751   1.3167
-SD.log_k_JSE76      1.2841   0.43247   2.1356
-SD.f_cyan_ilr_1     0.3748   0.13040   0.6192
-SD.f_cyan_ilr_2     0.4550   0.08396   0.8261
-SD.f_JCZ38_qlogis   2.0862  -0.73390   4.9062
-SD.f_JSE76_qlogis   1.9585  -3.14773   7.0647
-SD.log_k1           0.7389   0.25761   1.2201
-SD.log_k2           0.5132   0.18143   0.8450
-SD.g_qlogis         0.9870   0.35773   1.6164
-
-Correlation: 
-               cyan_0  l__JCZ3 l__J9Z3 l__JSE7 f_cy__1 f_cy__2 f_JCZ38 f_JSE76
-log_k_JCZ38    -0.0170                                                        
-log_k_J9Z38    -0.0457  0.0016                                                
-log_k_JSE76    -0.0046  0.1183  0.0005                                        
-f_cyan_ilr_1    0.0079  0.0072 -0.0909  0.0003                                
-f_cyan_ilr_2   -0.3114  0.0343  0.1542  0.0023 -0.0519                        
-f_JCZ38_qlogis  0.0777 -0.0601 -0.0152  0.0080 -0.0520 -0.2524                
-f_JSE76_qlogis -0.0356  0.0817  0.0073  0.0051  0.0388  0.1959 -0.6236        
-log_k1          0.0848 -0.0028  0.0010 -0.0010 -0.0014 -0.0245  0.0121 -0.0177
-log_k2          0.0274 -0.0001  0.0075  0.0000 -0.0023 -0.0060  0.0000 -0.0130
-g_qlogis        0.0159  0.0002 -0.0095  0.0002  0.0029 -0.0140 -0.0001  0.0149
-               log_k1  log_k2 
-log_k_JCZ38                   
-log_k_J9Z38                   
-log_k_JSE76                   
-f_cyan_ilr_1                  
-f_cyan_ilr_2                  
-f_JCZ38_qlogis                
-f_JSE76_qlogis                
-log_k1                        
-log_k2          0.0280        
-g_qlogis       -0.0278 -0.0310
-
-Random effects:
-                    est.    lower  upper
-SD.log_k_JCZ38    0.5818  0.15679 1.0067
-SD.log_k_J9Z38    0.7421  0.16751 1.3167
-SD.log_k_JSE76    1.2841  0.43247 2.1356
-SD.f_cyan_ilr_1   0.3748  0.13040 0.6192
-SD.f_cyan_ilr_2   0.4550  0.08396 0.8261
-SD.f_JCZ38_qlogis 2.0862 -0.73390 4.9062
-SD.f_JSE76_qlogis 1.9585 -3.14773 7.0647
-SD.log_k1         0.7389  0.25761 1.2201
-SD.log_k2         0.5132  0.18143 0.8450
-SD.g_qlogis       0.9870  0.35773 1.6164
-
-Variance model:
-     est. lower upper
-a.1 2.716 2.526 2.906
-
-Backtransformed parameters:
-                      est.     lower     upper
-cyan_0           1.027e+02 1.014e+02 103.93649
-k_JCZ38          9.056e-02 5.076e-02   0.16154
-k_J9Z38          5.591e-03 2.660e-03   0.01175
-k_JSE76          4.603e-02 1.423e-02   0.14890
-f_cyan_to_JCZ38  6.184e-01        NA        NA
-f_cyan_to_J9Z38  2.248e-01        NA        NA
-f_JCZ38_to_JSE76 9.908e-01 6.064e-01   0.99987
-f_JSE76_to_JCZ38 9.934e-01 2.662e-01   0.99998
-k1               1.406e-01 7.214e-02   0.27393
-k2               1.123e-02 7.086e-03   0.01779
-g                3.856e-01 2.068e-01   0.60177
-
-Resulting formation fractions:
-                  ff
-cyan_JCZ38  0.618443
-cyan_J9Z38  0.224770
-cyan_sink   0.156787
-JCZ38_JSE76 0.990803
-JCZ38_sink  0.009197
-JSE76_JCZ38 0.993360
-JSE76_sink  0.006640
-
-Estimated disappearance times:
-         DT50   DT90 DT50back DT50_k1 DT50_k2
-cyan   21.674 161.70    48.68   4.931   61.74
-JCZ38   7.654  25.43       NA      NA      NA
-J9Z38 123.966 411.81       NA      NA      NA
-JSE76  15.057  50.02       NA      NA      NA
-
-
    
-
    
-
-Hierarchical DFOP path 2 fit with two-component error
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:49:18 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-           time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-           * cyan
-d_JCZ38/dt = + f_cyan_to_JCZ38 * ((k1 * g * exp(-k1 * time) + k2 * (1 -
-           g) * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-           exp(-k2 * time))) * cyan - k_JCZ38 * JCZ38 +
-           f_JSE76_to_JCZ38 * k_JSE76 * JSE76
-d_J9Z38/dt = + f_cyan_to_J9Z38 * ((k1 * g * exp(-k1 * time) + k2 * (1 -
-           g) * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-           exp(-k2 * time))) * cyan - k_J9Z38 * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 724.515 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-        cyan_0    log_k_JCZ38    log_k_J9Z38    log_k_JSE76   f_cyan_ilr_1 
-      101.7523        -1.5948        -5.0119        -2.2723         0.6719 
-  f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis         log_k1         log_k2 
-        5.1681        12.8238        12.4130        -2.0057        -4.5526 
-      g_qlogis 
-       -0.5805 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-               cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1
-cyan_0          5.627       0.000       0.000       0.000       0.0000
-log_k_JCZ38     0.000       2.327       0.000       0.000       0.0000
-log_k_J9Z38     0.000       0.000       1.664       0.000       0.0000
-log_k_JSE76     0.000       0.000       0.000       4.566       0.0000
-f_cyan_ilr_1    0.000       0.000       0.000       0.000       0.6519
-f_cyan_ilr_2    0.000       0.000       0.000       0.000       0.0000
-f_JCZ38_qlogis  0.000       0.000       0.000       0.000       0.0000
-f_JSE76_qlogis  0.000       0.000       0.000       0.000       0.0000
-log_k1          0.000       0.000       0.000       0.000       0.0000
-log_k2          0.000       0.000       0.000       0.000       0.0000
-g_qlogis        0.000       0.000       0.000       0.000       0.0000
-               f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_k1 log_k2
-cyan_0                  0.0           0.00           0.00 0.0000 0.0000
-log_k_JCZ38             0.0           0.00           0.00 0.0000 0.0000
-log_k_J9Z38             0.0           0.00           0.00 0.0000 0.0000
-log_k_JSE76             0.0           0.00           0.00 0.0000 0.0000
-f_cyan_ilr_1            0.0           0.00           0.00 0.0000 0.0000
-f_cyan_ilr_2           10.1           0.00           0.00 0.0000 0.0000
-f_JCZ38_qlogis          0.0          13.99           0.00 0.0000 0.0000
-f_JSE76_qlogis          0.0           0.00          14.15 0.0000 0.0000
-log_k1                  0.0           0.00           0.00 0.8452 0.0000
-log_k2                  0.0           0.00           0.00 0.0000 0.5968
-g_qlogis                0.0           0.00           0.00 0.0000 0.0000
-               g_qlogis
-cyan_0            0.000
-log_k_JCZ38       0.000
-log_k_J9Z38       0.000
-log_k_JSE76       0.000
-f_cyan_ilr_1      0.000
-f_cyan_ilr_2      0.000
-f_JCZ38_qlogis    0.000
-f_JSE76_qlogis    0.000
-log_k1            0.000
-log_k2            0.000
-g_qlogis          1.691
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2234 2226  -1095
-
-Optimised parameters:
-                       est.      lower      upper
-cyan_0            101.10667  9.903e+01  103.18265
-log_k_JCZ38        -2.49437 -3.297e+00   -1.69221
-log_k_J9Z38        -5.08171 -5.875e+00   -4.28846
-log_k_JSE76        -3.20072 -4.180e+00   -2.22163
-f_cyan_ilr_1        0.71059  3.639e-01    1.05727
-f_cyan_ilr_2        1.15398  2.981e-01    2.00984
-f_JCZ38_qlogis      3.18027  1.056e+00    5.30452
-f_JSE76_qlogis      5.61578 -2.505e+01   36.28077
-log_k1             -2.38875 -2.517e+00   -2.26045
-log_k2             -4.67246 -4.928e+00   -4.41715
-g_qlogis           -0.28231 -1.135e+00    0.57058
-a.1                 2.08190  1.856e+00    2.30785
-b.1                 0.06114  5.015e-02    0.07214
-SD.log_k_JCZ38      0.84622  2.637e-01    1.42873
-SD.log_k_J9Z38      0.84564  2.566e-01    1.43464
-SD.log_k_JSE76      1.04385  3.242e-01    1.76351
-SD.f_cyan_ilr_1     0.38568  1.362e-01    0.63514
-SD.f_cyan_ilr_2     0.68046  7.166e-02    1.28925
-SD.f_JCZ38_qlogis   1.25244 -4.213e-02    2.54700
-SD.f_JSE76_qlogis   0.28202 -1.515e+03 1515.87968
-SD.log_k2           0.25749  7.655e-02    0.43843
-SD.g_qlogis         0.94535  3.490e-01    1.54174
-
-Correlation: 
-               cyan_0  l__JCZ3 l__J9Z3 l__JSE7 f_cy__1 f_cy__2 f_JCZ38 f_JSE76
-log_k_JCZ38    -0.0086                                                        
-log_k_J9Z38    -0.0363 -0.0007                                                
-log_k_JSE76     0.0015  0.1210 -0.0017                                        
-f_cyan_ilr_1   -0.0048  0.0095 -0.0572  0.0030                                
-f_cyan_ilr_2   -0.4788  0.0328  0.1143  0.0027 -0.0316                        
-f_JCZ38_qlogis  0.0736 -0.0664 -0.0137  0.0145 -0.0444 -0.2175                
-f_JSE76_qlogis -0.0137  0.0971  0.0035  0.0009  0.0293  0.1333 -0.6767        
-log_k1          0.2345 -0.0350 -0.0099 -0.0113 -0.0126 -0.1652  0.1756 -0.2161
-log_k2          0.0440 -0.0133  0.0199 -0.0040 -0.0097 -0.0119  0.0604 -0.1306
-g_qlogis        0.0438  0.0078 -0.0123  0.0029  0.0046 -0.0363 -0.0318  0.0736
-               log_k1  log_k2 
-log_k_JCZ38                   
-log_k_J9Z38                   
-log_k_JSE76                   
-f_cyan_ilr_1                  
-f_cyan_ilr_2                  
-f_JCZ38_qlogis                
-f_JSE76_qlogis                
-log_k1                        
-log_k2          0.3198        
-g_qlogis       -0.1666 -0.0954
-
-Random effects:
-                    est.      lower     upper
-SD.log_k_JCZ38    0.8462  2.637e-01    1.4287
-SD.log_k_J9Z38    0.8456  2.566e-01    1.4346
-SD.log_k_JSE76    1.0439  3.242e-01    1.7635
-SD.f_cyan_ilr_1   0.3857  1.362e-01    0.6351
-SD.f_cyan_ilr_2   0.6805  7.166e-02    1.2893
-SD.f_JCZ38_qlogis 1.2524 -4.213e-02    2.5470
-SD.f_JSE76_qlogis 0.2820 -1.515e+03 1515.8797
-SD.log_k2         0.2575  7.655e-02    0.4384
-SD.g_qlogis       0.9453  3.490e-01    1.5417
-
-Variance model:
-       est.   lower   upper
-a.1 2.08190 1.85595 2.30785
-b.1 0.06114 0.05015 0.07214
-
-Backtransformed parameters:
-                      est.     lower     upper
-cyan_0           1.011e+02 9.903e+01 103.18265
-k_JCZ38          8.255e-02 3.701e-02   0.18411
-k_J9Z38          6.209e-03 2.809e-03   0.01373
-k_JSE76          4.073e-02 1.530e-02   0.10843
-f_cyan_to_JCZ38  6.608e-01        NA        NA
-f_cyan_to_J9Z38  2.419e-01        NA        NA
-f_JCZ38_to_JSE76 9.601e-01 7.419e-01   0.99506
-f_JSE76_to_JCZ38 9.964e-01 1.322e-11   1.00000
-k1               9.174e-02 8.070e-02   0.10430
-k2               9.349e-03 7.243e-03   0.01207
-g                4.299e-01 2.432e-01   0.63890
-
-Resulting formation fractions:
-                  ff
-cyan_JCZ38  0.660808
-cyan_J9Z38  0.241904
-cyan_sink   0.097288
-JCZ38_JSE76 0.960085
-JCZ38_sink  0.039915
-JSE76_JCZ38 0.996373
-JSE76_sink  0.003627
-
-Estimated disappearance times:
-         DT50   DT90 DT50back DT50_k1 DT50_k2
-cyan   24.359 186.18    56.05   7.555   74.14
-JCZ38   8.397  27.89       NA      NA      NA
-J9Z38 111.631 370.83       NA      NA      NA
-JSE76  17.017  56.53       NA      NA      NA
-
-
    
-
    
-
-Hierarchical SFORB path 2 fit with constant variance
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:46:33 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound *
-           cyan_free + k_cyan_bound_free * cyan_bound
-d_cyan_bound/dt = + k_cyan_free_bound * cyan_free - k_cyan_bound_free *
-           cyan_bound
-d_JCZ38/dt = + f_cyan_free_to_JCZ38 * k_cyan_free * cyan_free - k_JCZ38
-           * JCZ38 + f_JSE76_to_JCZ38 * k_JSE76 * JSE76
-d_J9Z38/dt = + f_cyan_free_to_J9Z38 * k_cyan_free * cyan_free - k_J9Z38
-           * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 559.097 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
-          cyan_free_0       log_k_cyan_free log_k_cyan_free_bound 
-             102.4394               -2.7673               -2.8942 
-log_k_cyan_bound_free           log_k_JCZ38           log_k_J9Z38 
-              -3.6201               -2.3107               -5.3123 
-          log_k_JSE76          f_cyan_ilr_1          f_cyan_ilr_2 
-              -3.7120                0.6754                1.1448 
-       f_JCZ38_qlogis        f_JSE76_qlogis 
-              13.2672               13.3538 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-                      cyan_free_0 log_k_cyan_free log_k_cyan_free_bound
-cyan_free_0                 4.589          0.0000                  0.00
-log_k_cyan_free             0.000          0.4849                  0.00
-log_k_cyan_free_bound       0.000          0.0000                  1.62
-log_k_cyan_bound_free       0.000          0.0000                  0.00
-log_k_JCZ38                 0.000          0.0000                  0.00
-log_k_J9Z38                 0.000          0.0000                  0.00
-log_k_JSE76                 0.000          0.0000                  0.00
-f_cyan_ilr_1                0.000          0.0000                  0.00
-f_cyan_ilr_2                0.000          0.0000                  0.00
-f_JCZ38_qlogis              0.000          0.0000                  0.00
-f_JSE76_qlogis              0.000          0.0000                  0.00
-                      log_k_cyan_bound_free log_k_JCZ38 log_k_J9Z38 log_k_JSE76
-cyan_free_0                           0.000      0.0000       0.000         0.0
-log_k_cyan_free                       0.000      0.0000       0.000         0.0
-log_k_cyan_free_bound                 0.000      0.0000       0.000         0.0
-log_k_cyan_bound_free                 1.197      0.0000       0.000         0.0
-log_k_JCZ38                           0.000      0.7966       0.000         0.0
-log_k_J9Z38                           0.000      0.0000       1.561         0.0
-log_k_JSE76                           0.000      0.0000       0.000         0.8
-f_cyan_ilr_1                          0.000      0.0000       0.000         0.0
-f_cyan_ilr_2                          0.000      0.0000       0.000         0.0
-f_JCZ38_qlogis                        0.000      0.0000       0.000         0.0
-f_JSE76_qlogis                        0.000      0.0000       0.000         0.0
-                      f_cyan_ilr_1 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis
-cyan_free_0                 0.0000        0.000           0.00           0.00
-log_k_cyan_free             0.0000        0.000           0.00           0.00
-log_k_cyan_free_bound       0.0000        0.000           0.00           0.00
-log_k_cyan_bound_free       0.0000        0.000           0.00           0.00
-log_k_JCZ38                 0.0000        0.000           0.00           0.00
-log_k_J9Z38                 0.0000        0.000           0.00           0.00
-log_k_JSE76                 0.0000        0.000           0.00           0.00
-f_cyan_ilr_1                0.6349        0.000           0.00           0.00
-f_cyan_ilr_2                0.0000        1.797           0.00           0.00
-f_JCZ38_qlogis              0.0000        0.000          13.84           0.00
-f_JSE76_qlogis              0.0000        0.000           0.00          14.66
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2284 2275  -1120
-
-Optimised parameters:
-                             est.      lower      upper
-cyan_free_0              102.7730  1.015e+02  1.041e+02
-log_k_cyan_free           -2.8530 -3.167e+00 -2.539e+00
-log_k_cyan_free_bound     -2.7326 -3.543e+00 -1.922e+00
-log_k_cyan_bound_free     -3.5582 -4.126e+00 -2.990e+00
-log_k_JCZ38               -2.3810 -2.921e+00 -1.841e+00
-log_k_J9Z38               -5.2301 -5.963e+00 -4.497e+00
-log_k_JSE76               -3.0286 -4.286e+00 -1.771e+00
-f_cyan_ilr_1               0.7081  3.733e-01  1.043e+00
-f_cyan_ilr_2               0.5847  7.846e-03  1.162e+00
-f_JCZ38_qlogis             9.5676 -1.323e+03  1.342e+03
-f_JSE76_qlogis             3.7042  7.254e-02  7.336e+00
-a.1                        2.7222  2.532e+00  2.913e+00
-SD.log_k_cyan_free         0.3338  1.086e-01  5.589e-01
-SD.log_k_cyan_free_bound   0.8888  3.023e-01  1.475e+00
-SD.log_k_cyan_bound_free   0.6220  2.063e-01  1.038e+00
-SD.log_k_JCZ38             0.5221  1.334e-01  9.108e-01
-SD.log_k_J9Z38             0.7104  1.371e-01  1.284e+00
-SD.log_k_JSE76             1.3837  4.753e-01  2.292e+00
-SD.f_cyan_ilr_1            0.3620  1.248e-01  5.992e-01
-SD.f_cyan_ilr_2            0.4259  8.145e-02  7.704e-01
-SD.f_JCZ38_qlogis          3.5332 -1.037e+05  1.037e+05
-SD.f_JSE76_qlogis          1.6990 -2.771e-01  3.675e+00
-
-Correlation: 
-                      cyn_f_0 lg_k_c_ lg_k_cyn_f_ lg_k_cyn_b_ l__JCZ3 l__J9Z3
-log_k_cyan_free        0.2126                                                
-log_k_cyan_free_bound  0.0894  0.0871                                        
-log_k_cyan_bound_free  0.0033  0.0410  0.0583                                
-log_k_JCZ38           -0.0708 -0.0280 -0.0147      0.0019                    
-log_k_J9Z38           -0.0535 -0.0138  0.0012      0.0148      0.0085        
-log_k_JSE76           -0.0066 -0.0030 -0.0021     -0.0005      0.1090  0.0010
-f_cyan_ilr_1          -0.0364 -0.0157 -0.0095     -0.0015      0.0458 -0.0960
-f_cyan_ilr_2          -0.3814 -0.1104 -0.0423      0.0146      0.1540  0.1526
-f_JCZ38_qlogis         0.2507  0.0969  0.0482     -0.0097     -0.2282 -0.0363
-f_JSE76_qlogis        -0.1648 -0.0710 -0.0443     -0.0087      0.2002  0.0226
-                      l__JSE7 f_cy__1 f_cy__2 f_JCZ38
-log_k_cyan_free                                      
-log_k_cyan_free_bound                                
-log_k_cyan_bound_free                                
-log_k_JCZ38                                          
-log_k_J9Z38                                          
-log_k_JSE76                                          
-f_cyan_ilr_1           0.0001                        
-f_cyan_ilr_2           0.0031  0.0586                
-f_JCZ38_qlogis         0.0023 -0.1867 -0.6255        
-f_JSE76_qlogis         0.0082  0.1356  0.4519 -0.7951
-
-Random effects:
-                           est.      lower     upper
-SD.log_k_cyan_free       0.3338  1.086e-01 5.589e-01
-SD.log_k_cyan_free_bound 0.8888  3.023e-01 1.475e+00
-SD.log_k_cyan_bound_free 0.6220  2.063e-01 1.038e+00
-SD.log_k_JCZ38           0.5221  1.334e-01 9.108e-01
-SD.log_k_J9Z38           0.7104  1.371e-01 1.284e+00
-SD.log_k_JSE76           1.3837  4.753e-01 2.292e+00
-SD.f_cyan_ilr_1          0.3620  1.248e-01 5.992e-01
-SD.f_cyan_ilr_2          0.4259  8.145e-02 7.704e-01
-SD.f_JCZ38_qlogis        3.5332 -1.037e+05 1.037e+05
-SD.f_JSE76_qlogis        1.6990 -2.771e-01 3.675e+00
-
-Variance model:
-     est. lower upper
-a.1 2.722 2.532 2.913
-
-Backtransformed parameters:
-                          est.     lower     upper
-cyan_free_0          1.028e+02 1.015e+02 104.06475
-k_cyan_free          5.767e-02 4.213e-02   0.07894
-k_cyan_free_bound    6.505e-02 2.892e-02   0.14633
-k_cyan_bound_free    2.849e-02 1.614e-02   0.05028
-k_JCZ38              9.246e-02 5.390e-02   0.15859
-k_J9Z38              5.353e-03 2.572e-03   0.01114
-k_JSE76              4.838e-02 1.376e-02   0.17009
-f_cyan_free_to_JCZ38 6.011e-01 5.028e-01   0.83792
-f_cyan_free_to_J9Z38 2.208e-01 5.028e-01   0.83792
-f_JCZ38_to_JSE76     9.999e-01 0.000e+00   1.00000
-f_JSE76_to_JCZ38     9.760e-01 5.181e-01   0.99935
-
-Estimated Eigenvalues of SFORB model(s):
-cyan_b1 cyan_b2  cyan_g 
-0.13942 0.01178 0.35948 
-
-Resulting formation fractions:
-                       ff
-cyan_free_JCZ38 6.011e-01
-cyan_free_J9Z38 2.208e-01
-cyan_free_sink  1.780e-01
-cyan_free       1.000e+00
-JCZ38_JSE76     9.999e-01
-JCZ38_sink      6.996e-05
-JSE76_JCZ38     9.760e-01
-JSE76_sink      2.403e-02
-
-Estimated disappearance times:
-         DT50   DT90 DT50back DT50_cyan_b1 DT50_cyan_b2
-cyan   23.390 157.60    47.44        4.971        58.82
-JCZ38   7.497  24.90       NA           NA           NA
-J9Z38 129.482 430.13       NA           NA           NA
-JSE76  14.326  47.59       NA           NA           NA
-
-
    
-
    
-
-Hierarchical SFORB path 2 fit with two-component error
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 20:49:20 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound *
-           cyan_free + k_cyan_bound_free * cyan_bound
-d_cyan_bound/dt = + k_cyan_free_bound * cyan_free - k_cyan_bound_free *
-           cyan_bound
-d_JCZ38/dt = + f_cyan_free_to_JCZ38 * k_cyan_free * cyan_free - k_JCZ38
-           * JCZ38 + f_JSE76_to_JCZ38 * k_JSE76 * JSE76
-d_J9Z38/dt = + f_cyan_free_to_J9Z38 * k_cyan_free * cyan_free - k_J9Z38
-           * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 726.293 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-          cyan_free_0       log_k_cyan_free log_k_cyan_free_bound 
-              101.751                -2.837                -3.016 
-log_k_cyan_bound_free           log_k_JCZ38           log_k_J9Z38 
-               -3.660                -2.299                -5.313 
-          log_k_JSE76          f_cyan_ilr_1          f_cyan_ilr_2 
-               -3.699                 0.672                 5.873 
-       f_JCZ38_qlogis        f_JSE76_qlogis 
-               13.216                13.338 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-                      cyan_free_0 log_k_cyan_free log_k_cyan_free_bound
-cyan_free_0                 5.629           0.000                 0.000
-log_k_cyan_free             0.000           0.446                 0.000
-log_k_cyan_free_bound       0.000           0.000                 1.449
-log_k_cyan_bound_free       0.000           0.000                 0.000
-log_k_JCZ38                 0.000           0.000                 0.000
-log_k_J9Z38                 0.000           0.000                 0.000
-log_k_JSE76                 0.000           0.000                 0.000
-f_cyan_ilr_1                0.000           0.000                 0.000
-f_cyan_ilr_2                0.000           0.000                 0.000
-f_JCZ38_qlogis              0.000           0.000                 0.000
-f_JSE76_qlogis              0.000           0.000                 0.000
-                      log_k_cyan_bound_free log_k_JCZ38 log_k_J9Z38 log_k_JSE76
-cyan_free_0                           0.000      0.0000       0.000      0.0000
-log_k_cyan_free                       0.000      0.0000       0.000      0.0000
-log_k_cyan_free_bound                 0.000      0.0000       0.000      0.0000
-log_k_cyan_bound_free                 1.213      0.0000       0.000      0.0000
-log_k_JCZ38                           0.000      0.7801       0.000      0.0000
-log_k_J9Z38                           0.000      0.0000       1.575      0.0000
-log_k_JSE76                           0.000      0.0000       0.000      0.8078
-f_cyan_ilr_1                          0.000      0.0000       0.000      0.0000
-f_cyan_ilr_2                          0.000      0.0000       0.000      0.0000
-f_JCZ38_qlogis                        0.000      0.0000       0.000      0.0000
-f_JSE76_qlogis                        0.000      0.0000       0.000      0.0000
-                      f_cyan_ilr_1 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis
-cyan_free_0                 0.0000         0.00           0.00           0.00
-log_k_cyan_free             0.0000         0.00           0.00           0.00
-log_k_cyan_free_bound       0.0000         0.00           0.00           0.00
-log_k_cyan_bound_free       0.0000         0.00           0.00           0.00
-log_k_JCZ38                 0.0000         0.00           0.00           0.00
-log_k_J9Z38                 0.0000         0.00           0.00           0.00
-log_k_JSE76                 0.0000         0.00           0.00           0.00
-f_cyan_ilr_1                0.6519         0.00           0.00           0.00
-f_cyan_ilr_2                0.0000        10.78           0.00           0.00
-f_JCZ38_qlogis              0.0000         0.00          13.96           0.00
-f_JSE76_qlogis              0.0000         0.00           0.00          14.69
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2240 2232  -1098
-
-Optimised parameters:
-                              est.     lower    upper
-cyan_free_0              101.10205  98.99221 103.2119
-log_k_cyan_free           -3.16929  -3.61395  -2.7246
-log_k_cyan_free_bound     -3.38259  -3.63022  -3.1350
-log_k_cyan_bound_free     -3.81075  -4.13888  -3.4826
-log_k_JCZ38               -2.42057  -3.00756  -1.8336
-log_k_J9Z38               -5.07501  -5.85138  -4.2986
-log_k_JSE76               -3.12442  -4.21277  -2.0361
-f_cyan_ilr_1               0.70577   0.35788   1.0537
-f_cyan_ilr_2               1.14824   0.15810   2.1384
-f_JCZ38_qlogis             3.52245   0.43257   6.6123
-f_JSE76_qlogis             5.65140 -21.22295  32.5257
-a.1                        2.07062   1.84329   2.2980
-b.1                        0.06227   0.05124   0.0733
-SD.log_k_cyan_free         0.49468   0.18566   0.8037
-SD.log_k_cyan_bound_free   0.28972   0.07188   0.5076
-SD.log_k_JCZ38             0.58852   0.16800   1.0090
-SD.log_k_J9Z38             0.82500   0.24730   1.4027
-SD.log_k_JSE76             1.19201   0.40313   1.9809
-SD.f_cyan_ilr_1            0.38534   0.13640   0.6343
-SD.f_cyan_ilr_2            0.72463   0.10076   1.3485
-SD.f_JCZ38_qlogis          1.38223  -0.20997   2.9744
-SD.f_JSE76_qlogis          2.07989 -72.53027  76.6901
-
-Correlation: 
-                      cyn_f_0 lg_k_c_ lg_k_cyn_f_ lg_k_cyn_b_ l__JCZ3 l__J9Z3
-log_k_cyan_free        0.1117                                                
-log_k_cyan_free_bound  0.1763  0.1828                                        
-log_k_cyan_bound_free  0.0120  0.0593  0.5030                                
-log_k_JCZ38           -0.0459 -0.0230 -0.0931     -0.0337                    
-log_k_J9Z38           -0.0381 -0.0123 -0.0139      0.0237      0.0063        
-log_k_JSE76           -0.0044 -0.0038 -0.0175     -0.0072      0.1120  0.0003
-f_cyan_ilr_1          -0.0199 -0.0087 -0.0407     -0.0233      0.0268 -0.0552
-f_cyan_ilr_2          -0.4806 -0.1015 -0.2291     -0.0269      0.1156  0.1113
-f_JCZ38_qlogis         0.1805  0.0825  0.3085      0.0963     -0.1674 -0.0314
-f_JSE76_qlogis        -0.1586 -0.0810 -0.3560     -0.1563      0.2025  0.0278
-                      l__JSE7 f_cy__1 f_cy__2 f_JCZ38
-log_k_cyan_free                                      
-log_k_cyan_free_bound                                
-log_k_cyan_bound_free                                
-log_k_JCZ38                                          
-log_k_J9Z38                                          
-log_k_JSE76                                          
-f_cyan_ilr_1           0.0024                        
-f_cyan_ilr_2           0.0087  0.0172                
-f_JCZ38_qlogis        -0.0016 -0.1047 -0.4656        
-f_JSE76_qlogis         0.0119  0.1034  0.4584 -0.8137
-
-Random effects:
-                           est.     lower   upper
-SD.log_k_cyan_free       0.4947   0.18566  0.8037
-SD.log_k_cyan_bound_free 0.2897   0.07188  0.5076
-SD.log_k_JCZ38           0.5885   0.16800  1.0090
-SD.log_k_J9Z38           0.8250   0.24730  1.4027
-SD.log_k_JSE76           1.1920   0.40313  1.9809
-SD.f_cyan_ilr_1          0.3853   0.13640  0.6343
-SD.f_cyan_ilr_2          0.7246   0.10076  1.3485
-SD.f_JCZ38_qlogis        1.3822  -0.20997  2.9744
-SD.f_JSE76_qlogis        2.0799 -72.53027 76.6901
-
-Variance model:
-       est.   lower  upper
-a.1 2.07062 1.84329 2.2980
-b.1 0.06227 0.05124 0.0733
-
-Backtransformed parameters:
-                          est.     lower     upper
-cyan_free_0          1.011e+02 9.899e+01 103.21190
-k_cyan_free          4.203e-02 2.695e-02   0.06557
-k_cyan_free_bound    3.396e-02 2.651e-02   0.04350
-k_cyan_bound_free    2.213e-02 1.594e-02   0.03073
-k_JCZ38              8.887e-02 4.941e-02   0.15984
-k_J9Z38              6.251e-03 2.876e-03   0.01359
-k_JSE76              4.396e-02 1.481e-02   0.13054
-f_cyan_free_to_JCZ38 6.590e-01 5.557e-01   0.95365
-f_cyan_free_to_J9Z38 2.429e-01 5.557e-01   0.95365
-f_JCZ38_to_JSE76     9.713e-01 6.065e-01   0.99866
-f_JSE76_to_JCZ38     9.965e-01 6.067e-10   1.00000
-
-Estimated Eigenvalues of SFORB model(s):
-cyan_b1 cyan_b2  cyan_g 
-0.08749 0.01063 0.40855 
-
-Resulting formation fractions:
-                     ff
-cyan_free_JCZ38 0.65905
-cyan_free_J9Z38 0.24291
-cyan_free_sink  0.09805
-cyan_free       1.00000
-JCZ38_JSE76     0.97132
-JCZ38_sink      0.02868
-JSE76_JCZ38     0.99650
-JSE76_sink      0.00350
-
-Estimated disappearance times:
-        DT50   DT90 DT50back DT50_cyan_b1 DT50_cyan_b2
-cyan   24.91 167.16    50.32        7.922        65.19
-JCZ38   7.80  25.91       NA           NA           NA
-J9Z38 110.89 368.36       NA           NA           NA
-JSE76  15.77  52.38       NA           NA           NA
-
-
    
-
    
-
    
-
    
-
    Pathway 2, refined fits
-
    
-
-Hierarchical FOMC path 2 fit with reduced random effects, two-component
-error
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 21:02:39 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan
-d_JCZ38/dt = + f_cyan_to_JCZ38 * (alpha/beta) * 1/((time/beta) + 1) *
-           cyan - k_JCZ38 * JCZ38 + f_JSE76_to_JCZ38 * k_JSE76 * JSE76
-d_J9Z38/dt = + f_cyan_to_J9Z38 * (alpha/beta) * 1/((time/beta) + 1) *
-           cyan - k_J9Z38 * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 796.615 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-        cyan_0    log_k_JCZ38    log_k_J9Z38    log_k_JSE76   f_cyan_ilr_1 
-      101.9028        -1.9055        -5.0249        -2.5646         0.6807 
-  f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis      log_alpha       log_beta 
-        4.8883        16.0676         9.3923        -0.1346         3.0364 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-               cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1
-cyan_0          6.321       0.000       0.000       0.000       0.0000
-log_k_JCZ38     0.000       1.392       0.000       0.000       0.0000
-log_k_J9Z38     0.000       0.000       1.561       0.000       0.0000
-log_k_JSE76     0.000       0.000       0.000       3.614       0.0000
-f_cyan_ilr_1    0.000       0.000       0.000       0.000       0.6339
-f_cyan_ilr_2    0.000       0.000       0.000       0.000       0.0000
-f_JCZ38_qlogis  0.000       0.000       0.000       0.000       0.0000
-f_JSE76_qlogis  0.000       0.000       0.000       0.000       0.0000
-log_alpha       0.000       0.000       0.000       0.000       0.0000
-log_beta        0.000       0.000       0.000       0.000       0.0000
-               f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_alpha log_beta
-cyan_0                 0.00           0.00           0.00    0.0000   0.0000
-log_k_JCZ38            0.00           0.00           0.00    0.0000   0.0000
-log_k_J9Z38            0.00           0.00           0.00    0.0000   0.0000
-log_k_JSE76            0.00           0.00           0.00    0.0000   0.0000
-f_cyan_ilr_1           0.00           0.00           0.00    0.0000   0.0000
-f_cyan_ilr_2          10.41           0.00           0.00    0.0000   0.0000
-f_JCZ38_qlogis         0.00          12.24           0.00    0.0000   0.0000
-f_JSE76_qlogis         0.00           0.00          15.13    0.0000   0.0000
-log_alpha              0.00           0.00           0.00    0.3701   0.0000
-log_beta               0.00           0.00           0.00    0.0000   0.5662
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2251 2244  -1106
-
-Optimised parameters:
-                      est.   lower   upper
-cyan_0           101.05768      NA      NA
-log_k_JCZ38       -2.73252      NA      NA
-log_k_J9Z38       -5.07399      NA      NA
-log_k_JSE76       -3.52863      NA      NA
-f_cyan_ilr_1       0.72176      NA      NA
-f_cyan_ilr_2       1.34610      NA      NA
-f_JCZ38_qlogis     2.08337      NA      NA
-f_JSE76_qlogis  1590.31880      NA      NA
-log_alpha         -0.09336      NA      NA
-log_beta           3.10191      NA      NA
-a.1                2.08557 1.85439 2.31675
-b.1                0.06998 0.05800 0.08197
-SD.log_k_JCZ38     1.20053 0.43329 1.96777
-SD.log_k_J9Z38     0.85854 0.26708 1.45000
-SD.log_k_JSE76     0.62528 0.16061 1.08995
-SD.f_cyan_ilr_1    0.35190 0.12340 0.58039
-SD.f_cyan_ilr_2    0.85385 0.15391 1.55378
-SD.log_alpha       0.28971 0.08718 0.49225
-SD.log_beta        0.31614 0.05938 0.57290
-
-Correlation is not available
-
-Random effects:
-                  est.   lower  upper
-SD.log_k_JCZ38  1.2005 0.43329 1.9678
-SD.log_k_J9Z38  0.8585 0.26708 1.4500
-SD.log_k_JSE76  0.6253 0.16061 1.0900
-SD.f_cyan_ilr_1 0.3519 0.12340 0.5804
-SD.f_cyan_ilr_2 0.8538 0.15391 1.5538
-SD.log_alpha    0.2897 0.08718 0.4923
-SD.log_beta     0.3161 0.05938 0.5729
-
-Variance model:
-       est. lower   upper
-a.1 2.08557 1.854 2.31675
-b.1 0.06998 0.058 0.08197
-
-Backtransformed parameters:
-                      est. lower upper
-cyan_0           1.011e+02    NA    NA
-k_JCZ38          6.506e-02    NA    NA
-k_J9Z38          6.257e-03    NA    NA
-k_JSE76          2.935e-02    NA    NA
-f_cyan_to_JCZ38  6.776e-01    NA    NA
-f_cyan_to_J9Z38  2.442e-01    NA    NA
-f_JCZ38_to_JSE76 8.893e-01    NA    NA
-f_JSE76_to_JCZ38 1.000e+00    NA    NA
-alpha            9.109e-01    NA    NA
-beta             2.224e+01    NA    NA
-
-Resulting formation fractions:
-                 ff
-cyan_JCZ38  0.67761
-cyan_J9Z38  0.24417
-cyan_sink   0.07822
-JCZ38_JSE76 0.88928
-JCZ38_sink  0.11072
-JSE76_JCZ38 1.00000
-JSE76_sink  0.00000
-
-Estimated disappearance times:
-        DT50   DT90 DT50back
-cyan   25.36 256.37    77.18
-JCZ38  10.65  35.39       NA
-J9Z38 110.77 367.98       NA
-JSE76  23.62  78.47       NA
-
-
    
-
    
-
-Hierarchical DFOP path 2 fit with reduced random effects, constant
-variance
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 21:04:15 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-           time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-           * cyan
-d_JCZ38/dt = + f_cyan_to_JCZ38 * ((k1 * g * exp(-k1 * time) + k2 * (1 -
-           g) * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-           exp(-k2 * time))) * cyan - k_JCZ38 * JCZ38 +
-           f_JSE76_to_JCZ38 * k_JSE76 * JSE76
-d_J9Z38/dt = + f_cyan_to_J9Z38 * ((k1 * g * exp(-k1 * time) + k2 * (1 -
-           g) * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-           exp(-k2 * time))) * cyan - k_J9Z38 * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 893.328 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
-        cyan_0    log_k_JCZ38    log_k_J9Z38    log_k_JSE76   f_cyan_ilr_1 
-      102.4358        -2.3107        -5.3123        -3.7120         0.6753 
-  f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis         log_k1         log_k2 
-        1.1462        12.4095        12.3630        -1.9317        -4.4557 
-      g_qlogis 
-       -0.5648 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-               cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1
-cyan_0          4.594      0.0000       0.000         0.0       0.0000
-log_k_JCZ38     0.000      0.7966       0.000         0.0       0.0000
-log_k_J9Z38     0.000      0.0000       1.561         0.0       0.0000
-log_k_JSE76     0.000      0.0000       0.000         0.8       0.0000
-f_cyan_ilr_1    0.000      0.0000       0.000         0.0       0.6349
-f_cyan_ilr_2    0.000      0.0000       0.000         0.0       0.0000
-f_JCZ38_qlogis  0.000      0.0000       0.000         0.0       0.0000
-f_JSE76_qlogis  0.000      0.0000       0.000         0.0       0.0000
-log_k1          0.000      0.0000       0.000         0.0       0.0000
-log_k2          0.000      0.0000       0.000         0.0       0.0000
-g_qlogis        0.000      0.0000       0.000         0.0       0.0000
-               f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_k1 log_k2
-cyan_0                0.000           0.00            0.0  0.000 0.0000
-log_k_JCZ38           0.000           0.00            0.0  0.000 0.0000
-log_k_J9Z38           0.000           0.00            0.0  0.000 0.0000
-log_k_JSE76           0.000           0.00            0.0  0.000 0.0000
-f_cyan_ilr_1          0.000           0.00            0.0  0.000 0.0000
-f_cyan_ilr_2          1.797           0.00            0.0  0.000 0.0000
-f_JCZ38_qlogis        0.000          13.85            0.0  0.000 0.0000
-f_JSE76_qlogis        0.000           0.00           14.1  0.000 0.0000
-log_k1                0.000           0.00            0.0  1.106 0.0000
-log_k2                0.000           0.00            0.0  0.000 0.6141
-g_qlogis              0.000           0.00            0.0  0.000 0.0000
-               g_qlogis
-cyan_0            0.000
-log_k_JCZ38       0.000
-log_k_J9Z38       0.000
-log_k_JSE76       0.000
-f_cyan_ilr_1      0.000
-f_cyan_ilr_2      0.000
-f_JCZ38_qlogis    0.000
-f_JSE76_qlogis    0.000
-log_k1            0.000
-log_k2            0.000
-g_qlogis          1.595
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2282 2274  -1121
-
-Optimised parameters:
-                     est.   lower  upper
-cyan_0           102.5254      NA     NA
-log_k_JCZ38       -2.9358      NA     NA
-log_k_J9Z38       -5.1424      NA     NA
-log_k_JSE76       -3.6458      NA     NA
-f_cyan_ilr_1       0.6957      NA     NA
-f_cyan_ilr_2       0.6635      NA     NA
-f_JCZ38_qlogis  4984.8163      NA     NA
-f_JSE76_qlogis     1.9415      NA     NA
-log_k1            -1.9456      NA     NA
-log_k2            -4.4705      NA     NA
-g_qlogis          -0.5117      NA     NA
-a.1                2.7455 2.55392 2.9370
-SD.log_k_JCZ38     1.3163 0.47635 2.1563
-SD.log_k_J9Z38     0.7162 0.16133 1.2711
-SD.log_k_JSE76     0.6457 0.15249 1.1390
-SD.f_cyan_ilr_1    0.3424 0.11714 0.5677
-SD.f_cyan_ilr_2    0.4524 0.09709 0.8077
-SD.log_k1          0.7353 0.25445 1.2161
-SD.log_k2          0.5137 0.18206 0.8453
-SD.g_qlogis        0.9857 0.35651 1.6148
-
-Correlation is not available
-
-Random effects:
-                  est.   lower  upper
-SD.log_k_JCZ38  1.3163 0.47635 2.1563
-SD.log_k_J9Z38  0.7162 0.16133 1.2711
-SD.log_k_JSE76  0.6457 0.15249 1.1390
-SD.f_cyan_ilr_1 0.3424 0.11714 0.5677
-SD.f_cyan_ilr_2 0.4524 0.09709 0.8077
-SD.log_k1       0.7353 0.25445 1.2161
-SD.log_k2       0.5137 0.18206 0.8453
-SD.g_qlogis     0.9857 0.35651 1.6148
-
-Variance model:
-     est. lower upper
-a.1 2.745 2.554 2.937
-
-Backtransformed parameters:
-                      est. lower upper
-cyan_0           1.025e+02    NA    NA
-k_JCZ38          5.309e-02    NA    NA
-k_J9Z38          5.844e-03    NA    NA
-k_JSE76          2.610e-02    NA    NA
-f_cyan_to_JCZ38  6.079e-01    NA    NA
-f_cyan_to_J9Z38  2.272e-01    NA    NA
-f_JCZ38_to_JSE76 1.000e+00    NA    NA
-f_JSE76_to_JCZ38 8.745e-01    NA    NA
-k1               1.429e-01    NA    NA
-k2               1.144e-02    NA    NA
-g                3.748e-01    NA    NA
-
-Resulting formation fractions:
-                ff
-cyan_JCZ38  0.6079
-cyan_J9Z38  0.2272
-cyan_sink   0.1649
-JCZ38_JSE76 1.0000
-JCZ38_sink  0.0000
-JSE76_JCZ38 0.8745
-JSE76_sink  0.1255
-
-Estimated disappearance times:
-        DT50   DT90 DT50back DT50_k1 DT50_k2
-cyan   22.29 160.20    48.22    4.85   60.58
-JCZ38  13.06  43.37       NA      NA      NA
-J9Z38 118.61 394.02       NA      NA      NA
-JSE76  26.56  88.22       NA      NA      NA
-
-
    
-
    
-
-Hierarchical DFOP path 2 fit with reduced random effects, two-component
-error
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 21:04:33 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-           time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-           * cyan
-d_JCZ38/dt = + f_cyan_to_JCZ38 * ((k1 * g * exp(-k1 * time) + k2 * (1 -
-           g) * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-           exp(-k2 * time))) * cyan - k_JCZ38 * JCZ38 +
-           f_JSE76_to_JCZ38 * k_JSE76 * JSE76
-d_J9Z38/dt = + f_cyan_to_J9Z38 * ((k1 * g * exp(-k1 * time) + k2 * (1 -
-           g) * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-           exp(-k2 * time))) * cyan - k_J9Z38 * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 910.788 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-        cyan_0    log_k_JCZ38    log_k_J9Z38    log_k_JSE76   f_cyan_ilr_1 
-      101.7523        -1.5948        -5.0119        -2.2723         0.6719 
-  f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis         log_k1         log_k2 
-        5.1681        12.8238        12.4130        -2.0057        -4.5526 
-      g_qlogis 
-       -0.5805 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-               cyan_0 log_k_JCZ38 log_k_J9Z38 log_k_JSE76 f_cyan_ilr_1
-cyan_0          5.627       0.000       0.000       0.000       0.0000
-log_k_JCZ38     0.000       2.327       0.000       0.000       0.0000
-log_k_J9Z38     0.000       0.000       1.664       0.000       0.0000
-log_k_JSE76     0.000       0.000       0.000       4.566       0.0000
-f_cyan_ilr_1    0.000       0.000       0.000       0.000       0.6519
-f_cyan_ilr_2    0.000       0.000       0.000       0.000       0.0000
-f_JCZ38_qlogis  0.000       0.000       0.000       0.000       0.0000
-f_JSE76_qlogis  0.000       0.000       0.000       0.000       0.0000
-log_k1          0.000       0.000       0.000       0.000       0.0000
-log_k2          0.000       0.000       0.000       0.000       0.0000
-g_qlogis        0.000       0.000       0.000       0.000       0.0000
-               f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis log_k1 log_k2
-cyan_0                  0.0           0.00           0.00 0.0000 0.0000
-log_k_JCZ38             0.0           0.00           0.00 0.0000 0.0000
-log_k_J9Z38             0.0           0.00           0.00 0.0000 0.0000
-log_k_JSE76             0.0           0.00           0.00 0.0000 0.0000
-f_cyan_ilr_1            0.0           0.00           0.00 0.0000 0.0000
-f_cyan_ilr_2           10.1           0.00           0.00 0.0000 0.0000
-f_JCZ38_qlogis          0.0          13.99           0.00 0.0000 0.0000
-f_JSE76_qlogis          0.0           0.00          14.15 0.0000 0.0000
-log_k1                  0.0           0.00           0.00 0.8452 0.0000
-log_k2                  0.0           0.00           0.00 0.0000 0.5968
-g_qlogis                0.0           0.00           0.00 0.0000 0.0000
-               g_qlogis
-cyan_0            0.000
-log_k_JCZ38       0.000
-log_k_J9Z38       0.000
-log_k_JSE76       0.000
-f_cyan_ilr_1      0.000
-f_cyan_ilr_2      0.000
-f_JCZ38_qlogis    0.000
-f_JSE76_qlogis    0.000
-log_k1            0.000
-log_k2            0.000
-g_qlogis          1.691
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2232 2224  -1096
-
-Optimised parameters:
-                     est.   lower   upper
-cyan_0          101.20051      NA      NA
-log_k_JCZ38      -2.93542      NA      NA
-log_k_J9Z38      -5.03151      NA      NA
-log_k_JSE76      -3.67679      NA      NA
-f_cyan_ilr_1      0.67290      NA      NA
-f_cyan_ilr_2      0.99787      NA      NA
-f_JCZ38_qlogis  348.32484      NA      NA
-f_JSE76_qlogis    1.87846      NA      NA
-log_k1           -2.32738      NA      NA
-log_k2           -4.61295      NA      NA
-g_qlogis         -0.38342      NA      NA
-a.1               2.06184 1.83746 2.28622
-b.1               0.06329 0.05211 0.07447
-SD.log_k_JCZ38    1.29042 0.47468 2.10617
-SD.log_k_J9Z38    0.84235 0.25903 1.42566
-SD.log_k_JSE76    0.56930 0.13934 0.99926
-SD.f_cyan_ilr_1   0.35183 0.12298 0.58068
-SD.f_cyan_ilr_2   0.77269 0.17908 1.36631
-SD.log_k2         0.28549 0.09210 0.47888
-SD.g_qlogis       0.93830 0.34568 1.53093
-
-Correlation is not available
-
-Random effects:
-                  est.  lower  upper
-SD.log_k_JCZ38  1.2904 0.4747 2.1062
-SD.log_k_J9Z38  0.8423 0.2590 1.4257
-SD.log_k_JSE76  0.5693 0.1393 0.9993
-SD.f_cyan_ilr_1 0.3518 0.1230 0.5807
-SD.f_cyan_ilr_2 0.7727 0.1791 1.3663
-SD.log_k2       0.2855 0.0921 0.4789
-SD.g_qlogis     0.9383 0.3457 1.5309
-
-Variance model:
-       est.   lower   upper
-a.1 2.06184 1.83746 2.28622
-b.1 0.06329 0.05211 0.07447
-
-Backtransformed parameters:
-                      est. lower upper
-cyan_0           1.012e+02    NA    NA
-k_JCZ38          5.311e-02    NA    NA
-k_J9Z38          6.529e-03    NA    NA
-k_JSE76          2.530e-02    NA    NA
-f_cyan_to_JCZ38  6.373e-01    NA    NA
-f_cyan_to_J9Z38  2.461e-01    NA    NA
-f_JCZ38_to_JSE76 1.000e+00    NA    NA
-f_JSE76_to_JCZ38 8.674e-01    NA    NA
-k1               9.755e-02    NA    NA
-k2               9.922e-03    NA    NA
-g                4.053e-01    NA    NA
-
-Resulting formation fractions:
-                ff
-cyan_JCZ38  0.6373
-cyan_J9Z38  0.2461
-cyan_sink   0.1167
-JCZ38_JSE76 1.0000
-JCZ38_sink  0.0000
-JSE76_JCZ38 0.8674
-JSE76_sink  0.1326
-
-Estimated disappearance times:
-        DT50   DT90 DT50back DT50_k1 DT50_k2
-cyan   24.93 179.68    54.09   7.105   69.86
-JCZ38  13.05  43.36       NA      NA      NA
-J9Z38 106.16 352.67       NA      NA      NA
-JSE76  27.39  91.00       NA      NA      NA
-
-
    
-
    
-
-Hierarchical SFORB path 2 fit with reduced random effects, constant
-variance
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 21:04:09 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound *
-           cyan_free + k_cyan_bound_free * cyan_bound
-d_cyan_bound/dt = + k_cyan_free_bound * cyan_free - k_cyan_bound_free *
-           cyan_bound
-d_JCZ38/dt = + f_cyan_free_to_JCZ38 * k_cyan_free * cyan_free - k_JCZ38
-           * JCZ38 + f_JSE76_to_JCZ38 * k_JSE76 * JSE76
-d_J9Z38/dt = + f_cyan_free_to_J9Z38 * k_cyan_free * cyan_free - k_J9Z38
-           * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 887.369 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
-          cyan_free_0       log_k_cyan_free log_k_cyan_free_bound 
-             102.4394               -2.7673               -2.8942 
-log_k_cyan_bound_free           log_k_JCZ38           log_k_J9Z38 
-              -3.6201               -2.3107               -5.3123 
-          log_k_JSE76          f_cyan_ilr_1          f_cyan_ilr_2 
-              -3.7120                0.6754                1.1448 
-       f_JCZ38_qlogis        f_JSE76_qlogis 
-              13.2672               13.3538 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-                      cyan_free_0 log_k_cyan_free log_k_cyan_free_bound
-cyan_free_0                 4.589          0.0000                  0.00
-log_k_cyan_free             0.000          0.4849                  0.00
-log_k_cyan_free_bound       0.000          0.0000                  1.62
-log_k_cyan_bound_free       0.000          0.0000                  0.00
-log_k_JCZ38                 0.000          0.0000                  0.00
-log_k_J9Z38                 0.000          0.0000                  0.00
-log_k_JSE76                 0.000          0.0000                  0.00
-f_cyan_ilr_1                0.000          0.0000                  0.00
-f_cyan_ilr_2                0.000          0.0000                  0.00
-f_JCZ38_qlogis              0.000          0.0000                  0.00
-f_JSE76_qlogis              0.000          0.0000                  0.00
-                      log_k_cyan_bound_free log_k_JCZ38 log_k_J9Z38 log_k_JSE76
-cyan_free_0                           0.000      0.0000       0.000         0.0
-log_k_cyan_free                       0.000      0.0000       0.000         0.0
-log_k_cyan_free_bound                 0.000      0.0000       0.000         0.0
-log_k_cyan_bound_free                 1.197      0.0000       0.000         0.0
-log_k_JCZ38                           0.000      0.7966       0.000         0.0
-log_k_J9Z38                           0.000      0.0000       1.561         0.0
-log_k_JSE76                           0.000      0.0000       0.000         0.8
-f_cyan_ilr_1                          0.000      0.0000       0.000         0.0
-f_cyan_ilr_2                          0.000      0.0000       0.000         0.0
-f_JCZ38_qlogis                        0.000      0.0000       0.000         0.0
-f_JSE76_qlogis                        0.000      0.0000       0.000         0.0
-                      f_cyan_ilr_1 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis
-cyan_free_0                 0.0000        0.000           0.00           0.00
-log_k_cyan_free             0.0000        0.000           0.00           0.00
-log_k_cyan_free_bound       0.0000        0.000           0.00           0.00
-log_k_cyan_bound_free       0.0000        0.000           0.00           0.00
-log_k_JCZ38                 0.0000        0.000           0.00           0.00
-log_k_J9Z38                 0.0000        0.000           0.00           0.00
-log_k_JSE76                 0.0000        0.000           0.00           0.00
-f_cyan_ilr_1                0.6349        0.000           0.00           0.00
-f_cyan_ilr_2                0.0000        1.797           0.00           0.00
-f_JCZ38_qlogis              0.0000        0.000          13.84           0.00
-f_JSE76_qlogis              0.0000        0.000           0.00          14.66
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2279 2272  -1120
-
-Optimised parameters:
-                              est.   lower  upper
-cyan_free_0               102.5621      NA     NA
-log_k_cyan_free            -2.8531      NA     NA
-log_k_cyan_free_bound      -2.6916      NA     NA
-log_k_cyan_bound_free      -3.5032      NA     NA
-log_k_JCZ38                -2.9436      NA     NA
-log_k_J9Z38                -5.1140      NA     NA
-log_k_JSE76                -3.6472      NA     NA
-f_cyan_ilr_1                0.6887      NA     NA
-f_cyan_ilr_2                0.6874      NA     NA
-f_JCZ38_qlogis           4063.6389      NA     NA
-f_JSE76_qlogis              1.9556      NA     NA
-a.1                         2.7460 2.55451 2.9376
-SD.log_k_cyan_free          0.3131 0.09841 0.5277
-SD.log_k_cyan_free_bound    0.8850 0.29909 1.4710
-SD.log_k_cyan_bound_free    0.6167 0.20391 1.0295
-SD.log_k_JCZ38              1.3555 0.49101 2.2200
-SD.log_k_J9Z38              0.7200 0.16166 1.2783
-SD.log_k_JSE76              0.6252 0.14619 1.1042
-SD.f_cyan_ilr_1             0.3386 0.11447 0.5627
-SD.f_cyan_ilr_2             0.4699 0.09810 0.8417
-
-Correlation is not available
-
-Random effects:
-                           est.   lower  upper
-SD.log_k_cyan_free       0.3131 0.09841 0.5277
-SD.log_k_cyan_free_bound 0.8850 0.29909 1.4710
-SD.log_k_cyan_bound_free 0.6167 0.20391 1.0295
-SD.log_k_JCZ38           1.3555 0.49101 2.2200
-SD.log_k_J9Z38           0.7200 0.16166 1.2783
-SD.log_k_JSE76           0.6252 0.14619 1.1042
-SD.f_cyan_ilr_1          0.3386 0.11447 0.5627
-SD.f_cyan_ilr_2          0.4699 0.09810 0.8417
-
-Variance model:
-     est. lower upper
-a.1 2.746 2.555 2.938
-
-Backtransformed parameters:
-                          est. lower upper
-cyan_free_0          1.026e+02    NA    NA
-k_cyan_free          5.767e-02    NA    NA
-k_cyan_free_bound    6.777e-02    NA    NA
-k_cyan_bound_free    3.010e-02    NA    NA
-k_JCZ38              5.267e-02    NA    NA
-k_J9Z38              6.012e-03    NA    NA
-k_JSE76              2.606e-02    NA    NA
-f_cyan_free_to_JCZ38 6.089e-01    NA    NA
-f_cyan_free_to_J9Z38 2.299e-01    NA    NA
-f_JCZ38_to_JSE76     1.000e+00    NA    NA
-f_JSE76_to_JCZ38     8.761e-01    NA    NA
-
-Estimated Eigenvalues of SFORB model(s):
-cyan_b1 cyan_b2  cyan_g 
- 0.1434  0.0121  0.3469 
-
-Resulting formation fractions:
-                    ff
-cyan_free_JCZ38 0.6089
-cyan_free_J9Z38 0.2299
-cyan_free_sink  0.1612
-cyan_free       1.0000
-JCZ38_JSE76     1.0000
-JCZ38_sink      0.0000
-JSE76_JCZ38     0.8761
-JSE76_sink      0.1239
-
-Estimated disappearance times:
-        DT50   DT90 DT50back DT50_cyan_b1 DT50_cyan_b2
-cyan   23.94 155.06    46.68        4.832        57.28
-JCZ38  13.16  43.71       NA           NA           NA
-J9Z38 115.30 383.02       NA           NA           NA
-JSE76  26.59  88.35       NA           NA           NA
-
-
    
-
    
-
-Hierarchical SFORB path 2 fit with reduced random effects, two-component
-error
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.4 
-R version used for fitting:         4.2.3 
-Date of fit:     Thu Apr 20 21:04:32 2023 
-Date of summary: Thu Apr 20 21:04:34 2023 
-
-Equations:
-d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound *
-           cyan_free + k_cyan_bound_free * cyan_bound
-d_cyan_bound/dt = + k_cyan_free_bound * cyan_free - k_cyan_bound_free *
-           cyan_bound
-d_JCZ38/dt = + f_cyan_free_to_JCZ38 * k_cyan_free * cyan_free - k_JCZ38
-           * JCZ38 + f_JSE76_to_JCZ38 * k_JSE76 * JSE76
-d_J9Z38/dt = + f_cyan_free_to_J9Z38 * k_cyan_free * cyan_free - k_J9Z38
-           * J9Z38
-d_JSE76/dt = + f_JCZ38_to_JSE76 * k_JCZ38 * JCZ38 - k_JSE76 * JSE76
-
-Data:
-433 observations of 4 variable(s) grouped in 5 datasets
-
-Model predictions using solution type deSolve 
-
-Fitted in 910.017 s
-Using 300, 100 iterations and 10 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-          cyan_free_0       log_k_cyan_free log_k_cyan_free_bound 
-              101.751                -2.837                -3.016 
-log_k_cyan_bound_free           log_k_JCZ38           log_k_J9Z38 
-               -3.660                -2.299                -5.313 
-          log_k_JSE76          f_cyan_ilr_1          f_cyan_ilr_2 
-               -3.699                 0.672                 5.873 
-       f_JCZ38_qlogis        f_JSE76_qlogis 
-               13.216                13.338 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-                      cyan_free_0 log_k_cyan_free log_k_cyan_free_bound
-cyan_free_0                 5.629           0.000                 0.000
-log_k_cyan_free             0.000           0.446                 0.000
-log_k_cyan_free_bound       0.000           0.000                 1.449
-log_k_cyan_bound_free       0.000           0.000                 0.000
-log_k_JCZ38                 0.000           0.000                 0.000
-log_k_J9Z38                 0.000           0.000                 0.000
-log_k_JSE76                 0.000           0.000                 0.000
-f_cyan_ilr_1                0.000           0.000                 0.000
-f_cyan_ilr_2                0.000           0.000                 0.000
-f_JCZ38_qlogis              0.000           0.000                 0.000
-f_JSE76_qlogis              0.000           0.000                 0.000
-                      log_k_cyan_bound_free log_k_JCZ38 log_k_J9Z38 log_k_JSE76
-cyan_free_0                           0.000      0.0000       0.000      0.0000
-log_k_cyan_free                       0.000      0.0000       0.000      0.0000
-log_k_cyan_free_bound                 0.000      0.0000       0.000      0.0000
-log_k_cyan_bound_free                 1.213      0.0000       0.000      0.0000
-log_k_JCZ38                           0.000      0.7801       0.000      0.0000
-log_k_J9Z38                           0.000      0.0000       1.575      0.0000
-log_k_JSE76                           0.000      0.0000       0.000      0.8078
-f_cyan_ilr_1                          0.000      0.0000       0.000      0.0000
-f_cyan_ilr_2                          0.000      0.0000       0.000      0.0000
-f_JCZ38_qlogis                        0.000      0.0000       0.000      0.0000
-f_JSE76_qlogis                        0.000      0.0000       0.000      0.0000
-                      f_cyan_ilr_1 f_cyan_ilr_2 f_JCZ38_qlogis f_JSE76_qlogis
-cyan_free_0                 0.0000         0.00           0.00           0.00
-log_k_cyan_free             0.0000         0.00           0.00           0.00
-log_k_cyan_free_bound       0.0000         0.00           0.00           0.00
-log_k_cyan_bound_free       0.0000         0.00           0.00           0.00
-log_k_JCZ38                 0.0000         0.00           0.00           0.00
-log_k_J9Z38                 0.0000         0.00           0.00           0.00
-log_k_JSE76                 0.0000         0.00           0.00           0.00
-f_cyan_ilr_1                0.6519         0.00           0.00           0.00
-f_cyan_ilr_2                0.0000        10.78           0.00           0.00
-f_JCZ38_qlogis              0.0000         0.00          13.96           0.00
-f_JSE76_qlogis              0.0000         0.00           0.00          14.69
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-   AIC  BIC logLik
-  2236 2228  -1098
-
-Optimised parameters:
-                              est.   lower   upper
-cyan_free_0              100.72760      NA      NA
-log_k_cyan_free           -3.18281      NA      NA
-log_k_cyan_free_bound     -3.37924      NA      NA
-log_k_cyan_bound_free     -3.77107      NA      NA
-log_k_JCZ38               -2.92811      NA      NA
-log_k_J9Z38               -5.02759      NA      NA
-log_k_JSE76               -3.65835      NA      NA
-f_cyan_ilr_1               0.67390      NA      NA
-f_cyan_ilr_2               1.15106      NA      NA
-f_JCZ38_qlogis           827.82299      NA      NA
-f_JSE76_qlogis             1.83064      NA      NA
-a.1                        2.06921 1.84443 2.29399
-b.1                        0.06391 0.05267 0.07515
-SD.log_k_cyan_free         0.50518 0.18962 0.82075
-SD.log_k_cyan_bound_free   0.30991 0.08170 0.53813
-SD.log_k_JCZ38             1.26661 0.46578 2.06744
-SD.log_k_J9Z38             0.88272 0.27813 1.48730
-SD.log_k_JSE76             0.53050 0.12561 0.93538
-SD.f_cyan_ilr_1            0.35547 0.12461 0.58633
-SD.f_cyan_ilr_2            0.91446 0.20131 1.62761
-
-Correlation is not available
-
-Random effects:
-                           est.  lower  upper
-SD.log_k_cyan_free       0.5052 0.1896 0.8207
-SD.log_k_cyan_bound_free 0.3099 0.0817 0.5381
-SD.log_k_JCZ38           1.2666 0.4658 2.0674
-SD.log_k_J9Z38           0.8827 0.2781 1.4873
-SD.log_k_JSE76           0.5305 0.1256 0.9354
-SD.f_cyan_ilr_1          0.3555 0.1246 0.5863
-SD.f_cyan_ilr_2          0.9145 0.2013 1.6276
-
-Variance model:
-       est.   lower   upper
-a.1 2.06921 1.84443 2.29399
-b.1 0.06391 0.05267 0.07515
-
-Backtransformed parameters:
-                          est. lower upper
-cyan_free_0          1.007e+02    NA    NA
-k_cyan_free          4.147e-02    NA    NA
-k_cyan_free_bound    3.407e-02    NA    NA
-k_cyan_bound_free    2.303e-02    NA    NA
-k_JCZ38              5.350e-02    NA    NA
-k_J9Z38              6.555e-03    NA    NA
-k_JSE76              2.578e-02    NA    NA
-f_cyan_free_to_JCZ38 6.505e-01    NA    NA
-f_cyan_free_to_J9Z38 2.508e-01    NA    NA
-f_JCZ38_to_JSE76     1.000e+00    NA    NA
-f_JSE76_to_JCZ38     8.618e-01    NA    NA
-
-Estimated Eigenvalues of SFORB model(s):
-cyan_b1 cyan_b2  cyan_g 
-0.08768 0.01089 0.39821 
-
-Resulting formation fractions:
-                     ff
-cyan_free_JCZ38 0.65053
-cyan_free_J9Z38 0.25082
-cyan_free_sink  0.09864
-cyan_free       1.00000
-JCZ38_JSE76     1.00000
-JCZ38_sink      0.00000
-JSE76_JCZ38     0.86184
-JSE76_sink      0.13816
-
-Estimated disappearance times:
-        DT50   DT90 DT50back DT50_cyan_b1 DT50_cyan_b2
-cyan   25.32 164.79    49.61        7.906        63.64
-JCZ38  12.96  43.04       NA           NA           NA
-J9Z38 105.75 351.29       NA           NA           NA
-JSE76  26.89  89.33       NA           NA           NA
-
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-
    
-
    
-
    
-
    
-
    Session info
-
    
-
    R version 4.2.3 (2023-03-15)
-Platform: x86_64-pc-linux-gnu (64-bit)
-Running under: Debian GNU/Linux 12 (bookworm)
-
-Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/openblas-serial/libblas.so.3
-LAPACK: /usr/lib/x86_64-linux-gnu/openblas-serial/libopenblas-r0.3.21.so
-
-locale:
- [1] LC_CTYPE=de_DE.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=de_DE.UTF-8        LC_COLLATE=de_DE.UTF-8    
- [5] LC_MONETARY=de_DE.UTF-8    LC_MESSAGES=de_DE.UTF-8   
- [7] LC_PAPER=de_DE.UTF-8       LC_NAME=C                 
- [9] LC_ADDRESS=C               LC_TELEPHONE=C            
-[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C       
-
-attached base packages:
-[1] parallel  stats     graphics  grDevices utils     datasets  methods  
-[8] base     
-
-other attached packages:
-[1] saemix_3.2 npde_3.3   knitr_1.42 mkin_1.2.4
-
-loaded via a namespace (and not attached):
- [1] deSolve_1.35      zoo_1.8-12        tidyselect_1.2.0  xfun_0.38        
- [5] bslib_0.4.2       purrr_1.0.1       lattice_0.21-8    colorspace_2.1-0 
- [9] vctrs_0.6.1       generics_0.1.3    htmltools_0.5.5   yaml_2.3.7       
-[13] utf8_1.2.3        rlang_1.1.0       pkgbuild_1.4.0    pkgdown_2.0.7    
-[17] jquerylib_0.1.4   pillar_1.9.0      glue_1.6.2        DBI_1.1.3        
-[21] readxl_1.4.2      lifecycle_1.0.3   stringr_1.5.0     munsell_0.5.0    
-[25] gtable_0.3.3      cellranger_1.1.0  ragg_1.2.5        codetools_0.2-19 
-[29] memoise_2.0.1     evaluate_0.20     inline_0.3.19     callr_3.7.3      
-[33] fastmap_1.1.1     ps_1.7.4          lmtest_0.9-40     fansi_1.0.4      
-[37] highr_0.10        scales_1.2.1      cachem_1.0.7      desc_1.4.2       
-[41] jsonlite_1.8.4    systemfonts_1.0.4 fs_1.6.1          textshaping_0.3.6
-[45] gridExtra_2.3     ggplot2_3.4.2     digest_0.6.31     stringi_1.7.12   
-[49] processx_3.8.0    dplyr_1.1.1       grid_4.2.3        rprojroot_2.0.3  
-[53] cli_3.6.1         tools_4.2.3       magrittr_2.0.3    sass_0.4.5       
-[57] tibble_3.2.1      crayon_1.5.2      pkgconfig_2.0.3   prettyunits_1.1.1
-[61] rmarkdown_2.21    R6_2.5.1          mclust_6.0.0      nlme_3.1-162     
-[65] compiler_4.2.3   
    
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-
    Hardware info
-
    
-
    CPU model: AMD Ryzen 9 7950X 16-Core Processor
    
-
    MemTotal:       64936316 kB
    
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    Developed by Johannes Ranke.
    
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    Site built with pkgdown 2.0.7.
    
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-Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P • mkin
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    Testing hierarchical parent degradation kinetics
-with residue data on dimethenamid and dimethenamid-P
    
-                        
    Johannes
-Ranke
    
-            
-            
    Last change on 5 January
-2023, last compiled on 16 April 2023
    
-      
-      Source: vignettes/prebuilt/2022_dmta_parent.rmd
-      
-
-    
    
-
-    
-    
-
    
-
    Introduction
-
    
-
    The purpose of this document is to demonstrate how nonlinear
-hierarchical models (NLHM) based on the parent degradation models SFO,
-FOMC, DFOP and HS can be fitted with the mkin package.
    
-
    It was assembled in the course of work package 1.1 of Project Number
-173340 (Application of nonlinear hierarchical models to the kinetic
-evaluation of chemical degradation data) of the German Environment
-Agency carried out in 2022 and 2023.
    
-
    The mkin package is used in version 1.2.3. It contains the test data
-and the functions used in the evaluations. The saemix
-package is used as a backend for fitting the NLHM, but is also loaded to
-make the convergence plot function available.
    
-
    This document is processed with the knitr package, which
-also provides the kable function that is used to improve
-the display of tabular data in R markdown documents. For parallel
-processing, the parallel package is used.
    
-
    -library(mkin)
-library(knitr)
-library(saemix)
-library(parallel)
-n_cores <- detectCores()
-if (Sys.info()["sysname"] == "Windows") {
-  cl <- makePSOCKcluster(n_cores)
-} else {
-  cl <- makeForkCluster(n_cores)
-}
    
-
    
-
    
-
    Data
-
    
-
    The test data are available in the mkin package as an object of class
-mkindsg (mkin dataset group) under the identifier
-dimethenamid_2018. The following preprocessing steps are
-still necessary:
    
-
      
-
    • The data available for the enantiomer dimethenamid-P (DMTAP) are
-renamed to have the same substance name as the data for the racemic
-mixture dimethenamid (DMTA). The reason for this is that no difference
-between their degradation behaviour was identified in the EU risk
-assessment.
      • 
-
    • The data for transformation products and unnecessary columns are
-discarded
      • 
-
    • The observation times of each dataset are multiplied with the
-corresponding normalisation factor also available in the dataset, in
-order to make it possible to describe all datasets with a single set of
-parameters that are independent of temperature
      • 
-
    • Finally, datasets observed in the same soil (Elliot 1
-and Elliot 2) are combined, resulting in dimethenamid
-(DMTA) data from six soils.
      • 
-
    
-
    The following commented R code performs this preprocessing.
    
-
    -# Apply a function to each of the seven datasets in the mkindsg object to create a list
-dmta_ds <- lapply(1:7, function(i) {
-  ds_i <- dimethenamid_2018$ds[[i]]$data                     # Get a dataset
-  ds_i[ds_i$name == "DMTAP", "name"] <-  "DMTA"              # Rename DMTAP to DMTA
-  ds_i <- subset(ds_i, name == "DMTA", c("name", "time", "value")) # Select data
-  ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i]  # Normalise time
-  ds_i                                                       # Return the dataset
-})
-
-# Use dataset titles as names for the list elements
-names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title)
-
-# Combine data for Elliot soil to obtain a named list with six elements
-dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]]) #
-dmta_ds[["Elliot 1"]] <- NULL
-dmta_ds[["Elliot 2"]] <- NULL
    
-
    The following tables show the 6 datasets.
    
-
    -for (ds_name in names(dmta_ds)) {
-    print(kable(mkin_long_to_wide(dmta_ds[[ds_name]]),
-      caption = paste("Dataset", ds_name),
-      label = paste0("tab:", ds_name), booktabs = TRUE))
-    cat("\n\\clearpage\n")
-}
    
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    Dataset Calke
    timeDMTA
    095.8
    098.7
    1460.5
    3039.1
    5915.2
    1204.8
    1204.6
    
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    Dataset Borstel
    timeDMTA
    0.000000100.5
    0.00000099.6
    1.94129591.9
    1.94129591.3
    6.79453481.8
    6.79453482.1
    13.58906769.1
    13.58906768.0
    27.17813551.4
    27.17813551.4
    56.29756527.6
    56.29756526.8
    86.38764315.7
    86.38764315.3
    115.5070737.9
    115.5070738.1
    
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    Dataset Flaach
    timeDMTA
    0.000000096.5
    0.000000096.8
    0.000000097.0
    0.623385682.9
    0.623385686.7
    0.623385687.4
    1.870156772.8
    1.870156769.9
    1.870156771.9
    4.363698951.4
    4.363698952.9
    4.363698948.6
    8.727397928.5
    8.727397927.3
    8.727397927.5
    13.091096814.8
    13.091096813.4
    13.091096814.4
    17.45479577.7
    17.45479577.3
    17.45479578.1
    26.18219362.0
    26.18219361.5
    26.18219361.9
    34.90959151.3
    34.90959151.0
    34.90959151.1
    43.63698930.9
    43.63698930.7
    43.63698930.7
    52.36438720.6
    52.36438720.4
    52.36438720.5
    74.80626740.4
    74.80626740.3
    74.80626740.3
    
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    Dataset BBA 2.2
    timeDMTA
    0.000000098.09
    0.000000098.77
    0.767892293.52
    0.767892292.03
    2.303676588.39
    2.303676587.18
    5.375245269.38
    5.375245271.06
    10.750490445.21
    10.750490446.81
    16.125735530.54
    16.125735530.07
    21.500980721.60
    21.500980720.41
    32.25147119.10
    32.25147119.70
    43.00196146.58
    43.00196146.31
    53.75245183.47
    53.75245183.52
    64.50294213.40
    64.50294213.67
    91.37916801.62
    91.37916801.62
    
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    Dataset BBA 2.3
    timeDMTA
    0.000000099.33
    0.000000097.44
    0.673393893.73
    0.673393893.77
    2.020181487.84
    2.020181489.82
    4.713756571.61
    4.713756571.42
    9.427513145.60
    9.427513145.42
    14.141269631.12
    14.141269631.68
    18.855026223.20
    18.855026224.13
    28.28253939.43
    28.28253939.82
    37.71005237.08
    37.71005238.64
    47.13756544.41
    47.13756544.78
    56.56507854.92
    56.56507855.08
    80.13386122.13
    80.13386122.23
    
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    Dataset Elliot
    timeDMTA
    0.00000097.5
    0.000000100.7
    1.22847886.4
    1.22847888.5
    3.68543569.8
    3.68543577.1
    8.59934959.0
    8.59934954.2
    17.19869731.3
    17.19869733.5
    25.79804619.6
    25.79804620.9
    34.39739513.3
    34.39739515.8
    51.5960926.7
    51.5960928.7
    68.7947898.8
    68.7947898.7
    103.1921846.0
    103.1921844.4
    146.1889283.3
    146.1889282.8
    223.5830661.4
    223.5830661.8
    0.00000093.4
    0.000000103.2
    1.22847889.2
    1.22847886.6
    3.68543578.2
    3.68543578.1
    8.59934955.6
    8.59934953.0
    17.19869733.7
    17.19869733.2
    25.79804620.9
    25.79804619.9
    34.39739518.2
    34.39739512.7
    51.5960927.8
    51.5960929.0
    68.79478911.4
    68.7947899.0
    103.1921843.9
    103.1921844.4
    146.1889282.6
    146.1889283.4
    223.5830662.0
    223.5830661.7
    
-
    
-
    
-
    Separate evaluations
-
    
-
    In order to obtain suitable starting parameters for the NLHM fits,
-separate fits of the four models to the data for each soil are generated
-using the mmkin function from the mkin
-package. In a first step, constant variance is assumed. Convergence is
-checked with the status function.
    
-
    -deg_mods <- c("SFO", "FOMC", "DFOP", "HS")
-f_sep_const <- mmkin(
-  deg_mods,
-  dmta_ds,
-  error_model = "const",
-  quiet = TRUE)
-
-status(f_sep_const) |> kable()
    
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    CalkeBorstelFlaachBBA 2.2BBA 2.3Elliot
    SFOOKOKOKOKOKOK
    FOMCOKOKOKOKOKOK
    DFOPOKOKOKOKOKOK
    HSOKOKOKCOKOK
    
-
    In the table above, OK indicates convergence, and C indicates failure
-to converge. All separate fits with constant variance converged, with
-the sole exception of the HS fit to the BBA 2.2 data. To prepare for
-fitting NLHM using the two-component error model, the separate fits are
-updated assuming two-component error.
    
-
    -f_sep_tc <- update(f_sep_const, error_model = "tc")
-status(f_sep_tc) |> kable()
    
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    CalkeBorstelFlaachBBA 2.2BBA 2.3Elliot
    SFOOKOKOKOKOKOK
    FOMCOKOKOKOKCOK
    DFOPOKOKCOKCOK
    HSOKCOKOKOKOK
    
-
    Using the two-component error model, the one fit that did not
-converge with constant variance did converge, but other non-SFO fits
-failed to converge.
    
-
    
-
    
-
    Hierarchichal model fits
-
    
-
    The following code fits eight versions of hierarchical models to the
-data, using SFO, FOMC, DFOP and HS for the parent compound, and using
-either constant variance or two-component error for the error model. The
-default parameter distribution model in mkin allows for variation of all
-degradation parameters across the assumed population of soils. In other
-words, each degradation parameter is associated with a random effect as
-a first step. The mhmkin function makes it possible to fit
-all eight versions in parallel (given a sufficient number of computing
-cores being available) to save execution time.
    
-
    Convergence plots and summaries for these fits are shown in the
-appendix.
    
-
    -f_saem <- mhmkin(list(f_sep_const, f_sep_tc), transformations = "saemix")
    
-
    The output of the status function shows that all fits
-terminated successfully.
    
-
    -status(f_saem) |> kable()
    
-
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    consttc
    SFOOKOK
    FOMCOKOK
    DFOPOKOK
    HSOKOK
    
-
    The AIC and BIC values show that the biphasic models DFOP and HS give
-the best fits.
    
-
    -anova(f_saem) |> kable(digits = 1)
    
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    nparAICBICLik
    SFO const5796.3795.3-393.2
    SFO tc6798.3797.1-393.2
    FOMC const7734.2732.7-360.1
    FOMC tc8720.4718.8-352.2
    DFOP const9711.8710.0-346.9
    HS const9714.0712.1-348.0
    DFOP tc10665.5663.4-322.8
    HS tc10667.1665.0-323.6
    
-
    The DFOP model is preferred here, as it has a better mechanistic
-basis for batch experiments with constant incubation conditions. Also,
-it shows the lowest AIC and BIC values in the first set of fits when
-combined with the two-component error model. Therefore, the DFOP model
-was selected for further refinements of the fits with the aim to make
-the model fully identifiable.
    
-
    
-
    Parameter identifiability based on the Fisher Information
-Matrix
-
    
-
    Using the illparms function, ill-defined statistical
-model parameters such as standard deviations of the degradation
-parameters in the population and error model parameters can be
-found.
    
-
    -illparms(f_saem) |> kable()
    
-
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    consttc
    SFOb.1
    FOMCsd(DMTA_0)
    DFOPsd(k2)sd(k2)
    HSsd(tb)
    
-
    According to the illparms function, the fitted standard
-deviation of the second kinetic rate constant k2 is
-ill-defined in both DFOP fits. This suggests that different values would
-be obtained for this standard deviation when using different starting
-values.
    
-
    The thus identified overparameterisation is addressed by removing the
-random effect for k2 from the parameter model.
    
-
    -f_saem_dfop_tc_no_ranef_k2 <- update(f_saem[["DFOP", "tc"]],
-  no_random_effect = "k2")
    
-
    For the resulting fit, it is checked whether there are still
-ill-defined parameters,
    
-
    -illparms(f_saem_dfop_tc_no_ranef_k2)
    
-
    which is not the case. Below, the refined model is compared with the
-previous best model. The model without random effect for k2
-is a reduced version of the previous model. Therefore, the models are
-nested and can be compared using the likelihood ratio test. This is
-achieved with the argument test = TRUE to the
-anova function.
    
-
    -anova(f_saem[["DFOP", "tc"]], f_saem_dfop_tc_no_ranef_k2, test = TRUE) |>
-  kable(format.args = list(digits = 4))
    
-
----------
-
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-
    









    nparAICBICLikChisqDfPr(>Chisq)
    f_saem_dfop_tc_no_ranef_k29663.8661.9-322.9NANANA
    f_saem[[“DFOP”, “tc”]]10665.5663.4-322.80.280910.5961
    
-
    The AIC and BIC criteria are lower after removal of the ill-defined
-random effect for k2. The p value of the likelihood ratio
-test is much greater than 0.05, indicating that the model with the
-higher likelihood (here the model with random effects for all
-degradation parameters f_saem[["DFOP", "tc"]]) does not fit
-significantly better than the model with the lower likelihood (the
-reduced model f_saem_dfop_tc_no_ranef_k2).
    
-
    Therefore, AIC, BIC and likelihood ratio test suggest the use of the
-reduced model.
    
-
    The convergence of the fit is checked visually.
    
-
    
-Convergence plot for the NLHM DFOP fit with two-component error and without a random effect on 'k2'
    
-Convergence plot for the NLHM DFOP fit with two-component error and
-without a random effect on ‘k2’
-
    
-
    
-
    All parameters appear to have converged to a satisfactory degree. The
-final fit is plotted using the plot method from the mkin package.
    
-
    -plot(f_saem_dfop_tc_no_ranef_k2)
    
-
    
-Plot of the final NLHM DFOP fit
    
-Plot of the final NLHM DFOP fit
-
    
-
    
-
    Finally, a summary report of the fit is produced.
    
-
    -summary(f_saem_dfop_tc_no_ranef_k2)
    
-
    saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Sat Jan 28 11:22:51 2023 
-Date of summary: Sat Jan 28 11:22:52 2023 
-
-Equations:
-d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-           time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-           * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 3.74 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-   DMTA_0        k1        k2         g 
-98.759266  0.087034  0.009933  0.930827 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 k1 k2 g
-DMTA_0  98.76  0  0 0
-k1       0.00  1  0 0
-k2       0.00  0  1 0
-g        0.00  0  0 1
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC   BIC logLik
-  663.8 661.9 -322.9
-
-Optimised parameters:
-               est.     lower     upper
-DMTA_0    98.228939 96.285869 100.17201
-k1         0.064063  0.033477   0.09465
-k2         0.008297  0.005824   0.01077
-g          0.953821  0.914328   0.99331
-a.1        1.068479  0.869538   1.26742
-b.1        0.029424  0.022406   0.03644
-SD.DMTA_0  2.030437  0.404824   3.65605
-SD.k1      0.594692  0.256660   0.93272
-SD.g       1.006754  0.361327   1.65218
-
-Correlation: 
-   DMTA_0  k1      k2     
-k1  0.0218                
-k2  0.0556  0.0355        
-g  -0.0516 -0.0284 -0.2800
-
-Random effects:
-            est.  lower  upper
-SD.DMTA_0 2.0304 0.4048 3.6560
-SD.k1     0.5947 0.2567 0.9327
-SD.g      1.0068 0.3613 1.6522
-
-Variance model:
-       est.   lower   upper
-a.1 1.06848 0.86954 1.26742
-b.1 0.02942 0.02241 0.03644
-
-Estimated disappearance times:
-      DT50 DT90 DT50back DT50_k1 DT50_k2
-DMTA 11.45 41.4    12.46   10.82   83.54
    
-
    
-
    
-
    Alternative check of parameter identifiability
-
    
-
    The parameter check used in the illparms function is
-based on a quadratic approximation of the likelihood surface near its
-optimum, which is calculated using the Fisher Information Matrix (FIM).
-An alternative way to check parameter identifiability (Duchesne et al. 2021) based on a multistart
-approach has recently been implemented in mkin.
    
-
    The graph below shows boxplots of the parameters obtained in 50 runs
-of the saem algorithm with different parameter combinations, sampled
-from the range of the parameters obtained for the individual datasets
-fitted separately using nonlinear regression.
    
-
    -f_saem_dfop_tc_multi <- multistart(f_saem[["DFOP", "tc"]], n = 50, cores = 15)
    
-
    -par(mar = c(6.1, 4.1, 2.1, 2.1))
-parplot(f_saem_dfop_tc_multi, lpos = "bottomright", ylim = c(0.3, 10), las = 2)
    
-
    
-Scaled parameters from the multistart runs, full model
    
-Scaled parameters from the multistart runs, full model
-
    
-
    
-
    The graph clearly confirms the lack of identifiability of the
-variance of k2 in the full model. The overparameterisation
-of the model also indicates a lack of identifiability of the variance of
-parameter g.
    
-
    The parameter boxplots of the multistart runs with the reduced model
-shown below indicate that all runs give similar results, regardless of
-the starting parameters.
    
-
    -f_saem_dfop_tc_no_ranef_k2_multi <- multistart(f_saem_dfop_tc_no_ranef_k2,
-  n = 50, cores = 15)
    
-
    -par(mar = c(6.1, 4.1, 2.1, 2.1))
-parplot(f_saem_dfop_tc_no_ranef_k2_multi, ylim = c(0.5, 2), las = 2,
-  lpos = "bottomright")
    
-
    
-Scaled parameters from the multistart runs, reduced model
    
-Scaled parameters from the multistart runs, reduced model
-
    
-
    
-
    When only the parameters of the top 25% of the fits are shown (based
-on a feature introduced in mkin 1.2.2 currently under development), the
-scatter is even less as shown below.
    
-
    -par(mar = c(6.1, 4.1, 2.1, 2.1))
-parplot(f_saem_dfop_tc_no_ranef_k2_multi, ylim = c(0.5, 2), las = 2, llquant = 0.25,
-  lpos = "bottomright")
    
-
    
-Scaled parameters from the multistart runs, reduced model, fits with the top 25\% likelihood values
    
-Scaled parameters from the multistart runs, reduced model, fits with the
-top 25% likelihood values
-
    
-
    
-
    
-
    
-
    
-
    Conclusions
-
    
-
    Fitting the four parent degradation models SFO, FOMC, DFOP and HS as
-part of hierarchical model fits with two different error models and
-normal distributions of the transformed degradation parameters works
-without technical problems. The biphasic models DFOP and HS gave the
-best fit to the data, but the default parameter distribution model was
-not fully identifiable. Removing the random effect for the second
-kinetic rate constant of the DFOP model resulted in a reduced model that
-was fully identifiable and showed the lowest values for the model
-selection criteria AIC and BIC. The reliability of the identification of
-all model parameters was confirmed using multiple starting values.
    
-
    
-
    
-
    Acknowledgements
-
    
-
    The helpful comments by Janina Wöltjen of the German Environment
-Agency are gratefully acknowledged.
    
-
    
-
    
-
    References
-
    
-
    
-
    
-Duchesne, Ronan, Anissa Guillemin, Olivier Gandrillon, and Fabien
-Crauste. 2021. “Practical Identifiability in the Frame of
-Nonlinear Mixed Effects Models: The Example of the in Vitro
-Erythropoiesis.” BMC Bioinformatics 22 (478). https://doi.org/10.1186/s12859-021-04373-4.
-
    
-
    
-
    
-
    
-
    Appendix
-
    
-
    
-
    Hierarchical model fit listings
-
    
-
-Hierarchical mkin fit of the SFO model with error model const
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Sat Jan 28 11:22:44 2023 
-Date of summary: Sat Jan 28 11:23:57 2023 
-
-Equations:
-d_DMTA/dt = - k_DMTA * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 0.982 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
- DMTA_0  k_DMTA 
-97.2953  0.0566 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 k_DMTA
-DMTA_0   97.3      0
-k_DMTA    0.0      1
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC   BIC logLik
-  796.3 795.3 -393.2
-
-Optimised parameters:
-              est.    lower   upper
-DMTA_0    97.28130 95.71113 98.8515
-k_DMTA     0.05665  0.02909  0.0842
-a.1        2.66442  2.35579  2.9731
-SD.DMTA_0  1.54776  0.15447  2.9411
-SD.k_DMTA  0.60690  0.26248  0.9513
-
-Correlation: 
-       DMTA_0
-k_DMTA 0.0168
-
-Random effects:
-            est.  lower  upper
-SD.DMTA_0 1.5478 0.1545 2.9411
-SD.k_DMTA 0.6069 0.2625 0.9513
-
-Variance model:
-     est. lower upper
-a.1 2.664 2.356 2.973
-
-Estimated disappearance times:
-      DT50  DT90
-DMTA 12.24 40.65
-
-
    
-
    
-
-Hierarchical mkin fit of the SFO model with error model tc
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Sat Jan 28 11:22:46 2023 
-Date of summary: Sat Jan 28 11:23:57 2023 
-
-Equations:
-d_DMTA/dt = - k_DMTA * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 2.39 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-  DMTA_0   k_DMTA 
-96.99175  0.05603 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 k_DMTA
-DMTA_0  96.99      0
-k_DMTA   0.00      1
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC   BIC logLik
-  798.3 797.1 -393.2
-
-Optimised parameters:
-               est.     lower    upper
-DMTA_0    97.271822 95.703157 98.84049
-k_DMTA     0.056638  0.029110  0.08417
-a.1        2.660081  2.230398  3.08976
-b.1        0.001665 -0.006911  0.01024
-SD.DMTA_0  1.545520  0.145035  2.94601
-SD.k_DMTA  0.606422  0.262274  0.95057
-
-Correlation: 
-       DMTA_0
-k_DMTA 0.0169
-
-Random effects:
-            est.  lower  upper
-SD.DMTA_0 1.5455 0.1450 2.9460
-SD.k_DMTA 0.6064 0.2623 0.9506
-
-Variance model:
-        est.     lower   upper
-a.1 2.660081  2.230398 3.08976
-b.1 0.001665 -0.006911 0.01024
-
-Estimated disappearance times:
-      DT50  DT90
-DMTA 12.24 40.65
-
-
    
-
    
-
-Hierarchical mkin fit of the FOMC model with error model const
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Sat Jan 28 11:22:45 2023 
-Date of summary: Sat Jan 28 11:23:57 2023 
-
-Equations:
-d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 1.552 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
- DMTA_0   alpha    beta 
- 98.292   9.909 156.341 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 alpha beta
-DMTA_0  98.29     0    0
-alpha    0.00     1    0
-beta     0.00     0    1
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC   BIC logLik
-  734.2 732.7 -360.1
-
-Optimised parameters:
-              est.   lower   upper
-DMTA_0     98.3435 96.9033  99.784
-alpha       7.2007  2.5889  11.812
-beta      112.8746 34.8816 190.868
-a.1         2.0459  1.8054   2.286
-SD.DMTA_0   1.4795  0.2717   2.687
-SD.alpha    0.6396  0.1509   1.128
-SD.beta     0.6874  0.1587   1.216
-
-Correlation: 
-      DMTA_0  alpha  
-alpha -0.1125        
-beta  -0.1227  0.3632
-
-Random effects:
-            est.  lower upper
-SD.DMTA_0 1.4795 0.2717 2.687
-SD.alpha  0.6396 0.1509 1.128
-SD.beta   0.6874 0.1587 1.216
-
-Variance model:
-     est. lower upper
-a.1 2.046 1.805 2.286
-
-Estimated disappearance times:
-      DT50  DT90 DT50back
-DMTA 11.41 42.53     12.8
-
-
    
-
    
-
-Hierarchical mkin fit of the FOMC model with error model tc
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Sat Jan 28 11:22:46 2023 
-Date of summary: Sat Jan 28 11:23:57 2023 
-
-Equations:
-d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 2.764 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-DMTA_0  alpha   beta 
-98.772  4.663 92.597 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 alpha beta
-DMTA_0  98.77     0    0
-alpha    0.00     1    0
-beta     0.00     0    1
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC   BIC logLik
-  720.4 718.8 -352.2
-
-Optimised parameters:
-              est.    lower     upper
-DMTA_0    98.99136 97.26011 100.72261
-alpha      5.86312  2.57485   9.15138
-beta      88.55571 29.20889 147.90254
-a.1        1.51063  1.24384   1.77741
-b.1        0.02824  0.02040   0.03609
-SD.DMTA_0  1.57436 -0.04867   3.19739
-SD.alpha   0.59871  0.17132   1.02611
-SD.beta    0.72994  0.22849   1.23139
-
-Correlation: 
-      DMTA_0  alpha  
-alpha -0.1363        
-beta  -0.1414  0.2542
-
-Random effects:
-            est.    lower upper
-SD.DMTA_0 1.5744 -0.04867 3.197
-SD.alpha  0.5987  0.17132 1.026
-SD.beta   0.7299  0.22849 1.231
-
-Variance model:
-       est.  lower   upper
-a.1 1.51063 1.2438 1.77741
-b.1 0.02824 0.0204 0.03609
-
-Estimated disappearance times:
-      DT50 DT90 DT50back
-DMTA 11.11 42.6    12.82
-
-
    
-
    
-
-Hierarchical mkin fit of the DFOP model with error model const
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Sat Jan 28 11:22:45 2023 
-Date of summary: Sat Jan 28 11:23:57 2023 
-
-Equations:
-d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-           time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-           * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 1.649 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
-  DMTA_0       k1       k2        g 
-98.64383  0.09211  0.02999  0.76814 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 k1 k2 g
-DMTA_0  98.64  0  0 0
-k1       0.00  1  0 0
-k2       0.00  0  1 0
-g        0.00  0  0 1
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC BIC logLik
-  711.8 710 -346.9
-
-Optimised parameters:
-               est.     lower    upper
-DMTA_0    98.092481 96.573898 99.61106
-k1         0.062499  0.030336  0.09466
-k2         0.009065 -0.005133  0.02326
-g          0.948967  0.862079  1.03586
-a.1        1.821671  1.604774  2.03857
-SD.DMTA_0  1.677785  0.472066  2.88350
-SD.k1      0.634962  0.270788  0.99914
-SD.k2      1.033498 -0.205994  2.27299
-SD.g       1.710046  0.428642  2.99145
-
-Correlation: 
-   DMTA_0  k1      k2     
-k1  0.0246                
-k2  0.0491  0.0953        
-g  -0.0552 -0.0889 -0.4795
-
-Random effects:
-           est.   lower  upper
-SD.DMTA_0 1.678  0.4721 2.8835
-SD.k1     0.635  0.2708 0.9991
-SD.k2     1.033 -0.2060 2.2730
-SD.g      1.710  0.4286 2.9914
-
-Variance model:
-     est. lower upper
-a.1 1.822 1.605 2.039
-
-Estimated disappearance times:
-      DT50 DT90 DT50back DT50_k1 DT50_k2
-DMTA 11.79 42.8    12.88   11.09   76.46
-
-
    
-
    
-
-Hierarchical mkin fit of the DFOP model with error model tc
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Sat Jan 28 11:22:46 2023 
-Date of summary: Sat Jan 28 11:23:57 2023 
-
-Equations:
-d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-           time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-           * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 3.288 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-   DMTA_0        k1        k2         g 
-98.759266  0.087034  0.009933  0.930827 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 k1 k2 g
-DMTA_0  98.76  0  0 0
-k1       0.00  1  0 0
-k2       0.00  0  1 0
-g        0.00  0  0 1
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC   BIC logLik
-  665.5 663.4 -322.8
-
-Optimised parameters:
-               est.     lower     upper
-DMTA_0    98.377019 96.447952 100.30609
-k1         0.064843  0.034607   0.09508
-k2         0.008895  0.006368   0.01142
-g          0.949696  0.903815   0.99558
-a.1        1.065241  0.865754   1.26473
-b.1        0.029340  0.022336   0.03634
-SD.DMTA_0  2.007754  0.387982   3.62753
-SD.k1      0.580473  0.250286   0.91066
-SD.k2      0.006105 -4.920337   4.93255
-SD.g       1.097149  0.412779   1.78152
-
-Correlation: 
-   DMTA_0  k1      k2     
-k1  0.0235                
-k2  0.0595  0.0424        
-g  -0.0470 -0.0278 -0.2731
-
-Random effects:
-              est.   lower  upper
-SD.DMTA_0 2.007754  0.3880 3.6275
-SD.k1     0.580473  0.2503 0.9107
-SD.k2     0.006105 -4.9203 4.9325
-SD.g      1.097149  0.4128 1.7815
-
-Variance model:
-       est.   lower   upper
-a.1 1.06524 0.86575 1.26473
-b.1 0.02934 0.02234 0.03634
-
-Estimated disappearance times:
-      DT50  DT90 DT50back DT50_k1 DT50_k2
-DMTA 11.36 41.32    12.44   10.69   77.92
-
-
    
-
    
-
-Hierarchical mkin fit of the HS model with error model const
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Sat Jan 28 11:22:45 2023 
-Date of summary: Sat Jan 28 11:23:57 2023 
-
-Equations:
-d_DMTA/dt = - ifelse(time <= tb, k1, k2) * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 2.006 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Constant variance 
-
-Starting values for degradation parameters:
-  DMTA_0       k1       k2       tb 
-97.82176  0.06931  0.02997 11.13945 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 k1 k2 tb
-DMTA_0  97.82  0  0  0
-k1       0.00  1  0  0
-k2       0.00  0  1  0
-tb       0.00  0  0  1
-
-Starting values for error model parameters:
-a.1 
-  1 
-
-Results:
-
-Likelihood computed by importance sampling
-  AIC   BIC logLik
-  714 712.1   -348
-
-Optimised parameters:
-              est.    lower    upper
-DMTA_0    98.16102 96.47747 99.84456
-k1         0.07876  0.05261  0.10491
-k2         0.02227  0.01706  0.02747
-tb        13.99089 -7.40049 35.38228
-a.1        1.82305  1.60700  2.03910
-SD.DMTA_0  1.88413  0.56204  3.20622
-SD.k1      0.34292  0.10482  0.58102
-SD.k2      0.19851  0.01718  0.37985
-SD.tb      1.68168  0.58064  2.78272
-
-Correlation: 
-   DMTA_0  k1      k2     
-k1  0.0142                
-k2  0.0001 -0.0025        
-tb  0.0165 -0.1256 -0.0301
-
-Random effects:
-            est.   lower  upper
-SD.DMTA_0 1.8841 0.56204 3.2062
-SD.k1     0.3429 0.10482 0.5810
-SD.k2     0.1985 0.01718 0.3798
-SD.tb     1.6817 0.58064 2.7827
-
-Variance model:
-     est. lower upper
-a.1 1.823 1.607 2.039
-
-Estimated disappearance times:
-      DT50  DT90 DT50back DT50_k1 DT50_k2
-DMTA 8.801 67.91    20.44   8.801   31.13
-
-
    
-
    
-
-Hierarchical mkin fit of the HS model with error model tc
-
-
    
-saemix version used for fitting:      3.2 
-mkin version used for pre-fitting:  1.2.2 
-R version used for fitting:         4.2.2 
-Date of fit:     Sat Jan 28 11:22:46 2023 
-Date of summary: Sat Jan 28 11:23:57 2023 
-
-Equations:
-d_DMTA/dt = - ifelse(time <= tb, k1, k2) * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Model predictions using solution type analytical 
-
-Fitted in 3.267 s
-Using 300, 100 iterations and 9 chains
-
-Variance model: Two-component variance function 
-
-Starting values for degradation parameters:
-  DMTA_0       k1       k2       tb 
-98.45190  0.07525  0.02576 19.19375 
-
-Fixed degradation parameter values:
-None
-
-Starting values for random effects (square root of initial entries in omega):
-       DMTA_0 k1 k2 tb
-DMTA_0  98.45  0  0  0
-k1       0.00  1  0  0
-k2       0.00  0  1  0
-tb       0.00  0  0  1
-
-Starting values for error model parameters:
-a.1 b.1 
-  1   1 
-
-Results:
-
-Likelihood computed by importance sampling
-    AIC BIC logLik
-  667.1 665 -323.6
-
-Optimised parameters:
-              est.    lower    upper
-DMTA_0    97.76570 95.81350 99.71791
-k1         0.05855  0.03080  0.08630
-k2         0.02337  0.01664  0.03010
-tb        31.09638 29.38289 32.80987
-a.1        1.08835  0.88590  1.29080
-b.1        0.02964  0.02257  0.03671
-SD.DMTA_0  2.04877  0.42607  3.67147
-SD.k1      0.59166  0.25621  0.92711
-SD.k2      0.30698  0.09561  0.51835
-SD.tb      0.01274 -0.10914  0.13462
-
-Correlation: 
-   DMTA_0  k1      k2     
-k1  0.0160                
-k2 -0.0070 -0.0024        
-tb -0.0668 -0.0103 -0.2013
-
-Random effects:
-             est.    lower  upper
-SD.DMTA_0 2.04877  0.42607 3.6715
-SD.k1     0.59166  0.25621 0.9271
-SD.k2     0.30698  0.09561 0.5183
-SD.tb     0.01274 -0.10914 0.1346
-
-Variance model:
-       est.   lower   upper
-a.1 1.08835 0.88590 1.29080
-b.1 0.02964 0.02257 0.03671
-
-Estimated disappearance times:
-      DT50  DT90 DT50back DT50_k1 DT50_k2
-DMTA 11.84 51.71    15.57   11.84   29.66
-
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    Hierarchical model convergence plots
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-Convergence plot for the NLHM SFO fit with constant variance
    
-Convergence plot for the NLHM SFO fit with constant variance
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-Convergence plot for the NLHM SFO fit with two-component error
    
-Convergence plot for the NLHM SFO fit with two-component error
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-Convergence plot for the NLHM FOMC fit with constant variance
    
-Convergence plot for the NLHM FOMC fit with constant variance
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-Convergence plot for the NLHM FOMC fit with two-component error
    
-Convergence plot for the NLHM FOMC fit with two-component error
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-Convergence plot for the NLHM DFOP fit with constant variance
    
-Convergence plot for the NLHM DFOP fit with constant variance
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-Convergence plot for the NLHM DFOP fit with two-component error
    
-Convergence plot for the NLHM DFOP fit with two-component error
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-Convergence plot for the NLHM HS fit with constant variance
    
-Convergence plot for the NLHM HS fit with constant variance
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-Convergence plot for the NLHM HS fit with two-component error
    
-Convergence plot for the NLHM HS fit with two-component error
-
    
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    Session info
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-
    R version 4.2.2 Patched (2022-11-10 r83330)
-Platform: x86_64-pc-linux-gnu (64-bit)
-Running under: Debian GNU/Linux bookworm/sid
-
-Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/openblas-serial/libblas.so.3
-LAPACK: /usr/lib/x86_64-linux-gnu/openblas-serial/libopenblas-r0.3.21.so
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-locale:
- [1] LC_CTYPE=de_DE.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=de_DE.UTF-8        LC_COLLATE=de_DE.UTF-8    
- [5] LC_MONETARY=de_DE.UTF-8    LC_MESSAGES=de_DE.UTF-8   
- [7] LC_PAPER=de_DE.UTF-8       LC_NAME=C                 
- [9] LC_ADDRESS=C               LC_TELEPHONE=C            
-[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C       
-
-attached base packages:
-[1] parallel  stats     graphics  grDevices utils     datasets  methods  
-[8] base     
-
-other attached packages:
-[1] saemix_3.2 npde_3.3   knitr_1.41 mkin_1.2.2
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-loaded via a namespace (and not attached):
- [1] deSolve_1.34      zoo_1.8-11        tidyselect_1.2.0  xfun_0.35        
- [5] bslib_0.4.2       purrr_1.0.0       lattice_0.20-45   colorspace_2.0-3 
- [9] vctrs_0.5.1       generics_0.1.3    htmltools_0.5.4   yaml_2.3.6       
-[13] utf8_1.2.2        rlang_1.0.6       pkgdown_2.0.7     jquerylib_0.1.4  
-[17] pillar_1.8.1      glue_1.6.2        DBI_1.1.3         lifecycle_1.0.3  
-[21] stringr_1.5.0     munsell_0.5.0     gtable_0.3.1      ragg_1.2.4       
-[25] codetools_0.2-18  memoise_2.0.1     evaluate_0.19     fastmap_1.1.0    
-[29] lmtest_0.9-40     fansi_1.0.3       highr_0.9         scales_1.2.1     
-[33] cachem_1.0.6      desc_1.4.2        jsonlite_1.8.4    systemfonts_1.0.4
-[37] fs_1.5.2          textshaping_0.3.6 gridExtra_2.3     ggplot2_3.4.0    
-[41] digest_0.6.31     stringi_1.7.8     dplyr_1.0.10      grid_4.2.2       
-[45] rprojroot_2.0.3   cli_3.5.0         tools_4.2.2       magrittr_2.0.3   
-[49] sass_0.4.4        tibble_3.1.8      pkgconfig_2.0.3   assertthat_0.2.1 
-[53] rmarkdown_2.19    R6_2.5.1          mclust_6.0.0      nlme_3.1-161     
-[57] compiler_4.2.2   
    
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    Hardware info
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    CPU model: AMD Ryzen 9 7950X 16-Core Processor
    
-
    MemTotal:       64940452 kB
    
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    Developed by Johannes Ranke.
    
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-Testing hierarchical pathway kinetics with residue data on dimethenamid and dimethenamid-P • mkin
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    Testing hierarchical pathway kinetics with
-residue data on dimethenamid and dimethenamid-P
    
-                        
    Johannes
-Ranke
    
-            
-            
    Last change on 20 April 2023,
-last compiled on 20 April 2023
    
-      
-      Source: vignettes/prebuilt/2022_dmta_pathway.rmd
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    Introduction
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    The purpose of this document is to test demonstrate how nonlinear
-hierarchical models (NLHM) based on the parent degradation models SFO,
-FOMC, DFOP and HS, with parallel formation of two or more metabolites
-can be fitted with the mkin package.
    
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    It was assembled in the course of work package 1.2 of Project Number
-173340 (Application of nonlinear hierarchical models to the kinetic
-evaluation of chemical degradation data) of the German Environment
-Agency carried out in 2022 and 2023.
    
-
    The mkin package is used in version 1.2.4, which is currently under
-development. It contains the test data, and the functions used in the
-evaluations. The saemix package is used as a backend for
-fitting the NLHM, but is also loaded to make the convergence plot
-function available.
    
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    This document is processed with the knitr package, which
-also provides the kable function that is used to improve
-the display of tabular data in R markdown documents. For parallel
-processing, the parallel package is used.
    
-
    -library(mkin)
-library(knitr)
-library(saemix)
-library(parallel)
-n_cores <- detectCores()
-
-# We need to start a new cluster after defining a compiled model that is
-# saved as a DLL to the user directory, therefore we define a function
-# This is used again after defining the pathway model
-start_cluster <- function(n_cores) {
-  if (Sys.info()["sysname"] == "Windows") {
-    ret <- makePSOCKcluster(n_cores)
-  } else {
-    ret <- makeForkCluster(n_cores)
-  }
-  return(ret)
-}
    
-
    
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    Data
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-
    The test data are available in the mkin package as an object of class
-mkindsg (mkin dataset group) under the identifier
-dimethenamid_2018. The following preprocessing steps are
-done in this document.
    
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    • The data available for the enantiomer dimethenamid-P (DMTAP) are
-renamed to have the same substance name as the data for the racemic
-mixture dimethenamid (DMTA). The reason for this is that no difference
-between their degradation behaviour was identified in the EU risk
-assessment.
      • 
-
    • Unnecessary columns are discarded
      • 
-
    • The observation times of each dataset are multiplied with the
-corresponding normalisation factor also available in the dataset, in
-order to make it possible to describe all datasets with a single set of
-parameters that are independent of temperature
      • 
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    • Finally, datasets observed in the same soil (Elliot 1
-and Elliot 2) are combined, resulting in dimethenamid
-(DMTA) data from six soils.
      • 
-
    
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    The following commented R code performs this preprocessing.
    
-
    -# Apply a function to each of the seven datasets in the mkindsg object to create a list
-dmta_ds <- lapply(1:7, function(i) {
-  ds_i <- dimethenamid_2018$ds[[i]]$data                     # Get a dataset
-  ds_i[ds_i$name == "DMTAP", "name"] <-  "DMTA"              # Rename DMTAP to DMTA
-  ds_i <- subset(ds_i, select = c("name", "time", "value")) # Select data
-  ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i]  # Normalise time
-  ds_i                                                       # Return the dataset
-})
-
-# Use dataset titles as names for the list elements
-names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title)
-
-# Combine data for Elliot soil to obtain a named list with six elements
-dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]]) #
-dmta_ds[["Elliot 1"]] <- NULL
-dmta_ds[["Elliot 2"]] <- NULL
    
-
    The following tables show the 6 datasets.
    
-
    -for (ds_name in names(dmta_ds)) {
-  print(
-    kable(mkin_long_to_wide(dmta_ds[[ds_name]]),
-      caption = paste("Dataset", ds_name),
-      booktabs = TRUE, row.names = FALSE))
-    cat("\n\\clearpage\n")
-}
    
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    Dataset Calke
    timeDMTAM23M27M31
    095.8NANANA
    098.7NANANA
    1460.54.11.52.0
    3039.15.32.42.1
    5915.26.03.22.2
    1204.84.33.81.8
    1204.64.13.72.1
    
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    Dataset Borstel
    timeDMTAM23M27M31
    0.000000100.5NANANA
    0.00000099.6NANANA
    1.94129591.90.4NANA
    1.94129591.30.50.30.1
    6.79453481.81.20.81.0
    6.79453482.11.30.90.9
    13.58906769.12.81.42.0
    13.58906768.02.01.42.5
    27.17813551.42.92.74.3
    27.17813551.44.92.63.2
    56.29756527.612.24.44.3
    56.29756526.812.24.74.8
    86.38764315.712.25.45.0
    86.38764315.312.05.25.1
    115.5070737.910.45.44.3
    115.5070738.111.65.44.4
    
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    timeDMTAM23M27M31
    0.000000096.5NANANA
    0.000000096.8NANANA
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    0.623385682.90.71.10.3
    0.623385686.70.71.10.3
    0.623385687.40.20.30.1
    1.870156772.82.22.60.7
    1.870156769.91.82.40.6
    1.870156771.91.62.30.7
    4.363698951.44.15.01.3
    4.363698952.94.25.91.2
    4.363698948.64.24.81.4
    8.727397928.57.58.52.4
    8.727397927.37.18.52.1
    8.727397927.57.58.32.3
    13.091096814.88.49.33.3
    13.091096813.46.88.72.4
    13.091096814.48.09.12.6
    17.45479577.77.28.64.0
    17.45479577.37.28.53.6
    17.45479578.16.98.93.3
    26.18219362.04.98.12.1
    26.18219361.54.37.71.7
    26.18219361.94.57.41.8
    34.90959151.33.85.91.6
    34.90959151.03.16.01.6
    34.90959151.13.15.91.4
    43.63698930.92.75.61.8
    43.63698930.72.35.21.5
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    74.80626740.40.42.50.5
    74.80626740.30.42.40.5
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-
-
    Dataset BBA 2.2
    timeDMTAM23M27M31
    0.000000098.09NANANA
    0.000000098.77NANANA
    0.767892293.520.360.420.36
    0.767892292.030.400.470.33
    2.303676588.391.030.710.55
    2.303676587.181.070.820.64
    5.375245269.383.602.191.94
    5.375245271.063.662.281.62
    10.750490445.216.975.454.22
    10.750490446.817.225.194.37
    16.125735530.548.658.816.31
    16.125735530.078.387.936.85
    21.500980721.609.1010.257.05
    21.500980720.418.6310.776.84
    32.25147119.107.6310.896.53
    32.25147119.708.0110.857.11
    43.00196146.586.4010.416.06
    43.00196146.316.3510.356.05
    53.75245183.475.359.925.50
    53.75245183.525.069.425.07
    64.50294213.405.149.154.94
    64.50294213.675.919.254.39
    91.37916801.623.357.143.64
    91.37916801.622.877.133.55
    
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-
    Dataset BBA 2.3
    timeDMTAM23M27M31
    0.000000099.33NANANA
    0.000000097.44NANANA
    0.673393893.730.180.500.47
    0.673393893.770.180.830.34
    2.020181487.840.521.251.00
    2.020181489.820.431.090.89
    4.713756571.611.193.283.58
    4.713756571.421.113.243.41
    9.427513145.602.267.178.74
    9.427513145.421.997.918.28
    14.141269631.122.8110.159.67
    14.141269631.682.839.558.95
    18.855026223.203.3912.0910.34
    18.855026224.133.5611.8910.00
    28.28253939.433.4913.327.89
    28.28253939.823.2812.058.13
    37.71005237.082.8010.045.06
    37.71005238.642.9710.785.54
    47.13756544.412.429.323.79
    47.13756544.782.519.624.11
    56.56507854.922.228.003.11
    56.56507855.081.958.452.98
    80.13386122.131.285.711.78
    80.13386122.230.993.331.55
    
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-
    Dataset Elliot
    timeDMTAM23M27M31
    0.00000097.5NANANA
    0.000000100.7NANANA
    1.22847886.4NANANA
    1.22847888.5NANA1.5
    3.68543569.82.82.35.0
    3.68543577.11.72.12.4
    8.59934959.04.34.04.3
    8.59934954.25.83.45.0
    17.19869731.38.26.68.0
    17.19869733.55.26.97.7
    25.79804619.65.18.27.8
    25.79804620.96.18.86.5
    34.39739513.36.09.78.0
    34.39739515.86.08.87.4
    51.5960926.75.08.36.9
    51.5960928.74.29.29.0
    68.7947898.83.99.35.5
    68.7947898.72.98.56.1
    103.1921846.01.98.66.1
    103.1921844.41.56.04.0
    146.1889283.32.05.63.1
    146.1889282.82.34.52.9
    223.5830661.41.24.11.8
    223.5830661.81.93.92.6
    0.00000093.4NANANA
    0.000000103.2NANANA
    1.22847889.2NANA1.3
    1.22847886.6NANANA
    3.68543578.22.61.03.1
    3.68543578.12.42.62.3
    8.59934955.65.54.53.4
    8.59934953.05.64.64.3
    17.19869733.77.37.67.8
    17.19869733.26.56.78.7
    25.79804620.95.88.77.7
    25.79804619.97.77.66.5
    34.39739518.27.88.06.3
    34.39739512.77.38.68.7
    51.5960927.87.07.45.7
    51.5960929.06.37.24.2
    68.79478911.44.310.33.2
    68.7947899.03.89.44.2
    103.1921843.92.66.53.8
    103.1921844.42.86.94.0
    146.1889282.61.64.64.5
    146.1889283.41.14.54.5
    223.5830662.01.44.33.8
    223.5830661.71.34.22.3
    
-
    
-
    
-
    Separate evaluations
-
    
-
    As a first step to obtain suitable starting parameters for the NLHM
-fits, we do separate fits of several variants of the pathway model used
-previously (Ranke et al. 2021), varying
-the kinetic model for the parent compound. Because the SFORB model often
-provides faster convergence than the DFOP model, and can sometimes be
-fitted where the DFOP model results in errors, it is included in the set
-of parent models tested here.
    
-
    -if (!dir.exists("dmta_dlls")) dir.create("dmta_dlls")
-m_sfo_path_1 <- mkinmod(
-  DMTA = mkinsub("SFO", c("M23", "M27", "M31")),
-  M23 = mkinsub("SFO"),
-  M27 = mkinsub("SFO"),
-  M31 = mkinsub("SFO", "M27", sink = FALSE),
-  name = "m_sfo_path", dll_dir = "dmta_dlls",
-  unload = TRUE, overwrite = TRUE,
-  quiet = TRUE
-)
-m_fomc_path_1 <- mkinmod(
-  DMTA = mkinsub("FOMC", c("M23", "M27", "M31")),
-  M23 = mkinsub("SFO"),
-  M27 = mkinsub("SFO"),
-  M31 = mkinsub("SFO", "M27", sink = FALSE),
-  name = "m_fomc_path", dll_dir = "dmta_dlls",
-  unload = TRUE, overwrite = TRUE,
-  quiet = TRUE
-)
-m_dfop_path_1 <- mkinmod(
-  DMTA = mkinsub("DFOP", c("M23", "M27", "M31")),
-  M23 = mkinsub("SFO"),
-  M27 = mkinsub("SFO"),
-  M31 = mkinsub("SFO", "M27", sink = FALSE),
-  name = "m_dfop_path", dll_dir = "dmta_dlls",
-  unload = TRUE, overwrite = TRUE,
-  quiet = TRUE
-)
-m_sforb_path_1 <- mkinmod(
-  DMTA = mkinsub("SFORB", c("M23", "M27", "M31")),
-  M23 = mkinsub("SFO"),
-  M27 = mkinsub("SFO"),
-  M31 = mkinsub("SFO", "M27", sink = FALSE),
-  name = "m_sforb_path", dll_dir = "dmta_dlls",
-  unload = TRUE, overwrite = TRUE,
-  quiet = TRUE
-)
-m_hs_path_1 <- mkinmod(
-  DMTA = mkinsub("HS", c("M23", "M27", "M31")),
-  M23 = mkinsub("SFO"),
-  M27 = mkinsub("SFO"),
-  M31 = mkinsub("SFO", "M27", sink = FALSE),
-  name = "m_hs_path", dll_dir = "dmta_dlls",
-  unload = TRUE, overwrite = TRUE,
-  quiet = TRUE
-)
-cl <- start_cluster(n_cores)
-
-deg_mods_1 <- list(
-  sfo_path_1 = m_sfo_path_1,
-  fomc_path_1 = m_fomc_path_1,
-  dfop_path_1 = m_dfop_path_1,
-  sforb_path_1 = m_sforb_path_1,
-  hs_path_1 = m_hs_path_1)
-
-sep_1_const <- mmkin(
-  deg_mods_1,
-  dmta_ds,
-  error_model = "const",
-  quiet = TRUE)
-
-status(sep_1_const) |> kable()
    
-
-
-
-
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-
    CalkeBorstelFlaachBBA 2.2BBA 2.3Elliot
    sfo_path_1OKOKOKOKOKOK
    fomc_path_1OKOKOKOKOKOK
    dfop_path_1OKOKCOKOKOK
    sforb_path_1OKOKCOKOKOK
    hs_path_1CCCCCC
    
-
    All separate pathway fits with SFO or FOMC for the parent and
-constant variance converged (status OK). Most fits with DFOP or SFORB
-for the parent converged as well. The fits with HS for the parent did
-not converge with default settings.
    
-
    -sep_1_tc <- update(sep_1_const, error_model = "tc")
-status(sep_1_tc) |> kable()
    
-
-
-
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-
-
-
    CalkeBorstelFlaachBBA 2.2BBA 2.3Elliot
    sfo_path_1OKOKOKOKOKOK
    fomc_path_1OKOKCOKOKC
    dfop_path_1OKCOKOKOKOK
    sforb_path_1OKCOKOKOKOK
    hs_path_1CCCCCOK
    
-
    With the two-component error model, the set of fits with convergence
-problems is slightly different, with convergence problems appearing for
-different data sets when applying the DFOP and SFORB model and some
-additional convergence problems when using the FOMC model for the
-parent.
    
-
    
-
    
-
    Hierarchichal model fits
-
    
-
    The following code fits two sets of the corresponding hierarchical
-models to the data, one assuming constant variance, and one assuming
-two-component error.
    
-
    -saem_1 <- mhmkin(list(sep_1_const, sep_1_tc))
    
-
    The run time for these fits was around two hours on five year old
-hardware. After a recent hardware upgrade these fits complete in less
-than twenty minutes.
    
-
    -status(saem_1) |> kable()
    
-
-
-
-
-
-
-
-
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-
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-
-
    consttc
    sfo_path_1OKOK
    fomc_path_1OKOK
    dfop_path_1OKOK
    sforb_path_1OKOK
    hs_path_1OKOK
    
-
    According to the status function, all fits terminated
-successfully.
    
-
    -anova(saem_1) |> kable(digits = 1)
    
-
    Warning in FUN(X[[i]], ...): Could not obtain log likelihood with 'is' method
-for sforb_path_1 const
    
-
-
-
-
-
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-
    nparAICBICLik
    sfo_path_1 const172291.82288.3-1128.9
    sfo_path_1 tc182276.32272.5-1120.1
    fomc_path_1 const192099.02095.0-1030.5
    fomc_path_1 tc201939.61935.5-949.8
    dfop_path_1 const212038.82034.4-998.4
    hs_path_1 const212024.22019.8-991.1
    dfop_path_1 tc221879.81875.2-917.9
    sforb_path_1 tc221832.91828.3-894.4
    hs_path_1 tc221831.41826.8-893.7
    
-
    When the goodness-of-fit of the models is compared, a warning is
-obtained, indicating that the likelihood of the pathway fit with SFORB
-for the parent compound and constant variance could not be calculated
-with importance sampling (method ‘is’). As this is the default method on
-which all AIC and BIC comparisons are based, this variant is not
-included in the model comparison table. Comparing the goodness-of-fit of
-the remaining models, HS model model with two-component error provides
-the best fit. However, for batch experiments performed with constant
-conditions such as the experiments evaluated here, there is no reason to
-assume a discontinuity, so the SFORB model is preferable from a
-mechanistic viewpoint. In addition, the information criteria AIC and BIC
-are very similar for HS and SFORB. Therefore, the SFORB model is
-selected here for further refinements.
    
-
    
-
    Parameter identifiability based on the Fisher Information
-Matrix
-
    
-
    Using the illparms function, ill-defined statistical
-model parameters such as standard deviations of the degradation
-parameters in the population and error model parameters can be
-found.
    
-
    -illparms(saem_1) |> kable()
    
-
-
-
-
-
-
-
-
-
-
-
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-
-
-
-
-
-
-
-
    consttc
    sfo_path_1sd(DMTA_0)
    fomc_path_1sd(DMTA_0)
    dfop_path_1
    sforb_path_1sd(log_k_DMTA_bound_free)
    hs_path_1sd(log_tb)
    
-
    When using constant variance, no ill-defined variance parameters are
-identified with the illparms function in any of the
-degradation models. When using the two-component error model, there is
-one ill-defined variance parameter in all variants except for the
-variant using DFOP for the parent compound.
    
-
    For the selected combination of the SFORB pathway model with
-two-component error, the random effect for the rate constant from
-reversibly bound DMTA to the free DMTA (k_DMTA_bound_free)
-is not well-defined. Therefore, the fit is updated without assuming a
-random effect for this parameter.
    
-
    -saem_sforb_path_1_tc_reduced <- update(saem_1[["sforb_path_1", "tc"]],
-  no_random_effect = "log_k_DMTA_bound_free")
-illparms(saem_sforb_path_1_tc_reduced)
    
-
    As expected, no ill-defined parameters remain. The model comparison
-below shows that the reduced model is preferable.
    
-
    -anova(saem_1[["sforb_path_1", "tc"]], saem_sforb_path_1_tc_reduced) |> kable(digits = 1)
    
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
    nparAICBICLik
    saem_sforb_path_1_tc_reduced211830.31825.9-894.2
    saem_1[[“sforb_path_1”, “tc”]]221832.91828.3-894.4
    
-
    The convergence plot of the refined fit is shown below.
    
-
    -plot(saem_sforb_path_1_tc_reduced$so, plot.type = "convergence")
    
-
    
-
    For some parameters, for example for f_DMTA_ilr_1 and
-f_DMTA_ilr_2, i.e. for two of the parameters determining
-the formation fractions of the parallel formation of the three
-metabolites, some movement of the parameters is still visible in the
-second phase of the algorithm. However, the amplitude of this movement
-is in the range of the amplitude towards the end of the first phase.
-Therefore, it is likely that an increase in iterations would not improve
-the parameter estimates very much, and it is proposed that the fit is
-acceptable. No numeric convergence criterion is implemented in
-saemix.
    
-
    
-
    
-
    Alternative check of parameter identifiability
-
    
-
    As an alternative check of parameter identifiability (Duchesne et al. 2021), multistart runs were
-performed on the basis of the refined fit shown above.
    
-
    -saem_sforb_path_1_tc_reduced_multi <- multistart(saem_sforb_path_1_tc_reduced,
-  n = 32, cores = 10)
    
-
    -print(saem_sforb_path_1_tc_reduced_multi)
    
-
    <multistart> object with 32 fits:
- E OK 
-15 17 
-OK: Fit terminated successfully
-E: Error
    
-
    Out of the 32 fits that were initiated, only 17 terminated without an
-error. The reason for this is that the wide variation of starting
-parameters in combination with the parameter variation that is used in
-the SAEM algorithm leads to parameter combinations for the degradation
-model that the numerical integration routine cannot cope with. Because
-of this variation of initial parameters, some of the model fits take up
-to two times more time than the original fit.
    
-
    -par(mar = c(12.1, 4.1, 2.1, 2.1))
-parplot(saem_sforb_path_1_tc_reduced_multi, ylim = c(0.5, 2), las = 2)
    
-
    
-Parameter boxplots for the multistart runs that succeeded
    
-Parameter boxplots for the multistart runs that succeeded
-
    
-
    
-
    However, visual analysis of the boxplot of the parameters obtained in
-the successful fits confirms that the results are sufficiently
-independent of the starting parameters, and there are no remaining
-ill-defined parameters.
    
-
    
-
    
-
    
-
    Plots of selected fits
-
    
-
    The SFORB pathway fits with full and reduced parameter distribution
-model are shown below.
    
-
    -plot(saem_1[["sforb_path_1", "tc"]])
    
-
    
-SFORB pathway fit with two-component error
    
-SFORB pathway fit with two-component error
-
    
-
    
-
    -plot(saem_sforb_path_1_tc_reduced)
    
-
    
-SFORB pathway fit with two-component error, reduced parameter model
    
-SFORB pathway fit with two-component error, reduced parameter model
-
    
-
    
-
    Plots of the remaining fits and listings for all successful fits are
-shown in the Appendix.
    
-
-
    
-
    
-
    Conclusions
-
    
-
    Pathway fits with SFO, FOMC, DFOP, SFORB and HS models for the parent
-compound could be successfully performed.
    
-
    
-
    
-
    Acknowledgements
-
    
-
    The helpful comments by Janina Wöltjen of the German Environment
-Agency on earlier versions of this document are gratefully
-acknowledged.
    
-
    
-
    
-
    References
-
    
-
    
-
    
-Duchesne, Ronan, Anissa Guillemin, Olivier Gandrillon, and Fabien
-Crauste. 2021. “Practical Identifiability in the Frame of
-Nonlinear Mixed Effects Models: The Example of the in Vitro
-Erythropoiesis.” BMC Bioinformatics 22 (478). https://doi.org/10.1186/s12859-021-04373-4.
-
    
-
    
-Ranke, Johannes, Janina Wöltjen, Jana Schmidt, and Emmanuelle Comets.
-2021. “Taking Kinetic Evaluations of Degradation Data to the Next
-Level with Nonlinear Mixed-Effects Models.” Environments
-8 (8). https://doi.org/10.3390/environments8080071.
-
    
-
    
-
    
-
    
-
    Appendix
-
    
-
    
-
    Plots of hierarchical fits not selected for refinement
-
    
-
    -plot(saem_1[["sfo_path_1", "tc"]])
    
-
    
-SFO pathway fit with two-component error
    
-SFO pathway fit with two-component error
-
    
-
    
-
    -plot(saem_1[["fomc_path_1", "tc"]])
    
-
    
-FOMC pathway fit with two-component error
    
-FOMC pathway fit with two-component error
-
    
-
    
-
    -plot(saem_1[["sforb_path_1", "tc"]])
    
-
    
-HS pathway fit with two-component error
    
-HS pathway fit with two-component error
-
    
-
    
-
    
-
    
-
    Hierarchical model fit listings
-
    
-
    
-
    Fits with random effects for all degradation parameters
-
    
-
-
    
-
    
-
    Improved fit of the SFORB pathway model with two-component
-error
-
    
-
-
    
-
    
-
    
-
    Session info
-
    
-
    R version 4.2.3 (2023-03-15)
-Platform: x86_64-pc-linux-gnu (64-bit)
-Running under: Debian GNU/Linux 12 (bookworm)
-
-Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/openblas-serial/libblas.so.3
-LAPACK: /usr/lib/x86_64-linux-gnu/openblas-serial/libopenblas-r0.3.21.so
-
-locale:
- [1] LC_CTYPE=de_DE.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=de_DE.UTF-8        LC_COLLATE=de_DE.UTF-8    
- [5] LC_MONETARY=de_DE.UTF-8    LC_MESSAGES=de_DE.UTF-8   
- [7] LC_PAPER=de_DE.UTF-8       LC_NAME=C                 
- [9] LC_ADDRESS=C               LC_TELEPHONE=C            
-[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C       
-
-attached base packages:
-[1] parallel  stats     graphics  grDevices utils     datasets  methods  
-[8] base     
-
-other attached packages:
-[1] saemix_3.2 npde_3.3   knitr_1.42 mkin_1.2.4
-
-loaded via a namespace (and not attached):
- [1] deSolve_1.35      zoo_1.8-12        tidyselect_1.2.0  xfun_0.38        
- [5] bslib_0.4.2       purrr_1.0.1       lattice_0.21-8    colorspace_2.1-0 
- [9] vctrs_0.6.1       generics_0.1.3    htmltools_0.5.5   yaml_2.3.7       
-[13] utf8_1.2.3        rlang_1.1.0       pkgbuild_1.4.0    pkgdown_2.0.7    
-[17] jquerylib_0.1.4   pillar_1.9.0      glue_1.6.2        DBI_1.1.3        
-[21] lifecycle_1.0.3   stringr_1.5.0     munsell_0.5.0     gtable_0.3.3     
-[25] ragg_1.2.5        codetools_0.2-19  memoise_2.0.1     evaluate_0.20    
-[29] inline_0.3.19     callr_3.7.3       fastmap_1.1.1     ps_1.7.4         
-[33] lmtest_0.9-40     fansi_1.0.4       highr_0.10        scales_1.2.1     
-[37] cachem_1.0.7      desc_1.4.2        jsonlite_1.8.4    systemfonts_1.0.4
-[41] fs_1.6.1          textshaping_0.3.6 gridExtra_2.3     ggplot2_3.4.2    
-[45] digest_0.6.31     stringi_1.7.12    processx_3.8.0    dplyr_1.1.1      
-[49] grid_4.2.3        rprojroot_2.0.3   cli_3.6.1         tools_4.2.3      
-[53] magrittr_2.0.3    sass_0.4.5        tibble_3.2.1      crayon_1.5.2     
-[57] pkgconfig_2.0.3   prettyunits_1.1.1 rmarkdown_2.21    R6_2.5.1         
-[61] mclust_6.0.0      nlme_3.1-162      compiler_4.2.3   
    
-
    
-
    
-
    Hardware info
-
    
-
    CPU model: AMD Ryzen 9 7950X 16-Core Processor
    
-
    MemTotal:       64936316 kB
    
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-
-
-
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-
-
-
-Calculation of time weighted average concentrations with mkin • mkin
-
-
-
-
-
-
-
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-    
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-      
    
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-  
    
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-      
    Calculation of time weighted average
-concentrations with mkin
    
-                        
    Johannes
-Ranke
    
-            
-            
    Last change 18 September 2019
-(rebuilt 2023-04-16)
    
-      
-      Source: vignettes/twa.rmd
-      
-
-    
    
-
-    
-    
-
    Since version 0.9.45.1 of the ‘mkin’ package, a function for
-calculating time weighted average concentrations for decline kinetics
-(i.e. only for the compound applied in the experiment) is
-included. Strictly speaking, they are maximum moving window time
-weighted average concentrations, i.e. the maximum time weighted
-average concentration that can be found when moving a time window of a
-specified width over the decline curve.
    
-
    Time weighted average concentrations for the SFO, FOMC and the DFOP
-model are calculated using the formulas given in the FOCUS kinetics
-guidance (FOCUS Work Group on Degradation
-Kinetics 2014, 251):
    
-
    SFO:
    
-
    \[c_\textrm{twa} = c_0 \frac{\left( 1 -
-e^{- k t} \right)}{ k t} \]
    
-
    FOMC:
    
-
    \[c_\textrm{twa} = c_0 \frac{\beta}{t (1 -
-\alpha)}
-                   \left( \left(\frac{t}{\beta} + 1 \right)^{1 - \alpha}
-- 1 \right) \]
    
-
    DFOP:
    
-
    \[c_\textrm{twa} = \frac{c_0}{t} \left(
-  \frac{g}{k_1} \left( 1 - e^{- k_1 t} \right) +
-  \frac{1-g}{k_2} \left( 1 - e^{- k_2 t} \right)  \right) \]
    
-
    HS for \(t > t_b\):
    
-
    \[c_\textrm{twa} = \frac{c_0}{t} \left(
-  \frac{1}{k_1} \left( 1 - e^{- k_1 t_b} \right) +
-  \frac{e^{- k_1 t_b}}{k_2} \left( 1 - e^{- k_2 (t - t_b)}
-\right)  \right) \]
    
-
    Often, the ratio between the time weighted average concentration
-\(c_\textrm{twa}\) and the initial
-concentration \(c_0\)
    
-
    \[f_\textrm{twa} =
-\frac{c_\textrm{twa}}{c_0}\]
    
-
    is needed. This can be calculated from the fitted initial
-concentration \(c_0\) and the time
-weighted average concentration \(c_\textrm{twa}\), or directly from the
-model parameters using the following formulas:
    
-
    SFO:
    
-
    \[f_\textrm{twa} = \frac{\left( 1 - e^{- k
-t} \right)}{k t} \]
    
-
    FOMC:
    
-
    \[f_\textrm{twa} = \frac{\beta}{t (1 -
-\alpha)}
-                   \left( \left(\frac{t}{\beta} + 1 \right)^{1 - \alpha}
-- 1 \right) \]
    
-
    DFOP:
    
-
    \[f_\textrm{twa} = \frac{1}{t} \left(
-  \frac{g}{k_1} \left( 1 - e^{- k_1 t} \right) +
-  \frac{1-g}{k_2} \left( 1 - e^{- k_2 t} \right)  \right) \]
    
-
    HS for \(t > t_b\):
    
-
    \[f_\textrm{twa} = \frac{1}{t} \left(
-  \frac{1}{k_1} \left( 1 - e^{- k_1 t_b} \right) +
-  \frac{e^{- k_1 t_b}}{k_2} \left( 1 - e^{- k_2 (t - t_b)}
-\right)  \right) \]
    
-
    Note that a method for calculating maximum moving window time
-weighted average concentrations for a model fitted by ‘mkinfit’ or from
-parent decline model parameters is included in the
-max_twa_parent() function. If the same is needed for
-metabolites, the function pfm::max_twa() from the ‘pfm’
-package can be used.
    
-
    
-
    
-FOCUS Work Group on Degradation Kinetics. 2014. Generic Guidance for
-Estimating Persistence and Degradation Kinetics from Environmental Fate
-Studies on Pesticides in EU Registration. 1.1 ed. http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics.
-
    
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-
    
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-  
    
-
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-
    
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-      
    
-
    
-
-  
-
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-  
-
-  
-
diff --git a/docs/dev/articles/twa_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/dev/articles/twa_files/accessible-code-block-0.0.1/empty-anchor.js
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-// Hide empty  tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
-// v0.0.1
-// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
-
-document.addEventListener('DOMContentLoaded', function() {
-  const codeList = document.getElementsByClassName("sourceCode");
-  for (var i = 0; i < codeList.length; i++) {
-    var linkList = codeList[i].getElementsByTagName('a');
-    for (var j = 0; j < linkList.length; j++) {
-      if (linkList[j].innerHTML === "") {
-        linkList[j].setAttribute('aria-hidden', 'true');
-      }
-    }
-  }
-});
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-/* Styles for section anchors */
-a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
-a.anchor-section::before {content: '#';}
-.hasAnchor:hover a.anchor-section {visibility: visible;}
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-// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
-document.addEventListener('DOMContentLoaded', function() {
-  // Do nothing if AnchorJS is used
-  if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
-    return;
-  }
-
-  const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
-
-  // Do nothing if sections are already anchored
-  if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
-    return null;
-  }
-
-  // Use section id when pandoc runs with --section-divs
-  const section_id = function(x) {
-    return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
-            ? x.id : '');
-  };
-
-  // Add anchors
-  h.forEach(function(x) {
-    const id = x.id || section_id(x.parentElement);
-    if (id === '') {
-      return null;
-    }
-    let anchor = document.createElement('a');
-    anchor.href = '#' + id;
-    anchor.classList = ['anchor-section'];
-    x.classList.add('hasAnchor');
-    x.appendChild(anchor);
-  });
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-// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
-// be compatible with the behavior of Pandoc < 2.8).
-document.addEventListener('DOMContentLoaded', function(e) {
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diff --git a/docs/dev/articles/web_only/FOCUS_Z.html b/docs/dev/articles/web_only/FOCUS_Z.html
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-
-
-
-
-
-
-
-Example evaluation of FOCUS dataset Z • mkin
-
-
-
-
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-
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-    
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-      
    
-
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-  
    
-    
    
-      
    Example evaluation of FOCUS dataset Z
    
-                        
    Johannes
-Ranke
    
-            
-            
    Last change 16 January 2018
-(rebuilt 2023-04-16)
    
-      
-      Source: vignettes/web_only/FOCUS_Z.rmd
-      
-
-    
    
-
-    
-    
-
    Wissenschaftlicher Berater, Kronacher
-Str. 12, 79639 Grenzach-Wyhlen, Germany
    Privatdozent at the
-University of Bremen
    
-
    
-
    The data
-
    
-
    The following code defines the example dataset from Appendix 7 to the
-FOCUS kinetics report (FOCUS Work Group on
-Degradation Kinetics 2014, 354).
    
-
    -library(mkin, quietly = TRUE)
-LOD = 0.5
-FOCUS_2006_Z = data.frame(
-  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21,
-        42, 61, 96, 124),
-  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8,
-         2.9, 3.5, 5.3, 4.4, 1.2, 0.7),
-  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1,
-         1.6, 0.6, 0.5 * LOD, NA, NA, NA),
-  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5,
-         0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
-  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5,
-         25.2, 17.2, 4.8, 4.5, 2.8, 4.4))
-
-FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)
    
-
    
-
    
-
    Parent and one metabolite
-
    
-
    The next step is to set up the models used for the kinetic analysis.
-As the simultaneous fit of parent and the first metabolite is usually
-straightforward, Step 1 (SFO for parent only) is skipped here. We start
-with the model 2a, with formation and decline of metabolite Z1 and the
-pathway from parent directly to sink included (default in mkin).
    
-
    -Z.2a <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
-                Z1 = mkinsub("SFO"))
    
-
    ## Temporary DLL for differentials generated and loaded
    
-
    -m.Z.2a <- mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE)
    
-
    ## Warning in mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
-## value of zero were removed from the data
    
-
    -plot_sep(m.Z.2a)
    
-
    
-
    -summary(m.Z.2a, data = FALSE)$bpar
    
-
    ##            Estimate se_notrans t value     Pr(>t)    Lower    Upper
-## Z0_0       97.01488   3.301084 29.3888 3.2971e-21 91.66556 102.3642
-## k_Z0        2.23601   0.207078 10.7979 3.3309e-11  1.95303   2.5600
-## k_Z1        0.48212   0.063265  7.6207 2.8154e-08  0.40341   0.5762
-## f_Z0_to_Z1  1.00000   0.094764 10.5525 5.3560e-11  0.00000   1.0000
-## sigma       4.80411   0.635638  7.5579 3.2592e-08  3.52677   6.0815
    
-
    As obvious from the parameter summary (the component of the summary),
-the kinetic rate constant from parent compound Z to sink is very small
-and the t-test for this parameter suggests that it is not significantly
-different from zero. This suggests, in agreement with the analysis in
-the FOCUS kinetics report, to simplify the model by removing the pathway
-to sink.
    
-
    A similar result can be obtained when formation fractions are used in
-the model formulation:
    
-
    -Z.2a.ff <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
-                   Z1 = mkinsub("SFO"),
-                   use_of_ff = "max")
    
-
    ## Temporary DLL for differentials generated and loaded
    
-
    -m.Z.2a.ff <- mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE)
    
-
    ## Warning in mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
-## value of zero were removed from the data
    
-
    -plot_sep(m.Z.2a.ff)
    
-
    
-
    -summary(m.Z.2a.ff, data = FALSE)$bpar
    
-
    ##            Estimate se_notrans t value     Pr(>t)    Lower    Upper
-## Z0_0       97.01488   3.301084 29.3888 3.2971e-21 91.66556 102.3642
-## k_Z0        2.23601   0.207078 10.7979 3.3309e-11  1.95303   2.5600
-## k_Z1        0.48212   0.063265  7.6207 2.8154e-08  0.40341   0.5762
-## f_Z0_to_Z1  1.00000   0.094764 10.5525 5.3560e-11  0.00000   1.0000
-## sigma       4.80411   0.635638  7.5579 3.2592e-08  3.52677   6.0815
    
-
    Here, the ilr transformed formation fraction fitted in the model
-takes a very large value, and the backtransformed formation fraction
-from parent Z to Z1 is practically unity. Here, the covariance matrix
-used for the calculation of confidence intervals is not returned as the
-model is overparameterised.
    
-
    A simplified model is obtained by removing the pathway to the sink.
-
    
-
    In the following, we use the parameterisation with formation
-fractions in order to be able to compare with the results in the FOCUS
-guidance, and as it makes it easier to use parameters obtained in a
-previous fit when adding a further metabolite.
    
-
    -Z.3 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-               Z1 = mkinsub("SFO"), use_of_ff = "max")
    
-
    ## Temporary DLL for differentials generated and loaded
    
-
    -m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE)
    
-
    ## Warning in mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
-## value of zero were removed from the data
    
-
    -plot_sep(m.Z.3)
    
-
    
-
    -summary(m.Z.3, data = FALSE)$bpar
    
-
    ##       Estimate se_notrans t value     Pr(>t)    Lower    Upper
-## Z0_0  97.01488   2.597342  37.352 2.0106e-24 91.67597 102.3538
-## k_Z0   2.23601   0.146904  15.221 9.1477e-15  1.95354   2.5593
-## k_Z1   0.48212   0.041727  11.554 4.8268e-12  0.40355   0.5760
-## sigma  4.80411   0.620208   7.746 1.6110e-08  3.52925   6.0790
    
-
    As there is only one transformation product for Z0 and no pathway to
-sink, the formation fraction is internally fixed to unity.
    
-
    
-
    
-
    Metabolites Z2 and Z3
-
    
-
    As suggested in the FOCUS report, the pathway to sink was removed for
-metabolite Z1 as well in the next step. While this step appears
-questionable on the basis of the above results, it is followed here for
-the purpose of comparison. Also, in the FOCUS report, it is assumed that
-there is additional empirical evidence that Z1 quickly and exclusively
-hydrolyses to Z2.
    
-
    -Z.5 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-               Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-               Z2 = mkinsub("SFO"), use_of_ff = "max")
    
-
    ## Temporary DLL for differentials generated and loaded
    
-
    -m.Z.5 <- mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE)
    
-
    ## Warning in mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
-## value of zero were removed from the data
    
-
    -plot_sep(m.Z.5)
    
-
    
-
    Finally, metabolite Z3 is added to the model. We use the optimised
-differential equation parameter values from the previous fit in order to
-accelerate the optimization.
    
-
    -Z.FOCUS <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-                   Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                   Z2 = mkinsub("SFO", "Z3"),
-                   Z3 = mkinsub("SFO"),
-                   use_of_ff = "max")
    
-
    ## Temporary DLL for differentials generated and loaded
    
-
    -m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin,
-                     parms.ini = m.Z.5$bparms.ode,
-                     quiet = TRUE)
    
-
    ## Warning in mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, parms.ini = m.Z.5$bparms.ode, :
-## Observations with value of zero were removed from the data
    
-
    ## Warning in mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, parms.ini = m.Z.5$bparms.ode, : Optimisation did not converge:
-## false convergence (8)
    
-
    -plot_sep(m.Z.FOCUS)
    
-
    
-
    -summary(m.Z.FOCUS, data = FALSE)$bpar
    
-
    ##             Estimate se_notrans t value     Pr(>t)     Lower      Upper
-## Z0_0       96.838822   1.994274 48.5584 4.0280e-42 92.826981 100.850664
-## k_Z0        2.215393   0.118458 18.7019 1.0413e-23  1.989456   2.466989
-## k_Z1        0.478305   0.028258 16.9266 6.2418e-22  0.424708   0.538666
-## k_Z2        0.451627   0.042139 10.7176 1.6314e-14  0.374339   0.544872
-## k_Z3        0.058692   0.015245  3.8499 1.7803e-04  0.034808   0.098965
-## f_Z2_to_Z3  0.471502   0.058351  8.0805 9.6608e-11  0.357769   0.588274
-## sigma       3.984431   0.383402 10.3923 4.5575e-14  3.213126   4.755736
    
-
    -endpoints(m.Z.FOCUS)
    
-
    ## $ff
-##   Z2_Z3 Z2_sink 
-##  0.4715  0.5285 
-## 
-## $distimes
-##        DT50    DT90
-## Z0  0.31288  1.0394
-## Z1  1.44917  4.8141
-## Z2  1.53478  5.0984
-## Z3 11.80986 39.2315
    
-
    This fit corresponds to the final result chosen in Appendix 7 of the
-FOCUS report. Confidence intervals returned by mkin are based on
-internally transformed parameters, however.
    
-
    
-
    
-
    Using the SFORB model
-
    
-
    As the FOCUS report states, there is a certain tailing of the time
-course of metabolite Z3. Also, the time course of the parent compound is
-not fitted very well using the SFO model, as residues at a certain low
-level remain.
    
-
    Therefore, an additional model is offered here, using the single
-first-order reversible binding (SFORB) model for metabolite Z3. As
-expected, the \(\chi^2\) error level is
-lower for metabolite Z3 using this model and the graphical fit for Z3 is
-improved. However, the covariance matrix is not returned.
    
-
    -Z.mkin.1 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFORB"))
    
-
    ## Temporary DLL for differentials generated and loaded
    
-
    -m.Z.mkin.1 <- mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE)
    
-
    ## Warning in mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE): Observations
-## with value of zero were removed from the data
    
-
    -plot_sep(m.Z.mkin.1)
    
-
    
-
    -summary(m.Z.mkin.1, data = FALSE)$cov.unscaled
    
-
    ## NULL
    
-
    Therefore, a further stepwise model building is performed starting
-from the stage of parent and two metabolites, starting from the
-assumption that the model fit for the parent compound can be improved by
-using the SFORB model.
    
-
    -Z.mkin.3 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO"))
    
-
    ## Temporary DLL for differentials generated and loaded
    
-
    -m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE)
    
-
    ## Warning in mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE): Observations
-## with value of zero were removed from the data
    
-
    -plot_sep(m.Z.mkin.3)
    
-
    
-
    This results in a much better representation of the behaviour of the
-parent compound Z0.
    
-
    Finally, Z3 is added as well. These models appear overparameterised
-(no covariance matrix returned) if the sink for Z1 is left in the
-models.
    
-
    -Z.mkin.4 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFO"))
    
-
    ## Temporary DLL for differentials generated and loaded
    
-
    -m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.3$bparms.ode,
-                      quiet = TRUE)
    
-
    ## Warning in mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin, parms.ini =
-## m.Z.mkin.3$bparms.ode, : Observations with value of zero were removed from the
-## data
    
-
    -plot_sep(m.Z.mkin.4)
    
-
    
-
    The error level of the fit, but especially of metabolite Z3, can be
-improved if the SFORB model is chosen for this metabolite, as this model
-is capable of representing the tailing of the metabolite decline
-phase.
    
-
    -Z.mkin.5 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
-                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
-                    Z2 = mkinsub("SFO", "Z3"),
-                    Z3 = mkinsub("SFORB"))
    
-
    ## Temporary DLL for differentials generated and loaded
    
-
    -m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
-                      parms.ini = m.Z.mkin.4$bparms.ode[1:4],
-                      quiet = TRUE)
    
-
    ## Warning in mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, parms.ini =
-## m.Z.mkin.4$bparms.ode[1:4], : Observations with value of zero were removed from
-## the data
    
-
    -plot_sep(m.Z.mkin.5)
    
-
    
-
    The summary view of the backtransformed parameters shows that we get
-no confidence intervals due to overparameterisation. As the optimized is
-excessively small, it seems reasonable to fix it to zero.
    
-
    -m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
-                       parms.ini = c(m.Z.mkin.5$bparms.ode[1:7],
-                                     k_Z3_bound_free = 0),
-                       fixed_parms = "k_Z3_bound_free",
-                       quiet = TRUE)
    
-
    ## Warning in mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, parms.ini =
-## c(m.Z.mkin.5$bparms.ode[1:7], : Observations with value of zero were removed
-## from the data
    
-
    -plot_sep(m.Z.mkin.5a)
    
-
    
-
    As expected, the residual plots for Z0 and Z3 are more random than in
-the case of the all SFO model for which they were shown above. In
-conclusion, the model is proposed as the best-fit model for the dataset
-from Appendix 7 of the FOCUS report.
    
-
    A graphical representation of the confidence intervals can finally be
-obtained.
    
-
    -mkinparplot(m.Z.mkin.5a)
    
-
    
-
    The endpoints obtained with this model are
    
-
    -endpoints(m.Z.mkin.5a)
    
-
    ## $ff
-## Z0_free   Z2_Z3 Z2_sink Z3_free 
-## 1.00000 0.53656 0.46344 1.00000 
-## 
-## $SFORB
-##     Z0_b1     Z0_b2      Z0_g     Z3_b1     Z3_b2      Z3_g 
-## 2.4471322 0.0075125 0.9519862 0.0800069 0.0000000 0.9347820 
-## 
-## $distimes
-##      DT50   DT90 DT50back DT50_Z0_b1 DT50_Z0_b2 DT50_Z3_b1 DT50_Z3_b2
-## Z0 0.3043 1.1848  0.35666    0.28325     92.266         NA         NA
-## Z1 1.5148 5.0320       NA         NA         NA         NA         NA
-## Z2 1.6414 5.4526       NA         NA         NA         NA         NA
-## Z3     NA     NA       NA         NA         NA     8.6636        Inf
    
-
    It is clear the degradation rate of Z3 towards the end of the
-experiment is very low as DT50_Z3_b2 (the second Eigenvalue of the
-system of two differential equations representing the SFORB system for
-Z3, corresponding to the slower rate constant of the DFOP model) is
-reported to be infinity. However, this appears to be a feature of the
-data.
    
-
    
-
    
-
    References
-
    
-
-
    
-
    
-FOCUS Work Group on Degradation Kinetics. 2014. Generic Guidance for
-Estimating Persistence and Degradation Kinetics from Environmental Fate
-Studies on Pesticides in EU Registration. 1.1 ed. http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics.
-
    
-
    
-
    
-  
    
-
-  
-
-
    
-
-
-
-      
    
-  
    
-
    Developed by Johannes Ranke.
    
-
    
-
-
    
-  
    
-
    Site built with pkgdown 2.0.7.
    
-
    
-
-      
    
-
    
-
-  
-
-
-  
-
-  
-
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-// Hide empty  tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
-// v0.0.1
-// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
-
-document.addEventListener('DOMContentLoaded', function() {
-  const codeList = document.getElementsByClassName("sourceCode");
-  for (var i = 0; i < codeList.length; i++) {
-    var linkList = codeList[i].getElementsByTagName('a');
-    for (var j = 0; j < linkList.length; j++) {
-      if (linkList[j].innerHTML === "") {
-        linkList[j].setAttribute('aria-hidden', 'true');
-      }
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-  }
-});
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-/* Styles for section anchors */
-a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
-a.anchor-section::before {content: '#';}
-.hasAnchor:hover a.anchor-section {visibility: visible;}
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-// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
-document.addEventListener('DOMContentLoaded', function() {
-  // Do nothing if AnchorJS is used
-  if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
-    return;
-  }
-
-  const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
-
-  // Do nothing if sections are already anchored
-  if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
-    return null;
-  }
-
-  // Use section id when pandoc runs with --section-divs
-  const section_id = function(x) {
-    return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
-            ? x.id : '');
-  };
-
-  // Add anchors
-  h.forEach(function(x) {
-    const id = x.id || section_id(x.parentElement);
-    if (id === '') {
-      return null;
-    }
-    let anchor = document.createElement('a');
-    anchor.href = '#' + id;
-    anchor.classList = ['anchor-section'];
-    x.classList.add('hasAnchor');
-    x.appendChild(anchor);
-  });
-});
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-
-
-
-
-
-
-
-Evaluation of example datasets from Attachment 1 to the US EPA SOP for the NAFTA guidance • mkin
-
-
-
-
-
-
-
-
-
-
-
-    
-
-    
    
-      
    
-
-
-      
-
-      
    
-  
    
-    
    
-      
    Evaluation of example datasets from Attachment 1
-to the US EPA SOP for the NAFTA guidance
    
-                        
    Johannes
-Ranke
    
-            
-            
    26 February 2019 (rebuilt
-2023-04-16)
    
-      
-      Source: vignettes/web_only/NAFTA_examples.rmd
-      
-
-    
    
-
-    
-    
-
    
-
    Introduction
-
    
-
    In this document, the example evaluations provided in Attachment 1 to
-the SOP of US EPA for using the NAFTA guidance (US EPA 2015) are repeated using mkin. The
-original evaluations reported in the attachment were performed using
-PestDF in version 0.8.4. Note that PestDF 0.8.13 is the version
-distributed at the US EPA website today (2019-02-26).
    
-
    The datasets are now distributed with the mkin package.
    
-
    
-
    
-
    Examples where DFOP did not converge with PestDF 0.8.4
-
    
-
    In attachment 1, it is reported that the DFOP model does not converge
-for these datasets when PestDF 0.8.4 was used. For all four datasets,
-the DFOP model can be fitted with mkin (see below). The negative
-half-life given by PestDF 0.8.4 for these fits appears to be the result
-of a bug. The results for the other two models (SFO and IORE) are the
-same.
    
-
    
-
    Example on page 5, upper panel
-
    
-
    -p5a <- nafta(NAFTA_SOP_Attachment[["p5a"]])
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p5a)
    
-
    
-
    -print(p5a)
    
-
    ## Sums of squares:
-##       SFO      IORE      DFOP 
-## 465.21753  56.27506  32.06401 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 64.4304
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)  Lower   Upper
-## parent_0  95.8401 4.67e-21 92.245 99.4357
-## k_parent   0.0102 3.92e-12  0.009  0.0117
-## sigma      4.8230 3.81e-06  3.214  6.4318
-## 
-## $IORE
-##                Estimate Pr(>t)    Lower    Upper
-## parent_0       1.01e+02     NA 9.91e+01 1.02e+02
-## k__iore_parent 1.54e-05     NA 4.08e-06 5.84e-05
-## N_parent       2.57e+00     NA 2.25e+00 2.89e+00
-## sigma          1.68e+00     NA 1.12e+00 2.24e+00
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower    Upper
-## parent_0 9.99e+01 1.41e-26 98.8116 101.0810
-## k1       2.67e-02 5.05e-06  0.0243   0.0295
-## k2       2.26e-12 5.00e-01  0.0000      Inf
-## g        6.47e-01 3.67e-06  0.6248   0.6677
-## sigma    1.27e+00 8.91e-06  0.8395   1.6929
-## 
-## 
-## DTx values:
-##      DT50     DT90 DT50_rep
-## SFO  67.7 2.25e+02 6.77e+01
-## IORE 58.2 1.07e+03 3.22e+02
-## DFOP 55.5 5.59e+11 3.07e+11
-## 
-## Representative half-life:
-## [1] 321.51
    
-
    
-
    
-
    Example on page 5, lower panel
-
    
-
    -p5b <- nafta(NAFTA_SOP_Attachment[["p5b"]])
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p5b)
    
-
    
-
    -print(p5b)
    
-
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 94.81123 10.10936  7.55871 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 11.77879
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0   96.497 2.32e-24 94.85271 98.14155
-## k_parent    0.008 3.42e-14  0.00737  0.00869
-## sigma       2.295 1.22e-05  1.47976  3.11036
-## 
-## $IORE
-##                Estimate   Pr(>t)    Lower    Upper
-## parent_0       9.85e+01 1.17e-28 9.79e+01 9.92e+01
-## k__iore_parent 1.53e-04 6.50e-03 7.21e-05 3.26e-04
-## N_parent       1.94e+00 5.88e-13 1.76e+00 2.12e+00
-## sigma          7.49e-01 1.63e-05 4.82e-01 1.02e+00
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0 9.84e+01 1.24e-27 97.8078 98.9187
-## k1       1.55e-02 4.10e-04  0.0143  0.0167
-## k2       8.63e-12 5.00e-01  0.0000     Inf
-## g        6.89e-01 2.92e-03  0.6626  0.7142
-## sigma    6.48e-01 2.38e-05  0.4147  0.8813
-## 
-## 
-## DTx values:
-##      DT50     DT90 DT50_rep
-## SFO  86.6 2.88e+02 8.66e+01
-## IORE 85.5 7.17e+02 2.16e+02
-## DFOP 83.6 1.32e+11 8.04e+10
-## 
-## Representative half-life:
-## [1] 215.87
    
-
    
-
    
-
    Example on page 6
-
    
-
    -p6 <- nafta(NAFTA_SOP_Attachment[["p6"]])
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p6)
    
-
    
-
    -print(p6)
    
-
    ## Sums of squares:
-##       SFO      IORE      DFOP 
-## 188.45361  51.00699  42.46931 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 58.39888
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0  94.7759 7.29e-24 92.3478 97.2039
-## k_parent   0.0179 8.02e-16  0.0166  0.0194
-## sigma      3.0696 3.81e-06  2.0456  4.0936
-## 
-## $IORE
-##                Estimate   Pr(>t)    Lower    Upper
-## parent_0       97.12446 2.63e-26 95.62461 98.62431
-## k__iore_parent  0.00252 1.95e-03  0.00134  0.00472
-## N_parent        1.49587 4.07e-13  1.33896  1.65279
-## sigma           1.59698 5.05e-06  1.06169  2.13227
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0 9.66e+01 1.57e-25 95.3476 97.8979
-## k1       2.55e-02 7.33e-06  0.0233  0.0278
-## k2       3.22e-11 5.00e-01  0.0000     Inf
-## g        8.61e-01 7.55e-06  0.8314  0.8867
-## sigma    1.46e+00 6.93e-06  0.9661  1.9483
-## 
-## 
-## DTx values:
-##      DT50     DT90 DT50_rep
-## SFO  38.6 1.28e+02 3.86e+01
-## IORE 34.0 1.77e+02 5.32e+01
-## DFOP 34.1 1.01e+10 2.15e+10
-## 
-## Representative half-life:
-## [1] 53.17
    
-
    
-
    
-
    Example on page 7
-
    
-
    -p7 <- nafta(NAFTA_SOP_Attachment[["p7"]])
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p7)
    
-
    
-
    -print(p7)
    
-
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 3661.661 3195.030 3174.145 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 3334.194
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 96.41796 4.80e-53 93.32245 99.51347
-## k_parent  0.00735 7.64e-21  0.00641  0.00843
-## sigma     7.94557 1.83e-15  6.46713  9.42401
-## 
-## $IORE
-##                Estimate Pr(>t)    Lower    Upper
-## parent_0       9.92e+01     NA 9.55e+01 1.03e+02
-## k__iore_parent 1.60e-05     NA 1.45e-07 1.77e-03
-## N_parent       2.45e+00     NA 1.35e+00 3.54e+00
-## sigma          7.42e+00     NA 6.04e+00 8.80e+00
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower    Upper
-## parent_0 9.89e+01 9.44e-49 95.4640 102.2573
-## k1       1.81e-02 1.75e-01  0.0116   0.0281
-## k2       3.63e-10 5.00e-01  0.0000      Inf
-## g        6.06e-01 2.19e-01  0.4826   0.7178
-## sigma    7.40e+00 2.97e-15  6.0201   8.7754
-## 
-## 
-## DTx values:
-##      DT50     DT90 DT50_rep
-## SFO  94.3 3.13e+02 9.43e+01
-## IORE 96.7 1.51e+03 4.55e+02
-## DFOP 96.4 3.77e+09 1.91e+09
-## 
-## Representative half-life:
-## [1] 454.55
    
-
    
-
    
-
    
-
    Examples where the representative half-life deviates from the
-observed DT50
-
    
-
    
-
    Example on page 8
-
    
-
    For this dataset, the IORE fit does not converge when the default
-starting values used by mkin for the IORE model are used. Therefore, a
-lower value for the rate constant is used here.
    
-
    -p8 <- nafta(NAFTA_SOP_Attachment[["p8"]], parms.ini = c(k__iore_parent = 1e-3))
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p8)
    
-
    
-
    -print(p8)
    
-
    ## Sums of squares:
-##       SFO      IORE      DFOP 
-## 1996.9408  444.9237  547.5616 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 477.4924
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 88.16549 6.53e-29 83.37344 92.95754
-## k_parent  0.00803 1.67e-13  0.00674  0.00957
-## sigma     7.44786 4.17e-10  5.66209  9.23363
-## 
-## $IORE
-##                Estimate   Pr(>t)    Lower    Upper
-## parent_0       9.77e+01 7.03e-35 9.44e+01 1.01e+02
-## k__iore_parent 6.14e-05 3.20e-02 2.12e-05 1.78e-04
-## N_parent       2.27e+00 4.23e-18 2.00e+00 2.54e+00
-## sigma          3.52e+00 5.36e-10 2.67e+00 4.36e+00
-## 
-## $DFOP
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 95.70619 8.99e-32 91.87941 99.53298
-## k1        0.02500 5.25e-04  0.01422  0.04394
-## k2        0.00273 6.84e-03  0.00125  0.00597
-## g         0.58835 2.84e-06  0.36595  0.77970
-## sigma     3.90001 6.94e-10  2.96260  4.83741
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO  86.3  287     86.3
-## IORE 53.4  668    201.0
-## DFOP 55.6  517    253.0
-## 
-## Representative half-life:
-## [1] 201.03
    
-
    
-
    
-
    
-
    Examples where SFO was not selected for an abiotic study
-
    
-
    
-
    Example on page 9, upper panel
-
    
-
    -p9a <- nafta(NAFTA_SOP_Attachment[["p9a"]])
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p9a)
    
-
    
-
    -print(p9a)
    
-
    ## Sums of squares:
-##       SFO      IORE      DFOP 
-## 839.35238  88.57064   9.93363 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 105.5678
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0  88.1933 3.06e-12 79.9447 96.4419
-## k_parent   0.0409 2.07e-07  0.0324  0.0516
-## sigma      7.2429 3.92e-05  4.4768 10.0090
-## 
-## $IORE
-##                Estimate   Pr(>t)    Lower    Upper
-## parent_0       9.89e+01 1.12e-16 9.54e+01 1.02e+02
-## k__iore_parent 1.93e-05 1.13e-01 3.49e-06 1.06e-04
-## N_parent       2.91e+00 1.45e-09 2.50e+00 3.32e+00
-## sigma          2.35e+00 5.31e-05 1.45e+00 3.26e+00
-## 
-## $DFOP
-##          Estimate   Pr(>t)  Lower  Upper
-## parent_0 9.85e+01 2.54e-20 97.390 99.672
-## k1       1.38e-01 3.52e-05  0.131  0.146
-## k2       9.02e-13 5.00e-01  0.000    Inf
-## g        6.52e-01 8.13e-06  0.642  0.661
-## sigma    7.88e-01 6.13e-02  0.481  1.095
-## 
-## 
-## DTx values:
-##      DT50     DT90 DT50_rep
-## SFO  16.9 5.63e+01 1.69e+01
-## IORE 11.6 3.37e+02 1.01e+02
-## DFOP 10.5 1.38e+12 7.69e+11
-## 
-## Representative half-life:
-## [1] 101.43
    
-
    In this example, the residuals of the SFO indicate a lack of fit of
-this model, so even if it was an abiotic experiment, the data do not
-suggest a simple exponential decline.
    
-
    
-
    
-
    Example on page 9, lower panel
-
    
-
    -p9b <- nafta(NAFTA_SOP_Attachment[["p9b"]])
    
-
    ## Warning in sqrt(diag(covar)): NaNs produced
    
-
    ## Warning in sqrt(diag(covar_notrans)): NaNs produced
    
-
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
-
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result
-## is doubtful
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p9b)
    
-
    
-
    -print(p9b)
    
-
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 35.64867 23.22334 35.64867 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 28.54188
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)  Lower   Upper
-## parent_0  94.7123 2.15e-19 93.178 96.2464
-## k_parent   0.0389 4.47e-14  0.037  0.0408
-## sigma      1.5957 1.28e-04  0.932  2.2595
-## 
-## $IORE
-##                Estimate   Pr(>t)   Lower  Upper
-## parent_0         93.863 2.32e-18 92.4565 95.269
-## k__iore_parent    0.127 1.85e-02  0.0504  0.321
-## N_parent          0.711 1.88e-05  0.4843  0.937
-## sigma             1.288 1.76e-04  0.7456  1.830
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0  94.7123 1.61e-16 93.1355 96.2891
-## k1         0.0389 1.08e-04  0.0266  0.0569
-## k2         0.0389 2.23e-04  0.0255  0.0592
-## g          0.5256      NaN      NA      NA
-## sigma      1.5957 2.50e-04  0.9135  2.2779
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO  17.8 59.2     17.8
-## IORE 18.4 49.2     14.8
-## DFOP 17.8 59.2     17.8
-## 
-## Representative half-life:
-## [1] 14.8
    
-
    Here, mkin gives a longer slow DT50 for the DFOP model (17.8 days)
-than PestDF (13.5 days). Presumably, this is related to the fact that
-PestDF gives a negative value for the proportion of the fast degradation
-which should be between 0 and 1, inclusive. This parameter is called f
-in PestDF and g in mkin. In mkin, it is restricted to the interval from
-0 to 1.
    
-
    
-
    
-
    Example on page 10
-
    
-
    -p10 <- nafta(NAFTA_SOP_Attachment[["p10"]])
    
-
    ## Warning in sqrt(diag(covar)): NaNs produced
    
-
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
-
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result
-## is doubtful
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p10)
    
-
    
-
    -print(p10)
    
-
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 899.4089 336.4348 899.4089 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 413.4841
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)   Lower    Upper
-## parent_0 101.7315 6.42e-11 91.9259 111.5371
-## k_parent   0.0495 1.70e-07  0.0404   0.0607
-## sigma      8.0152 1.28e-04  4.6813  11.3491
-## 
-## $IORE
-##                Estimate   Pr(>t)  Lower   Upper
-## parent_0          96.86 3.32e-12 90.848 102.863
-## k__iore_parent     2.96 7.91e-02  0.687  12.761
-## N_parent           0.00 5.00e-01 -0.372   0.372
-## sigma              4.90 1.77e-04  2.837   6.968
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower    Upper
-## parent_0 101.7315 1.41e-09 91.6534 111.8097
-## k1         0.0495 6.58e-03  0.0303   0.0809
-## k2         0.0495 2.60e-03  0.0410   0.0598
-## g          0.4487 5.00e-01      NA       NA
-## sigma      8.0152 2.50e-04  4.5886  11.4418
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO  14.0 46.5    14.00
-## IORE 16.4 29.4     8.86
-## DFOP 14.0 46.5    14.00
-## 
-## Representative half-life:
-## [1] 8.86
    
-
    Here, a value below N is given for the IORE model, because the data
-suggests a faster decline towards the end of the experiment, which
-appears physically rather unlikely in the case of a photolysis study. It
-seems PestDF does not constrain N to values above zero, thus the slight
-difference in IORE model parameters between PestDF and mkin.
    
-
    
-
    
-
    
-
    The DT50 was not observed during the study
-
    
-
    
-
    Example on page 11
-
    
-
    -p11 <- nafta(NAFTA_SOP_Attachment[["p11"]])
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p11)
    
-
    
-
    -print(p11)
    
-
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 579.6805 204.7932 144.7783 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 251.6944
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 96.15820 4.83e-13 90.24934 1.02e+02
-## k_parent  0.00321 4.71e-05  0.00222 4.64e-03
-## sigma     6.43473 1.28e-04  3.75822 9.11e+00
-## 
-## $IORE
-##                Estimate Pr(>t)    Lower    Upper
-## parent_0       1.05e+02     NA 9.90e+01 1.10e+02
-## k__iore_parent 3.11e-17     NA 1.35e-20 7.18e-14
-## N_parent       8.36e+00     NA 6.62e+00 1.01e+01
-## sigma          3.82e+00     NA 2.21e+00 5.44e+00
-## 
-## $DFOP
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 1.05e+02 9.47e-13  99.9990 109.1224
-## k1       4.41e-02 5.95e-03   0.0296   0.0658
-## k2       9.94e-13 5.00e-01   0.0000      Inf
-## g        3.22e-01 1.45e-03   0.2814   0.3650
-## sigma    3.22e+00 3.52e-04   1.8410   4.5906
-## 
-## 
-## DTx values:
-##          DT50     DT90 DT50_rep
-## SFO  2.16e+02 7.18e+02 2.16e+02
-## IORE 9.73e+02 1.37e+08 4.11e+07
-## DFOP 3.07e+11 1.93e+12 6.98e+11
-## 
-## Representative half-life:
-## [1] 41148170
    
-
    In this case, the DFOP fit reported for PestDF resulted in a negative
-value for the slower rate constant, which is not possible in mkin. The
-other results are in agreement.
    
-
    
-
    
-
    
-
    N is less than 1 and the DFOP rate constants are like the SFO rate
-constant
-
    
-
    In the following three examples, the same results are obtained with
-mkin as reported for PestDF. As in the case on page 10, the N values
-below 1 are deemed unrealistic and appear to be the result of an
-overparameterisation.
    
-
    
-
    Example on page 12, upper panel
-
    
-
    -p12a <- nafta(NAFTA_SOP_Attachment[["p12a"]])
    
-
    ## Warning in summary.mkinfit(x): Could not calculate correlation; no covariance
-## matrix
    
-
    ## Warning in sqrt(diag(covar)): NaNs produced
    
-
    ## Warning in sqrt(diag(covar_notrans)): NaNs produced
    
-
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
-
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result
-## is doubtful
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p12a)
    
-
    
-
    -print(p12a)
    
-
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 695.4440 220.0685 695.4440 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 270.4679
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)  Lower   Upper
-## parent_0  100.521 8.75e-12 92.461 108.581
-## k_parent    0.124 3.61e-08  0.104   0.148
-## sigma       7.048 1.28e-04  4.116   9.980
-## 
-## $IORE
-##                Estimate Pr(>t) Lower Upper
-## parent_0         96.823     NA    NA    NA
-## k__iore_parent    2.436     NA    NA    NA
-## N_parent          0.263     NA    NA    NA
-## sigma             3.965     NA    NA    NA
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower   Upper
-## parent_0  100.521 2.74e-10 92.2366 108.805
-## k1          0.124 2.53e-05  0.0908   0.170
-## k2          0.124 2.52e-02  0.0456   0.339
-## g           0.793      NaN      NA      NA
-## sigma       7.048 2.50e-04  4.0349  10.061
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO  5.58 18.5     5.58
-## IORE 6.49 13.2     3.99
-## DFOP 5.58 18.5     5.58
-## 
-## Representative half-life:
-## [1] 3.99
    
-
    
-
    
-
    Example on page 12, lower panel
-
    
-
    -p12b <- nafta(NAFTA_SOP_Attachment[["p12b"]])
    
-
    ## Warning in qt(alpha/2, rdf): NaNs produced
    
-
    ## Warning in qt(1 - alpha/2, rdf): NaNs produced
    
-
    ## Warning in sqrt(diag(covar_notrans)): NaNs produced
    
-
    ## Warning in pt(abs(tval), rdf, lower.tail = FALSE): NaNs produced
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p12b)
    
-
    
-
    -print(p12b)
    
-
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 58.90242 19.06353 58.90242 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 51.51756
-## 
-## Parameters:
-## $SFO
-##          Estimate  Pr(>t)   Lower    Upper
-## parent_0  97.6840 0.00039 85.9388 109.4292
-## k_parent   0.0589 0.00261  0.0431   0.0805
-## sigma      3.4323 0.04356 -1.2377   8.1023
-## 
-## $IORE
-##                Estimate Pr(>t)     Lower  Upper
-## parent_0         95.523 0.0055 74.539157 116.51
-## k__iore_parent    0.333 0.1433  0.000717 154.57
-## N_parent          0.568 0.0677 -0.989464   2.13
-## sigma             1.953 0.0975 -5.893100   9.80
-## 
-## $DFOP
-##          Estimate Pr(>t) Lower Upper
-## parent_0  97.6840    NaN   NaN   NaN
-## k1         0.0589    NaN    NA    NA
-## k2         0.0589    NaN    NA    NA
-## g          0.6473    NaN    NA    NA
-## sigma      3.4323    NaN   NaN   NaN
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO  11.8 39.1    11.80
-## IORE 12.9 31.4     9.46
-## DFOP 11.8 39.1    11.80
-## 
-## Representative half-life:
-## [1] 9.46
    
-
    
-
    
-
    Example on page 13
-
    
-
    -p13 <- nafta(NAFTA_SOP_Attachment[["p13"]])
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p13)
    
-
    
-
    -print(p13)
    
-
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 174.5971 142.3951 174.5971 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 172.131
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 92.73500 5.99e-17 89.61936 95.85065
-## k_parent  0.00258 2.42e-09  0.00223  0.00299
-## sigma     3.41172 7.07e-05  2.05455  4.76888
-## 
-## $IORE
-##                Estimate   Pr(>t)    Lower  Upper
-## parent_0        91.6016 6.34e-16 88.53086 94.672
-## k__iore_parent   0.0396 2.36e-01  0.00207  0.759
-## N_parent         0.3541 1.46e-01 -0.35153  1.060
-## sigma            3.0811 9.64e-05  1.84296  4.319
-## 
-## $DFOP
-##          Estimate Pr(>t)    Lower    Upper
-## parent_0 92.73500     NA 8.95e+01 95.92118
-## k1        0.00258     NA 4.14e-04  0.01611
-## k2        0.00258     NA 1.74e-03  0.00383
-## g         0.16452     NA 0.00e+00  1.00000
-## sigma     3.41172     NA 2.02e+00  4.79960
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO   269  892      269
-## IORE  261  560      169
-## DFOP  269  892      269
-## 
-## Representative half-life:
-## [1] 168.51
    
-
    
-
    
-
    
-
    DT50 not observed in the study and DFOP problems in PestDF
-
    
-
    -p14 <- nafta(NAFTA_SOP_Attachment[["p14"]])
    
-
    ## Warning in sqrt(diag(covar)): NaNs produced
    
-
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
-
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result
-## is doubtful
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p14)
    
-
    
-
    -print(p14)
    
-
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 48.43249 28.67746 27.26248 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 32.83337
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 99.47124 2.06e-30 98.42254 1.01e+02
-## k_parent  0.00279 3.75e-15  0.00256 3.04e-03
-## sigma     1.55616 3.81e-06  1.03704 2.08e+00
-## 
-## $IORE
-##                Estimate Pr(>t) Lower Upper
-## parent_0       1.00e+02     NA   NaN   NaN
-## k__iore_parent 9.44e-08     NA   NaN   NaN
-## N_parent       3.31e+00     NA   NaN   NaN
-## sigma          1.20e+00     NA 0.796   1.6
-## 
-## $DFOP
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 1.00e+02 2.96e-28 99.40280 101.2768
-## k1       9.53e-03 1.20e-01  0.00638   0.0143
-## k2       6.08e-12 5.00e-01  0.00000      Inf
-## g        3.98e-01 2.19e-01  0.30481   0.4998
-## sigma    1.17e+00 7.68e-06  0.77406   1.5610
-## 
-## 
-## DTx values:
-##          DT50     DT90 DT50_rep
-## SFO  2.48e+02 8.25e+02 2.48e+02
-## IORE 4.34e+02 2.22e+04 6.70e+03
-## DFOP 3.05e+10 2.95e+11 1.14e+11
-## 
-## Representative half-life:
-## [1] 6697.44
    
-
    The slower rate constant reported by PestDF is negative, which is not
-physically realistic, and not possible in mkin. The other fits give the
-same results in mkin and PestDF.
    
-
    
-
    
-
    N is less than 1 and DFOP fraction parameter is below zero
-
    
-
    -p15a <- nafta(NAFTA_SOP_Attachment[["p15a"]])
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p15a)
    
-
    
-
    -print(p15a)
    
-
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 245.5248 135.0132 245.5248 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 165.9335
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower   Upper
-## parent_0 97.96751 2.00e-15 94.32049 101.615
-## k_parent  0.00952 4.93e-09  0.00824   0.011
-## sigma     4.18778 1.28e-04  2.44588   5.930
-## 
-## $IORE
-##                Estimate   Pr(>t)  Lower  Upper
-## parent_0         95.874 2.94e-15 92.937 98.811
-## k__iore_parent    0.629 2.11e-01  0.044  8.982
-## N_parent          0.000 5.00e-01 -0.642  0.642
-## sigma             3.105 1.78e-04  1.795  4.416
-## 
-## $DFOP
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 97.96751 2.85e-13 94.21913 101.7159
-## k1        0.00952 6.28e-02  0.00250   0.0363
-## k2        0.00952 1.27e-04  0.00646   0.0140
-## g         0.21241 5.00e-01  0.00000   1.0000
-## sigma     4.18778 2.50e-04  2.39747   5.9781
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO  72.8  242     72.8
-## IORE 76.3  137     41.3
-## DFOP 72.8  242     72.8
-## 
-## Representative half-life:
-## [1] 41.33
    
-
    -p15b <- nafta(NAFTA_SOP_Attachment[["p15b"]])
    
-
    ## Warning in sqrt(diag(covar)): NaNs produced
    
-
    ## Warning in sqrt(1/diag(V)): NaNs produced
    
-
    ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result
-## is doubtful
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The half-life obtained from the IORE model may be used
    
-
    -plot(p15b)
    
-
    
-
    -print(p15b)
    
-
    ## Sums of squares:
-##       SFO      IORE      DFOP 
-## 106.91629  68.55574 106.91629 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 84.25618
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)    Lower    Upper
-## parent_0 1.01e+02 3.06e-17 98.31594 1.03e+02
-## k_parent 4.86e-03 2.48e-10  0.00435 5.42e-03
-## sigma    2.76e+00 1.28e-04  1.61402 3.91e+00
-## 
-## $IORE
-##                Estimate   Pr(>t)    Lower  Upper
-## parent_0          99.83 1.81e-16 97.51349 102.14
-## k__iore_parent     0.38 3.22e-01  0.00352  41.05
-## N_parent           0.00 5.00e-01 -1.07696   1.08
-## sigma              2.21 2.57e-04  1.23245   3.19
-## 
-## $DFOP
-##          Estimate Pr(>t)    Lower    Upper
-## parent_0 1.01e+02     NA 9.82e+01 1.04e+02
-## k1       4.86e-03     NA 8.63e-04 2.73e-02
-## k2       4.86e-03     NA 3.21e-03 7.35e-03
-## g        1.88e-01     NA       NA       NA
-## sigma    2.76e+00     NA 1.58e+00 3.94e+00
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO   143  474    143.0
-## IORE  131  236     71.2
-## DFOP  143  474    143.0
-## 
-## Representative half-life:
-## [1] 71.18
    
-
    In mkin, only the IORE fit is affected (deemed unrealistic), as the
-fraction parameter of the DFOP model is restricted to the interval
-between 0 and 1 in mkin. The SFO fits give the same results for both
-mkin and PestDF.
    
-
    
-
    
-
    The DFOP fraction parameter is greater than 1
-
    
-
    -p16 <- nafta(NAFTA_SOP_Attachment[["p16"]])
    
-
    ## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
    
-
    ## The representative half-life of the IORE model is longer than the one corresponding
    
-
    ## to the terminal degradation rate found with the DFOP model.
    
-
    ## The representative half-life obtained from the DFOP model may be used
    
-
    -plot(p16)
    
-
    
-
    -print(p16)
    
-
    ## Sums of squares:
-##      SFO     IORE     DFOP 
-## 3831.804 2062.008 1550.980 
-## 
-## Critical sum of squares for checking the SFO model:
-## [1] 2247.348
-## 
-## Parameters:
-## $SFO
-##          Estimate   Pr(>t)  Lower Upper
-## parent_0   71.953 2.33e-13 60.509 83.40
-## k_parent    0.159 4.86e-05  0.102  0.25
-## sigma      11.302 1.25e-08  8.308 14.30
-## 
-## $IORE
-##                Estimate   Pr(>t)    Lower    Upper
-## parent_0       8.74e+01 2.48e-16 7.72e+01 97.52972
-## k__iore_parent 4.55e-04 2.16e-01 3.48e-05  0.00595
-## N_parent       2.70e+00 1.21e-08 1.99e+00  3.40046
-## sigma          8.29e+00 1.61e-08 6.09e+00 10.49062
-## 
-## $DFOP
-##          Estimate   Pr(>t)   Lower  Upper
-## parent_0  88.5333 7.40e-18 79.9836 97.083
-## k1        18.8461 5.00e-01  0.0000    Inf
-## k2         0.0776 1.41e-05  0.0518  0.116
-## g          0.4733 1.41e-09  0.3674  0.582
-## sigma      7.1902 2.11e-08  5.2785  9.102
-## 
-## 
-## DTx values:
-##      DT50 DT90 DT50_rep
-## SFO  4.35 14.4     4.35
-## IORE 1.48 32.1     9.67
-## DFOP 0.67 21.4     8.93
-## 
-## Representative half-life:
-## [1] 8.93
    
-
    In PestDF, the DFOP fit seems to have stuck in a local minimum, as
-mkin finds a solution with a much lower \(\chi^2\) error level. As the half-life from
-the slower rate constant of the DFOP model is larger than the IORE
-derived half-life, the NAFTA recommendation obtained with mkin is to use
-the DFOP representative half-life of 8.9 days.
    
-
    
-
    
-
    Conclusions
-
    
-
    The results obtained with mkin deviate from the results obtained with
-PestDF either in cases where one of the interpretive rules would apply,
-i.e. the IORE parameter N is less than one or the DFOP k values obtained
-with PestDF are equal to the SFO k values, or in cases where the DFOP
-model did not converge, which often lead to negative rate constants
-returned by PestDF.
    
-
    Therefore, mkin appears to suitable for kinetic evaluations according
-to the NAFTA guidance.
    
-
    
-
    
-
    References
-
    
-
    
-
    
-US EPA. 2015. “Standard Operating Procedure for Using the NAFTA
-Guidance to Calculate Representative Half-Life Values and Characterizing
-Pesticide Degradation.” https://www.epa.gov/pesticide-science-and-assessing-pesticide-risks/standard-operating-procedure-using-nafta-guidance.
-
    
-
    
-
    
-  
    
-
-  
-
-
    
-
-
-
-      
    
-  
    
-
    Developed by Johannes Ranke.
    
-
    
-
-
    
-  
    
-
    Site built with pkgdown 2.0.7.
    
-
    
-
-      
    
-
    
-
-  
-
-
-  
-
-  
-
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-// Hide empty  tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
-// v0.0.1
-// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
-
-document.addEventListener('DOMContentLoaded', function() {
-  const codeList = document.getElementsByClassName("sourceCode");
-  for (var i = 0; i < codeList.length; i++) {
-    var linkList = codeList[i].getElementsByTagName('a');
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-      if (linkList[j].innerHTML === "") {
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-});
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-/* Styles for section anchors */
-a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
-a.anchor-section::before {content: '#';}
-.hasAnchor:hover a.anchor-section {visibility: visible;}
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-// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
-document.addEventListener('DOMContentLoaded', function() {
-  // Do nothing if AnchorJS is used
-  if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
-    return;
-  }
-
-  const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
-
-  // Do nothing if sections are already anchored
-  if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
-    return null;
-  }
-
-  // Use section id when pandoc runs with --section-divs
-  const section_id = function(x) {
-    return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
-            ? x.id : '');
-  };
-
-  // Add anchors
-  h.forEach(function(x) {
-    const id = x.id || section_id(x.parentElement);
-    if (id === '') {
-      return null;
-    }
-    let anchor = document.createElement('a');
-    anchor.href = '#' + id;
-    anchor.classList = ['anchor-section'];
-    x.classList.add('hasAnchor');
-    x.appendChild(anchor);
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-// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
-// be compatible with the behavior of Pandoc < 2.8).
-document.addEventListener('DOMContentLoaded', function(e) {
-  var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
-  var i, h, a;
-  for (i = 0; i < hs.length; i++) {
-    h = hs[i];
-    if (!/^h[1-6]$/i.test(h.tagName)) continue;  // it should be a header h1-h6
-    a = h.attributes;
-    while (a.length > 0) h.removeAttribute(a[0].name);
-  }
-});
diff --git a/docs/dev/articles/web_only/benchmarks.html b/docs/dev/articles/web_only/benchmarks.html
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-
-Benchmark timings for mkin • mkin
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-      
    Benchmark timings for mkin
    
-                        
    Johannes
-Ranke
    
-            
-            
    Last change 17 February 2023
-(rebuilt 2023-04-16)
    
-      
-      Source: vignettes/web_only/benchmarks.rmd
-      
-
-    
    
-
-    
-    
-
    Each system is characterized by the operating system type, the CPU
-type, the mkin version, and, as in June 2022 the current R version lead
-to worse performance, the R version. A compiler was available, so if no
-analytical solution was available, compiled ODE models are used.
    
-
    Every fit is only performed once, so the accuracy of the benchmarks
-is limited.
    
-
    The following wrapper function for mmkin is used because
-the way the error model is specified was changed in mkin version
-0.9.49.1.
    
-
    -if (packageVersion("mkin") > "0.9.48.1") {
-  mmkin_bench <- function(models, datasets, error_model = "const") {
-    mmkin(models, datasets, error_model = error_model, cores = 1, quiet = TRUE)
-  }
-} else {
-  mmkin_bench <- function(models, datasets, error_model = NULL) {
-    mmkin(models, datasets, reweight.method = error_model, cores = 1, quiet = TRUE)
-  }
-}
    
-
    
-
    Test cases
-
    
-
    Parent only:
    
-
    -FOCUS_C <- FOCUS_2006_C
-FOCUS_D <- subset(FOCUS_2006_D, value != 0)
-parent_datasets <- list(FOCUS_C, FOCUS_D)
-
-
-t1 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), parent_datasets))[["elapsed"]]
-t2 <- system.time(mmkin_bench(c("SFO", "FOMC", "DFOP", "HS"), parent_datasets,
-    error_model = "tc"))[["elapsed"]]
    
-
    One metabolite:
    
-
    -SFO_SFO <- mkinmod(
-  parent = mkinsub("SFO", "m1"),
-  m1 = mkinsub("SFO"))
-FOMC_SFO <- mkinmod(
-  parent = mkinsub("FOMC", "m1"),
-  m1 = mkinsub("SFO"))
-DFOP_SFO <- mkinmod(
-  parent = mkinsub("FOMC", "m1"), # erroneously used FOMC twice, not fixed for consistency
-  m1 = mkinsub("SFO"))
-t3 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D)))[["elapsed"]]
-t4 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D),
-    error_model = "tc"))[["elapsed"]]
-t5 <- system.time(mmkin_bench(list(SFO_SFO, FOMC_SFO, DFOP_SFO), list(FOCUS_D),
-    error_model = "obs"))[["elapsed"]]
    
-
    Two metabolites, synthetic data:
    
-
    -m_synth_SFO_lin <- mkinmod(parent = mkinsub("SFO", "M1"),
-                           M1 = mkinsub("SFO", "M2"),
-                           M2 = mkinsub("SFO"),
-                           use_of_ff = "max", quiet = TRUE)
-
-m_synth_DFOP_par <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")),
-                           M1 = mkinsub("SFO"),
-                           M2 = mkinsub("SFO"),
-                           use_of_ff = "max", quiet = TRUE)
-
-SFO_lin_a <- synthetic_data_for_UBA_2014[[1]]$data
-
-DFOP_par_c <- synthetic_data_for_UBA_2014[[12]]$data
-
-t6 <- system.time(mmkin_bench(list(m_synth_SFO_lin), list(SFO_lin_a)))[["elapsed"]]
-t7 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c)))[["elapsed"]]
-
-t8 <- system.time(mmkin_bench(list(m_synth_SFO_lin), list(SFO_lin_a),
-    error_model = "tc"))[["elapsed"]]
-t9 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c),
-    error_model = "tc"))[["elapsed"]]
-
-t10 <- system.time(mmkin_bench(list(m_synth_SFO_lin), list(SFO_lin_a),
-    error_model = "obs"))[["elapsed"]]
-t11 <- system.time(mmkin_bench(list(m_synth_DFOP_par), list(DFOP_par_c),
-    error_model = "obs"))[["elapsed"]]
    
-
    
-
    
-
    Results
-
    
-
    Benchmarks for all available error models are shown. They are
-intended for improving mkin, not for comparing CPUs or operating
-systems. All trademarks belong to their respective owners.
    
-
    
-
    Parent only
-
    
-
    Constant variance (t1) and two-component error model (t2) for four
-models fitted to two datasets, i.e. eight fits for each test.
    
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    OSCPURmkint1t2
    LinuxRyzen 7 1700NA0.9.48.13.61011.019
    LinuxRyzen 7 1700NA0.9.49.18.18422.889
    LinuxRyzen 7 1700NA0.9.49.27.06412.558
    LinuxRyzen 7 1700NA0.9.49.37.29621.239
    LinuxRyzen 7 1700NA0.9.49.45.93620.545
    LinuxRyzen 7 1700NA0.9.50.21.7143.971
    LinuxRyzen 7 1700NA0.9.50.31.7524.156
    LinuxRyzen 7 1700NA0.9.50.41.7863.729
    LinuxRyzen 7 1700NA1.0.31.8813.504
    LinuxRyzen 7 1700NA1.0.41.8673.450
    LinuxRyzen 7 17004.1.31.1.01.7913.289
    LinuxRyzen 7 17004.2.11.1.01.8423.453
    Linuxi7-4710MQ4.2.11.1.01.9594.116
    Linuxi7-4710MQ4.1.31.1.01.8773.906
    Linuxi7-4710MQ4.2.11.1.11.6443.172
    LinuxRyzen 7 17004.2.11.1.11.7703.377
    LinuxRyzen 7 17004.2.11.1.21.9573.633
    LinuxRyzen 7 17004.2.21.2.02.1403.774
    LinuxRyzen 7 17004.2.21.2.22.1873.851
    LinuxRyzen 9 7950X4.2.21.2.01.2881.794
    LinuxRyzen 9 7950X4.2.21.2.21.2761.804
    LinuxRyzen 9 7950X4.2.21.2.31.3701.883
    LinuxRyzen 9 7950X4.2.31.2.31.4041.933
    
-
    
-
    
-
    One metabolite
-
    
-
    Constant variance (t3), two-component error model (t4), and variance
-by variable (t5) for three models fitted to one dataset, i.e. three fits
-for each test.
    
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    OSCPURmkint3t4t5
    LinuxRyzen 7 1700NA0.9.48.13.76414.3479.495
    LinuxRyzen 7 1700NA0.9.49.14.64913.7896.395
    LinuxRyzen 7 1700NA0.9.49.24.7868.4615.675
    LinuxRyzen 7 1700NA0.9.49.34.51013.8057.386
    LinuxRyzen 7 1700NA0.9.49.44.44615.3356.002
    LinuxRyzen 7 1700NA0.9.50.21.4026.1742.764
    LinuxRyzen 7 1700NA0.9.50.31.4306.6152.878
    LinuxRyzen 7 1700NA0.9.50.41.3977.2512.810
    LinuxRyzen 7 1700NA1.0.31.4306.3442.798
    LinuxRyzen 7 1700NA1.0.41.4156.3642.820
    LinuxRyzen 7 17004.1.31.1.01.3106.2792.681
    LinuxRyzen 7 17004.2.11.1.03.80221.2478.461
    Linuxi7-4710MQ4.2.11.1.03.33419.5217.565
    Linuxi7-4710MQ4.1.31.1.01.5788.0583.339
    Linuxi7-4710MQ4.2.11.1.11.2305.8392.444
    LinuxRyzen 7 17004.2.11.1.11.3085.7582.558
    LinuxRyzen 7 17004.2.11.1.21.5036.1472.803
    LinuxRyzen 7 17004.2.21.2.01.5546.1932.843
    LinuxRyzen 7 17004.2.21.2.21.5856.3353.003
    LinuxRyzen 9 7950X4.2.21.2.00.7922.3781.245
    LinuxRyzen 9 7950X4.2.21.2.20.7842.3551.233
    LinuxRyzen 9 7950X4.2.21.2.30.7702.0111.123
    LinuxRyzen 9 7950X4.2.31.2.30.7972.1241.182
    
-
    
-
    
-
    Two metabolites
-
    
-
    Constant variance (t6 and t7), two-component error model (t8 and t9),
-and variance by variable (t10 and t11) for one model fitted to one
-dataset, i.e. one fit for each test.
    
-
------------
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    OSCPURmkint6t7t8t9t10t11
    LinuxRyzen 7 1700NA0.9.48.12.6234.5877.52516.6218.57631.267
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diff --git a/docs/dev/articles/web_only/benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/dev/articles/web_only/benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js
deleted file mode 100644
index ca349fd6..00000000
--- a/docs/dev/articles/web_only/benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js
+++ /dev/null
@@ -1,15 +0,0 @@
-// Hide empty  tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
-// v0.0.1
-// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
-
-document.addEventListener('DOMContentLoaded', function() {
-  const codeList = document.getElementsByClassName("sourceCode");
-  for (var i = 0; i < codeList.length; i++) {
-    var linkList = codeList[i].getElementsByTagName('a');
-    for (var j = 0; j < linkList.length; j++) {
-      if (linkList[j].innerHTML === "") {
-        linkList[j].setAttribute('aria-hidden', 'true');
-      }
-    }
-  }
-});
diff --git a/docs/dev/articles/web_only/benchmarks_files/anchor-sections-1.0/anchor-sections.css b/docs/dev/articles/web_only/benchmarks_files/anchor-sections-1.0/anchor-sections.css
deleted file mode 100644
index 07aee5fc..00000000
--- a/docs/dev/articles/web_only/benchmarks_files/anchor-sections-1.0/anchor-sections.css
+++ /dev/null
@@ -1,4 +0,0 @@
-/* Styles for section anchors */
-a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
-a.anchor-section::before {content: '#';}
-.hasAnchor:hover a.anchor-section {visibility: visible;}
diff --git a/docs/dev/articles/web_only/benchmarks_files/anchor-sections-1.0/anchor-sections.js b/docs/dev/articles/web_only/benchmarks_files/anchor-sections-1.0/anchor-sections.js
deleted file mode 100644
index 570f99a0..00000000
--- a/docs/dev/articles/web_only/benchmarks_files/anchor-sections-1.0/anchor-sections.js
+++ /dev/null
@@ -1,33 +0,0 @@
-// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
-document.addEventListener('DOMContentLoaded', function() {
-  // Do nothing if AnchorJS is used
-  if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
-    return;
-  }
-
-  const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
-
-  // Do nothing if sections are already anchored
-  if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
-    return null;
-  }
-
-  // Use section id when pandoc runs with --section-divs
-  const section_id = function(x) {
-    return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
-            ? x.id : '');
-  };
-
-  // Add anchors
-  h.forEach(function(x) {
-    const id = x.id || section_id(x.parentElement);
-    if (id === '') {
-      return null;
-    }
-    let anchor = document.createElement('a');
-    anchor.href = '#' + id;
-    anchor.classList = ['anchor-section'];
-    x.classList.add('hasAnchor');
-    x.appendChild(anchor);
-  });
-});
diff --git a/docs/dev/articles/web_only/benchmarks_files/header-attrs-2.6/header-attrs.js b/docs/dev/articles/web_only/benchmarks_files/header-attrs-2.6/header-attrs.js
deleted file mode 100644
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--- a/docs/dev/articles/web_only/benchmarks_files/header-attrs-2.6/header-attrs.js
+++ /dev/null
@@ -1,12 +0,0 @@
-// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
-// be compatible with the behavior of Pandoc < 2.8).
-document.addEventListener('DOMContentLoaded', function(e) {
-  var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
-  var i, h, a;
-  for (i = 0; i < hs.length; i++) {
-    h = hs[i];
-    if (!/^h[1-6]$/i.test(h.tagName)) continue;  // it should be a header h1-h6
-    a = h.attributes;
-    while (a.length > 0) h.removeAttribute(a[0].name);
-  }
-});
diff --git a/docs/dev/articles/web_only/compiled_models.html b/docs/dev/articles/web_only/compiled_models.html
deleted file mode 100644
index e7905860..00000000
--- a/docs/dev/articles/web_only/compiled_models.html
+++ /dev/null
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-
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-
-
-
-
-Performance benefit by using compiled model definitions in mkin • mkin
-
-
-
-
-
-
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-
-
-    
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-    
    
-      
    
-
-
-      
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-      
    
-  
    
-    
    
-      
    Performance benefit by using compiled model
-definitions in mkin
    
-                        
    Johannes
-Ranke
    
-            
-            
    2023-04-16
    
-      
-      Source: vignettes/web_only/compiled_models.rmd
-      
-
-    
    
-
-    
-    
-
    
-
    How to benefit from compiled models
-
    
-
    When using an mkin version equal to or greater than 0.9-36 and a C
-compiler is available, you will see a message that the model is being
-compiled from autogenerated C code when defining a model using mkinmod.
-Starting from version 0.9.49.9, the mkinmod() function
-checks for presence of a compiler using
    
-
    -pkgbuild::has_compiler()
    
-
    In previous versions, it used Sys.which("gcc") for this
-check.
    
-
    On Linux, you need to have the essential build tools like make and
-gcc or clang installed. On Debian based linux distributions, these will
-be pulled in by installing the build-essential package.
    
-
    On MacOS, which I do not use personally, I have had reports that a
-compiler is available by default.
    
-
    On Windows, you need to install Rtools and have the path to its bin
-directory in your PATH variable. You do not need to modify the PATH
-variable when installing Rtools. Instead, I would recommend to put the
-line
    
-
    -Sys.setenv(PATH = paste("C:/Rtools/bin", Sys.getenv("PATH"), sep=";"))
    
-
    into your .Rprofile startup file. This is just a text file with some
-R code that is executed when your R session starts. It has to be named
-.Rprofile and has to be located in your home directory, which will
-generally be your Documents folder. You can check the location of the
-home directory used by R by issuing
    
-
    -Sys.getenv("HOME")
    
-
    
-
    
-
    Comparison with other solution methods
-
    
-
    First, we build a simple degradation model for a parent compound with
-one metabolite, and we remove zero values from the dataset.
    
-
    -library("mkin", quietly = TRUE)
-SFO_SFO <- mkinmod(
-  parent = mkinsub("SFO", "m1"),
-  m1 = mkinsub("SFO"))
    
-
    ## Temporary DLL for differentials generated and loaded
    
-
    -FOCUS_D <- subset(FOCUS_2006_D, value != 0)
    
-
    We can compare the performance of the Eigenvalue based solution
-against the compiled version and the R implementation of the
-differential equations using the benchmark package. In the output of
-below code, the warnings about zero being removed from the FOCUS D
-dataset are suppressed. Since mkin version 0.9.49.11, an analytical
-solution is also implemented, which is included in the tests below.
    
-
    -if (require(rbenchmark)) {
-  b.1 <- benchmark(
-    "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_D,
-       solution_type = "deSolve",
-       use_compiled = FALSE, quiet = TRUE),
-    "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_D,
-       solution_type = "eigen", quiet = TRUE),
-    "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_D,
-       solution_type = "deSolve", quiet = TRUE),
-    "analytical" = mkinfit(SFO_SFO, FOCUS_D,
-       solution_type = "analytical",
-       use_compiled = FALSE, quiet = TRUE),
-    replications = 1, order = "relative",
-    columns = c("test", "replications", "relative", "elapsed"))
-  print(b.1)
-} else {
-  print("R package rbenchmark is not available")
-}
    
-
    ##                    test replications relative elapsed
-## 4            analytical            1    1.000   0.105
-## 3     deSolve, compiled            1    1.276   0.134
-## 2      Eigenvalue based            1    1.762   0.185
-## 1 deSolve, not compiled            1   21.914   2.301
    
-
    We see that using the compiled model is by more than a factor of 10
-faster than using deSolve without compiled code.
    
-
    
-
    
-
    Model without analytical solution
-
    
-
    This evaluation is also taken from the example section of mkinfit. No
-analytical solution is available for this system, and now Eigenvalue
-based solution is possible, so only deSolve using with or without
-compiled code is available.
    
-
    -if (require(rbenchmark)) {
-  FOMC_SFO <- mkinmod(
-    parent = mkinsub("FOMC", "m1"),
-    m1 = mkinsub( "SFO"))
-
-  b.2 <- benchmark(
-    "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_D,
-                                      use_compiled = FALSE, quiet = TRUE),
-    "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_D, quiet = TRUE),
-    replications = 1, order = "relative",
-    columns = c("test", "replications", "relative", "elapsed"))
-  print(b.2)
-  factor_FOMC_SFO <- round(b.2["1", "relative"])
-} else {
-  factor_FOMC_SFO <- NA
-  print("R package benchmark is not available")
-}
    
-
    ## Temporary DLL for differentials generated and loaded
    
-
    ##                    test replications relative elapsed
-## 2     deSolve, compiled            1    1.000   0.176
-## 1 deSolve, not compiled            1   23.938   4.213
    
-
    Here we get a performance benefit of a factor of 24 using the version
-of the differential equation model compiled from C code!
    
-
    This vignette was built with mkin 1.2.3 on
    
-
    ## R version 4.2.3 (2023-03-15)
-## Platform: x86_64-pc-linux-gnu (64-bit)
-## Running under: Debian GNU/Linux 12 (bookworm)
    
-
    ## CPU model: AMD Ryzen 9 7950X 16-Core Processor
    
-
    
-  
    
-
-  
-
-
    
-
-
-
-      
    
-  
    
-
    Developed by Johannes Ranke.
    
-
    
-
-
    
-  
    
-
    Site built with pkgdown 2.0.7.
    
-
    
-
-      
    
-
    
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/articles/web_only/compiled_models_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/dev/articles/web_only/compiled_models_files/accessible-code-block-0.0.1/empty-anchor.js
deleted file mode 100644
index ca349fd6..00000000
--- a/docs/dev/articles/web_only/compiled_models_files/accessible-code-block-0.0.1/empty-anchor.js
+++ /dev/null
@@ -1,15 +0,0 @@
-// Hide empty  tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
-// v0.0.1
-// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
-
-document.addEventListener('DOMContentLoaded', function() {
-  const codeList = document.getElementsByClassName("sourceCode");
-  for (var i = 0; i < codeList.length; i++) {
-    var linkList = codeList[i].getElementsByTagName('a');
-    for (var j = 0; j < linkList.length; j++) {
-      if (linkList[j].innerHTML === "") {
-        linkList[j].setAttribute('aria-hidden', 'true');
-      }
-    }
-  }
-});
diff --git a/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.css b/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.css
deleted file mode 100644
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--- a/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.css
+++ /dev/null
@@ -1,4 +0,0 @@
-/* Styles for section anchors */
-a.anchor-section {margin-left: 10px; visibility: hidden; color: inherit;}
-a.anchor-section::before {content: '#';}
-.hasAnchor:hover a.anchor-section {visibility: visible;}
diff --git a/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.js b/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.js
deleted file mode 100644
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--- a/docs/dev/articles/web_only/compiled_models_files/anchor-sections-1.0/anchor-sections.js
+++ /dev/null
@@ -1,33 +0,0 @@
-// Anchor sections v1.0 written by Atsushi Yasumoto on Oct 3rd, 2020.
-document.addEventListener('DOMContentLoaded', function() {
-  // Do nothing if AnchorJS is used
-  if (typeof window.anchors === 'object' && anchors.hasOwnProperty('hasAnchorJSLink')) {
-    return;
-  }
-
-  const h = document.querySelectorAll('h1, h2, h3, h4, h5, h6');
-
-  // Do nothing if sections are already anchored
-  if (Array.from(h).some(x => x.classList.contains('hasAnchor'))) {
-    return null;
-  }
-
-  // Use section id when pandoc runs with --section-divs
-  const section_id = function(x) {
-    return ((x.classList.contains('section') || (x.tagName === 'SECTION'))
-            ? x.id : '');
-  };
-
-  // Add anchors
-  h.forEach(function(x) {
-    const id = x.id || section_id(x.parentElement);
-    if (id === '') {
-      return null;
-    }
-    let anchor = document.createElement('a');
-    anchor.href = '#' + id;
-    anchor.classList = ['anchor-section'];
-    x.classList.add('hasAnchor');
-    x.appendChild(anchor);
-  });
-});
diff --git a/docs/dev/articles/web_only/compiled_models_files/header-attrs-2.6/header-attrs.js b/docs/dev/articles/web_only/compiled_models_files/header-attrs-2.6/header-attrs.js
deleted file mode 100644
index dd57d92e..00000000
--- a/docs/dev/articles/web_only/compiled_models_files/header-attrs-2.6/header-attrs.js
+++ /dev/null
@@ -1,12 +0,0 @@
-// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
-// be compatible with the behavior of Pandoc < 2.8).
-document.addEventListener('DOMContentLoaded', function(e) {
-  var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
-  var i, h, a;
-  for (i = 0; i < hs.length; i++) {
-    h = hs[i];
-    if (!/^h[1-6]$/i.test(h.tagName)) continue;  // it should be a header h1-h6
-    a = h.attributes;
-    while (a.length > 0) h.removeAttribute(a[0].name);
-  }
-});
diff --git a/docs/dev/articles/web_only/dimethenamid_2018.html b/docs/dev/articles/web_only/dimethenamid_2018.html
deleted file mode 100644
index eb4a11a5..00000000
--- a/docs/dev/articles/web_only/dimethenamid_2018.html
+++ /dev/null
@@ -1,710 +0,0 @@
-
-
-
-
-
-
-
-Example evaluations of the dimethenamid data from 2018 • mkin
-
-
-
-
-
-
-
-
-
-
-
-    
-
-    
    
-      
    
-
-
-      
-
-      
    
-  
    
-    
    
-      
    Example evaluations of the dimethenamid data
-from 2018
    
-                        
    Johannes
-Ranke
    
-            
-            
    Last change 1 July 2022,
-built on 16 Apr 2023
    
-      
-      Source: vignettes/web_only/dimethenamid_2018.rmd
-      
-
-    
    
-
-    
-    
-
    Wissenschaftlicher Berater, Kronacher
-Str. 12, 79639 Grenzach-Wyhlen, Germany
    
-
    
-
    Introduction
-
    
-
    A first analysis of the data analysed here was presented in a recent
-journal article on nonlinear mixed-effects models in degradation
-kinetics (Ranke et al. 2021). That
-analysis was based on the nlme package and a development
-version of the saemix package that was unpublished at the
-time. Meanwhile, version 3.0 of the saemix package is
-available from the CRAN repository. Also, it turned out that there was
-an error in the handling of the Borstel data in the mkin package at the
-time, leading to the duplication of a few data points from that soil.
-The dataset in the mkin package has been corrected, and the interface to
-saemix in the mkin package has been updated to use the
-released version.
    
-
    This vignette is intended to present an up to date analysis of the
-data, using the corrected dataset and released versions of
-mkin and saemix.
    
-
    
-
    
-
    Data
-
    
-
    Residue data forming the basis for the endpoints derived in the
-conclusion on the peer review of the pesticide risk assessment of
-dimethenamid-P published by the European Food Safety Authority (EFSA) in
-2018 (EFSA 2018) were transcribed from the
-risk assessment report (Rapporteur Member State
-Germany, Co-Rapporteur Member State Bulgaria 2018) which can be
-downloaded from the Open EFSA repository https://open.efsa.europa.eu/study-inventory/EFSA-Q-2014-00716.
    
-
    The data are available
-in the mkin package. The following code (hidden by default, please
-use the button to the right to show it) treats the data available for
-the racemic mixture dimethenamid (DMTA) and its enantiomer
-dimethenamid-P (DMTAP) in the same way, as no difference between their
-degradation behaviour was identified in the EU risk assessment. The
-observation times of each dataset are multiplied with the corresponding
-normalisation factor also available in the dataset, in order to make it
-possible to describe all datasets with a single set of parameters.
    
-
    Also, datasets observed in the same soil are merged, resulting in
-dimethenamid (DMTA) data from six soils.
    
-
    -library(mkin, quietly = TRUE)
-dmta_ds <- lapply(1:7, function(i) {
-  ds_i <- dimethenamid_2018$ds[[i]]$data
-  ds_i[ds_i$name == "DMTAP", "name"] <-  "DMTA"
-  ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i]
-  ds_i
-})
-names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title)
-dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]])
-dmta_ds[["Elliot 1"]] <- NULL
-dmta_ds[["Elliot 2"]] <- NULL
    
-
    
-
    
-
    Parent degradation
-
    
-
    We evaluate the observed degradation of the parent compound using
-simple exponential decline (SFO) and biexponential decline (DFOP), using
-constant variance (const) and a two-component variance (tc) as error
-models.
    
-
    
-
    Separate evaluations
-
    
-
    As a first step, to get a visual impression of the fit of the
-different models, we do separate evaluations for each soil using the
-mmkin function from the mkin package:
    
-
    -f_parent_mkin_const <- mmkin(c("SFO", "DFOP"), dmta_ds,
-  error_model = "const", quiet = TRUE)
-f_parent_mkin_tc <- mmkin(c("SFO", "DFOP"), dmta_ds,
-  error_model = "tc", quiet = TRUE)
    
-
    The plot of the individual SFO fits shown below suggests that at
-least in some datasets the degradation slows down towards later time
-points, and that the scatter of the residuals error is smaller for
-smaller values (panel to the right):
    
-
    -plot(mixed(f_parent_mkin_const["SFO", ]))
    
-
    
-
    Using biexponential decline (DFOP) results in a slightly more random
-scatter of the residuals:
    
-
    -plot(mixed(f_parent_mkin_const["DFOP", ]))
    
-
    
-
    The population curve (bold line) in the above plot results from
-taking the mean of the individual transformed parameters, i.e. of log k1
-and log k2, as well as of the logit of the g parameter of the DFOP
-model). Here, this procedure does not result in parameters that
-represent the degradation well, because in some datasets the fitted
-value for k2 is extremely close to zero, leading to a log k2 value that
-dominates the average. This is alleviated if only rate constants that
-pass the t-test for significant difference from zero (on the
-untransformed scale) are considered in the averaging:
    
-
    -plot(mixed(f_parent_mkin_const["DFOP", ]), test_log_parms = TRUE)
    
-
    
-
    While this is visually much more satisfactory, such an average
-procedure could introduce a bias, as not all results from the individual
-fits enter the population curve with the same weight. This is where
-nonlinear mixed-effects models can help out by treating all datasets
-with equally by fitting a parameter distribution model together with the
-degradation model and the error model (see below).
    
-
    The remaining trend of the residuals to be higher for higher
-predicted residues is reduced by using the two-component error
-model:
    
-
    -plot(mixed(f_parent_mkin_tc["DFOP", ]), test_log_parms = TRUE)
    
-
    
-
    However, note that in the case of using this error model, the fits to
-the Flaach and BBA 2.3 datasets appear to be ill-defined, indicated by
-the fact that they did not converge:
    
-
    -print(f_parent_mkin_tc["DFOP", ])
    
-
    <mmkin> object
-Status of individual fits:
-
-      dataset
-model  Calke Borstel Flaach BBA 2.2 BBA 2.3 Elliot
-  DFOP OK    OK      C      OK      C       OK    
-
-C: Optimisation did not converge:
-iteration limit reached without convergence (10)
-OK: No warnings
    
-
    
-
    
-
    Nonlinear mixed-effects models
-
    
-
    Instead of taking a model selection decision for each of the
-individual fits, we fit nonlinear mixed-effects models (using different
-fitting algorithms as implemented in different packages) and do model
-selection using all available data at the same time. In order to make
-sure that these decisions are not unduly influenced by the type of
-algorithm used, by implementation details or by the use of wrong control
-parameters, we compare the model selection results obtained with
-different R packages, with different algorithms and checking control
-parameters.
    
-
    
-
    nlme
-
    
-
    The nlme package was the first R extension providing facilities to
-fit nonlinear mixed-effects models. We would like to do model selection
-from all four combinations of degradation models and error models based
-on the AIC. However, fitting the DFOP model with constant variance and
-using default control parameters results in an error, signalling that
-the maximum number of 50 iterations was reached, potentially indicating
-overparameterisation. Nevertheless, the algorithm converges when the
-two-component error model is used in combination with the DFOP model.
-This can be explained by the fact that the smaller residues observed at
-later sampling times get more weight when using the two-component error
-model which will counteract the tendency of the algorithm to try
-parameter combinations unsuitable for fitting these data.
    
-
    -library(nlme)
-f_parent_nlme_sfo_const <- nlme(f_parent_mkin_const["SFO", ])
-# f_parent_nlme_dfop_const <- nlme(f_parent_mkin_const["DFOP", ])
-f_parent_nlme_sfo_tc <- nlme(f_parent_mkin_tc["SFO", ])
-f_parent_nlme_dfop_tc <- nlme(f_parent_mkin_tc["DFOP", ])
    
-
    Note that a certain degree of overparameterisation is also indicated
-by a warning obtained when fitting DFOP with the two-component error
-model (‘false convergence’ in the ‘LME step’ in iteration 3). However,
-as this warning does not occur in later iterations, and specifically not
-in the last of the 5 iterations, we can ignore this warning.
    
-
    The model comparison function of the nlme package can directly be
-applied to these fits showing a much lower AIC for the DFOP model fitted
-with the two-component error model. Also, the likelihood ratio test
-indicates that this difference is significant as the p-value is below
-0.0001.
    
-
    -anova(
-  f_parent_nlme_sfo_const, f_parent_nlme_sfo_tc, f_parent_nlme_dfop_tc
-)
    
-
                            Model df    AIC    BIC  logLik   Test L.Ratio p-value
-f_parent_nlme_sfo_const     1  5 796.60 811.82 -393.30                       
-f_parent_nlme_sfo_tc        2  6 798.60 816.86 -393.30 1 vs 2    0.00   0.998
-f_parent_nlme_dfop_tc       3 10 671.91 702.34 -325.96 2 vs 3  134.69  <.0001
    
-
    In addition to these fits, attempts were also made to include
-correlations between random effects by using the log Cholesky
-parameterisation of the matrix specifying them. The code used for these
-attempts can be made visible below.
    
-
    -f_parent_nlme_sfo_const_logchol <- nlme(f_parent_mkin_const["SFO", ],
-  random = nlme::pdLogChol(list(DMTA_0 ~ 1, log_k_DMTA ~ 1)))
-anova(f_parent_nlme_sfo_const, f_parent_nlme_sfo_const_logchol)
-f_parent_nlme_sfo_tc_logchol <- nlme(f_parent_mkin_tc["SFO", ],
-  random = nlme::pdLogChol(list(DMTA_0 ~ 1, log_k_DMTA ~ 1)))
-anova(f_parent_nlme_sfo_tc, f_parent_nlme_sfo_tc_logchol)
-f_parent_nlme_dfop_tc_logchol <- nlme(f_parent_mkin_const["DFOP", ],
-  random = nlme::pdLogChol(list(DMTA_0 ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1)))
-anova(f_parent_nlme_dfop_tc, f_parent_nlme_dfop_tc_logchol)
    
-
    While the SFO variants converge fast, the additional parameters
-introduced by this lead to convergence warnings for the DFOP model. The
-model comparison clearly show that adding correlations between random
-effects does not improve the fits.
    
-
    The selected model (DFOP with two-component error) fitted to the data
-assuming no correlations between random effects is shown below.
    
-
    -plot(f_parent_nlme_dfop_tc)
    
-
    
-
    
-
    
-
    saemix
-
    
-
    The saemix package provided the first Open Source implementation of
-the Stochastic Approximation to the Expectation Maximisation (SAEM)
-algorithm. SAEM fits of degradation models can be conveniently performed
-using an interface to the saemix package available in current
-development versions of the mkin package.
    
-
    The corresponding SAEM fits of the four combinations of degradation
-and error models are fitted below. As there is no convergence criterion
-implemented in the saemix package, the convergence plots need to be
-manually checked for every fit. We define control settings that work
-well for all the parent data fits shown in this vignette.
    
-
    -library(saemix)
-saemix_control <- saemixControl(nbiter.saemix = c(800, 300), nb.chains = 15,
-    print = FALSE, save = FALSE, save.graphs = FALSE, displayProgress = FALSE)
-saemix_control_moreiter <- saemixControl(nbiter.saemix = c(1600, 300), nb.chains = 15,
-    print = FALSE, save = FALSE, save.graphs = FALSE, displayProgress = FALSE)
-saemix_control_10k <- saemixControl(nbiter.saemix = c(10000, 300), nb.chains = 15,
-    print = FALSE, save = FALSE, save.graphs = FALSE, displayProgress = FALSE)
    
-
    The convergence plot for the SFO model using constant variance is
-shown below.
    
-
    -f_parent_saemix_sfo_const <- mkin::saem(f_parent_mkin_const["SFO", ], quiet = TRUE,
-  control = saemix_control, transformations = "saemix")
-plot(f_parent_saemix_sfo_const$so, plot.type = "convergence")
    
-
    
-
    Obviously the selected number of iterations is sufficient to reach
-convergence. This can also be said for the SFO fit using the
-two-component error model.
    
-
    -f_parent_saemix_sfo_tc <- mkin::saem(f_parent_mkin_tc["SFO", ], quiet = TRUE,
-  control = saemix_control, transformations = "saemix")
-plot(f_parent_saemix_sfo_tc$so, plot.type = "convergence")
    
-
    
-
    When fitting the DFOP model with constant variance (see below),
-parameter convergence is not as unambiguous.
    
-
    -f_parent_saemix_dfop_const <- mkin::saem(f_parent_mkin_const["DFOP", ], quiet = TRUE,
-  control = saemix_control, transformations = "saemix")
-plot(f_parent_saemix_dfop_const$so, plot.type = "convergence")
    
-
    
-
    -print(f_parent_saemix_dfop_const)
    
-
    Kinetic nonlinear mixed-effects model fit by SAEM
-Structural model:
-d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-           time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-           * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Likelihood computed by importance sampling
-  AIC BIC logLik
-  706 704   -344
-
-Fitted parameters:
-          estimate    lower   upper
-DMTA_0    97.99583 96.50079 99.4909
-k1         0.06377  0.03432  0.0932
-k2         0.00848  0.00444  0.0125
-g          0.95701  0.91313  1.0009
-a.1        1.82141  1.65122  1.9916
-SD.DMTA_0  1.64787  0.45772  2.8380
-SD.k1      0.57439  0.24731  0.9015
-SD.k2      0.03296 -2.50195  2.5679
-SD.g       1.10266  0.32369  1.8816
    
-
    While the other parameters converge to credible values, the variance
-of k2 (omega2.k2) converges to a very small value. The
-printout of the saem.mmkin model shows that the estimated
-standard deviation of k2 across the population of soils
-(SD.k2) is ill-defined, indicating overparameterisation of
-this model.
    
-
    When the DFOP model is fitted with the two-component error model, we
-also observe that the estimated variance of k2 becomes very small, while
-being ill-defined, as illustrated by the excessive confidence interval
-of SD.k2.
    
-
    -f_parent_saemix_dfop_tc <- mkin::saem(f_parent_mkin_tc["DFOP", ], quiet = TRUE,
-  control = saemix_control, transformations = "saemix")
-f_parent_saemix_dfop_tc_moreiter <- mkin::saem(f_parent_mkin_tc["DFOP", ], quiet = TRUE,
-  control = saemix_control_moreiter, transformations = "saemix")
-plot(f_parent_saemix_dfop_tc$so, plot.type = "convergence")
    
-
    
-
    -print(f_parent_saemix_dfop_tc)
    
-
    Kinetic nonlinear mixed-effects model fit by SAEM
-Structural model:
-d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-           time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-           * DMTA
-
-Data:
-155 observations of 1 variable(s) grouped in 6 datasets
-
-Likelihood computed by importance sampling
-  AIC BIC logLik
-  666 664   -323
-
-Fitted parameters:
-          estimate    lower    upper
-DMTA_0    98.27617  96.3088 100.2436
-k1         0.06437   0.0337   0.0950
-k2         0.00880   0.0063   0.0113
-g          0.95249   0.9100   0.9949
-a.1        1.06161   0.8625   1.2607
-b.1        0.02967   0.0226   0.0367
-SD.DMTA_0  2.06075   0.4187   3.7028
-SD.k1      0.59357   0.2561   0.9310
-SD.k2      0.00292 -10.2960  10.3019
-SD.g       1.05725   0.3808   1.7337
    
-
    Doubling the number of iterations in the first phase of the algorithm
-leads to a slightly lower likelihood, and therefore to slightly higher
-AIC and BIC values. With even more iterations, the algorithm stops with
-an error message. This is related to the variance of k2 approximating
-zero and has been submitted as a bug
-to the saemix package, as the algorithm does not converge in this
-case.
    
-
    An alternative way to fit DFOP in combination with the two-component
-error model is to use the model formulation with transformed parameters
-as used per default in mkin. When using this option, convergence is
-slower, but eventually the algorithm stops as well with the same error
-message.
    
-
    The four combinations (SFO/const, SFO/tc, DFOP/const and DFOP/tc) and
-the version with increased iterations can be compared using the model
-comparison function of the saemix package:
    
-
    -AIC_parent_saemix <- saemix::compare.saemix(
-  f_parent_saemix_sfo_const$so,
-  f_parent_saemix_sfo_tc$so,
-  f_parent_saemix_dfop_const$so,
-  f_parent_saemix_dfop_tc$so,
-  f_parent_saemix_dfop_tc_moreiter$so)
    
-
    Likelihoods calculated by importance sampling
    
-
    -rownames(AIC_parent_saemix) <- c(
-  "SFO const", "SFO tc", "DFOP const", "DFOP tc", "DFOP tc more iterations")
-print(AIC_parent_saemix)
    
-
                               AIC    BIC
-SFO const               796.38 795.34
-SFO tc                  798.38 797.13
-DFOP const              705.75 703.88
-DFOP tc                 665.65 663.57
-DFOP tc more iterations 665.88 663.80
    
-
    In order to check the influence of the likelihood calculation
-algorithms implemented in saemix, the likelihood from Gaussian
-quadrature is added to the best fit, and the AIC values obtained from
-the three methods are compared.
    
-
    -f_parent_saemix_dfop_tc$so <-
-  saemix::llgq.saemix(f_parent_saemix_dfop_tc$so)
-AIC_parent_saemix_methods <- c(
-  is = AIC(f_parent_saemix_dfop_tc$so, method = "is"),
-  gq = AIC(f_parent_saemix_dfop_tc$so, method = "gq"),
-  lin = AIC(f_parent_saemix_dfop_tc$so, method = "lin")
-)
-print(AIC_parent_saemix_methods)
    
-
        is     gq    lin 
-665.65 665.68 665.11 
    
-
    The AIC values based on importance sampling and Gaussian quadrature
-are very similar. Using linearisation is known to be less accurate, but
-still gives a similar value.
    
-
    In order to illustrate that the comparison of the three method
-depends on the degree of convergence obtained in the fit, the same
-comparison is shown below for the fit using the defaults for the number
-of iterations and the number of MCMC chains.
    
-
    When using OpenBlas for linear algebra, there is a large difference
-in the values obtained with Gaussian quadrature, so the larger number of
-iterations makes a lot of difference. When using the LAPACK version
-coming with Debian Bullseye, the AIC based on Gaussian quadrature is
-almost the same as the one obtained with the other methods, also when
-using defaults for the fit.
    
-
    -f_parent_saemix_dfop_tc_defaults <- mkin::saem(f_parent_mkin_tc["DFOP", ])
-f_parent_saemix_dfop_tc_defaults$so <-
-  saemix::llgq.saemix(f_parent_saemix_dfop_tc_defaults$so)
-AIC_parent_saemix_methods_defaults <- c(
-  is = AIC(f_parent_saemix_dfop_tc_defaults$so, method = "is"),
-  gq = AIC(f_parent_saemix_dfop_tc_defaults$so, method = "gq"),
-  lin = AIC(f_parent_saemix_dfop_tc_defaults$so, method = "lin")
-)
-print(AIC_parent_saemix_methods_defaults)
    
-
        is     gq    lin 
-669.77 669.36 670.95 
    
-
    
-
    
-
    
-
    Comparison
-
    
-
    The following table gives the AIC values obtained with both backend
-packages using the same control parameters (800 iterations burn-in, 300
-iterations second phase, 15 chains).
    
-
    -AIC_all <- data.frame(
-  check.names = FALSE,
-  "Degradation model" = c("SFO", "SFO", "DFOP", "DFOP"),
-  "Error model" = c("const", "tc", "const", "tc"),
-  nlme = c(AIC(f_parent_nlme_sfo_const), AIC(f_parent_nlme_sfo_tc), NA, AIC(f_parent_nlme_dfop_tc)),
-  saemix_lin = sapply(list(f_parent_saemix_sfo_const$so, f_parent_saemix_sfo_tc$so,
-    f_parent_saemix_dfop_const$so, f_parent_saemix_dfop_tc$so), AIC, method = "lin"),
-  saemix_is = sapply(list(f_parent_saemix_sfo_const$so, f_parent_saemix_sfo_tc$so,
-    f_parent_saemix_dfop_const$so, f_parent_saemix_dfop_tc$so), AIC, method = "is")
-)
-kable(AIC_all)
    
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
    Degradation modelError modelnlmesaemix_linsaemix_is
    SFOconst796.60796.60796.38
    SFOtc798.60798.60798.38
    DFOPconstNA709.26705.75
    DFOPtc671.91665.11665.65
    
-
    
-
    
-
    
-
    Conclusion
-
    
-
    A more detailed analysis of the dimethenamid dataset confirmed that
-the DFOP model provides the most appropriate description of the decline
-of the parent compound in these data. On the other hand, closer
-inspection of the results revealed that the variability of the k2
-parameter across the population of soils is ill-defined. This coincides
-with the observation that this parameter cannot robustly be quantified
-for some of the soils.
    
-
    Regarding the regulatory use of these data, it is claimed that an
-improved characterisation of the mean parameter values across the
-population is obtained using the nonlinear mixed-effects models
-presented here. However, attempts to quantify the variability of the
-slower rate constant of the biphasic decline of dimethenamid indicate
-that the data are not sufficient to characterise this variability to a
-satisfactory precision.
    
-
    
-
    
-
    Session Info
-
    
-
-
    R version 4.2.3 (2023-03-15)
-Platform: x86_64-pc-linux-gnu (64-bit)
-Running under: Debian GNU/Linux 12 (bookworm)
-
-Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/openblas-serial/libblas.so.3
-LAPACK: /usr/lib/x86_64-linux-gnu/openblas-serial/libopenblas-r0.3.21.so
-
-locale:
- [1] LC_CTYPE=de_DE.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=C                  LC_COLLATE=de_DE.UTF-8    
- [5] LC_MONETARY=de_DE.UTF-8    LC_MESSAGES=de_DE.UTF-8   
- [7] LC_PAPER=de_DE.UTF-8       LC_NAME=C                 
- [9] LC_ADDRESS=C               LC_TELEPHONE=C            
-[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C       
-
-attached base packages:
-[1] stats     graphics  grDevices utils     datasets  methods   base     
-
-other attached packages:
-[1] saemix_3.2   npde_3.3     nlme_3.1-162 mkin_1.2.3   knitr_1.42  
-
-loaded via a namespace (and not attached):
- [1] highr_0.10        pillar_1.9.0      bslib_0.4.2       compiler_4.2.3   
- [5] jquerylib_0.1.4   tools_4.2.3       mclust_6.0.0      digest_0.6.31    
- [9] tibble_3.2.1      jsonlite_1.8.4    evaluate_0.20     memoise_2.0.1    
-[13] lifecycle_1.0.3   gtable_0.3.3      lattice_0.21-8    pkgconfig_2.0.3  
-[17] rlang_1.1.0       DBI_1.1.3         cli_3.6.1         yaml_2.3.7       
-[21] parallel_4.2.3    pkgdown_2.0.7     xfun_0.38         fastmap_1.1.1    
-[25] gridExtra_2.3     dplyr_1.1.1       stringr_1.5.0     generics_0.1.3   
-[29] desc_1.4.2        fs_1.6.1          vctrs_0.6.1       sass_0.4.5       
-[33] systemfonts_1.0.4 tidyselect_1.2.0  rprojroot_2.0.3   lmtest_0.9-40    
-[37] grid_4.2.3        glue_1.6.2        R6_2.5.1          textshaping_0.3.6
-[41] fansi_1.0.4       rmarkdown_2.21    purrr_1.0.1       ggplot2_3.4.2    
-[45] magrittr_2.0.3    codetools_0.2-19  scales_1.2.1      htmltools_0.5.5  
-[49] colorspace_2.1-0  ragg_1.2.5        utf8_1.2.3        stringi_1.7.12   
-[53] munsell_0.5.0     cachem_1.0.7      zoo_1.8-12       
    
-
    
-
    
-
    References
-
    
-
-
    
-
    
-EFSA. 2018. “Peer Review of the Pesticide Risk Assessment of the
-Active Substance Dimethenamid-p.” EFSA Journal 16: 5211.
-
    
-
    
-Ranke, Johannes, Janina Wöltjen, Jana Schmidt, and Emmanuelle Comets.
-2021. “Taking Kinetic Evaluations of Degradation Data to the Next
-Level with Nonlinear Mixed-Effects Models.” Environments
-8 (8). https://doi.org/10.3390/environments8080071.
-
    
-
    
-Rapporteur Member State Germany, Co-Rapporteur Member State Bulgaria.
-2018. “Renewal Assessment Report
-Dimethenamid-P Volume 3 - B.8 Environmental fate and behaviour, Rev. 2 -
-November 2017.” https://open.efsa.europa.eu/study-inventory/EFSA-Q-2014-00716.
-
    
-
    
-
    
-  
    
-
-  
-
-
    
-
-
-
-      
    
-  
    
-
    Developed by Johannes Ranke.
    
-
    
-
-
    
-  
    
-
    Site built with pkgdown 2.0.7.
    
-
    
-
-      
    
-
    
-
-  
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-
-  
-
-  
-
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-// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
-// be compatible with the behavior of Pandoc < 2.8).
-document.addEventListener('DOMContentLoaded', function(e) {
-  var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
-  var i, h, a;
-  for (i = 0; i < hs.length; i++) {
-    h = hs[i];
-    if (!/^h[1-6]$/i.test(h.tagName)) continue;  // it should be a header h1-h6
-    a = h.attributes;
-    while (a.length > 0) h.removeAttribute(a[0].name);
-  }
-});
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-// Pandoc 2.9 adds attributes on both header and div. We remove the former (to
-// be compatible with the behavior of Pandoc < 2.8).
-document.addEventListener('DOMContentLoaded', function(e) {
-  var hs = document.querySelectorAll("div.section[class*='level'] > :first-child");
-  var i, h, a;
-  for (i = 0; i < hs.length; i++) {
-    h = hs[i];
-    if (!/^h[1-6]$/i.test(h.tagName)) continue;  // it should be a header h1-h6
-    a = h.attributes;
-    while (a.length > 0) h.removeAttribute(a[0].name);
-  }
-});
diff --git a/docs/dev/articles/web_only/multistart.html b/docs/dev/articles/web_only/multistart.html
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-
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-
-Short demo of the multistart method • mkin
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-      
    
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-      
    Short demo of the multistart method
    
-                        
    Johannes
-Ranke
    
-            
-            
    Last change 20 April 2023
-(rebuilt 2023-04-20)
    
-      
-      Source: vignettes/web_only/multistart.rmd
-      
-
-    
    
-
-    
-    
-
    The dimethenamid data from 2018 from seven soils is used as example
-data in this vignette.
    
-
    -library(mkin)
-dmta_ds <- lapply(1:7, function(i) {
-  ds_i <- dimethenamid_2018$ds[[i]]$data
-  ds_i[ds_i$name == "DMTAP", "name"] <-  "DMTA"
-  ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i]
-  ds_i
-})
-names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title)
-dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]])
-dmta_ds[["Elliot 1"]] <- dmta_ds[["Elliot 2"]] <- NULL
    
-
    First, we check the DFOP model with the two-component error model and
-random effects for all degradation parameters.
    
-
    -f_mmkin <- mmkin("DFOP", dmta_ds, error_model = "tc", cores = 7, quiet = TRUE)
-f_saem_full <- saem(f_mmkin)
-illparms(f_saem_full)
    
-
    ## [1] "sd(log_k2)"
    
-
    We see that not all variability parameters are identifiable. The
-illparms function tells us that the confidence interval for
-the standard deviation of ‘log_k2’ includes zero. We check this
-assessment using multiple runs with different starting values.
    
-
    -f_saem_full_multi <- multistart(f_saem_full, n = 16, cores = 16)
-parplot(f_saem_full_multi, lpos = "topleft")
    
-
    
-
    This confirms that the variance of k2 is the most problematic
-parameter, so we reduce the parameter distribution model by removing the
-intersoil variability for k2.
    
-
    -f_saem_reduced <- stats::update(f_saem_full, no_random_effect = "log_k2")
-illparms(f_saem_reduced)
-f_saem_reduced_multi <- multistart(f_saem_reduced, n = 16, cores = 16)
-parplot(f_saem_reduced_multi, lpos = "topright", ylim = c(0.5, 2))
    
-
    
-
    The results confirm that all remaining parameters can be determined
-with sufficient certainty.
    
-
    We can also analyse the log-likelihoods obtained in the multiple
-runs:
    
-
    -llhist(f_saem_reduced_multi)
    
-
    
-
    We can use the anova method to compare the models.
    
-
    -anova(f_saem_full, best(f_saem_full_multi),
-  f_saem_reduced, best(f_saem_reduced_multi), test = TRUE)
    
-
    ## Data: 155 observations of 1 variable(s) grouped in 6 datasets
-## 
-##                            npar    AIC    BIC     Lik  Chisq Df Pr(>Chisq)
-## f_saem_reduced                9 663.73 661.86 -322.86                     
-## best(f_saem_reduced_multi)    9 663.69 661.82 -322.85 0.0361  0           
-## f_saem_full                  10 669.77 667.69 -324.89 0.0000  1          1
-## best(f_saem_full_multi)      10 665.56 663.48 -322.78 4.2060  0
    
-
    The reduced model results in lower AIC and BIC values, so it is
-clearly preferable. Using multiple starting values gives a large
-improvement in case of the full model, because it is less well-defined,
-which impedes convergence. For the reduced model, using multiple
-starting values only results in a small improvement of the model
-fit.
    
-  
    
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-      
    
-  
    
-
    Developed by Johannes Ranke.
    
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-
    Site built with pkgdown 2.0.7.
    
-
    
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-      
    
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-// Hide empty  tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
-// v0.0.1
-// Written by JooYoung Seo (jooyoung@psu.edu) and Atsushi Yasumoto on June 1st, 2020.
-
-document.addEventListener('DOMContentLoaded', function() {
-  const codeList = document.getElementsByClassName("sourceCode");
-  for (var i = 0; i < codeList.length; i++) {
-    var linkList = codeList[i].getElementsByTagName('a');
-    for (var j = 0; j < linkList.length; j++) {
-      if (linkList[j].innerHTML === "") {
-        linkList[j].setAttribute('aria-hidden', 'true');
-      }
-    }
-  }
-});
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-
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-
-
-Benchmark timings for saem.mmkin • mkin
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-    
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-      
    
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-      
    Benchmark timings for saem.mmkin
    
-                        
    Johannes
-Ranke
    
-            
-            
    Last change 17 February 2023
-(rebuilt 2023-04-16)
    
-      
-      Source: vignettes/web_only/saem_benchmarks.rmd
-      
-
-    
    
-
-    
-    
-
    Each system is characterized by operating system type, CPU type, mkin
-version, saemix version and R version. A compiler was available, so if
-no analytical solution was available, compiled ODE models are used.
    
-
    Every fit is only performed once, so the accuracy of the benchmarks
-is limited.
    
-
    For the initial mmkin fits, we use all available cores.
    
-
    -n_cores <- parallel::detectCores()
    
-
    
-
    Test data
-
    
-
    Please refer to the vignette dimethenamid_2018 for an
-explanation of the following preprocessing.
    
-
    -dmta_ds <- lapply(1:7, function(i) {
-  ds_i <- dimethenamid_2018$ds[[i]]$data
-  ds_i[ds_i$name == "DMTAP", "name"] <-  "DMTA"
-  ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i]
-  ds_i
-})
-names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title)
-dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]])
-dmta_ds[["Elliot 1"]] <- NULL
-dmta_ds[["Elliot 2"]] <- NULL
    
-
    
-
    
-
    Test cases
-
    
-
    
-
    Parent only
-
    
-
    -parent_mods <- c("SFO", "DFOP", "SFORB", "HS")
-parent_sep_const <- mmkin(parent_mods, dmta_ds, quiet = TRUE, cores = n_cores)
-parent_sep_tc <- update(parent_sep_const, error_model = "tc")
-
-t1 <- system.time(sfo_const <- saem(parent_sep_const["SFO", ]))[["elapsed"]]
-t2 <- system.time(dfop_const <- saem(parent_sep_const["DFOP", ]))[["elapsed"]]
-t3 <- system.time(sforb_const <- saem(parent_sep_const["SFORB", ]))[["elapsed"]]
-t4 <- system.time(hs_const <- saem(parent_sep_const["HS", ]))[["elapsed"]]
-t5 <- system.time(sfo_tc <- saem(parent_sep_tc["SFO", ]))[["elapsed"]]
-t6 <- system.time(dfop_tc <- saem(parent_sep_tc["DFOP", ]))[["elapsed"]]
-t7 <- system.time(sforb_tc <- saem(parent_sep_tc["SFORB", ]))[["elapsed"]]
-t8 <- system.time(hs_tc <- saem(parent_sep_tc["HS", ]))[["elapsed"]]
    
-
    -anova(
-  sfo_const, dfop_const, sforb_const, hs_const,
-  sfo_tc, dfop_tc, sforb_tc, hs_tc) |> kable(, digits = 1)
    
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    nparAICBICLik
    sfo_const5796.3795.3-393.2
    sfo_tc6798.3797.1-393.2
    dfop_const9709.4707.5-345.7
    sforb_const9710.0708.1-346.0
    hs_const9713.7711.8-347.8
    dfop_tc10669.8667.7-324.9
    sforb_tc10662.8660.7-321.4
    hs_tc10667.3665.2-323.6
    
-
    The above model comparison suggests to use the SFORB model with
-two-component error. For comparison, we keep the DFOP model with
-two-component error, as it competes with SFORB for biphasic curves.
    
-
    -illparms(dfop_tc)
    
-
    ## [1] "sd(log_k2)"
    
-
    -illparms(sforb_tc)
    
-
    ## [1] "sd(log_k_DMTA_bound_free)"
    
-
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-k2 and k_DMTA_bound_free could not be
-quantified.
    
-
    
-
    
-
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-
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-only fits.
    
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    -one_met_mods <- list(
-  DFOP_SFO = mkinmod(
-    DMTA = mkinsub("DFOP", "M23"),
-    M23 = mkinsub("SFO")),
-  SFORB_SFO = mkinmod(
-    DMTA = mkinsub("SFORB", "M23"),
-    M23 = mkinsub("SFO")))
-
-one_met_sep_const <- mmkin(one_met_mods, dmta_ds, error_model = "const",
-  cores = n_cores, quiet = TRUE)
-one_met_sep_tc <- mmkin(one_met_mods, dmta_ds, error_model = "tc",
-  cores = n_cores, quiet = TRUE)
-
-t9 <- system.time(dfop_sfo_tc <- saem(one_met_sep_tc["DFOP_SFO", ],
-    no_random_effect = "log_k2"))[["elapsed"]]
-t10 <- system.time(sforb_sfo_tc <- saem(one_met_sep_tc["SFORB_SFO", ],
-    no_random_effect = "log_k_DMTA_bound_free"))[["elapsed"]]
    
-
    
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-
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-
    
-
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-order to limit the time for compiling this vignette, and as fitting in
-parallel may disturb the benchmark. Again, we do not include random
-effects that were ill-defined in previous fits of subsets of the
-degradation model.
    
-
    -illparms(sforb_sfo_tc)
    
-
    -three_met_mods <- list(
-  SFORB_SFO3_plus = mkinmod(
-    DMTA = mkinsub("SFORB", c("M23", "M27", "M31")),
-    M23 = mkinsub("SFO"),
-    M27 = mkinsub("SFO"),
-    M31 = mkinsub("SFO", "M27", sink = FALSE)))
-
-three_met_sep_tc <- mmkin(three_met_mods, dmta_ds, error_model = "tc",
-  cores = n_cores, quiet = TRUE)
-
-t11 <- system.time(sforb_sfo3_plus_const <- saem(three_met_sep_tc["SFORB_SFO3_plus", ],
-    no_random_effect = "log_k_DMTA_bound_free"))[["elapsed"]]
    
-
    
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-
    Benchmarks for all available error models are shown. They are
-intended for improving mkin, not for comparing CPUs or operating
-systems. All trademarks belong to their respective owners.
    
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    Ryzen 7 1700Linux1.2.03.22.1404.6264.3284.998
    Ryzen 7 1700Linux1.2.23.22.4274.5504.2174.851
    Ryzen 9 7950XLinux1.2.13.21.3522.8132.4012.074
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    Ryzen 9 7950XLinux1.2.33.21.1182.0362.0102.088
    Ryzen 9 7950XLinux1.2.33.21.3892.3001.8802.355
    
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    Ryzen 9 7950XLinux1.2.33.22.1593.5843.3073.460
    Ryzen 9 7950XLinux1.2.33.22.3003.0753.2063.471
    
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diff --git a/docs/dev/articles/web_only/saem_benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js b/docs/dev/articles/web_only/saem_benchmarks_files/accessible-code-block-0.0.1/empty-anchor.js
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-// Hide empty  tag within highlighted CodeBlock for screen reader accessibility (see https://github.com/jgm/pandoc/issues/6352#issuecomment-626106786) -->
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diff --git a/docs/dev/authors.html b/docs/dev/authors.html
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-Authors and Citation • mkin
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      Johannes Ranke. Author, maintainer, copyright holder. 
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-        
    • 
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      Katrin Lindenberger. Contributor. 
-          
      contributed to mkinresplot()
      
-        
      • 
-        
    • 
-          
      René Lehmann. Contributor. 
-          
      ilr() and invilr()
      
-        
      • 
-        
    • 
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      Eurofins Regulatory AG. Copyright holder. 
-          
      copyright for some of the contributions of JR 2012-2014
      
-        
      • 
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-    
    
-    
    
-      
    Citation
    
-      Source: DESCRIPTION
-    
    
-    
    
-
-
-    
    Ranke J (2023).
-mkin: Kinetic Evaluation of Chemical Degradation Data.
-R package version 1.2.4, https://pkgdown.jrwb.de/mkin/. 
-
    
-    
    @Manual{,
-  title = {mkin: Kinetic Evaluation of Chemical Degradation Data},
-  author = {Johannes Ranke},
-  year = {2023},
-  note = {R package version 1.2.4},
-  url = {https://pkgdown.jrwb.de/mkin/},
-}
    
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diff --git a/docs/dev/bootstrap-toc.css b/docs/dev/bootstrap-toc.css
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diff --git a/docs/dev/index.html b/docs/dev/index.html
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-Kinetic Evaluation of Chemical Degradation Data • mkin
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      mkin
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       mkin status badge Build Status codecov
      
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      The R package mkin provides calculation routines for the analysis of chemical degradation data, including multicompartment kinetics as needed for modelling the formation and decline of transformation products, or if several degradation compartments are involved. It provides stable functionality for kinetic evaluations according to the FOCUS guidance (see below for details). In addition, it provides functionality to do hierarchical kinetics based on nonlinear mixed-effects models.
      
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      Installation
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      You can install the latest released version from CRAN from within R:
      
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      Background
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      In the regulatory evaluation of chemical substances like plant protection products (pesticides), biocides and other chemicals, degradation data play an important role. For the evaluation of pesticide degradation experiments, detailed guidance and various helpful tools have been developed as detailed in ‘Credits and historical remarks’ below. This package aims to provide a one stop solution for degradation kinetics, addressing modellers that are willing to, or even prefer to work with R.
      
-
      
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      Basic usage
-
      
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      For a start, have a look at the code examples provided for plot.mkinfit and plot.mmkin, and at the package vignettes FOCUS L and FOCUS D.
      
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      Documentation
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      The HTML documentation of the latest version released to CRAN is available at jrwb.de and github.
      
-
      Documentation of the development version is found in the ‘dev’ subdirectory. In the articles section of this documentation, you can also find demonstrations of the application of nonlinear hierarchical models, also known as nonlinear mixed-effects models, to more complex data, including transformation products and covariates.
      
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      Features
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      General
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      • Highly flexible model specification using mkinmod, including equilibrium reactions and using the single first-order reversible binding (SFORB) model, which will automatically create two state variables for the observed variable.
        • 
-
      • Model solution (forward modelling) in the function mkinpredict is performed either using the analytical solution for the case of parent only degradation or some simple models involving a single transformation product, , an eigenvalue based solution if only simple first-order (SFO) or SFORB kinetics are used in the model, or using a numeric solver from the deSolve package (default is lsoda).
        • 
-
      • The usual one-sided t-test for significant difference from zero is shown based on estimators for the untransformed parameters.
        • 
-
      • Summary and plotting functions. The summary of an mkinfit object is in fact a full report that should give enough information to be able to approximately reproduce the fit with other tools.
        • 
-
      • The chi-squared error level as defined in the FOCUS kinetics guidance (see below) is calculated for each observed variable.
        • 
-
      • The ‘variance by variable’ error model which is often fitted using Iteratively Reweighted Least Squares (IRLS) can be specified as error_model = "obs".
        • 
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      • Three different error models can be selected using the argument error_model to the mkinfit function. A two-component error model similar to the one proposed by Rocke and Lorenzato can be selected using the argument error_model = "tc".
        • 
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      • Model comparisons using the Akaike Information Criterion (AIC) are supported which can also be used for non-constant variance. In such cases the FOCUS chi-squared error level is not meaningful.
        • 
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      • By default, kinetic rate constants and kinetic formation fractions are transformed internally using transform_odeparms so their estimators can more reasonably be expected to follow a normal distribution.
        • 
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      • When parameter estimates are backtransformed to match the model definition, confidence intervals calculated from standard errors are also backtransformed to the correct scale, and will not include meaningless values like negative rate constants or formation fractions adding up to more than 1, which cannot occur in a single experiment with a single defined radiolabel position.
        • 
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      • When a metabolite decline phase is not described well by SFO kinetics, SFORB kinetics can be used for the metabolite. Mathematically, the SFORB model is equivalent to the DFOP model. However, the SFORB model has the advantage that there is a mechanistic interpretation of the model parameters.
        • 
-
      • Nonlinear mixed-effects models (hierarchical models) can be created from fits of the same degradation model to different datasets for the same compound by using the nlme.mmkin and saem.mmkin methods. Note that the convergence of the nlme fits depends on the quality of the data. Convergence is better for simple models and data for many groups (e.g. soils). The saem method uses the saemix package as a backend. Analytical solutions suitable for use with this package have been implemented for parent only models and the most important models including one metabolite (SFO-SFO and DFOP-SFO). Fitting other models with saem.mmkin, while it makes use of the compiled ODE models that mkin provides, has longer run times (from a couple of minutes to more than an hour).
        • 
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      • Parallel fitting of several models to several datasets is supported, see for example plot.mmkin.
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      • If a C compiler is installed, the kinetic models are compiled from automatically generated C code, see vignette compiled_models. The autogeneration of C code was inspired by the ccSolve package. Thanks to Karline Soetaert for her work on that.
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      • Even if no compiler is installed, many degradation models still give very good performance, as current versions of mkin also have analytical solutions for some models with one metabolite, and if SFO or SFORB are used for the parent compound, Eigenvalue based solutions of the degradation model are available.
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      GUI
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      There is a graphical user interface that may be useful. Please refer to its documentation page for installation instructions and a manual. It only supports evaluations using (generalised) nonlinear regression, but not simultaneous fits using nonlinear mixed-effects models.
      
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      News
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      There is a list of changes for the latest CRAN release and one for each github branch, e.g. the main branch.
      
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      Credits and historical remarks
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      mkin would not be possible without the underlying software stack consisting of, among others, R and the package deSolve. In previous version, mkin was also using the functionality of the FME package. Please refer to the package page on CRAN for the full list of imported and suggested R packages. Also, Debian Linux, the vim editor and the Nvim-R plugin have been invaluable in its development.
      
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      mkin could not have been written without me being introduced to regulatory fate modelling of pesticides by Adrian Gurney during my time at Harlan Laboratories Ltd (formerly RCC Ltd). mkin greatly profits from and largely follows the work done by the FOCUS Degradation Kinetics Workgroup, as detailed in their guidance document from 2006, slightly updated in 2011 and in 2014.
      
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      Also, it was inspired by the first version of KinGUI developed by BayerCropScience, which is based on the MatLab runtime environment.
      
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      The companion package kinfit (now deprecated) was started in 2008 and first published on CRAN on 01 May 2010.
      
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      The first mkin code was published on 11 May 2010 and the first CRAN version on 18 May 2010.
      
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      In 2011, Bayer Crop Science started to distribute an R based successor to KinGUI named KinGUII whose R code is based on mkin, but which added, among other refinements, a closed source graphical user interface (GUI), iteratively reweighted least squares (IRLS) optimisation of the variance for each of the observed variables, and Markov Chain Monte Carlo (MCMC) simulation functionality, similar to what is available e.g. in the FME package.
      
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      Somewhat in parallel, Syngenta has sponsored the development of an mkin and KinGUII based GUI application called CAKE, which also adds IRLS and MCMC, is more limited in the model formulation, but puts more weight on usability. CAKE is available for download from the CAKE website, where you can also find a zip archive of the R scripts derived from mkin, published under the GPL license.
      
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      Finally, there is KineticEval, which contains some further development of the scripts used for KinGUII.
      
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      Thanks to René Lehmann, formerly working at the Umweltbundesamt, for the nice cooperation on parameter transformations, especially the isometric log-ratio transformation that is now used for formation fractions in case there are more than two transformation targets.
      
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      Many inspirations for improvements of mkin resulted from doing kinetic evaluations of degradation data for my clients while working at Harlan Laboratories and at Eurofins Regulatory AG, and now as an independent consultant.
      
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      Funding was received from the Umweltbundesamt in the course of the projects
      
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      • Project Number 27452 (Testing and validation of modelling software as an alternative to ModelMaker 4.0, 2014-2015)
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      • Project Number 56703 (Optimization of gmkin for routine use in the Umweltbundesamt, 2015)
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      • Project Number 92570 (Update of Project Number 27452, 2017-2018)
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      • Project Number 112407 (Testing the feasibility of using an error model according to Rocke and Lorenzato for more realistic parameter estimates in the kinetic evaluation of degradation data, 2018-2019)
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      • Project Number 120667 (Development of objective criteria for the evaluation of the visual fit in the kinetic evaluation of degradation data, 2019-2020)
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      • Project Number 146839 (Checking the feasibility of using mixed-effects models for the derivation of kinetic modelling parameters from degradation studies, 2020-2021)
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      • Project Number 173340 (Application of nonlinear hierarchical models to the kinetic evaluation of chemical degradation data)
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      Thanks to everyone involved for collaboration and support!
      
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      Thanks are due also to Emmanuelle Comets, maintainer of the saemix package, for her interest and support for using the SAEM algorithm and its implementation in saemix for the evaluation of chemical degradation data.
      
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      References
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-Ranke J, Wöltjen J, Schmidt J, and Comets E (2021) Taking kinetic evaluations of degradation data to the next level with nonlinear mixed-effects models. Environments 8 (8) 71 doi:10.3390/environments8080071
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-Ranke J, Meinecke S (2019) Error Models for the Kinetic Evaluation of Chemical Degradation Data Environments 6 (12) 124 doi:10.3390/environments6120124
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-Ranke J, Wöltjen J, Meinecke S (2018) Comparison of software tools for kinetic evaluation of chemical degradation data Environmental Sciences Europe 30 17 doi:10.1186/s12302-018-0145-1
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      Development
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      Developed by Johannes Ranke.
      
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-Changelog • mkin
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      Changelog 
      
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      mkin 1.2.4
      
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      mkin 1.2.3.1 (unreleased)
      
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      • Small fixes to get the online docs right (example code in R/hierarchical_kinetics, cluster setup in cyantraniliprole and dmta pathway vignettes, graphics and model comparison in multistart vignette), rebuild online docs
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      mkin 1.2.3
      
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      • ‘R/{endpoints,parms,plot.mixed.mmkin,summary.saem.mmkin}.R’: Calculate parameters and endpoints and plot population curves for specific covariate values, or specific percentiles of covariate values used in saem fits.
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      • Depend on current deSolve version with the possibility to avoid resolving symbols in a shared library (compiled models) over and over, thanks to Thomas Petzoldt.
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      • ‘inst/rmarkdown/templates/hierarchical_kinetics/skeleton/skeleton.Rmd’: Start a new cluster after creating a model stored in the user specified location, because otherwise symbols are not found by the worker processes.
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      • ‘tests/testthat/test_compiled_symbols.R’: Some new tests to control problems that may have been introduced by the possibility to use pre-resolved symbols.
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      • ‘R/mkinerrmin.R’: Fix typo in subset (use of = instead of ==), thanks to Sebastian Meyer for spotting this during his work on R 4.3.0.
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      mkin 1.2.2 (unreleased)
      
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      • ‘inst/rmarkdown/templates/hierarchical_kinetics’: R markdown template to facilitate the application of hierarchical kinetic models.
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      • ‘inst/testdata/{cyantraniliprole_soil_efsa_2014,lambda-cyhalothrin_soil_efsa_2014}.xlsx’: Example spreadsheets for use with ‘read_spreadsheet()’.
        • 
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      • ‘R/mhmkin.R’: Allow an ‘illparms.mhmkin’ object or a list with suitable dimensions as value of the argument ‘no_random_effects’, making it possible to exclude random effects that were ill-defined in simpler variants of the set of degradation models. Remove the possibility to exclude random effects based on separate fits, as it did not work well.
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      • ‘R/summary.saem.mmkin.R’: List all initial parameter values in the summary, including random effects and error model parameters. Avoid redundant warnings that occurred in the calculation of correlations of the fixed effects in the case that the Fisher information matrix could not be inverted. List correlations of random effects if specified by the user in the covariance model.
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      • ‘R/parplot.R’: Possibility to select the top ‘llquant’ fraction of the fits for the parameter plots, and improved legend text.
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      • ‘R/illparms.R’: Also check if confidence intervals for slope parameters in covariate models include zero. Only implemented for fits obtained with the saemix backend.
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      • ‘R/parplot.R’: Make the function work also in the case that some of the multistart runs failed.
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      • ‘R/intervals.R’: Include correlations of random effects in the model in case there are any.
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      mkin 1.2.1 (2022-11-19)
      
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      • ‘{data,R}/ds_mixed.rda’: Include the test data in the package instead of generating it in ‘tests/testthat/setup_script.R’. Refactor the generating code to make it consistent and update tests.
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      • ‘tests/testthat/setup_script.R’: Excluded another ill-defined random effect for the DFOP fit with ‘saem’, in an attempt to avoid a platform dependence that surfaced on Fedora systems on the CRAN check farm
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      • ‘tests/testthat/test_mixed.R’: Round parameters found by saemix to two significant digits before printing, to also help to avoid platform dependence of tests
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      • ‘R/saem.R’: Fix a bug that prevented that ‘error.ini’ is passed to ‘saemix_model’, and set default to c(1, 1) to avoid changing test results
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      • ‘R/parplot.R’: Show initial values for error model parameters
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      • ‘R/loglik.mkinfit.R’: Add ‘nobs’ attribute to the resulting ‘logLik’ object, in order to make test_AIC.R succeed on current R-devel
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      mkin 1.2.0 (2022-11-17)
      
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      • ‘R/saem.R’: ‘logLik’, ‘update’ and ‘anova’ methods for ‘saem.mmkin’ objects.
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      • ‘R/saem.R’: Automatic estimation of start parameters for random effects for the case of mkin transformations, nicely improving convergence and reducing problems with iterative ODE solutions.
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      • ‘R/status.R’: New generic to show status information for fit array objects with methods for ‘mmkin’, ‘mhmkin’ and ‘multistart’ objects.
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      • ‘R/mhmkin.R’: New method for performing multiple hierarchical mkin fits in one function call, optionally in parallel.
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      • ‘R/mhmkin.R’: ‘anova.mhmkin’ for conveniently comparing the resulting fits.
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      • ‘R/illparms.R’: New generic to show ill-defined parameters with methods for ‘mkinfit’, ‘mmkin’, ‘saem.mmkin’ and ‘mhmkin’ objects.
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      • ‘R/multistart.R’: New method for testing multiple start parameters for hierarchical model fits, with function ‘llhist’ and new generic ‘parplot’ for diagnostics, and new generics ‘which.best’ and ‘best’ for extracting the fit with the highest likelihood
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      • ‘R/summary.mmkin.R’: Summary method for mmkin objects.
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      • ‘R/saem.R’: Implement and test saemix transformations for FOMC and HS. Also, error out if saemix transformations are requested but not supported.
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      • ‘R/read_spreadsheet.R’: Conveniently read in data from a spreadsheet file.
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      • ‘R/tex_listings.R’: Conveniently include summaries of fit objects in R markdown documents that are compiled to LaTeX.
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      mkin 1.1.1 (2022-07-12)
      
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      • ’R/{mkinmod,mkinpredict}.R: Store DLL information in mkinmod objects and use that information in mkinpredict to avoid a performance regression brought by a bugfix in R 4.2.x. Thanks to Tomas Kalibera for his analysis of the problem on the r-package-devel list and his suggestion on how to fix it.
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      • ‘vignettes/FOCUS_L.rmd’: Remove an outdated note referring to a failure to calculate the covariance matrix for DFOP with the L2 dataset. Since 0.9.45.5 the covariance matrix is available
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      • ‘vignettes/web_only/benchmarks.rmd’: Add the first benchmark data using my laptop system, therefore add the CPU when showing the benchmark results.
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      • ‘dimethenamid_2018’: Update example code to use saemix
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      • ‘CAKE_export’: Check for validity of the map argument, updates
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      • ‘saem()’: Slightly improve speed in the case that no analytical solution for saemix is implemented, activate a test of the respective code
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      • ‘mean_degparms’: New argument ‘default_log_parms’ that makes it possible to supply a surrogate value (default) for log parameters that fail the t-test
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      • ‘plot.mixed.mmkin’: Pass the frame argument also to residual plots, take the ‘default_log_parms’ argument for ‘mean_degparms’ used for constructing approximate population curves, plot population curve last to avoid that it is covered by data
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      • ‘plot.mkinfit’: Respect argument ‘maxabs’ for residual plots, and make it possible to give ylim as a list, for row layouts
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      mkin 1.1.0 (2022-03-14)
      
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      Mixed-effects models
      
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      • Reintroduce the interface to saemix version 3.0 (now on CRAN), in particular the generic function ‘saem’ with a generator ‘saem.mmkin’, currently using ‘saemix_model’ and ‘saemix_data’, summary and plot methods
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      • ‘mean_degparms’: New argument ‘test_log_parms’ that makes the function only consider log-transformed parameters where the untransformed parameters pass the t-test for a certain confidence level. This can be used to obtain more plausible starting parameters for the different mixed-effects model backends
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      • ‘plot.mixed.mmkin’: Gains arguments ‘test_log_parms’ and ‘conf.level’
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      • ‘vignettes/web_only/dimethenamid_2018.rmd’: Example evaluations of the dimethenamid data.
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      • ‘intervals’: Provide a method of this nlme function for ‘saem.mmkin’ objects.
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      mkin 1.0.5 (2021-09-15)
      
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      • ‘dimethenamid_2018’: Correct the data for the Borstel soil. The five observations from Staudenmaier (2013) that were previously stored as “Borstel 2” are actually just a subset of the 16 observations in “Borstel 1” which is now simply “Borstel”
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      mkin 1.0.4 (2021-04-20)
      
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      • All plotting functions setting graphical parameters: Use on.exit() for resetting graphical parameters
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      • ‘plot.mkinfit’: Use xlab and xlim for the residual plot if show_residuals is TRUE
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      • ‘mmkin’: Use cores = 1 per default on Windows to make it easier for first time users
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      mkin 1.0.3 (2021-02-15)
      
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      • Review and update README, the ‘Introduction to mkin’ vignette and some of the help pages
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      mkin 1.0.2 (Unreleased)
      
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      • ‘mkinfit’: Keep model names stored in ‘mkinmod’ objects, avoiding their loss in ‘gmkin’
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      mkin 1.0.1 (2021-02-10)
      
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      • ‘confint.mmkin’, ‘nlme.mmkin’, ‘transform_odeparms’: Fix example code in dontrun sections that failed with current defaults
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      • ‘logLik.mkinfit’: Improve example code to avoid warnings and show convenient syntax
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      • ‘mkinresplot’: Re-add Katrin Lindenberger as coauthor who was accidentally removed long ago
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      • Remove tests relying on non-convergence of the FOMC fit to the FOCUS A dataset as this is platform dependent (revealed by the new additional tests on CRAN, thanks!)
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      • Increase test tolerance for some parameter comparisons that also proved to be platform dependent
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      mkin 1.0.0 (2021-02-03)
      
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      General
      
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      • ‘mkinmod’ models gain arguments ‘name’ and ‘dll_dir’ which, in conjunction with a current version of the ‘inline’ package, make it possible to still use the DLL used for fast ODE solutions with ‘deSolve’ after saving and restoring the ‘mkinmod’ object.
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      • ‘mkindsg’ R6 class for groups of ‘mkinds’ datasets with metadata
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      • ‘f_norm_temp_focus’ generic function to normalise time intervals using the FOCUS method, with methods for numeric vectors and ‘mkindsg’ objects
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      • ‘D24_2014’ and ‘dimethenamid_2018’ datasets
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      • ‘focus_soil_moisture’ FOCUS default soil moisture data
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      • ‘update’ method for ‘mmkin’ objects
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      • ‘transform_odeparms’, ‘backtransform_odeparms’: Use logit transformation for solitary fractions like the g parameter of the DFOP model, or formation fractions for a pathway to only one target variable
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      • ‘plot.mmkin’: Add a ylab argument, making it possible to customize the y axis label of the panels on the left without affecting the residual plots. Reduce legend size and vertical distance between panels
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      • ‘plot.mkinfit’: Change default ylab from “Observed” to “Residue”. Pass xlab to residual plot if show_residuals is TRUE.
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      Mixed-effects models
      
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      • ‘mixed.mmkin’ New container for mmkin objects for plotting with the ‘plot.mixed.mmkin’ method
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      • ‘plot.mixed.mmkin’ method used for ‘nlme.mmkin’ inheriting from ‘mixed.mmkin’ (currently virtual)
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      • ‘plot’, ‘summary’ and ‘print’ methods for ‘nlme.mmkin’ objects
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      mkin 0.9.50.3 (2020-10-08)
      
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      • ‘parms’: Add a method for mmkin objects
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      • ‘mmkin’ and ‘confint(method = ’profile’): Use all cores detected by parallel::detectCores() per default
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      • ‘confint(method = ’profile’): Choose accuracy based on ‘rel_tol’ argument, relative to the bounds obtained by the quadratic approximation
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      • ‘mkinfit’: Make ‘use_of_ff’ = “max” also the default for models specified using short names like “SFO” or “FOMC”
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      • ‘mkinfit’: Run ‘stats::shapiro.test()’ on standardized residuals and warn if p < 0.05
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      • ‘mkinfit’: ‘error_model_algorithm’ = ‘d_3’ does not fail if direct fitting fails, but reports that the results for the threestep algorithm are returned
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      • ‘mmkin’: Do not fail any more if one of the fits fails, but assign the try-error to the respective position in the mmkin object
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      • ‘mkinfit’: Ignore components of state.ini that do not correspond to state variables in the model
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      • ‘endpoints’: Back-calculate DT50 value from DT90 also for the biphasic models DFOP, HS and SFORB
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      mkin 0.9.50.2 (2020-05-12)
      
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      • Increase tolerance for a platform specific test results on the Solaris test machine on CRAN
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      • Updates and corrections (using the spelling package) to the documentation
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      mkin 0.9.50.1 (2020-05-11)
      
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      • Support SFORB with formation fractions
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      • ‘mkinmod’: Make ‘use_of_ff’ = “max” the default
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      • Improve performance by a) avoiding expensive calls in the cost function like merge() and data.frame(), and b) by implementing analytical solutions for SFO-SFO and DFOP-SFO
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      mkin 0.9.49.11 (2020-04-20)
      
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      • Increase a test tolerance to make it pass on all CRAN check machines
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      mkin 0.9.49.10 (2020-04-18)
      
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      • ‘nlme.mmkin’: An nlme method for mmkin row objects and an associated S3 class with print, plot, anova and endpoint methods
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      • ‘mean_degparms, nlme_data, nlme_function’: Three new functions to facilitate building nlme models from mmkin row objects
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      • ‘endpoints’: Don’t return the SFORB list component if it’s empty. This reduces distraction and complies with the documentation
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      • Article in compiled models: Add some platform specific code and suppress warnings about zero values being removed from the FOCUS D dataset
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      • ‘plot.mmkin’: Add the argument ‘standardized’ to avoid warnings that occurred when it was passed as part of the additional arguments captured by the dots (…)
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      • ‘summary.mkinfit’: Add AIC, BIC and log likelihood to the summary
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      mkin 0.9.49.9 (2020-03-31)
      
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      • ‘mkinmod’: Use pkgbuild::has_compiler instead of Sys.which(‘gcc’), as the latter will often fail even if Rtools are installed
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      • ‘mkinds’: Use roxygen for documenting fields and methods of this R6 class
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      mkin 0.9.49.8 (2020-01-09)
      
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      • ‘aw’: Generic function for calculating Akaike weights, methods for mkinfit objects and mmkin columns
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      • ‘loftest’: Add a lack-of-fit test
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      • ‘plot_res’, ‘plot_sep’ and ‘mkinerrplot’: Add the possibility to show standardized residuals and make it the default for fits with error models other than ‘const’
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      • ‘lrtest.mkinfit’: Improve naming of the compared fits in the case of fixed parameters
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      • ‘confint.mkinfit’: Make the quadratic approximation the default, as the likelihood profiling takes a lot of time, especially if the fit has more than three parameters
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      mkin 0.9.49.7 (2019-11-01)
      
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      • Fix a bug introduced in 0.9.49.6 that occurred if the direct optimisation yielded a higher likelihood than the three-step optimisation in the d_3 algorithm, which caused the fitted parameters of the three-step optimisation to be returned instead of the parameters of the direct optimisation
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      • Add a ‘nobs’ method for mkinfit objects, enabling the default ‘BIC’ method from the stats package. Also, add a ‘BIC’ method for mmkin column objects.
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      mkin 0.9.49.6 (2019-10-31)
      
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      • Implement a likelihood ratio test as a method for ‘lrtest’ from the lmtest package
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      • Add an ‘update’ method for mkinfit objects which remembers fitted parameters if appropriate
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      • Add a ‘residuals’ method for mkinfit objects that supports scaling based on the error model
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      • Fix a bug in ‘mkinfit’ that prevented summaries of objects fitted with fixed parameters to be generated
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      • Add ‘parms’ and ‘confint’ methods for mkinfit objects. Confidence intervals based on the quadratic approximation as in the summary, and based on the profile likelihood
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      • Move long-running tests to tests/testthat/slow with a separate test log. They currently take around 7 minutes on my system
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      • ‘mkinfit’: Clean the code and return functions to calculate the log-likelihood and the sum of squared residuals
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      • Vignette ‘twa.html’: Add the maximum time weighted average formulas for the hockey stick model
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      • Support frameless plots (‘frame = FALSE’)
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      • Support to suppress the chi2 error level (‘show_errmin = FALSE’) in ‘plot.mmkin’
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      • Update README and the introductory vignette
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      • Report ‘OLS’ as error_model_algorithm in the summary in the case that the default error_model (‘const’) is used
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      • Support summarizing ‘mkinfit’ objects generated with versions < 0.9.49.5
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      mkin 0.9.49.5 (2019-07-04)
      
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      • Several algorithms for minimization of the negative log-likelihood for non-constant error models (two-component and variance by variable). In the case the error model is constant variance, least squares is used as this is more stable. The default algorithm ‘d_3’ tries direct minimization and a three-step procedure, and returns the model with the highest likelihood.
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      • The argument ‘reweight.method’ to mkinfit and mmkin is now obsolete, use ‘error_model’ and ‘error_model_algorithm’ instead
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      • Add a test that checks if we get the best known AIC for parent only fits to 12 test datasets. Add these test datasets for this purpose.
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      • New function ‘mkinerrplot’. This function is also used for residual plots in ‘plot.mmkin’ if the argument ‘resplot = “errmod”’ is given, and in ‘plot.mkinfit’ if ‘show_errplot’ is set to TRUE.
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      • Remove dependency on FME, only use nlminb for optimisation (‘Port’ algorithm). I cannot remember cases where one of the other optimisation algorithms was preferable, except that I sometime used Levenberg-Marquardt for speed in cases where I did not expect to get trapped in a local minimum.
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      • Use the numDeriv package to calculate hessians. This results in slightly different confidence intervals, takes a bit longer, but is apparently more robust
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      • Add a simple benchmark vignette to document the impact on performance.
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      • The code for manual weighting was removed. This functionality might get added again at a later time. For the time being, please use an earlier version, e.g. 0.9.48.1 if you want to do manual weighting.
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      • The fitting time reported in the summary now includes the time used for calculation of the hessians
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      • Adapt tests
        • 
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      • Fix an error in the FOCUS chi2 error level calculations that occurred if parameters were specified in parms.ini that were not in the model. A warning was already issued, but when fitting in parallel via mmkin this could go unnoticed.
        • 
-
      • Add example datasets obtained from risk assessment reports published by the European Food Safety Agency.
        • 
-
      
-    
      
-
      mkin 0.9.48.1 (2019-03-04)
      
-
      • Add the function ‘logLik.mkinfit’ which makes it possible to calculate an AIC for mkinfit objects
        • 
-
      • Add the function ‘AIC.mmkin’ to make it easy to compare columns of mmkin objects
        • 
-
      • ‘add_err’: Respect the argument giving the number of replicates in the synthetic dataset
        • 
-
      • ‘max_twa_parent’: Support maximum time weighted average concentration calculations for the hockey stick (HS) model
        • 
-
      • ‘mkinpredict’: Make the function generic and create a method for mkinfit objects
        • 
-
      • ‘mkinfit’: Improve the correctness of the fitted two component error model by fitting the mean absolute deviance at each observation against the observed values, weighting with the current two-component error model
        • 
-
      • ‘tests/testthat/test_irls.R’: Test if the components of the error model used to generate the data can be reproduced with moderate accuracy
        • 
-
      • Add the function ‘CAKE_export’ to facilitate cross-checking of results
        • 
-
      • Implement the logistic model (only tested for parent fits)
        • 
-
      • ‘nafta’: Add evaluations according to the NAFTA guidance
        • 
-
      
-    
      
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      mkin 0.9.47.5 (2018-09-14)
      
-
      • Make the two-component error model stop in cases where it is inadequate to avoid nls crashes on windows
        • 
-
      • Move two vignettes to a location where they will not be built on CRAN (to avoid more NOTES from long execution times)
        • 
-
      • Exclude more example code from testing on CRAN to avoid NOTES from long execution times
        • 
-
      
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      mkin 0.9.47.3
      
-
      • ‘mkinfit’: Improve fitting the error model for reweight.method = ‘tc’. Add ‘manual’ to possible arguments for ‘weight’
        • 
-
      • Test that FOCUS_2006_C can be evaluated with DFOP and reweight.method = ‘tc’
        • 
-
      
-    
      
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      mkin 0.9.47.2 (2018-07-19)
      
-
      • ‘sigma_twocomp’: Rename ‘sigma_rl’ to ‘sigma_twocomp’ as the Rocke and Lorenzato model assumes lognormal distribution for large y. Correct references to the Rocke and Lorenzato model accordingly.
        • 
-
      • ‘mkinfit’: Use 1.1 as starting value for N parameter of IORE models to obtain convergence in more difficult cases. Show parameter names when ‘trace_parms’ is ‘TRUE’.
        • 
-
      
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      mkin 0.9.47.1 (2018-02-06)
      
-
      • Skip some tests on CRAN and winbuilder to avoid timeouts
        • 
-
      • ‘test_data_from_UBA_2014’: Added this list of datasets containing experimental data used in the expertise from 2014
        • 
-
      • ‘mkinfit’: Added the iterative reweighting method ‘tc’ using the two-component error model from Rocke and Lorenzato. NA values in the data are not returned any more.
        • 
-
      • ‘mkinfit’: Work around a bug in the current FME version that prevented the convergence message to be returned in the case of non-convergence.
        • 
-
      • ‘summary.mkinfit’: Improved output regarding weighting method. No predictions are returned for NA values in the model (see above).
        • 
-
      • ‘summary.mkinfit’: Show versions of mkin and R used for fitting (not the ones used for the summary) if the fit was generated with mkin >= 0.9.47.1
        • 
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      mkin 0.9.46.3 (2017-11-16)
      
-
      • README.md, vignettes/mkin.Rmd: URLs were updated
        • 
-
      • synthetic_data_for_UBA: Add the code used to generate the data in the interest of reproducibility
        • 
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      mkin 0.9.46.2 (2017-10-10)
      
-
      • Converted the vignette FOCUS_Z from tex/pdf to markdown/html
        • 
-
      • DESCRIPTION: Add ORCID
        • 
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      mkin 0.9.46.1 (2017-09-14)
      
-
      • plot.mkinfit: Fix scaling of residual plots for the case of separate plots for each observed variable
        • 
-
      • plot.mkinfit: Use all data points of the fitted curve for y axis scaling for the case of separate plots for each observed variable
        • 
-
      • Documentation updates
        • 
-
      
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      mkin 0.9.46 (2017-07-24)
      
-
      • Remove test_FOMC_ill-defined.R as it is too platform dependent
        • 
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      mkin 0.9.45.2 (2017-07-24)
      
-
      • Rename twa to max_twa_parent to avoid conflict with twa from my pfm package
        • 
-
      • Update URLs in documentation
        • 
-
      • Limit test code to one core to pass on windows
        • 
-
      • Switch from microbenchmark to rbenchmark as the former is not supported on all platforms
        • 
-
      
-    
      
-
      mkin 0.9.45.1 (2016-12-20)
      
-
      
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      New features
      
-
      • A twa function, calculating maximum time weighted average concentrations for the parent (SFO, FOMC and DFOP).
        • 
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      mkin 0.9.45 (2016-12-08)
      
-
      
-
      Minor changes
      
-
      • plot.mkinfit and plot.mmkin: If the plotting device is tikz, LaTeX markup is being used for the chi2 error in the graphs.
        • 
-
      • Use pkgdown, the successor of staticdocs for generating static HTML documentation. Include example output and graphs also for dontrun sections.
        • 
-
      • plot.mkinfit: Plotting does not fail any more when the compiled model is not available, e.g. because it was removed from the temporary directory. In this case, the uncompiled model is now used for plotting
        • 
-
      
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      mkin 0.9.44 (2016-06-29)
      
-
      
-
      Bug fixes
      
-
      • The test test_FOMC_ill-defined failed on several architectures, so the test is now skipped
        • 
-
      
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      mkin 0.9.43 (2016-06-28)
      
-
      
-
      Major changes
      
-
      • The title was changed to Kinetic evaluations of chemical degradation data
        • 
-
      • plot.mkinfit: Add the possibility to show fits (and residual plots if requested) separately for the observed variables
        • 
-
      • plot.mkinfit: Add the possibility to show the chi2 error levels in the plot, similar to the way they are shown in plot.mmkin
        • 
-
      • plot_sep: Add this function as a convenience wrapper for plotting observed variables of mkinfit objects separately, with chi2 error values and residual plots.
        • 
-
      • Vignettes: The main vignette mkin was converted to R markdown and updated. The other vignettes were also updated to show current improved functionality.
        • 
-
      • The function add_err was added to the package, making it easy to generate simulated data using an error model based on the normal distribution
        • 
-
      
-
      
-
      Minor changes
      
-
      • Remove an outdated reference to the inline package in the compiled_models vignette
        • 
-
      • mkinfit: Do not error out in cases where the fit converges, but the Jacobian for the untransformed model cost can not be estimated. Give a warning instead and return NA for the t-test results.
        • 
-
      • summary.mkinfit: Give a warning message when the covariance matrix can not be obtained.
        • 
-
      • A test has been added to containing a corresponding edge case to check that the warnings are correctly issued and the fit does not terminate.
        • 
-
      • plot.mmkin: Round the chi2 error value to three significant digits, instead of two decimal digits.
        • 
-
      • mkinfit: Return the err values used on weighted fits as a column named err. Also include these inverse weights when the column value in the observed data is used, which is returned as observed in the data component of the mkinfit object.
        • 
-
      
-
      
-
      Bug fixes
      
-
      • endpoints: When the name of a substance degrading to a metabolite (e.g. a parent compound) used in the model formulation ended in the letter f, some rate parameters could be listed as formation fractions with mixed up names. These would also appear in the summary.
        • 
-
      • mkinfit: Check for all observed variables when checking if the user tried to fix formation fractions when fitting them using ilr transformation.
        • 
-
      • plot.mmkin: Set the plot margins correctly, also in the case of a single fit to be plotted, so the main title is placed in a reasonable way.
        • 
-
      • plot.mkinfit: Correct default values for col_obs, pch_obs and lty_obs for the case that obs_vars is specified.
        • 
-
      
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-
      mkin 0.9.42 (2016-03-25)
      
-
      
-
      Major changes
      
-
      • Add the argument from_max_mean to mkinfit, for fitting only the decline from the maximum observed value for models with a single observed variable
        • 
-
      
-
      
-
      Minor changes
      
-
      • Add plots to compiled_models vignette
        • 
-
      • Give an explanatory error message when mkinmod fails due to a missing definition of a target variable
        • 
-
      • print.mkinmod(): Improve formatting when printing mkinmod model definitions
        • 
-
      
-
      
-    
      
-
      mkin 0.9-41 (2015-11-09)
      
-
      
-
      Minor changes
      
-
      • Add an R6 class mkinds representing datasets with a printing method
        • 
-
      • Add a printing method for mkinmod objects
        • 
-
      • Make it possible to specify arbitrary strings as names for the compounds in mkinmod, and show them in the plot
        • 
-
      • Use an index.r file to group help topics in static documentation
        • 
-
      
-
      
-
      Bug fixes
      
-
      • 
-print.summary.mkinfit(): Avoid an error that occurred when printing summaries generated with mkin versions before 0.9-36
        • 
-
      
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-
      mkin 0.9-40 (2015-07-21)
      
-
      
-
      Bug fixes
      
-
      • 
-endpoints(): For DFOP and SFORB models, where optimize() is used, make use of the fact that the DT50 must be between DT50_k1 and DT50_k2 (DFOP) or DT50_b1 and DT50_b2 (SFORB), as optimize() sometimes did not find the minimum. Likewise for finding DT90 values. Also fit on the log scale to make the function more efficient.
        • 
-
      
-
      
-
      Internal changes
      
-
      • 
-DESCRIPTION, NAMESPACE, R/*.R: Import (from) stats, graphics and methods packages, and qualify some function calls for non-base packages installed with R to avoid NOTES made by R CMD check –as-cran with upcoming R versions.
        • 
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      mkin 0.9-39 (2015-06-26)
      
-
      
-
      Major changes
      
-
      • New function mmkin(): This function takes a character vector of model shorthand names, or alternatively a list of mkinmod models, as well as a list of dataset as main arguments. It returns a matrix of mkinfit objects, with a row for each model and a column for each dataset. A subsetting method with single brackets is available. Fitting the models in parallel using the parallel package is supported.
        • 
-
      • New function plot.mmkin(): Plots single-row or single-column mmkin objects including residual plots.
        • 
-
      
-
      
-
      Bug fixes
      
-
      • 
-mkinparplot(): Fix the x axis scaling for rate constants and formation fractions that got confused by the introduction of the t-values of transformed parameters.
        • 
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      mkin 0.9-38 (2015-06-24)
      
-
      
-
      Minor changes
      
-
      • vignettes/compiled_models.html: Show the performance improvement factor actually obtained when building the vignette, as well as mkin version, some system info and the CPU model used for building the vignette.
        • 
-
      • GNUMakefile,vignettes/*: Clean up vignette generation and include table of contents in HTML vignettes.
        • 
-
      
-
      
-
      Bug fixes
      
-
      • 
-mkinmod(): When generating the C code for the derivatives, only declare the time variable when it is needed and remove the ‘-W-no-unused-variable’ compiler flag as the C compiler used in the CRAN checks on Solaris does not know it.
        • 
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      mkin 0.9-36 (2015-06-21)
      
-
      
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      Major changes
      
-
      • summary.mkinfit(): A one-sided t-test for significant difference of untransformed parameters from zero is now always shown, based on the assumption of normal distribution for estimators of all untransformed parameters. Use with caution, as this assumption is unrealistic e.g. for rate constants in these nonlinear kinetic models.
        • 
-
      • If a compiler (gcc) is installed, use a version of the differential equation model compiled from C code, which is a huge performance boost for models where only the deSolve method works.
        • 
-
      • mkinmod(): Create a list component $cf (of class CFuncList) in the list returned by mkinmod, if a version can be compiled from autogenerated C code (see above).
        • 
-
      • mkinfit(): Set the default solution_type to deSolve when a compiled version of the model is present, except when an analytical solution is possible.
        • 
-
      
-
      
-
      Minor changes
      
-
      • Added a simple showcase vignette with an evaluation of FOCUS example dataset D
        • 
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      mkin 0.9-35 (2015-05-15)
      
-
      
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      Major changes
      
-
      • Switch from RUnit to testthat for testing
        • 
-
      
-
      
-
      Bug fixes
      
-
      • mkinparplot(): Avoid warnings that occurred when not all confidence intervals were available in the summary of the fit
        • 
-
      • print.summary.mkinfit(): Fix printing the summary for the case that the number of iterations is not available
        • 
-
      • NAMESPACE: export S3 methods plot.mkinfit, summary.mkinfit and print.summary.mkinfit to satisfy R CMD check on R-devel
        • 
-
      • mkinparplot(): Avoid warning in R CMD check about undeclared global variable Lower
        • 
-
      
-
      
-
      New features
      
-
      • mkinfit(): Report successful termination when quiet = FALSE. This is helpful for more difficult problems fitted with reweight.method = obs, as no progress is often indicated during the reweighting.
        • 
-
      • A first test using results established in the expertise written for the German Federal Environmental Agency (UBA) was added.
        • 
-
      • Add synthetic datasets generated for expertise written for the German Federal Environmental Agency UBA
        • 
-
      • Add tests based on these datasets
        • 
-
      
-
      
-    
      
-
      mkin 0.9-34 (2014-11-22)
      
-
      
-
      New features
      
-
      • Add the convenience function mkinsub() for creating the lists used in mkinmod()
        • 
-
      • Add the possibility to fit indeterminate order rate equation (IORE) models using an analytical solution (parent only) or a numeric solution. Paths from IORE compounds to metabolites are supported when using formation fractions (use_of_ff = ‘max’). Note that the numerical solution (method.ode = ‘deSolve’) of the IORE differential equations sometimes fails due to numerical problems.
        • 
-
      • Switch to using the Port algorithm (using a model/trust region approach) per default. While needing more iterations than the Levenberg-Marquardt algorithm previously used per default, it is less sensitive to starting parameters.
        • 
-
      
-
      
-
      Minor changes
      
-
      • The formatting of differential equations in the summary was further improved
        • 
-
      • Always include 0 on y axis when plotting during the fit
        • 
-
      
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-    
      
-
      mkin 0.9-33 (2014-10-22)
      
-
      
-
      New features
      
-
      • The initial value (state.ini) for the observed variable with the highest observed residue is set to 100 in case it has no time zero observation and state.ini = "auto"
        • 
-
      • A basic unit test for mkinerrmin() was written
        • 
-
      
-
      
-
      Bug fixes
      
-
      • mkinfit(): The internally fitted parameter for g was named g_ilr even when transform_fractions=FALSE
        • 
-
      • mkinfit(): The initial value (state.ini) for the parent compound was not set when the parent was not the (only) variable with the highest value in the observed data.
        • 
-
      • mkinerrmin(): When checking for degrees of freedom for metabolites, check if their time zero value is fixed instead of checking if the observed value is zero. This ensures correct calculation of degrees of freedom also in cases where the metabolite residue at time zero is greater zero.
        • 
-
      • plot.mkinfit(): Avoid a warning message about only using the first component of ylim that occurred when ylim was specified explicitly
        • 
-
      
-
      
-
      Minor changes
      
-
      • The formatting of differential equations in the summary was improved by wrapping overly long lines
        • 
-
      • The FOCUS_Z vignette was rebuilt with the above improvement and using a width of 70 to avoid output outside of the grey area
        • 
-
      • print.summary.mkinfit(): Avoid a warning that occurred when gmkin showed summaries of initial fits without iterations
        • 
-
      • mkinfit(): Avoid a warning that occurred when summarising a fit that was performed with maxitmodFit = 0 as done in gmkin for configuring new fits.
        • 
-
      
-
      
-    
      
-
      mkin 0.9-32 (2014-07-24)
      
-
      
-
      New features
      
-
      • The number of degrees of freedom is difficult to define in the case of ilr transformation of formation fractions. Now for each source compartment the number of ilr parameters (=number of optimised parameters) is divided by the number of pathways to metabolites (=number of affected data series) which leads to fractional degrees of freedom in some cases.
        • 
-
      • The default for the initial value for the first state value is now taken from the mean of the observations at time zero, if available.
        • 
-
      • The kinetic model can alternatively be specified with a shorthand name for parent only degradation models, e.g. SFO, or DFOP.
        • 
-
      • Optimisation method, number of model evaluations and time elapsed during optimisation are given in the summary of mkinfit objects.
        • 
-
      • The maximum number of iterations in the optimisation algorithm can be specified using the argument maxit.modFit to the mkinfit function.
        • 
-
      • mkinfit gives a warning when the fit does not converge (does not apply to SANN method). This warning is included in the summary.
        • 
-
      
-
      
-
      Bug fixes
      
-
      • Avoid plotting an artificial 0 residual at time zero in mkinresplot
        • 
-
      • In the determination of the degrees of freedom in mkinerrmin, formation fractions were accounted for multiple times in the case of parallel formation of metabolites. See the new feature described above for the solution.
        • 
-
      • transform_rates=FALSE in mkinfit now also works for FOMC and HS models.
        • 
-
      • Initial values for formation fractions were not set in all cases.
        • 
-
      • No warning was given when the fit did not converge when a method other than the default Levenberg-Marquardt method Marq was used.
        • 
-
      
-
      
-
      Minor changes
      
-
      • Vignettes were rebuilt to reflect the changes in the summary method.
        • 
-
      • Algorithm Pseudo was excluded because it needs user-defined parameter limits which are not supported.
        • 
-
      • Algorithm Newton was excluded because of its different way to specify the maximum number of iterations and because it does not appear to provide additional benefits.
        • 
-
      
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-
      mkin 0.9-31 (2014-07-14)
      
-
      
-
      Bug fixes
      
-
      • The internal renaming of optimised parameters in Version 0.9-30 led to errors in the determination of the degrees of freedom for the chi2 error level calulations in mkinerrmin() used by the summary function.
        • 
-
      
-
      
-    
      
-
      mkin 0.9-30 (2014-07-11)
      
-
      
-
      New features
      
-
      • It is now possible to use formation fractions in combination with turning off the sink in mkinmod().
        • 
-
      
-
      
-
      Major changes
      
-
      • The original and the transformed parameters now have different names (e.g. k_parent and log_k_parent. They also differ in how many they are when we have formation fractions but no pathway to sink.
        • 
-
      • The order of some of the information blocks in print.summary.mkinfit.R() has been ordered in a more logical way.
        • 
-
      
-
      
-
      Minor changes
      
-
      • The vignette FOCUS_Z has been simplified to use formation fractions with turning off the sink, and slightly amended to use the new versions of DT50 values calculated since mkin 0.9-29.
        • 
-
      • All vignettes have been rebuilt so they reflect all changes.
        • 
-
      • The ChangeLog was renamed to NEWS.md and the entries were converted to markdown syntax compatible with the tools::news() function built into R.
        • 
-
      • The test suite was overhauled. Tests of the DFOP and SFORB models with dataset FOCUS_2006_A were removed, as they were too much dependent on the optimisation algorithm and/or starting parameters, because the dataset is SFO (compare kinfit vignette).
        • 
-
      • Also, the Schaefer complex case can now be fitted using formation fractions, and with the ‘Port’ optimisation method we also fit A2 in the same way as published in the Piacenza paper.
        • 
-
      • Some more checks were introduced to mkinfit(), leading to warnings or stopping execution if unsupported combinations of methods and parameters are requested.
        • 
-
      
-
      
-    
      
-
      mkin 0.9-29 (2014-06-27)
      
-
      • R/mkinresplot.R: Make it possible to specify xlim
        • 
-
      • R/geometric_mean.R, man/geometric_mean.Rd: Add geometric mean function
        • 
-
      • R/endpoints.R, man/endpoints.Rd: Calculate additional (pseudo)-DT50 values for FOMC, DFOP, HS and SFORB. Avoid calculation of formation fractions from rate constants when they are directly fitted
        • 
-
      
-    
      
-
      mkin 0.9-28 (2014-05-20)
      
-
      • Do not backtransform confidence intervals for formation fractions if more than one compound is formed, as such parameters only define the pathways as a set
        • 
-
      • Add historical remarks and some background to the main package vignette
        • 
-
      • Correct ‘isotropic’ into ‘isometric’ for the ilr transformation
        • 
-
      
-    
      
-
      mkin 0.9-27 (2014-05-10)
      
-
      • Fork the GUI into a separate package gmkin
        • 
-
      • DESCRIPTION, NAMESPACE, TODO: Adapt and add copyright information
        • 
-
      • Remove files belonging to the GUI
        • 
-
      • Possibility to fit without parameter transformations, using bounds as implemented in FME
        • 
-
      • Add McCall 2,4,5-T dataset
        • 
-
      • Enable selection of observed variables in plotting
        • 
-
      • Add possibility to show residual plot in plot.mkinfit
        • 
-
      • R/mkinparplot.R, man/mkinparplot.Rd: plot parameters with confidence intervals
        • 
-
      • Change vignette format from Sweave to knitr
        • 
-
      • Split examples vignette to FOCUS_L and FOCUS_Z
        • 
-
      • Remove warning about constant formation fractions in mkinmod as it was based on a misconception
        • 
-
      • Restrict the unit test with the Schaefer data to parent and primary metabolites as formation fraction and DT50 for A2 are highly correlated and passing the test is platform dependent. For example, the test fails in 1 out of 14 platforms on CRAN as of today.
        • 
-
      • Add Eurofins Regulatory AG copyright notices
        • 
-
      • Import FME and deSolve instead of depending on them to have clean startup
        • 
-
      • Add a starter function for the GUI: gmkin()
        • 
-
      • Change the format of the workspace files of gmkin so they can be distributed and documented in the package
        • 
-
      • Add gmkin workspace datasets FOCUS_2006_gmkin and FOCUS_2006_Z_gmkin
        • 
-
      
-    
      
-
      mkin 0.9-24 (2013-11-06)
      
-
      • Bugfix re-enabling the fixing of any combination of initial values for state variables
        • 
-
      • Default values for kinetic rate constants are not all 0.1 any more but are “salted” with a small increment to avoid numeric artefacts with the eigenvalue based solutions
        • 
-
      • Backtransform fixed ODE parameters for the summary
        • 
-
      
-    
      
-
      mkin 0.9-22 (2013-10-26)
      
-
      • Get rid of the optimisation step in mkinerrmin - this was unnecessary. Thanks to KinGUII for the inspiration - actually this is equation 6-2 in FOCUS kinetics p. 91 that I had overlooked originally
        • 
-
      • Fix plot.mkinfit as it passed graphical arguments like main to the solver
        • 
-
      • Do not use plot=TRUE in mkinfit() example
        • 
-
      • The first successful fits in the not so simple GUI
        • 
-
      • Fix iteratively reweighted least squares for the case of many metabolites
        • 
-
      • Unify naming of initial values of state variables
        • 
-
      • Unify naming in dataframes of optimised and fixed parameters in the summary
        • 
-
      • Show the weighting method for residuals in the summary
        • 
-
      • Correct the output of the data in the case of manual weighting
        • 
-
      • Implement IRLS assuming different variances for observed variables
        • 
-
      • Do not use 0 values at time zero for chi2 error level calculations. This is the way it is done in KinGUII and it makes sense. It does impact the chi2 error levels in the output. Generally they seem to be lower for metabolites now, presumably because the mean of the observed values is higher
        • 
-
      For a detailed list of changes to the mkin source please consult the commit history on http://github.com/jranke/mkin
      
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-/* Sticky footer */
-
-/**
- * Basic idea: https://philipwalton.github.io/solved-by-flexbox/demos/sticky-footer/
- * Details: https://github.com/philipwalton/solved-by-flexbox/blob/master/assets/css/components/site.css
- *
- * .Site -> body > .container
- * .Site-content -> body > .container .row
- * .footer -> footer
- *
- * Key idea seems to be to ensure that .container and __all its parents__
- * have height set to 100%
- *
- */
-
-html, body {
-  height: 100%;
-}
-
-body {
-  position: relative;
-}
-
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-  display: flex;
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-.contents img {
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-  height: auto;
-}
-
-/* Fix bug in bootstrap (only seen in firefox) */
-summary {
-  display: list-item;
-}
-
-/* Typographic tweaking ---------------------------------*/
-
-.contents .page-header {
-  margin-top: calc(-60px + 1em);
-}
-
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-  margin-left: 3em;
-}
-
-/* Section anchors ---------------------------------*/
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-  display: none;
-  margin-left: 5px;
-  width: 20px;
-  height: 20px;
-
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-  background-size: 20px 20px;
-  background-position: center center;
-}
-
-h1:hover .anchor,
-h2:hover .anchor,
-h3:hover .anchor,
-h4:hover .anchor,
-h5:hover .anchor,
-h6:hover .anchor {
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-}
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-/* Fixes for fixed navbar --------------------------*/
-
-.contents h1, .contents h2, .contents h3, .contents h4 {
-  padding-top: 60px;
-  margin-top: -40px;
-}
-
-/* Navbar submenu --------------------------*/
-
-.dropdown-submenu {
-  position: relative;
-}
-
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-  top: 0;
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-.dropdown-submenu:hover>a:after {
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-/* Sidebar --------------------------*/
-
-#pkgdown-sidebar {
-  margin-top: 30px;
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-  margin-bottom: 0.5em;
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-
-/* bootstrap-toc tweaks ------------------------------------------------------*/
-
-/* All levels of nav */
-
-nav[data-toggle='toc'] .nav > li > a {
-  padding: 4px 20px 4px 6px;
-  font-size: 1.5rem;
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-  padding-left: 5px;
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-nav[data-toggle='toc'] .nav > .active > a,
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-nav[data-toggle='toc'] .nav > .active:focus > a {
-  padding-left: 5px;
-  font-size: 1.5rem;
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-}
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-/* Nav: second level (shown on .active) */
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-nav[data-toggle='toc'] .nav .nav {
-  display: none; /* Hide by default, but at >768px, show it */
-  padding-bottom: 10px;
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-nav[data-toggle='toc'] .nav .nav > li > a {
-  padding-left: 16px;
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-nav[data-toggle='toc'] .nav .nav > .active:hover > a,
-nav[data-toggle='toc'] .nav .nav > .active:focus > a {
-  padding-left: 15px;
-  font-weight: 500;
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-
-/* orcid ------------------------------------------------------------------- */
-
-.orcid {
-  font-size: 16px;
-  color: #A6CE39;
-  /* margins are required by official ORCID trademark and display guidelines */
-  margin-left:4px;
-  margin-right:4px;
-  vertical-align: middle;
-}
-
-/* Reference index & topics ----------------------------------------------- */
-
-.ref-index th {font-weight: normal;}
-
-.ref-index td {vertical-align: top; min-width: 100px}
-.ref-index .icon {width: 40px;}
-.ref-index .alias {width: 40%;}
-.ref-index-icons .alias {width: calc(40% - 40px);}
-.ref-index .title {width: 60%;}
-
-.ref-arguments th {text-align: right; padding-right: 10px;}
-.ref-arguments th, .ref-arguments td {vertical-align: top; min-width: 100px}
-.ref-arguments .name {width: 20%;}
-.ref-arguments .desc {width: 80%;}
-
-/* Nice scrolling for wide elements --------------------------------------- */
-
-table {
-  display: block;
-  overflow: auto;
-}
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-/* Syntax highlighting ---------------------------------------------------- */
-
-pre, code, pre code {
-  background-color: #f8f8f8;
-  color: #333;
-}
-pre, pre code {
-  white-space: pre-wrap;
-  word-break: break-all;
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-}
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-pre {
-  border: 1px solid #eee;
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-pre .img, pre .r-plt {
-  margin: 5px 0;
-}
-
-pre .img img, pre .r-plt img {
-  background-color: #fff;
-}
-
-code a, pre a {
-  color: #375f84;
-}
-
-a.sourceLine:hover {
-  text-decoration: none;
-}
-
-.fl      {color: #1514b5;}
-.fu      {color: #000000;} /* function */
-.ch,.st  {color: #036a07;} /* string */
-.kw      {color: #264D66;} /* keyword */
-.co      {color: #888888;} /* comment */
-
-.error   {font-weight: bolder;}
-.warning {font-weight: bolder;}
-
-/* Clipboard --------------------------*/
-
-.hasCopyButton {
-  position: relative;
-}
-
-.btn-copy-ex {
-  position: absolute;
-  right: 0;
-  top: 0;
-  visibility: hidden;
-}
-
-.hasCopyButton:hover button.btn-copy-ex {
-  visibility: visible;
-}
-
-/* headroom.js ------------------------ */
-
-.headroom {
-  will-change: transform;
-  transition: transform 200ms linear;
-}
-.headroom--pinned {
-  transform: translateY(0%);
-}
-.headroom--unpinned {
-  transform: translateY(-100%);
-}
-
-/* mark.js ----------------------------*/
-
-mark {
-  background-color: rgba(255, 255, 51, 0.5);
-  border-bottom: 2px solid rgba(255, 153, 51, 0.3);
-  padding: 1px;
-}
-
-/* vertical spacing after htmlwidgets */
-.html-widget {
-  margin-bottom: 10px;
-}
-
-/* fontawesome ------------------------ */
-
-.fab {
-    font-family: "Font Awesome 5 Brands" !important;
-}
-
-/* don't display links in code chunks when printing */
-/* source: https://stackoverflow.com/a/10781533 */
-@media print {
-  code a:link:after, code a:visited:after {
-    content: "";
-  }
-}
-
-/* Section anchors ---------------------------------
-   Added in pandoc 2.11: https://github.com/jgm/pandoc-templates/commit/9904bf71
-*/
-
-div.csl-bib-body { }
-div.csl-entry {
-  clear: both;
-}
-.hanging-indent div.csl-entry {
-  margin-left:2em;
-  text-indent:-2em;
-}
-div.csl-left-margin {
-  min-width:2em;
-  float:left;
-}
-div.csl-right-inline {
-  margin-left:2em;
-  padding-left:1em;
-}
-div.csl-indent {
-  margin-left: 2em;
-}
diff --git a/docs/dev/pkgdown.js b/docs/dev/pkgdown.js
deleted file mode 100644
index 6f0eee40..00000000
--- a/docs/dev/pkgdown.js
+++ /dev/null
@@ -1,108 +0,0 @@
-/* http://gregfranko.com/blog/jquery-best-practices/ */
-(function($) {
-  $(function() {
-
-    $('.navbar-fixed-top').headroom();
-
-    $('body').css('padding-top', $('.navbar').height() + 10);
-    $(window).resize(function(){
-      $('body').css('padding-top', $('.navbar').height() + 10);
-    });
-
-    $('[data-toggle="tooltip"]').tooltip();
-
-    var cur_path = paths(location.pathname);
-    var links = $("#navbar ul li a");
-    var max_length = -1;
-    var pos = -1;
-    for (var i = 0; i < links.length; i++) {
-      if (links[i].getAttribute("href") === "#")
-        continue;
-      // Ignore external links
-      if (links[i].host !== location.host)
-        continue;
-
-      var nav_path = paths(links[i].pathname);
-
-      var length = prefix_length(nav_path, cur_path);
-      if (length > max_length) {
-        max_length = length;
-        pos = i;
-      }
-    }
-
-    // Add class to parent 
    • , and enclosing 
    •  if in dropdown
-    if (pos >= 0) {
-      var menu_anchor = $(links[pos]);
-      menu_anchor.parent().addClass("active");
-      menu_anchor.closest("li.dropdown").addClass("active");
-    }
-  });
-
-  function paths(pathname) {
-    var pieces = pathname.split("/");
-    pieces.shift(); // always starts with /
-
-    var end = pieces[pieces.length - 1];
-    if (end === "index.html" || end === "")
-      pieces.pop();
-    return(pieces);
-  }
-
-  // Returns -1 if not found
-  function prefix_length(needle, haystack) {
-    if (needle.length > haystack.length)
-      return(-1);
-
-    // Special case for length-0 haystack, since for loop won't run
-    if (haystack.length === 0) {
-      return(needle.length === 0 ? 0 : -1);
-    }
-
-    for (var i = 0; i < haystack.length; i++) {
-      if (needle[i] != haystack[i])
-        return(i);
-    }
-
-    return(haystack.length);
-  }
-
-  /* Clipboard --------------------------*/
-
-  function changeTooltipMessage(element, msg) {
-    var tooltipOriginalTitle=element.getAttribute('data-original-title');
-    element.setAttribute('data-original-title', msg);
-    $(element).tooltip('show');
-    element.setAttribute('data-original-title', tooltipOriginalTitle);
-  }
-
-  if(ClipboardJS.isSupported()) {
-    $(document).ready(function() {
-      var copyButton = "";
-
-      $("div.sourceCode").addClass("hasCopyButton");
-
-      // Insert copy buttons:
-      $(copyButton).prependTo(".hasCopyButton");
-
-      // Initialize tooltips:
-      $('.btn-copy-ex').tooltip({container: 'body'});
-
-      // Initialize clipboard:
-      var clipboardBtnCopies = new ClipboardJS('[data-clipboard-copy]', {
-        text: function(trigger) {
-          return trigger.parentNode.textContent.replace(/\n#>[^\n]*/g, "");
-        }
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-
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-        changeTooltipMessage(e.trigger, 'Copied!');
-        e.clearSelection();
-      });
-
-      clipboardBtnCopies.on('error', function() {
-        changeTooltipMessage(e.trigger,'Press Ctrl+C or Command+C to copy');
-      });
-    });
-  }
-})(window.jQuery || window.$)
diff --git a/docs/dev/pkgdown.yml b/docs/dev/pkgdown.yml
deleted file mode 100644
index c3829f60..00000000
--- a/docs/dev/pkgdown.yml
+++ /dev/null
@@ -1,23 +0,0 @@
-pandoc: 2.17.1.1
-pkgdown: 2.0.7
-pkgdown_sha: ~
-articles:
-  FOCUS_D: FOCUS_D.html
-  FOCUS_L: FOCUS_L.html
-  mkin: mkin.html
-  2022_cyan_pathway: prebuilt/2022_cyan_pathway.html
-  2022_dmta_parent: prebuilt/2022_dmta_parent.html
-  2022_dmta_pathway: prebuilt/2022_dmta_pathway.html
-  twa: twa.html
-  FOCUS_Z: web_only/FOCUS_Z.html
-  NAFTA_examples: web_only/NAFTA_examples.html
-  benchmarks: web_only/benchmarks.html
-  compiled_models: web_only/compiled_models.html
-  dimethenamid_2018: web_only/dimethenamid_2018.html
-  multistart: web_only/multistart.html
-  saem_benchmarks: web_only/saem_benchmarks.html
-last_built: 2023-04-20T18:24Z
-urls:
-  reference: https://pkgdown.jrwb.de/mkin/reference
-  article: https://pkgdown.jrwb.de/mkin/articles
-
diff --git a/docs/dev/reference/AIC.mmkin.html b/docs/dev/reference/AIC.mmkin.html
deleted file mode 100644
index ebfe052d..00000000
--- a/docs/dev/reference/AIC.mmkin.html
+++ /dev/null
@@ -1,220 +0,0 @@
-
-Calculate the AIC for a column of an mmkin object — AIC.mmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Calculate the AIC for a column of an mmkin object
      
-    Source: R/AIC.mmkin.R
-    
-    
      
-
-    
      
-    
      Provides a convenient way to compare different kinetic models fitted to the
-same dataset.
      
-    
      
-
-    
      
-    
      # S3 method for mmkin
-AIC(object, ..., k = 2)
-
-# S3 method for mmkin
-BIC(object, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      An object of class mmkin, containing only one
-column.
      
-
-
-
      ...
      
-
      For compatibility with the generic method
      
-
-
-
      k
      
-
      As in the generic method
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      As in the generic method (a numeric value for single fits, or a
-dataframe if there are several fits in the column).
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-   # skip, as it takes > 10 s on winbuilder
-  f <- mmkin(c("SFO", "FOMC", "DFOP"),
-    list("FOCUS A" = FOCUS_2006_A,
-         "FOCUS C" = FOCUS_2006_C), cores = 1, quiet = TRUE)
-  # We get a warning because the FOMC model does not converge for the
-  # FOCUS A dataset, as it is well described by SFO
-
-  AIC(f["SFO", "FOCUS A"]) # We get a single number for a single fit
-#> [1] 55.28197
-  AIC(f[["SFO", "FOCUS A"]]) # or when extracting an mkinfit object
-#> [1] 55.28197
-
-  # For FOCUS A, the models fit almost equally well, so the higher the number
-  # of parameters, the higher (worse) the AIC
-  AIC(f[, "FOCUS A"])
-#>      df      AIC
-#> SFO   3 55.28197
-#> FOMC  4 57.28222
-#> DFOP  5 59.28197
-  AIC(f[, "FOCUS A"], k = 0) # If we do not penalize additional parameters, we get nearly the same
-#>      df      AIC
-#> SFO   3 49.28197
-#> FOMC  4 49.28222
-#> DFOP  5 49.28197
-  BIC(f[, "FOCUS A"])        # Comparing the BIC gives a very similar picture
-#>      df      BIC
-#> SFO   3 55.52030
-#> FOMC  4 57.59999
-#> DFOP  5 59.67918
-
-  # For FOCUS C, the more complex models fit better
-  AIC(f[, "FOCUS C"])
-#>      df      AIC
-#> SFO   3 59.29336
-#> FOMC  4 44.68652
-#> DFOP  5 29.02372
-  BIC(f[, "FOCUS C"])
-#>      df      BIC
-#> SFO   3 59.88504
-#> FOMC  4 45.47542
-#> DFOP  5 30.00984
-  
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/CAKE_export.html b/docs/dev/reference/CAKE_export.html
deleted file mode 100644
index 7b52a8c5..00000000
--- a/docs/dev/reference/CAKE_export.html
+++ /dev/null
@@ -1,225 +0,0 @@
-
-Export a list of datasets format to a CAKE study file — CAKE_export • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Export a list of datasets format to a CAKE study file
      
-    Source: R/CAKE_export.R
-    
-    
      
-
-    
      
-    
      In addition to the datasets, the pathways in the degradation model can be
-specified as well.
      
-    
      
-
-    
      
-    
      CAKE_export(
-  ds,
-  map = c(parent = "Parent"),
-  links = NA,
-  filename = "CAKE_export.csf",
-  path = ".",
-  overwrite = FALSE,
-  study = "Degradinol aerobic soil degradation",
-  description = "",
-  time_unit = "days",
-  res_unit = "% AR",
-  comment = "",
-  date = Sys.Date(),
-  optimiser = "IRLS"
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      ds
      
-
      A named list of datasets in long format as compatible with
-mkinfit.
      
-
-
-
      map
      
-
      A character vector with CAKE compartment names (Parent, A1, ...),
-named with the names used in the list of datasets.
      
-
-
-
      links
      
-
      An optional character vector of target compartments, named with
-the names of the source compartments. In order to make this easier, the
-names are used as in the datasets supplied.
      
-
-
-
      filename
      
-
      Where to write the result. Should end in .csf in order to be
-compatible with CAKE.
      
-
-
-
      path
      
-
      An optional path to the output file.
      
-
-
-
      overwrite
      
-
      If TRUE, existing files are overwritten.
      
-
-
-
      study
      
-
      The name of the study.
      
-
-
-
      description
      
-
      An optional description.
      
-
-
-
      time_unit
      
-
      The time unit for the residue data.
      
-
-
-
      res_unit
      
-
      The unit used for the residues.
      
-
-
-
      comment
      
-
      An optional comment.
      
-
-
-
      date
      
-
      The date of file creation.
      
-
-
-
      optimiser
      
-
      Can be OLS or IRLS.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The function is called for its side effect.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/D24_2014.html b/docs/dev/reference/D24_2014.html
deleted file mode 100644
index 8af0a8e2..00000000
--- a/docs/dev/reference/D24_2014.html
+++ /dev/null
@@ -1,261 +0,0 @@
-
-Aerobic soil degradation data on 2,4-D from the EU assessment in 2014 — D24_2014 • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Aerobic soil degradation data on 2,4-D from the EU assessment in 2014
      
-    Source: R/D24_2014.R
-    
-    
      
-
-    
      
-    
      The five datasets were extracted from the active substance evaluation dossier
-published by EFSA. Kinetic evaluations shown for these datasets are intended
-to illustrate and advance kinetic modelling. The fact that these data and
-some results are shown here does not imply a license to use them in the
-context of pesticide  registrations, as the use of the data may be
-constrained by data protection regulations.
      
-    
      
-
-    
      
-    
      D24_2014
      
-    
      
-
-    
      
-    
      Format
      
-    
      An mkindsg object grouping five datasets
      
-    
      
-    
      
-    
      Source
      
-    
      Hellenic Ministry of Rural Development and Agriculture (2014)
-Final addendum to the Renewal Assessment Report - public version - 2,4-D
-Volume 3 Annex B.8 Fate and behaviour in the environment
-https://open.efsa.europa.eu/study-inventory/EFSA-Q-2013-00811
      
-    
      
-    
      
-    
      Details
      
-    
      Data for the first dataset are from p. 685. Data for the other four
-datasets were used in the preprocessed versions given in the kinetics
-section (p. 761ff.), with the exception of residues smaller than 1 for DCP
-in the soil from Site I2, where the values given on p. 694 were used.
      
-
      The R code used to create this data object is installed with this package
-in the 'dataset_generation' directory. In the code, page numbers are given for
-specific pieces of information in the comments.
      
-    
      
-
-    
      
-    
      Examples
      
-    
      print(D24_2014)
-#> <mkindsg> holding 5 mkinds objects
-#> Title $title:  Aerobic soil degradation data on 2,4-D from the EU assessment in 2014 
-#> Occurrence of observed compounds $observed_n:
-#> D24 DCP DCA 
-#>   5   4   4 
-#> Time normalisation factors $f_time_norm:
-#> [1] 1.6062378 0.7118732 0.7156063 0.7156063 0.8977124
-#> Meta information $meta:
-#>                                 study usda_soil_type study_moisture_ref_type
-#> Mississippi                Cohen 1991      Silt loam                    <NA>
-#> Fayette     Liu and Adelfinskaya 2011      Silt loam                     pF1
-#> RefSol 03-G Liu and Adelfinskaya 2011           Loam                     pF1
-#> Site E1     Liu and Adelfinskaya 2011           Loam                     pF1
-#> Site I2     Liu and Adelfinskaya 2011     Loamy sand                     pF1
-#>             rel_moisture temperature
-#> Mississippi           NA          25
-#> Fayette              0.5          20
-#> RefSol 03-G          0.5          20
-#> Site E1              0.5          20
-#> Site I2              0.5          20
-# \dontrun{
-print(D24_2014$ds[[1]], data = TRUE)
-#> <mkinds> with $title:  Mississippi 
-#> Observed compounds $observed:  D24 
-#> Sampling times $sampling_times:
-#> 0, 2, 4, 7, 15, 24, 35, 56, 71, 114, 183, 273, 365 
-#> With a maximum of  1  replicates
-#>    time  D24
-#> 1     0 96.8
-#> 2     2 81.0
-#> 3     4 81.7
-#> 4     7 88.2
-#> 5    15 66.3
-#> 6    24 72.9
-#> 7    35 62.6
-#> 8    56 54.6
-#> 9    71 35.2
-#> 10  114 18.0
-#> 11  183 11.3
-#> 12  273  9.9
-#> 13  365  6.3
-m_D24 = mkinmod(D24 = mkinsub("SFO", to = "DCP"),
-  DCP = mkinsub("SFO", to = "DCA"),
-  DCA = mkinsub("SFO"))
-#> Temporary DLL for differentials generated and loaded
-print(m_D24)
-#> <mkinmod> model generated with
-#> Use of formation fractions $use_of_ff: max 
-#> Specification $spec:
-#> $D24
-#> $type: SFO; $to: DCP; $sink: TRUE
-#> $DCP
-#> $type: SFO; $to: DCA; $sink: TRUE
-#> $DCA
-#> $type: SFO; $sink: TRUE
-#> Coefficient matrix $coefmat available
-#> Compiled model $cf available
-#> Differential equations:
-#> d_D24/dt = - k_D24 * D24
-#> d_DCP/dt = + f_D24_to_DCP * k_D24 * D24 - k_DCP * DCP
-#> d_DCA/dt = + f_DCP_to_DCA * k_DCP * DCP - k_DCA * DCA
-m_D24_2 = mkinmod(D24 = mkinsub("DFOP", to = "DCP"),
-  DCP = mkinsub("SFO", to = "DCA"),
-  DCA = mkinsub("SFO"))
-#> Temporary DLL for differentials generated and loaded
-print(m_D24_2)
-#> <mkinmod> model generated with
-#> Use of formation fractions $use_of_ff: max 
-#> Specification $spec:
-#> $D24
-#> $type: DFOP; $to: DCP; $sink: TRUE
-#> $DCP
-#> $type: SFO; $to: DCA; $sink: TRUE
-#> $DCA
-#> $type: SFO; $sink: TRUE
-#> Compiled model $cf available
-#> Differential equations:
-#> d_D24/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-#>            time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-#>            * D24
-#> d_DCP/dt = + f_D24_to_DCP * ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
-#>            exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2
-#>            * time))) * D24 - k_DCP * DCP
-#> d_DCA/dt = + f_DCP_to_DCA * k_DCP * DCP - k_DCA * DCA
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/DFOP.solution-1.png b/docs/dev/reference/DFOP.solution-1.png
deleted file mode 100644
index 6b78836f..00000000
Binary files a/docs/dev/reference/DFOP.solution-1.png and /dev/null differ
diff --git a/docs/dev/reference/DFOP.solution.html b/docs/dev/reference/DFOP.solution.html
deleted file mode 100644
index d462133c..00000000
--- a/docs/dev/reference/DFOP.solution.html
+++ /dev/null
@@ -1,202 +0,0 @@
-
-Double First-Order in Parallel kinetics — DFOP.solution • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Double First-Order in Parallel kinetics
      
-    Source: R/parent_solutions.R
-    
-    
      
-
-    
      
-    
      Function describing decline from a defined starting value using the sum of
-two exponential decline functions.
      
-    
      
-
-    
      
-    
      DFOP.solution(t, parent_0, k1, k2, g)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      t
      
-
      Time.
      
-
-
-
      parent_0
      
-
      Starting value for the response variable at time zero.
      
-
-
-
      k1
      
-
      First kinetic constant.
      
-
-
-
      k2
      
-
      Second kinetic constant.
      
-
-
-
      g
      
-
      Fraction of the starting value declining according to the first
-kinetic constant.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The value of the response variable at time t.
      
-    
      
-    
      
-    
      References
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
-FOCUS (2014) “Generic guidance for Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-Version 1.1, 18 December 2014
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-    
      
-    
      
-    
      See also
      
-    
      Other parent solutions: 
-FOMC.solution(),
-HS.solution(),
-IORE.solution(),
-SFO.solution(),
-SFORB.solution(),
-logistic.solution()
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-  plot(function(x) DFOP.solution(x, 100, 5, 0.5, 0.3), 0, 4, ylim = c(0,100))
-
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/Extract.mmkin.html b/docs/dev/reference/Extract.mmkin.html
deleted file mode 100644
index 3a22d14b..00000000
--- a/docs/dev/reference/Extract.mmkin.html
+++ /dev/null
@@ -1,235 +0,0 @@
-
-Subsetting method for mmkin objects — [.mmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Subsetting method for mmkin objects
      
-    Source: R/mmkin.R
-    
-    
      
-
-    
      
-    
      Subsetting method for mmkin objects
      
-    
      
-
-    
      
-    
      # S3 method for mmkin
-[(x, i, j, ..., drop = FALSE)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      x
      
-
      An mmkin object
      
-
-
-
      i
      
-
      Row index selecting the fits for specific models
      
-
-
-
      j
      
-
      Column index selecting the fits to specific datasets
      
-
-
-
      ...
      
-
      Not used, only there to satisfy the generic method definition
      
-
-
-
      drop
      
-
      If FALSE, the method always returns an mmkin object, otherwise
-either a list of mkinfit objects or a single mkinfit object.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      An object of class mmkin.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-  # Only use one core, to pass R CMD check --as-cran
-  fits <- mmkin(c("SFO", "FOMC"), list(B = FOCUS_2006_B, C = FOCUS_2006_C),
-                cores = 1, quiet = TRUE)
-  fits["FOMC", ]
-#> <mmkin> object
-#> Status of individual fits:
-#> 
-#>       dataset
-#> model  B  C 
-#>   FOMC OK OK
-#> 
-#> OK: No warnings
-  fits[, "B"]
-#> <mmkin> object
-#> Status of individual fits:
-#> 
-#>       dataset
-#> model  B 
-#>   SFO  OK
-#>   FOMC OK
-#> 
-#> OK: No warnings
-  fits["SFO", "B"]
-#> <mmkin> object
-#> Status of individual fits:
-#> 
-#>      dataset
-#> model B 
-#>   SFO OK
-#> 
-#> OK: No warnings
-
-  head(
-    # This extracts an mkinfit object with lots of components
-    fits[["FOMC", "B"]]
-  )
-#> $par
-#>  parent_0 log_alpha  log_beta     sigma 
-#> 99.666192  2.549850  5.050586  1.890202 
-#> 
-#> $objective
-#> [1] 28.58291
-#> 
-#> $convergence
-#> [1] 0
-#> 
-#> $iterations
-#> [1] 21
-#> 
-#> $evaluations
-#> function gradient 
-#>       25       78 
-#> 
-#> $message
-#> [1] "both X-convergence and relative convergence (5)"
-#> 
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/FOCUS_2006_DFOP_ref_A_to_B.html b/docs/dev/reference/FOCUS_2006_DFOP_ref_A_to_B.html
deleted file mode 100644
index a8eb25cf..00000000
--- a/docs/dev/reference/FOCUS_2006_DFOP_ref_A_to_B.html
+++ /dev/null
@@ -1,189 +0,0 @@
-
-Results of fitting the DFOP model to Datasets A to B of FOCUS (2006) — FOCUS_2006_DFOP_ref_A_to_B • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Results of fitting the DFOP model to Datasets A to B of FOCUS (2006)
      
-    
-    
-    
      
-
-    
      
-    
      A table with the fitted parameters and the resulting DT50 and DT90 values
-generated with different software packages. Taken directly from FOCUS (2006).
-The results from fitting the data with the Topfit software was removed, as
-the initial concentration of the parent compound was fixed to a value of 100
-in this fit.
      
-    
      
-
-    
      
-    
      FOCUS_2006_DFOP_ref_A_to_B
      
-    
      
-
-    
      
-    
      Format
      
-    
      A data frame containing the following variables.
      package
      
-
      a factor giving the name of the software package
      
-
-    
      M0
      
-
      The fitted initial concentration of the parent compound
      
-
-    
      f
      
-
      The fitted f parameter
      
-
-    
      k1
      
-
      The fitted k1 parameter
      
-
-    
      k2
      
-
      The fitted k2 parameter
      
-
-    
      DT50
      
-
      The resulting half-life of the parent compound
      
-
-    
      DT90
      
-
      The resulting DT90 of the parent compound
      
-
-    
      dataset
      
-
      The FOCUS dataset that was used
      
-
-  
-
      
-    
      
-    
      Source
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence and
-  Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
-  Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-  EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-    
      
-
-    
      
-    
      Examples
      
-    
      data(FOCUS_2006_DFOP_ref_A_to_B)
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/FOCUS_2006_FOMC_ref_A_to_F.html b/docs/dev/reference/FOCUS_2006_FOMC_ref_A_to_F.html
deleted file mode 100644
index 24297c78..00000000
--- a/docs/dev/reference/FOCUS_2006_FOMC_ref_A_to_F.html
+++ /dev/null
@@ -1,186 +0,0 @@
-
-Results of fitting the FOMC model to Datasets A to F of FOCUS (2006) — FOCUS_2006_FOMC_ref_A_to_F • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Results of fitting the FOMC model to Datasets A to F of FOCUS (2006)
      
-    
-    
-    
      
-
-    
      
-    
      A table with the fitted parameters and the resulting DT50 and DT90 values
-generated with different software packages. Taken directly from FOCUS (2006).
-The results from fitting the data with the Topfit software was removed, as
-the initial concentration of the parent compound was fixed to a value of 100
-in this fit.
      
-    
      
-
-    
      
-    
      FOCUS_2006_FOMC_ref_A_to_F
      
-    
      
-
-    
      
-    
      Format
      
-    
      A data frame containing the following variables.
      package
      
-
      a factor giving the name of the software package
      
-
-    
      M0
      
-
      The fitted initial concentration of the parent compound
      
-
-    
      alpha
      
-
      The fitted alpha parameter
      
-
-    
      beta
      
-
      The fitted beta parameter
      
-
-    
      DT50
      
-
      The resulting half-life of the parent compound
      
-
-    
      DT90
      
-
      The resulting DT90 of the parent compound
      
-
-    
      dataset
      
-
      The FOCUS dataset that was used
      
-
-  
-
      
-    
      
-    
      Source
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence and
-  Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
-  Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-  EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-    
      
-
-    
      
-    
      Examples
      
-    
      data(FOCUS_2006_FOMC_ref_A_to_F)
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/FOCUS_2006_HS_ref_A_to_F.html b/docs/dev/reference/FOCUS_2006_HS_ref_A_to_F.html
deleted file mode 100644
index caf258ba..00000000
--- a/docs/dev/reference/FOCUS_2006_HS_ref_A_to_F.html
+++ /dev/null
@@ -1,189 +0,0 @@
-
-Results of fitting the HS model to Datasets A to F of FOCUS (2006) — FOCUS_2006_HS_ref_A_to_F • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Results of fitting the HS model to Datasets A to F of FOCUS (2006)
      
-    
-    
-    
      
-
-    
      
-    
      A table with the fitted parameters and the resulting DT50 and DT90 values
-generated with different software packages. Taken directly from FOCUS (2006).
-The results from fitting the data with the Topfit software was removed, as
-the initial concentration of the parent compound was fixed to a value of 100
-in this fit.
      
-    
      
-
-    
      
-    
      FOCUS_2006_HS_ref_A_to_F
      
-    
      
-
-    
      
-    
      Format
      
-    
      A data frame containing the following variables.
      package
      
-
      a factor giving the name of the software package
      
-
-    
      M0
      
-
      The fitted initial concentration of the parent compound
      
-
-    
      tb
      
-
      The fitted tb parameter
      
-
-    
      k1
      
-
      The fitted k1 parameter
      
-
-    
      k2
      
-
      The fitted k2 parameter
      
-
-    
      DT50
      
-
      The resulting half-life of the parent compound
      
-
-    
      DT90
      
-
      The resulting DT90 of the parent compound
      
-
-    
      dataset
      
-
      The FOCUS dataset that was used
      
-
-  
-
      
-    
      
-    
      Source
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence and
-  Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
-  Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-  EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-    
      
-
-    
      
-    
      Examples
      
-    
      data(FOCUS_2006_HS_ref_A_to_F)
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/FOCUS_2006_SFO_ref_A_to_F.html b/docs/dev/reference/FOCUS_2006_SFO_ref_A_to_F.html
deleted file mode 100644
index bc3d1c08..00000000
--- a/docs/dev/reference/FOCUS_2006_SFO_ref_A_to_F.html
+++ /dev/null
@@ -1,183 +0,0 @@
-
-Results of fitting the SFO model to Datasets A to F of FOCUS (2006) — FOCUS_2006_SFO_ref_A_to_F • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Results of fitting the SFO model to Datasets A to F of FOCUS (2006)
      
-    
-    
-    
      
-
-    
      
-    
      A table with the fitted parameters and the resulting DT50 and DT90 values
-generated with different software packages. Taken directly from FOCUS (2006).
-The results from fitting the data with the Topfit software was removed, as
-the initial concentration of the parent compound was fixed to a value of 100
-in this fit.
      
-    
      
-
-    
      
-    
      FOCUS_2006_SFO_ref_A_to_F
      
-    
      
-
-    
      
-    
      Format
      
-    
      A data frame containing the following variables.
      package
      
-
      a factor giving the name of the software package
      
-
-    
      M0
      
-
      The fitted initial concentration of the parent compound
      
-
-    
      k
      
-
      The fitted first-order degradation rate constant
      
-
-    
      DT50
      
-
      The resulting half-life of the parent compound
      
-
-    
      DT90
      
-
      The resulting DT90 of the parent compound
      
-
-    
      dataset
      
-
      The FOCUS dataset that was used
      
-
-  
-
      
-    
      
-    
      Source
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence and
-  Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
-  Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-  EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-    
      
-
-    
      
-    
      Examples
      
-    
      data(FOCUS_2006_SFO_ref_A_to_F)
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/FOCUS_2006_datasets.html b/docs/dev/reference/FOCUS_2006_datasets.html
deleted file mode 100644
index 78f8e81b..00000000
--- a/docs/dev/reference/FOCUS_2006_datasets.html
+++ /dev/null
@@ -1,181 +0,0 @@
-
-Datasets A to F from the FOCUS Kinetics report from 2006 — FOCUS_2006_datasets • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Datasets A to F from the FOCUS Kinetics report from 2006
      
-    
-    
-    
      
-
-    
      
-    
      Data taken from FOCUS (2006), p. 258.
      
-    
      
-
-    
      
-    
      FOCUS_2006_A
-  FOCUS_2006_B
-  FOCUS_2006_C
-  FOCUS_2006_D
-  FOCUS_2006_E
-  FOCUS_2006_F
      
-    
      
-
-    
      
-    
      Format
      
-    
      6 datasets with observations on the following variables.
      name
      
-
      a factor containing the name of the observed variable
      
-
-    
      time
      
-
      a numeric vector containing time points
      
-
-    
      value
      
-
      a numeric vector containing concentrations in percent of applied radioactivity
      
-
-  
-
      
-    
      
-    
      Source
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence and
-  Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
-  Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-  EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-    
      
-
-    
      
-    
      Examples
      
-    
      FOCUS_2006_C
-#>     name time value
-#> 1 parent    0  85.1
-#> 2 parent    1  57.9
-#> 3 parent    3  29.9
-#> 4 parent    7  14.6
-#> 5 parent   14   9.7
-#> 6 parent   28   6.6
-#> 7 parent   63   4.0
-#> 8 parent   91   3.9
-#> 9 parent  119   0.6
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/FOMC.solution-1.png b/docs/dev/reference/FOMC.solution-1.png
deleted file mode 100644
index 18a4b586..00000000
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diff --git a/docs/dev/reference/FOMC.solution.html b/docs/dev/reference/FOMC.solution.html
deleted file mode 100644
index e1813261..00000000
--- a/docs/dev/reference/FOMC.solution.html
+++ /dev/null
@@ -1,213 +0,0 @@
-
-First-Order Multi-Compartment kinetics — FOMC.solution • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      First-Order Multi-Compartment kinetics
      
-    Source: R/parent_solutions.R
-    
-    
      
-
-    
      
-    
      Function describing exponential decline from a defined starting value, with
-a decreasing rate constant.
      
-    
      
-
-    
      
-    
      FOMC.solution(t, parent_0, alpha, beta)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      t
      
-
      Time.
      
-
-
-
      parent_0
      
-
      Starting value for the response variable at time zero.
      
-
-
-
      alpha
      
-
      Shape parameter determined by coefficient of variation of rate
-constant values.
      
-
-
-
      beta
      
-
      Location parameter.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The value of the response variable at time t.
      
-    
      
-    
      
-    
      Details
      
-    
      The form given here differs slightly from the original reference by
-Gustafson and Holden (1990). The parameter beta corresponds to 1/beta
-in the original equation.
      
-    
      
-    
      
-    
      Note
      
-    
      The solution of the FOMC kinetic model reduces to the
-SFO.solution for large values of alpha and beta
-with \(k = \frac{\beta}{\alpha}\).
      
-    
      
-    
      
-    
      References
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-
      FOCUS (2014) “Generic guidance for Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-Version 1.1, 18 December 2014
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-
      Gustafson DI and Holden LR (1990) Nonlinear pesticide dissipation in soil:
-A new model based on spatial variability. Environmental Science and
-Technology 24, 1032-1038
      
-    
      
-    
      
-    
      See also
      
-    
      Other parent solutions: 
-DFOP.solution(),
-HS.solution(),
-IORE.solution(),
-SFO.solution(),
-SFORB.solution(),
-logistic.solution()
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-  plot(function(x) FOMC.solution(x, 100, 10, 2), 0, 2, ylim = c(0, 100))
-
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/HS.solution-1.png b/docs/dev/reference/HS.solution-1.png
deleted file mode 100644
index 61d89dbc..00000000
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diff --git a/docs/dev/reference/HS.solution.html b/docs/dev/reference/HS.solution.html
deleted file mode 100644
index d42eaef6..00000000
--- a/docs/dev/reference/HS.solution.html
+++ /dev/null
@@ -1,203 +0,0 @@
-
-Hockey-Stick kinetics — HS.solution • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Hockey-Stick kinetics
      
-    Source: R/parent_solutions.R
-    
-    
      
-
-    
      
-    
      Function describing two exponential decline functions with a break point
-between them.
      
-    
      
-
-    
      
-    
      HS.solution(t, parent_0, k1, k2, tb)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      t
      
-
      Time.
      
-
-
-
      parent_0
      
-
      Starting value for the response variable at time zero.
      
-
-
-
      k1
      
-
      First kinetic constant.
      
-
-
-
      k2
      
-
      Second kinetic constant.
      
-
-
-
      tb
      
-
      Break point. Before this time, exponential decline according to
-k1 is calculated, after this time, exponential decline proceeds
-according to k2.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The value of the response variable at time t.
      
-    
      
-    
      
-    
      References
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
-FOCUS (2014) “Generic guidance for Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-Version 1.1, 18 December 2014
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-    
      
-    
      
-    
      See also
      
-    
      Other parent solutions: 
-DFOP.solution(),
-FOMC.solution(),
-IORE.solution(),
-SFO.solution(),
-SFORB.solution(),
-logistic.solution()
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-  plot(function(x) HS.solution(x, 100, 2, 0.3, 0.5), 0, 2, ylim=c(0,100))
-
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/IORE.solution-1.png b/docs/dev/reference/IORE.solution-1.png
deleted file mode 100644
index 54c9dcae..00000000
Binary files a/docs/dev/reference/IORE.solution-1.png and /dev/null differ
diff --git a/docs/dev/reference/IORE.solution.html b/docs/dev/reference/IORE.solution.html
deleted file mode 100644
index b9d4734f..00000000
--- a/docs/dev/reference/IORE.solution.html
+++ /dev/null
@@ -1,218 +0,0 @@
-
-Indeterminate order rate equation kinetics — IORE.solution • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Indeterminate order rate equation kinetics
      
-    Source: R/parent_solutions.R
-    
-    
      
-
-    
      
-    
      Function describing exponential decline from a defined starting value, with
-a concentration dependent rate constant.
      
-    
      
-
-    
      
-    
      IORE.solution(t, parent_0, k__iore, N)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      t
      
-
      Time.
      
-
-
-
      parent_0
      
-
      Starting value for the response variable at time zero.
      
-
-
-
      k__iore
      
-
      Rate constant. Note that this depends on the concentration
-units used.
      
-
-
-
      N
      
-
      Exponent describing the nonlinearity of the rate equation
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The value of the response variable at time t.
      
-    
      
-    
      
-    
      Note
      
-    
      The solution of the IORE kinetic model reduces to the
-SFO.solution if N = 1.  The parameters of the IORE model can
-be transformed to equivalent parameters of the FOMC mode - see the NAFTA
-guidance for details.
      
-    
      
-    
      
-    
      References
      
-    
      NAFTA Technical Working Group on Pesticides (not dated) Guidance
-for Evaluating and Calculating Degradation Kinetics in Environmental Media
      
-    
      
-    
      
-    
      See also
      
-    
      Other parent solutions: 
-DFOP.solution(),
-FOMC.solution(),
-HS.solution(),
-SFO.solution(),
-SFORB.solution(),
-logistic.solution()
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-  plot(function(x) IORE.solution(x, 100, 0.2, 1.3), 0, 2, ylim = c(0, 100))
-
-  # \dontrun{
-    fit.fomc <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
-    fit.iore <- mkinfit("IORE", FOCUS_2006_C, quiet = TRUE)
-    fit.iore.deS <- mkinfit("IORE", FOCUS_2006_C, solution_type = "deSolve", quiet = TRUE)
-#> Error in is.loaded(initfunc, PACKAGE = dllname, type = "") : 
-#>   invalid 'PACKAGE' argument
-
-    print(data.frame(fit.fomc$par, fit.iore$par, fit.iore.deS$par,
-                     row.names = paste("model par", 1:4)))
-#>             fit.fomc.par fit.iore.par fit.iore.deS.par
-#> model par 1  85.87489063    85.874890        85.874890
-#> model par 2   0.05192238    -4.826631        -4.826631
-#> model par 3   0.65096665     1.949403         1.949403
-#> model par 4   1.85744396     1.857444         1.857444
-    print(rbind(fomc = endpoints(fit.fomc)$distimes, iore = endpoints(fit.iore)$distimes,
-                iore.deS = endpoints(fit.iore)$distimes))
-#>              DT50    DT90 DT50back
-#> fomc     1.785233 15.1479 4.559973
-#> iore     1.785233 15.1479 4.559973
-#> iore.deS 1.785233 15.1479 4.559973
-  # }
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/NAFTA_SOP_2015-1.png b/docs/dev/reference/NAFTA_SOP_2015-1.png
deleted file mode 100644
index 98d4246c..00000000
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diff --git a/docs/dev/reference/NAFTA_SOP_2015.html b/docs/dev/reference/NAFTA_SOP_2015.html
deleted file mode 100644
index 299863d7..00000000
--- a/docs/dev/reference/NAFTA_SOP_2015.html
+++ /dev/null
@@ -1,215 +0,0 @@
-
-Example datasets from the NAFTA SOP published 2015 — NAFTA_SOP_2015 • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Example datasets from the NAFTA SOP published 2015
      
-    
-    
-    
      
-
-    
      
-    
      Data taken from US EPA (2015), p. 19 and 23.
      
-    
      
-
-    
      
-    
      NAFTA_SOP_Appendix_B
-  NAFTA_SOP_Appendix_D
      
-    
      
-
-    
      
-    
      Format
      
-    
      2 datasets with observations on the following variables.
      name
      
-
      a factor containing the name of the observed variable
      
-
-    
      time
      
-
      a numeric vector containing time points
      
-
-    
      value
      
-
      a numeric vector containing concentrations
      
-
-  
-
      
-    
      
-    
      Source
      
-    
      NAFTA (2011) Guidance for evaluating and calculating degradation kinetics
-  in environmental media. NAFTA Technical Working Group on Pesticides
-  https://www.epa.gov/pesticide-science-and-assessing-pesticide-risks/guidance-evaluating-and-calculating-degradation
-  accessed 2019-02-22
      
-
      US EPA (2015) Standard Operating Procedure for Using the NAFTA Guidance to
-  Calculate Representative Half-life Values and Characterizing Pesticide
-  Degradation
-  https://www.epa.gov/pesticide-science-and-assessing-pesticide-risks/standard-operating-procedure-using-nafta-guidance
      
-    
      
-
-    
      
-    
      Examples
      
-    
        nafta_evaluation <- nafta(NAFTA_SOP_Appendix_D, cores = 1)
-#> The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
-#> The representative half-life of the IORE model is longer than the one corresponding
-#> to the terminal degradation rate found with the DFOP model.
-#> The representative half-life obtained from the DFOP model may be used
-  print(nafta_evaluation)
-#> Sums of squares:
-#>       SFO      IORE      DFOP 
-#> 1378.6832  615.7730  517.8836 
-#> 
-#> Critical sum of squares for checking the SFO model:
-#> [1] 717.4598
-#> 
-#> Parameters:
-#> $SFO
-#>          Estimate   Pr(>t)    Lower   Upper
-#> parent_0  83.7558 1.80e-14 77.18268 90.3288
-#> k_parent   0.0017 7.43e-05  0.00112  0.0026
-#> sigma      8.7518 1.22e-05  5.64278 11.8608
-#> 
-#> $IORE
-#>                Estimate Pr(>t)    Lower    Upper
-#> parent_0       9.69e+01     NA 8.88e+01 1.05e+02
-#> k__iore_parent 8.40e-14     NA 1.79e-18 3.94e-09
-#> N_parent       6.68e+00     NA 4.19e+00 9.17e+00
-#> sigma          5.85e+00     NA 3.76e+00 7.94e+00
-#> 
-#> $DFOP
-#>          Estimate   Pr(>t)    Lower    Upper
-#> parent_0 9.76e+01 1.94e-13 9.02e+01 1.05e+02
-#> k1       4.24e-02 5.92e-03 2.03e-02 8.88e-02
-#> k2       8.24e-04 6.48e-03 3.89e-04 1.75e-03
-#> g        2.88e-01 2.47e-05 1.95e-01 4.03e-01
-#> sigma    5.36e+00 2.22e-05 3.43e+00 7.30e+00
-#> 
-#> 
-#> DTx values:
-#>      DT50    DT90 DT50_rep
-#> SFO   407    1350      407
-#> IORE  541 5190000  1560000
-#> DFOP  429    2380      841
-#> 
-#> Representative half-life:
-#> [1] 841.41
-  plot(nafta_evaluation)
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/NAFTA_SOP_Attachment-1.png b/docs/dev/reference/NAFTA_SOP_Attachment-1.png
deleted file mode 100644
index a6066441..00000000
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diff --git a/docs/dev/reference/NAFTA_SOP_Attachment.html b/docs/dev/reference/NAFTA_SOP_Attachment.html
deleted file mode 100644
index 6bc86b46..00000000
--- a/docs/dev/reference/NAFTA_SOP_Attachment.html
+++ /dev/null
@@ -1,204 +0,0 @@
-
-Example datasets from Attachment 1 to the NAFTA SOP published 2015 — NAFTA_SOP_Attachment • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Example datasets from Attachment 1 to the NAFTA SOP published 2015
      
-    
-    
-    
      
-
-    
      
-    
      Data taken from from Attachment 1 of the SOP.
      
-    
      
-
-    
      
-    
      NAFTA_SOP_Attachment
      
-    
      
-
-    
      
-    
      Format
      
-    
      A list (NAFTA_SOP_Attachment) containing 16 datasets suitable
-  for the evaluation with nafta
      
-    
      
-    
      
-    
      Source
      
-    
      NAFTA (2011) Guidance for evaluating and calculating degradation kinetics
-  in environmental media. NAFTA Technical Working Group on Pesticides
-  https://www.epa.gov/pesticide-science-and-assessing-pesticide-risks/guidance-evaluating-and-calculating-degradation
-  accessed 2019-02-22
      
-
      US EPA (2015) Standard Operating Procedure for Using the NAFTA Guidance to
-  Calculate Representative Half-life Values and Characterizing Pesticide
-  Degradation
-  https://www.epa.gov/pesticide-science-and-assessing-pesticide-risks/standard-operating-procedure-using-nafta-guidance
      
-    
      
-
-    
      
-    
      Examples
      
-    
        nafta_att_p5a <- nafta(NAFTA_SOP_Attachment[["p5a"]], cores = 1)
-#> The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
-#> The half-life obtained from the IORE model may be used
-  print(nafta_att_p5a)
-#> Sums of squares:
-#>       SFO      IORE      DFOP 
-#> 465.21753  56.27506  32.06401 
-#> 
-#> Critical sum of squares for checking the SFO model:
-#> [1] 64.4304
-#> 
-#> Parameters:
-#> $SFO
-#>          Estimate   Pr(>t)  Lower   Upper
-#> parent_0  95.8401 4.67e-21 92.245 99.4357
-#> k_parent   0.0102 3.92e-12  0.009  0.0117
-#> sigma      4.8230 3.81e-06  3.214  6.4318
-#> 
-#> $IORE
-#>                Estimate Pr(>t)    Lower    Upper
-#> parent_0       1.01e+02     NA 9.91e+01 1.02e+02
-#> k__iore_parent 1.54e-05     NA 4.08e-06 5.84e-05
-#> N_parent       2.57e+00     NA 2.25e+00 2.89e+00
-#> sigma          1.68e+00     NA 1.12e+00 2.24e+00
-#> 
-#> $DFOP
-#>          Estimate   Pr(>t)   Lower    Upper
-#> parent_0 9.99e+01 1.41e-26 98.8116 101.0810
-#> k1       2.67e-02 5.05e-06  0.0243   0.0295
-#> k2       2.26e-12 5.00e-01  0.0000      Inf
-#> g        6.47e-01 3.67e-06  0.6248   0.6677
-#> sigma    1.27e+00 8.91e-06  0.8395   1.6929
-#> 
-#> 
-#> DTx values:
-#>      DT50     DT90 DT50_rep
-#> SFO  67.7 2.25e+02 6.77e+01
-#> IORE 58.2 1.07e+03 3.22e+02
-#> DFOP 55.5 5.59e+11 3.07e+11
-#> 
-#> Representative half-life:
-#> [1] 321.51
-  plot(nafta_att_p5a)
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
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diff --git a/docs/dev/reference/SFO.solution.html b/docs/dev/reference/SFO.solution.html
deleted file mode 100644
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--- a/docs/dev/reference/SFO.solution.html
+++ /dev/null
@@ -1,191 +0,0 @@
-
-Single First-Order kinetics — SFO.solution • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Single First-Order kinetics
      
-    Source: R/parent_solutions.R
-    
-    
      
-
-    
      
-    
      Function describing exponential decline from a defined starting value.
      
-    
      
-
-    
      
-    
      SFO.solution(t, parent_0, k)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      t
      
-
      Time.
      
-
-
-
      parent_0
      
-
      Starting value for the response variable at time zero.
      
-
-
-
      k
      
-
      Kinetic rate constant.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The value of the response variable at time t.
      
-    
      
-    
      
-    
      References
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
-FOCUS (2014) “Generic guidance for Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-Version 1.1, 18 December 2014
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-    
      
-    
      
-    
      See also
      
-    
      Other parent solutions: 
-DFOP.solution(),
-FOMC.solution(),
-HS.solution(),
-IORE.solution(),
-SFORB.solution(),
-logistic.solution()
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-  plot(function(x) SFO.solution(x, 100, 3), 0, 2)
-
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/SFORB.solution-1.png b/docs/dev/reference/SFORB.solution-1.png
deleted file mode 100644
index 08d25616..00000000
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diff --git a/docs/dev/reference/SFORB.solution.html b/docs/dev/reference/SFORB.solution.html
deleted file mode 100644
index 7e584ace..00000000
--- a/docs/dev/reference/SFORB.solution.html
+++ /dev/null
@@ -1,209 +0,0 @@
-
-Single First-Order Reversible Binding kinetics — SFORB.solution • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Single First-Order Reversible Binding kinetics
      
-    Source: R/parent_solutions.R
-    
-    
      
-
-    
      
-    
      Function describing the solution of the differential equations describing
-the kinetic model with first-order terms for a two-way transfer from a free
-to a bound fraction, and a first-order degradation term for the free
-fraction.  The initial condition is a defined amount in the free fraction
-and no substance in the bound fraction.
      
-    
      
-
-    
      
-    
      SFORB.solution(t, parent_0, k_12, k_21, k_1output)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      t
      
-
      Time.
      
-
-
-
      parent_0
      
-
      Starting value for the response variable at time zero.
      
-
-
-
      k_12
      
-
      Kinetic constant describing transfer from free to bound.
      
-
-
-
      k_21
      
-
      Kinetic constant describing transfer from bound to free.
      
-
-
-
      k_1output
      
-
      Kinetic constant describing degradation of the free
-fraction.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The value of the response variable, which is the sum of free and
-bound fractions at time t.
      
-    
      
-    
      
-    
      References
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
-FOCUS (2014) “Generic guidance for Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-Version 1.1, 18 December 2014
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-    
      
-    
      
-    
      See also
      
-    
      Other parent solutions: 
-DFOP.solution(),
-FOMC.solution(),
-HS.solution(),
-IORE.solution(),
-SFO.solution(),
-logistic.solution()
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-  plot(function(x) SFORB.solution(x, 100, 0.5, 2, 3), 0, 2)
-
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/add_err-1.png b/docs/dev/reference/add_err-1.png
deleted file mode 100644
index 68cfb344..00000000
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diff --git a/docs/dev/reference/add_err-2.png b/docs/dev/reference/add_err-2.png
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diff --git a/docs/dev/reference/add_err-3.png b/docs/dev/reference/add_err-3.png
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diff --git a/docs/dev/reference/add_err.html b/docs/dev/reference/add_err.html
deleted file mode 100644
index 57db40d1..00000000
--- a/docs/dev/reference/add_err.html
+++ /dev/null
@@ -1,262 +0,0 @@
-
-Add normally distributed errors to simulated kinetic degradation data — add_err • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Add normally distributed errors to simulated kinetic degradation data
      
-    Source: R/add_err.R
-    
-    
      
-
-    
      
-    
      Normally distributed errors are added to data predicted for a specific
-degradation model using mkinpredict. The variance of the error
-may depend on the predicted value and is specified as a standard deviation.
      
-    
      
-
-    
      
-    
      add_err(
-  prediction,
-  sdfunc,
-  secondary = c("M1", "M2"),
-  n = 10,
-  LOD = 0.1,
-  reps = 2,
-  digits = 1,
-  seed = NA
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      prediction
      
-
      A prediction from a kinetic model as produced by
-mkinpredict.
      
-
-
-
      sdfunc
      
-
      A function taking the predicted value as its only argument and
-returning a standard deviation that should be used for generating the
-random error terms for this value.
      
-
-
-
      secondary
      
-
      The names of state variables that should have an initial
-value of zero
      
-
-
-
      n
      
-
      The number of datasets to be generated.
      
-
-
-
      LOD
      
-
      The limit of detection (LOD). Values that are below the LOD after
-adding the random error will be set to NA.
      
-
-
-
      reps
      
-
      The number of replicates to be generated within the datasets.
      
-
-
-
      digits
      
-
      The number of digits to which the values will be rounded.
      
-
-
-
      seed
      
-
      The seed used for the generation of random numbers. If NA, the
-seed is not set.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      A list of datasets compatible with mmkin, i.e. the
-components of the list are datasets compatible with mkinfit.
      
-    
      
-    
      
-    
      References
      
-    
      Ranke J and Lehmann R (2015) To t-test or not to t-test, that is
-the question. XV Symposium on Pesticide Chemistry 2-4 September 2015,
-Piacenza, Italy
-https://jrwb.de/posters/piacenza_2015.pdf
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-# The kinetic model
-m_SFO_SFO <- mkinmod(parent = mkinsub("SFO", "M1"),
-                     M1 = mkinsub("SFO"), use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-
-# Generate a prediction for a specific set of parameters
-sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-
-# This is the prediction used for the "Type 2 datasets" on the Piacenza poster
-# from 2015
-d_SFO_SFO <- mkinpredict(m_SFO_SFO,
-                         c(k_parent = 0.1, f_parent_to_M1 = 0.5,
-                           k_M1 = log(2)/1000),
-                         c(parent = 100, M1 = 0),
-                         sampling_times)
-
-# Add an error term with a constant (independent of the value) standard deviation
-# of 10, and generate three datasets
-d_SFO_SFO_err <- add_err(d_SFO_SFO, function(x) 10, n = 3, seed = 123456789 )
-
-# Name the datasets for nicer plotting
-names(d_SFO_SFO_err) <- paste("Dataset", 1:3)
-
-# Name the model in the list of models (with only one member in this case) for
-# nicer plotting later on.  Be quiet and use only one core not to offend CRAN
-# checks
-# \dontrun{
-f_SFO_SFO <- mmkin(list("SFO-SFO" = m_SFO_SFO),
-                   d_SFO_SFO_err, cores = 1,
-                   quiet = TRUE)
-
-plot(f_SFO_SFO)
-
-
-# We would like to inspect the fit for dataset 3 more closely
-# Using double brackets makes the returned object an mkinfit object
-# instead of a list of mkinfit objects, so plot.mkinfit is used
-plot(f_SFO_SFO[[3]], show_residuals = TRUE)
-
-
-# If we use single brackets, we should give two indices (model and dataset),
-# and plot.mmkin is used
-plot(f_SFO_SFO[1, 3])
-
-# }
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/anova.saem.mmkin.html b/docs/dev/reference/anova.saem.mmkin.html
deleted file mode 100644
index 39a30dff..00000000
--- a/docs/dev/reference/anova.saem.mmkin.html
+++ /dev/null
@@ -1,185 +0,0 @@
-
-Anova method for saem.mmkin objects — anova.saem.mmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Anova method for saem.mmkin objects
      
-    Source: R/anova.saem.mmkin.R
-    
-    
      
-
-    
      
-    
      Generate an anova object. The method to calculate the BIC is that from the
-saemix package. As in other prominent anova methods, models are sorted by
-number of parameters, and the tests (if requested) are always relative to
-the model on the previous line.
      
-    
      
-
-    
      
-    
      # S3 method for saem.mmkin
-anova(
-  object,
-  ...,
-  method = c("is", "lin", "gq"),
-  test = FALSE,
-  model.names = NULL
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      An saem.mmkin object
      
-
-
-
      ...
      
-
      further such objects
      
-
-
-
      method
      
-
      Method for likelihood calculation: "is" (importance sampling),
-"lin" (linear approximation), or "gq" (Gaussian quadrature). Passed
-to saemix::logLik.SaemixObject
      
-
-
-
      test
      
-
      Should a likelihood ratio test be performed? If TRUE,
-the alternative models are tested against the first model. Should
-only be done for nested models.
      
-
-
-
      model.names
      
-
      Optional character vector of model names
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      an "anova" data frame; the traditional (S3) result of anova()
      
-    
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/aw.html b/docs/dev/reference/aw.html
deleted file mode 100644
index fc5ff777..00000000
--- a/docs/dev/reference/aw.html
+++ /dev/null
@@ -1,197 +0,0 @@
-
-Calculate Akaike weights for model averaging — aw • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Calculate Akaike weights for model averaging
      
-    Source: R/aw.R
-    
-    
      
-
-    
      
-    
      Akaike weights are calculated based on the relative
-expected Kullback-Leibler information as specified
-by Burnham and Anderson (2004).
      
-    
      
-
-    
      
-    
      aw(object, ...)
-
-# S3 method for mkinfit
-aw(object, ...)
-
-# S3 method for mmkin
-aw(object, ...)
-
-# S3 method for mixed.mmkin
-aw(object, ...)
-
-# S3 method for multistart
-aw(object, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      An mmkin column object, containing two or more
-mkinfit models that have been fitted to the same data,
-or an mkinfit object. In the latter case, further mkinfit
-objects fitted to the same data should be specified
-as dots arguments.
      
-
-
-
      ...
      
-
      Not used in the method for mmkin column objects,
-further mkinfit objects in the method for mkinfit objects.
      
-
-
      
-    
      
-    
      References
      
-    
      Burnham KP and Anderson DR (2004) Multimodel
-Inference: Understanding AIC and BIC in Model Selection.
-Sociological Methods & Research 33(2) 261-304
      
-    
      
-
-    
      
-    
      Examples
      
-    
      # \dontrun{
-f_sfo <- mkinfit("SFO", FOCUS_2006_D, quiet = TRUE)
-f_dfop <- mkinfit("DFOP", FOCUS_2006_D, quiet = TRUE)
-aw_sfo_dfop <- aw(f_sfo, f_dfop)
-sum(aw_sfo_dfop)
-#> [1] 1
-aw_sfo_dfop # SFO gets more weight as it has less parameters and a similar fit
-#> [1] 0.5970258 0.4029742
-f <- mmkin(c("SFO", "FOMC", "DFOP"), list("FOCUS D" = FOCUS_2006_D), cores = 1, quiet = TRUE)
-aw(f)
-#> [1] 0.4808722 0.1945539 0.3245740
-sum(aw(f))
-#> [1] 1
-aw(f[c("SFO", "DFOP")])
-#> [1] 0.5970258 0.4029742
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/confint.mkinfit.html b/docs/dev/reference/confint.mkinfit.html
deleted file mode 100644
index a3571fa5..00000000
--- a/docs/dev/reference/confint.mkinfit.html
+++ /dev/null
@@ -1,423 +0,0 @@
-
-Confidence intervals for parameters of mkinfit objects — confint.mkinfit • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Confidence intervals for parameters of mkinfit objects
      
-    Source: R/confint.mkinfit.R
-    
-    
      
-
-    
      
-    
      The default method 'quadratic' is based on the quadratic approximation of
-the curvature of the likelihood function at the maximum likelihood parameter
-estimates.
-The alternative method 'profile' is based on the profile likelihood for each
-parameter. The 'profile' method uses two nested optimisations and can take a
-very long time, even if parallelized by specifying 'cores' on unixoid
-platforms. The speed of the method could likely be improved by using the
-method of Venzon and Moolgavkar (1988).
      
-    
      
-
-    
      
-    
      # S3 method for mkinfit
-confint(
-  object,
-  parm,
-  level = 0.95,
-  alpha = 1 - level,
-  cutoff,
-  method = c("quadratic", "profile"),
-  transformed = TRUE,
-  backtransform = TRUE,
-  cores = parallel::detectCores(),
-  rel_tol = 0.01,
-  quiet = FALSE,
-  ...
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      An mkinfit object
      
-
-
-
      parm
      
-
      A vector of names of the parameters which are to be given
-confidence intervals. If missing, all parameters are considered.
      
-
-
-
      level
      
-
      The confidence level required
      
-
-
-
      alpha
      
-
      The allowed error probability, overrides 'level' if specified.
      
-
-
-
      cutoff
      
-
      Possibility to specify an alternative cutoff for the difference
-in the log-likelihoods at the confidence boundary. Specifying an explicit
-cutoff value overrides arguments 'level' and 'alpha'
      
-
-
-
      method
      
-
      The 'quadratic' method approximates the likelihood function at
-the optimised parameters using the second term of the Taylor expansion,
-using a second derivative (hessian) contained in the object.
-The 'profile' method searches the parameter space for the
-cutoff of the confidence intervals by means of a likelihood ratio test.
      
-
-
-
      transformed
      
-
      If the quadratic approximation is used, should it be
-applied to the likelihood based on the transformed parameters?
      
-
-
-
      backtransform
      
-
      If we approximate the likelihood in terms of the
-transformed parameters, should we backtransform the parameters with
-their confidence intervals?
      
-
-
-
      cores
      
-
      The number of cores to be used for multicore processing.
-On Windows machines, cores > 1 is currently not supported.
      
-
-
-
      rel_tol
      
-
      If the method is 'profile', what should be the accuracy
-of the lower and upper bounds, relative to the estimate obtained from
-the quadratic method?
      
-
-
-
      quiet
      
-
      Should we suppress the message "Profiling the likelihood"
      
-
-
-
      ...
      
-
      Not used
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      A matrix with columns giving lower and upper confidence limits for
-each parameter.
      
-    
      
-    
      
-    
      References
      
-    
      Bates DM and Watts GW (1988) Nonlinear regression analysis & its applications
      
-
      Pawitan Y (2013) In all likelihood - Statistical modelling and
-inference using likelihood. Clarendon Press, Oxford.
      
-
      Venzon DJ and Moolgavkar SH (1988) A Method for Computing
-Profile-Likelihood Based Confidence Intervals, Applied Statistics, 37,
-87–94.
      
-    
      
-
-    
      
-    
      Examples
      
-    
      f <- mkinfit("SFO", FOCUS_2006_C, quiet = TRUE)
-confint(f, method = "quadratic")
-#>                2.5%      97.5%
-#> parent_0 71.8242430 93.1600766
-#> k_parent  0.2109541  0.4440528
-#> sigma     1.9778868  7.3681380
-
-# \dontrun{
-confint(f, method = "profile")
-#> Profiling the likelihood
-#>                2.5%      97.5%
-#> parent_0 73.0641834 92.1392181
-#> k_parent  0.2170293  0.4235348
-#> sigma     3.1307772  8.0628314
-
-# Set the number of cores for the profiling method for further examples
-if (identical(Sys.getenv("NOT_CRAN"), "true")) {
-  n_cores <- parallel::detectCores() - 1
-} else {
-  n_cores <- 1
-}
-if (Sys.getenv("TRAVIS") != "") n_cores = 1
-if (Sys.info()["sysname"] == "Windows") n_cores = 1
-
-SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"),
-  use_of_ff = "min", quiet = TRUE)
-SFO_SFO.ff <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"),
-  use_of_ff = "max", quiet = TRUE)
-f_d_1 <- mkinfit(SFO_SFO, subset(FOCUS_2006_D, value != 0), quiet = TRUE)
-system.time(ci_profile <- confint(f_d_1, method = "profile", cores = 1, quiet = TRUE))
-#>    user  system elapsed 
-#>   1.183   0.000   1.182 
-# Using more cores does not save much time here, as parent_0 takes up most of the time
-# If we additionally exclude parent_0 (the confidence of which is often of
-# minor interest), we get a nice performance improvement if we use at least 4 cores
-system.time(ci_profile_no_parent_0 <- confint(f_d_1, method = "profile",
-  c("k_parent_sink", "k_parent_m1", "k_m1_sink", "sigma"), cores = n_cores))
-#> Profiling the likelihood
-#>    user  system elapsed 
-#>   0.418   0.116   0.294 
-ci_profile
-#>                       2.5%        97.5%
-#> parent_0      96.456003640 1.027703e+02
-#> k_parent_sink  0.040762501 5.549764e-02
-#> k_parent_m1    0.046786482 5.500879e-02
-#> k_m1_sink      0.003892605 6.702778e-03
-#> sigma          2.535612399 3.985263e+00
-ci_quadratic_transformed <- confint(f_d_1, method = "quadratic")
-ci_quadratic_transformed
-#>                       2.5%        97.5%
-#> parent_0      96.403841640 1.027931e+02
-#> k_parent_sink  0.041033378 5.596269e-02
-#> k_parent_m1    0.046777902 5.511931e-02
-#> k_m1_sink      0.004012217 6.897547e-03
-#> sigma          2.396089689 3.854918e+00
-ci_quadratic_untransformed <- confint(f_d_1, method = "quadratic", transformed = FALSE)
-ci_quadratic_untransformed
-#>                       2.5%        97.5%
-#> parent_0      96.403841645 102.79312449
-#> k_parent_sink  0.040485331   0.05535491
-#> k_parent_m1    0.046611582   0.05494364
-#> k_m1_sink      0.003835483   0.00668582
-#> sigma          2.396089689   3.85491806
-# Against the expectation based on Bates and Watts (1988), the confidence
-# intervals based on the internal parameter transformation are less
-# congruent with the likelihood based intervals. Note the superiority of the
-# interval based on the untransformed fit for k_m1_sink
-rel_diffs_transformed <- abs((ci_quadratic_transformed - ci_profile)/ci_profile)
-rel_diffs_untransformed <- abs((ci_quadratic_untransformed - ci_profile)/ci_profile)
-rel_diffs_transformed < rel_diffs_untransformed
-#>                2.5% 97.5%
-#> parent_0      FALSE FALSE
-#> k_parent_sink  TRUE FALSE
-#> k_parent_m1    TRUE FALSE
-#> k_m1_sink     FALSE FALSE
-#> sigma         FALSE FALSE
-signif(rel_diffs_transformed, 3)
-#>                   2.5%    97.5%
-#> parent_0      0.000541 0.000222
-#> k_parent_sink 0.006650 0.008380
-#> k_parent_m1   0.000183 0.002010
-#> k_m1_sink     0.030700 0.029100
-#> sigma         0.055000 0.032700
-signif(rel_diffs_untransformed, 3)
-#>                   2.5%    97.5%
-#> parent_0      0.000541 0.000222
-#> k_parent_sink 0.006800 0.002570
-#> k_parent_m1   0.003740 0.001180
-#> k_m1_sink     0.014700 0.002530
-#> sigma         0.055000 0.032700
-
-
-# Investigate a case with formation fractions
-f_d_2 <- mkinfit(SFO_SFO.ff, subset(FOCUS_2006_D, value != 0), quiet = TRUE)
-ci_profile_ff <- confint(f_d_2, method = "profile", cores = n_cores)
-#> Profiling the likelihood
-ci_profile_ff
-#>                        2.5%        97.5%
-#> parent_0       96.456003640 1.027703e+02
-#> k_parent        0.090911032 1.071578e-01
-#> k_m1            0.003892606 6.702775e-03
-#> f_parent_to_m1  0.471328495 5.611550e-01
-#> sigma           2.535612399 3.985263e+00
-ci_quadratic_transformed_ff <- confint(f_d_2, method = "quadratic")
-ci_quadratic_transformed_ff
-#>                        2.5%        97.5%
-#> parent_0       96.403833578 102.79311649
-#> k_parent        0.090823771   0.10725430
-#> k_m1            0.004012219   0.00689755
-#> f_parent_to_m1  0.469118824   0.55959615
-#> sigma           2.396089689   3.85491806
-ci_quadratic_untransformed_ff <- confint(f_d_2, method = "quadratic", transformed = FALSE)
-ci_quadratic_untransformed_ff
-#>                        2.5%        97.5%
-#> parent_0       96.403833583 1.027931e+02
-#> k_parent        0.090491913 1.069035e-01
-#> k_m1            0.003835485 6.685823e-03
-#> f_parent_to_m1  0.469113477 5.598387e-01
-#> sigma           2.396089689 3.854918e+00
-rel_diffs_transformed_ff <- abs((ci_quadratic_transformed_ff - ci_profile_ff)/ci_profile_ff)
-rel_diffs_untransformed_ff <- abs((ci_quadratic_untransformed_ff - ci_profile_ff)/ci_profile_ff)
-# While the confidence interval for the parent rate constant is closer to
-# the profile based interval when using the internal parameter
-# transformation, the interval for the metabolite rate constant is 'better
-# without internal parameter transformation.
-rel_diffs_transformed_ff < rel_diffs_untransformed_ff
-#>                 2.5% 97.5%
-#> parent_0       FALSE FALSE
-#> k_parent        TRUE  TRUE
-#> k_m1           FALSE FALSE
-#> f_parent_to_m1  TRUE FALSE
-#> sigma           TRUE FALSE
-rel_diffs_transformed_ff
-#>                        2.5%        97.5%
-#> parent_0       0.0005408690 0.0002217233
-#> k_parent       0.0009598532 0.0009001864
-#> k_m1           0.0307283041 0.0290588361
-#> f_parent_to_m1 0.0046881769 0.0027780063
-#> sigma          0.0550252516 0.0327066836
-rel_diffs_untransformed_ff
-#>                        2.5%        97.5%
-#> parent_0       0.0005408689 0.0002217232
-#> k_parent       0.0046102156 0.0023732281
-#> k_m1           0.0146740690 0.0025291820
-#> f_parent_to_m1 0.0046995211 0.0023457712
-#> sigma          0.0550252516 0.0327066836
-
-# The profiling for the following fit does not finish in a reasonable time,
-# therefore we use the quadratic approximation
-m_synth_DFOP_par <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")),
-  M1 = mkinsub("SFO"),
-  M2 = mkinsub("SFO"),
-  use_of_ff = "max", quiet = TRUE)
-DFOP_par_c <- synthetic_data_for_UBA_2014[[12]]$data
-f_tc_2 <- mkinfit(m_synth_DFOP_par, DFOP_par_c, error_model = "tc",
-  error_model_algorithm = "direct", quiet = TRUE)
-confint(f_tc_2, method = "quadratic")
-#>                        2.5%        97.5%
-#> parent_0       94.596039609 106.19954892
-#> k_M1            0.037605368   0.04490762
-#> k_M2            0.008568731   0.01087676
-#> f_parent_to_M1  0.021462489   0.62023882
-#> f_parent_to_M2  0.015165617   0.37975348
-#> k1              0.273897348   0.33388101
-#> k2              0.018614554   0.02250378
-#> g               0.671943411   0.73583305
-#> sigma_low       0.251283495   0.83992077
-#> rsd_high        0.040411024   0.07662008
-confint(f_tc_2, "parent_0", method = "quadratic")
-#>              2.5%    97.5%
-#> parent_0 94.59604 106.1995
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/convergence.html b/docs/dev/reference/convergence.html
deleted file mode 100644
index e9fac3bb..00000000
--- a/docs/dev/reference/convergence.html
+++ /dev/null
@@ -1,163 +0,0 @@
-
-Method to get convergence information — convergence • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Method to get convergence information
      
-    Source: R/convergence.R
-    
-    
      
-
-    
      
-    
      Method to get convergence information
      
-    
      
-
-    
      
-    
      convergence(object, ...)
-
-# S3 method for mmkin
-convergence(object, ...)
-
-# S3 method for convergence.mmkin
-print(x, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      The object to investigate
      
-
-
-
      ...
      
-
      For potential future extensions
      
-
-
-
      x
      
-
      The object to be printed
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      For mkinfit objects, a character vector containing
-For mmkin objects, an object of class 'convergence.mmkin' with a
-suitable printing method.
      
-    
      
-
-    
      
-    
      Examples
      
-    
      # \dontrun{
-fits <- mmkin(
-  c("SFO", "FOMC"),
-  list("FOCUS A" = FOCUS_2006_A,
-       "FOCUS B" = FOCUS_2006_C),
-  quiet = TRUE)
-convergence(fits)
-#>       dataset
-#> model  FOCUS A FOCUS B
-#>   SFO  OK      OK     
-#>   FOMC OK      OK     
-#> 
-#> OK: No warnings
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.6.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/create_deg_func.html b/docs/dev/reference/create_deg_func.html
deleted file mode 100644
index fd8325c0..00000000
--- a/docs/dev/reference/create_deg_func.html
+++ /dev/null
@@ -1,196 +0,0 @@
-
-Create degradation functions for known analytical solutions — create_deg_func • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Create degradation functions for known analytical solutions
      
-    Source: R/create_deg_func.R
-    
-    
      
-
-    
      
-    
      Create degradation functions for known analytical solutions
      
-    
      
-
-    
      
-    
      create_deg_func(spec, use_of_ff = c("min", "max"))
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      spec
      
-
      List of model specifications as contained in mkinmod objects
      
-
-
-
      use_of_ff
      
-
      Minimum or maximum use of formation fractions
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      Degradation function to be attached to mkinmod objects
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-SFO_SFO <- mkinmod(
-  parent = mkinsub("SFO", "m1"),
-  m1 = mkinsub("SFO"))
-#> Temporary DLL for differentials generated and loaded
-FOCUS_D <- subset(FOCUS_2006_D, value != 0) # to avoid warnings
-fit_1 <- mkinfit(SFO_SFO, FOCUS_D, solution_type = "analytical", quiet = TRUE)
-# \dontrun{
-fit_2 <- mkinfit(SFO_SFO, FOCUS_D, solution_type = "deSolve", quiet = TRUE)
-if (require(rbenchmark))
-  benchmark(
-    analytical = mkinfit(SFO_SFO, FOCUS_D, solution_type = "analytical", quiet = TRUE),
-    deSolve = mkinfit(SFO_SFO, FOCUS_D, solution_type = "deSolve", quiet = TRUE),
-    replications = 2)
-#> Loading required package: rbenchmark
-#>         test replications elapsed relative user.self sys.self user.child
-#> 1 analytical            2   0.235    1.000     0.235        0          0
-#> 2    deSolve            2   0.294    1.251     0.294        0          0
-#>   sys.child
-#> 1         0
-#> 2         0
-  DFOP_SFO <- mkinmod(
-    parent = mkinsub("DFOP", "m1"),
-    m1 = mkinsub("SFO"))
-#> Temporary DLL for differentials generated and loaded
-  benchmark(
-    analytical = mkinfit(DFOP_SFO, FOCUS_D, solution_type = "analytical", quiet = TRUE),
-    deSolve = mkinfit(DFOP_SFO, FOCUS_D, solution_type = "deSolve", quiet = TRUE),
-    replications = 2)
-#>         test replications elapsed relative user.self sys.self user.child
-#> 1 analytical            2   0.374    1.000     0.374        0          0
-#> 2    deSolve            2   0.527    1.409     0.526        0          0
-#>   sys.child
-#> 1         0
-#> 2         0
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/dimethenamid_2018-1.png b/docs/dev/reference/dimethenamid_2018-1.png
deleted file mode 100644
index 27ed5329..00000000
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diff --git a/docs/dev/reference/dimethenamid_2018-2.png b/docs/dev/reference/dimethenamid_2018-2.png
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index 36db063c..00000000
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diff --git a/docs/dev/reference/dimethenamid_2018-3.png b/docs/dev/reference/dimethenamid_2018-3.png
deleted file mode 100644
index 7c876208..00000000
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diff --git a/docs/dev/reference/dimethenamid_2018.html b/docs/dev/reference/dimethenamid_2018.html
deleted file mode 100644
index 0fcd0c61..00000000
--- a/docs/dev/reference/dimethenamid_2018.html
+++ /dev/null
@@ -1,390 +0,0 @@
-
-Aerobic soil degradation data on dimethenamid and dimethenamid-P from the EU assessment in 2018 — dimethenamid_2018 • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Aerobic soil degradation data on dimethenamid and dimethenamid-P from the EU assessment in 2018
      
-    Source: R/dimethenamid_2018.R
-    
-    
      
-
-    
      
-    
      The datasets were extracted from the active substance evaluation dossier
-published by EFSA. Kinetic evaluations shown for these datasets are intended
-to illustrate and advance kinetic modelling. The fact that these data and
-some results are shown here does not imply a license to use them in the
-context of pesticide  registrations, as the use of the data may be
-constrained by data protection regulations.
      
-    
      
-
-    
      
-    
      dimethenamid_2018
      
-    
      
-
-    
      
-    
      Format
      
-    
      An mkindsg object grouping seven datasets with some meta information
      
-    
      
-    
      
-    
      Source
      
-    
      Rapporteur Member State Germany, Co-Rapporteur Member State Bulgaria (2018)
-Renewal Assessment Report Dimethenamid-P Volume 3 - B.8 Environmental fate and behaviour
-Rev. 2 - November 2017
-https://open.efsa.europa.eu/study-inventory/EFSA-Q-2014-00716
      
-    
      
-    
      
-    
      Details
      
-    
      The R code used to create this data object is installed with this package
-in the 'dataset_generation' directory. In the code, page numbers are given for
-specific pieces of information in the comments.
      
-    
      
-
-    
      
-    
      Examples
      
-    
      print(dimethenamid_2018)
-#> <mkindsg> holding 7 mkinds objects
-#> Title $title:  Aerobic soil degradation data on dimethenamid-P from the EU assessment in 2018 
-#> Occurrence of observed compounds $observed_n:
-#> DMTAP   M23   M27   M31  DMTA 
-#>     3     7     7     7     4 
-#> Time normalisation factors $f_time_norm:
-#> [1] 1.0000000 0.9706477 1.2284784 1.2284784 0.6233856 0.7678922 0.6733938
-#> Meta information $meta:
-#>                      study  usda_soil_type study_moisture_ref_type rel_moisture
-#> Calke        Unsworth 2014      Sandy loam                     pF2         1.00
-#> Borstel  Staudenmaier 2009            Sand                     pF1         0.50
-#> Elliot 1        Wendt 1997       Clay loam                   pF2.5         0.75
-#> Elliot 2        Wendt 1997       Clay loam                   pF2.5         0.75
-#> Flaach          König 1996 Sandy clay loam                     pF1         0.40
-#> BBA 2.2         König 1995      Loamy sand                     pF1         0.40
-#> BBA 2.3         König 1995      Sandy loam                     pF1         0.40
-#>          study_ref_moisture temperature
-#> Calke                    NA          20
-#> Borstel               23.00          20
-#> Elliot 1              33.37          23
-#> Elliot 2              33.37          23
-#> Flaach                   NA          20
-#> BBA 2.2                  NA          20
-#> BBA 2.3                  NA          20
-dmta_ds <- lapply(1:7, function(i) {
-  ds_i <- dimethenamid_2018$ds[[i]]$data
-  ds_i[ds_i$name == "DMTAP", "name"] <-  "DMTA"
-  ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i]
-  ds_i
-})
-names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title)
-dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]])
-dmta_ds[["Elliot 1"]] <- NULL
-dmta_ds[["Elliot 2"]] <- NULL
-# \dontrun{
-# We don't use DFOP for the parent compound, as this gives numerical
-# instabilities in the fits
-sfo_sfo3p <- mkinmod(
- DMTA = mkinsub("SFO", c("M23", "M27", "M31")),
- M23 = mkinsub("SFO"),
- M27 = mkinsub("SFO"),
- M31 = mkinsub("SFO", "M27", sink = FALSE),
- quiet = TRUE
-)
-dmta_sfo_sfo3p_tc <- mmkin(list("SFO-SFO3+" = sfo_sfo3p),
-  dmta_ds, error_model = "tc", quiet = TRUE)
-print(dmta_sfo_sfo3p_tc)
-#> <mmkin> object
-#> Status of individual fits:
-#> 
-#>            dataset
-#> model       Calke Borstel Flaach BBA 2.2 BBA 2.3 Elliot
-#>   SFO-SFO3+ OK    OK      OK     OK      OK      OK    
-#> 
-#> OK: No warnings
-# The default (test_log_parms = FALSE) gives an undue
-# influence of ill-defined rate constants that have
-# extremely small values:
-plot(mixed(dmta_sfo_sfo3p_tc), test_log_parms = FALSE)
-# If we disregards ill-defined rate constants, the results
-# look more plausible, but the truth is likely to be in
-# between these variants
-plot(mixed(dmta_sfo_sfo3p_tc), test_log_parms = TRUE)
-
-# We can also specify a default value for the failing
-# log parameters, to mimic FOCUS guidance
-plot(mixed(dmta_sfo_sfo3p_tc), test_log_parms = TRUE,
-  default_log_parms = log(2)/1000)
-# As these attempts are not satisfying, we use nonlinear mixed-effects models
-# f_dmta_nlme_tc <- nlme(dmta_sfo_sfo3p_tc)
-# nlme reaches maxIter = 50 without convergence
-f_dmta_saem_tc <- saem(dmta_sfo_sfo3p_tc)
-# I am commenting out the convergence plot as rendering them
-# with pkgdown fails (at least without further tweaks to the
-# graphics device used)
-#saemix::plot(f_dmta_saem_tc$so, plot.type = "convergence")
-summary(f_dmta_saem_tc)
-#> saemix version used for fitting:      3.2 
-#> mkin version used for pre-fitting:  1.2.3 
-#> R version used for fitting:         4.2.3 
-#> Date of fit:     Sun Apr 16 08:30:03 2023 
-#> Date of summary: Sun Apr 16 08:30:03 2023 
-#> 
-#> Equations:
-#> d_DMTA/dt = - k_DMTA * DMTA
-#> d_M23/dt = + f_DMTA_to_M23 * k_DMTA * DMTA - k_M23 * M23
-#> d_M27/dt = + f_DMTA_to_M27 * k_DMTA * DMTA - k_M27 * M27 + k_M31 * M31
-#> d_M31/dt = + f_DMTA_to_M31 * k_DMTA * DMTA - k_M31 * M31
-#> 
-#> Data:
-#> 563 observations of 4 variable(s) grouped in 6 datasets
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted in 304.528 s
-#> Using 300, 100 iterations and 9 chains
-#> 
-#> Variance model: Two-component variance function 
-#> 
-#> Starting values for degradation parameters:
-#>       DMTA_0   log_k_DMTA    log_k_M23    log_k_M27    log_k_M31 f_DMTA_ilr_1 
-#>      95.5662      -2.9048      -3.8130      -4.1600      -4.1486       0.1341 
-#> f_DMTA_ilr_2 f_DMTA_ilr_3 
-#>       0.1385      -1.6700 
-#> 
-#> Fixed degradation parameter values:
-#> None
-#> 
-#> Starting values for random effects (square root of initial entries in omega):
-#>              DMTA_0 log_k_DMTA log_k_M23 log_k_M27 log_k_M31 f_DMTA_ilr_1
-#> DMTA_0        4.802     0.0000    0.0000     0.000    0.0000       0.0000
-#> log_k_DMTA    0.000     0.9834    0.0000     0.000    0.0000       0.0000
-#> log_k_M23     0.000     0.0000    0.6983     0.000    0.0000       0.0000
-#> log_k_M27     0.000     0.0000    0.0000     1.028    0.0000       0.0000
-#> log_k_M31     0.000     0.0000    0.0000     0.000    0.9841       0.0000
-#> f_DMTA_ilr_1  0.000     0.0000    0.0000     0.000    0.0000       0.7185
-#> f_DMTA_ilr_2  0.000     0.0000    0.0000     0.000    0.0000       0.0000
-#> f_DMTA_ilr_3  0.000     0.0000    0.0000     0.000    0.0000       0.0000
-#>              f_DMTA_ilr_2 f_DMTA_ilr_3
-#> DMTA_0             0.0000       0.0000
-#> log_k_DMTA         0.0000       0.0000
-#> log_k_M23          0.0000       0.0000
-#> log_k_M27          0.0000       0.0000
-#> log_k_M31          0.0000       0.0000
-#> f_DMTA_ilr_1       0.0000       0.0000
-#> f_DMTA_ilr_2       0.7378       0.0000
-#> f_DMTA_ilr_3       0.0000       0.4451
-#> 
-#> Starting values for error model parameters:
-#> a.1 b.1 
-#>   1   1 
-#> 
-#> Results:
-#> 
-#> Likelihood computed by importance sampling
-#>    AIC  BIC logLik
-#>   2276 2273  -1120
-#> 
-#> Optimised parameters:
-#>                    est.   lower   upper
-#> DMTA_0          88.3192 83.8656 92.7729
-#> log_k_DMTA      -3.0530 -3.5686 -2.5373
-#> log_k_M23       -4.0620 -4.9202 -3.2038
-#> log_k_M27       -3.8633 -4.2668 -3.4598
-#> log_k_M31       -3.9731 -4.4763 -3.4699
-#> f_DMTA_ilr_1     0.1346 -0.2150  0.4841
-#> f_DMTA_ilr_2     0.1449 -0.2593  0.5491
-#> f_DMTA_ilr_3    -1.3882 -1.7011 -1.0753
-#> a.1              0.9156  0.8217  1.0095
-#> b.1              0.1383  0.1216  0.1550
-#> SD.DMTA_0        3.7280 -0.6949  8.1508
-#> SD.log_k_DMTA    0.6431  0.2781  1.0080
-#> SD.log_k_M23     1.0096  0.3782  1.6409
-#> SD.log_k_M27     0.4583  0.1541  0.7625
-#> SD.log_k_M31     0.5738  0.1942  0.9533
-#> SD.f_DMTA_ilr_1  0.4119  0.1528  0.6709
-#> SD.f_DMTA_ilr_2  0.4780  0.1806  0.7754
-#> SD.f_DMTA_ilr_3  0.3657  0.1383  0.5931
-#> 
-#> Correlation: 
-#>              DMTA_0  l__DMTA lg__M23 lg__M27 lg__M31 f_DMTA__1 f_DMTA__2
-#> log_k_DMTA    0.0303                                                    
-#> log_k_M23    -0.0229 -0.0032                                            
-#> log_k_M27    -0.0372 -0.0049  0.0041                                    
-#> log_k_M31    -0.0245 -0.0032  0.0022  0.0815                            
-#> f_DMTA_ilr_1 -0.0046 -0.0006  0.0415 -0.0433  0.0324                    
-#> f_DMTA_ilr_2 -0.0008 -0.0002  0.0214 -0.0267 -0.0893 -0.0361            
-#> f_DMTA_ilr_3 -0.1755 -0.0135  0.0423  0.0775  0.0377 -0.0066    0.0060  
-#> 
-#> Random effects:
-#>                   est.   lower  upper
-#> SD.DMTA_0       3.7280 -0.6949 8.1508
-#> SD.log_k_DMTA   0.6431  0.2781 1.0080
-#> SD.log_k_M23    1.0096  0.3782 1.6409
-#> SD.log_k_M27    0.4583  0.1541 0.7625
-#> SD.log_k_M31    0.5738  0.1942 0.9533
-#> SD.f_DMTA_ilr_1 0.4119  0.1528 0.6709
-#> SD.f_DMTA_ilr_2 0.4780  0.1806 0.7754
-#> SD.f_DMTA_ilr_3 0.3657  0.1383 0.5931
-#> 
-#> Variance model:
-#>       est.  lower upper
-#> a.1 0.9156 0.8217 1.009
-#> b.1 0.1383 0.1216 0.155
-#> 
-#> Backtransformed parameters:
-#>                   est.     lower    upper
-#> DMTA_0        88.31924 83.865625 92.77286
-#> k_DMTA         0.04722  0.028196  0.07908
-#> k_M23          0.01721  0.007298  0.04061
-#> k_M27          0.02100  0.014027  0.03144
-#> k_M31          0.01882  0.011375  0.03112
-#> f_DMTA_to_M23  0.14608        NA       NA
-#> f_DMTA_to_M27  0.12077        NA       NA
-#> f_DMTA_to_M31  0.11123        NA       NA
-#> 
-#> Resulting formation fractions:
-#>               ff
-#> DMTA_M23  0.1461
-#> DMTA_M27  0.1208
-#> DMTA_M31  0.1112
-#> DMTA_sink 0.6219
-#> 
-#> Estimated disappearance times:
-#>       DT50   DT90
-#> DMTA 14.68  48.76
-#> M23  40.27 133.76
-#> M27  33.01 109.65
-#> M31  36.84 122.38
-# As the confidence interval for the random effects of DMTA_0
-# includes zero, we could try an alternative model without
-# such random effects
-# f_dmta_saem_tc_2 <- saem(dmta_sfo_sfo3p_tc,
-#   covariance.model = diag(c(0, rep(1, 7))))
-# saemix::plot(f_dmta_saem_tc_2$so, plot.type = "convergence")
-# This does not perform better judged by AIC and BIC
-# saemix::compare.saemix(f_dmta_saem_tc$so, f_dmta_saem_tc_2$so)
-# }
-
      
-    
      
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      Developed by Johannes Ranke.
      
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diff --git a/docs/dev/reference/ds_mixed-1.png b/docs/dev/reference/ds_mixed-1.png
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diff --git a/docs/dev/reference/ds_mixed.html b/docs/dev/reference/ds_mixed.html
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-
-Synthetic data for hierarchical kinetic degradation models — ds_mixed • mkin
-    
-
-    
      
-      
      
-
-      
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-      
      
-  
      
-    
      
-    
      Synthetic data for hierarchical kinetic degradation models
      
-    Source: R/ds_mixed.R
-    
-    
      
-
-    
      
-    
      The R code used to create this data object is installed with this package in
-the 'dataset_generation' directory.
      
-    
      
-
-
-
-    
      
-    
      Examples
      
-    
      # \dontrun{
-  sfo_mmkin <- mmkin("SFO", ds_sfo, quiet = TRUE, error_model = "tc", cores = 15)
-  sfo_saem <- saem(sfo_mmkin, no_random_effect = "parent_0")
-  plot(sfo_saem)
-
-# }
-
-# This is the code used to generate the datasets
-cat(readLines(system.file("dataset_generation/ds_mixed.R", package = "mkin")), sep = "\n")
-#> # Synthetic data for hierarchical kinetic models
-#> # Refactored version of the code previously in tests/testthat/setup_script.R
-#> # The number of datasets was 3 for FOMC, and 10 for HS in that script, now it
-#> # is always 15 for consistency
-#> 
-#> library(mkin)  # We use mkinmod and mkinpredict
-#> sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-#> n <- 15
-#> log_sd <- 0.3
-#> err_1 = list(const = 1, prop = 0.05)
-#> tc <- function(value) sigma_twocomp(value, err_1$const, err_1$prop)
-#> const <- function(value) 2
-#> 
-#> set.seed(123456)
-#> SFO <- mkinmod(parent = mkinsub("SFO"))
-#> sfo_pop <- list(parent_0 = 100, k_parent = 0.03)
-#> sfo_parms <- as.matrix(data.frame(
-#>     k_parent = rlnorm(n, log(sfo_pop$k_parent), log_sd)))
-#> set.seed(123456)
-#> ds_sfo <- lapply(1:n, function(i) {
-#>   ds_mean <- mkinpredict(SFO, sfo_parms[i, ],
-#>     c(parent = sfo_pop$parent_0), sampling_times)
-#>   add_err(ds_mean, tc, n = 1)[[1]]
-#> })
-#> attr(ds_sfo, "pop") <- sfo_pop
-#> attr(ds_sfo, "parms") <- sfo_parms
-#> 
-#> set.seed(123456)
-#> FOMC <- mkinmod(parent = mkinsub("FOMC"))
-#> fomc_pop <- list(parent_0 = 100, alpha = 2, beta = 8)
-#> fomc_parms <- as.matrix(data.frame(
-#>     alpha = rlnorm(n, log(fomc_pop$alpha), 0.4),
-#>     beta = rlnorm(n, log(fomc_pop$beta), 0.2)))
-#> set.seed(123456)
-#> ds_fomc <- lapply(1:n, function(i) {
-#>   ds_mean <- mkinpredict(FOMC, fomc_parms[i, ],
-#>     c(parent = fomc_pop$parent_0), sampling_times)
-#>   add_err(ds_mean, tc, n = 1)[[1]]
-#> })
-#> attr(ds_fomc, "pop") <- fomc_pop
-#> attr(ds_fomc, "parms") <- fomc_parms
-#> 
-#> set.seed(123456)
-#> DFOP <- mkinmod(parent = mkinsub("DFOP"))
-#> dfop_pop <- list(parent_0 = 100, k1 = 0.06, k2 = 0.015, g = 0.4)
-#> dfop_parms <- as.matrix(data.frame(
-#>   k1 = rlnorm(n, log(dfop_pop$k1), log_sd),
-#>   k2 = rlnorm(n, log(dfop_pop$k2), log_sd),
-#>   g = plogis(rnorm(n, qlogis(dfop_pop$g), log_sd))))
-#> set.seed(123456)
-#> ds_dfop <- lapply(1:n, function(i) {
-#>   ds_mean <- mkinpredict(DFOP, dfop_parms[i, ],
-#>     c(parent = dfop_pop$parent_0), sampling_times)
-#>   add_err(ds_mean, tc, n = 1)[[1]]
-#> })
-#> attr(ds_dfop, "pop") <- dfop_pop
-#> attr(ds_dfop, "parms") <- dfop_parms
-#> 
-#> set.seed(123456)
-#> HS <- mkinmod(parent = mkinsub("HS"))
-#> hs_pop <- list(parent_0 = 100, k1 = 0.08, k2 = 0.01, tb = 15)
-#> hs_parms <- as.matrix(data.frame(
-#>   k1 = rlnorm(n, log(hs_pop$k1), log_sd),
-#>   k2 = rlnorm(n, log(hs_pop$k2), log_sd),
-#>   tb = rlnorm(n, log(hs_pop$tb), 0.1)))
-#> set.seed(123456)
-#> ds_hs <- lapply(1:n, function(i) {
-#>   ds_mean <- mkinpredict(HS, hs_parms[i, ],
-#>     c(parent = hs_pop$parent_0), sampling_times)
-#>   add_err(ds_mean, const, n = 1)[[1]]
-#> })
-#> attr(ds_hs, "pop") <- hs_pop
-#> attr(ds_hs, "parms") <- hs_parms
-#> 
-#> set.seed(123456)
-#> DFOP_SFO <- mkinmod(
-#>   parent = mkinsub("DFOP", "m1"),
-#>   m1 = mkinsub("SFO"),
-#>   quiet = TRUE)
-#> dfop_sfo_pop <- list(parent_0 = 100,
-#>   k_m1 = 0.007, f_parent_to_m1 = 0.5,
-#>   k1 = 0.1, k2 = 0.02, g = 0.5)
-#> dfop_sfo_parms <- as.matrix(data.frame(
-#>   k1 = rlnorm(n, log(dfop_sfo_pop$k1), log_sd),
-#>   k2 = rlnorm(n, log(dfop_sfo_pop$k2), log_sd),
-#>   g = plogis(rnorm(n, qlogis(dfop_sfo_pop$g), log_sd)),
-#>   f_parent_to_m1 = plogis(rnorm(n,
-#>       qlogis(dfop_sfo_pop$f_parent_to_m1), log_sd)),
-#>   k_m1 = rlnorm(n, log(dfop_sfo_pop$k_m1), log_sd)))
-#> ds_dfop_sfo_mean <- lapply(1:n,
-#>   function(i) {
-#>     mkinpredict(DFOP_SFO, dfop_sfo_parms[i, ],
-#>       c(parent = dfop_sfo_pop$parent_0, m1 = 0), sampling_times)
-#>   }
-#> )
-#> set.seed(123456)
-#> ds_dfop_sfo <- lapply(ds_dfop_sfo_mean, function(ds) {
-#>   add_err(ds,
-#>     sdfunc = function(value) sqrt(err_1$const^2 + value^2 * err_1$prop^2),
-#>     n = 1, secondary = "m1")[[1]]
-#> })
-#> attr(ds_dfop_sfo, "pop") <- dfop_sfo_pop
-#> attr(ds_dfop_sfo, "parms") <- dfop_sfo_parms
-#> 
-#> #save(ds_sfo, ds_fomc, ds_dfop, ds_hs, ds_dfop_sfo, file = "data/ds_mixed.rda", version = 2)
-
      
-    
      
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      Developed by Johannes Ranke.
      
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      Site built with pkgdown 2.0.7.
      
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diff --git a/docs/dev/reference/endpoints.html b/docs/dev/reference/endpoints.html
deleted file mode 100644
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-
-Function to calculate endpoints for further use from kinetic models fitted
-with mkinfit — endpoints • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Function to calculate endpoints for further use from kinetic models fitted
-with mkinfit
      
-    Source: R/endpoints.R
-    
-    
      
-
-    
      
-    
      This function calculates DT50 and DT90 values as well as formation fractions
-from kinetic models fitted with mkinfit. If the SFORB model was specified
-for one of the parents or metabolites, the Eigenvalues are returned. These
-are equivalent to the rate constants of the DFOP model, but with the
-advantage that the SFORB model can also be used for metabolites.
      
-    
      
-
-    
      
-    
      endpoints(fit, covariates = NULL, covariate_quantile = 0.5)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      fit
      
-
      An object of class mkinfit, nlme.mmkin or saem.mmkin, or
-another object that has list components mkinmod containing an mkinmod
-degradation model, and two numeric vectors, bparms.optim and bparms.fixed,
-that contain parameter values for that model.
      
-
-
-
      covariates
      
-
      Numeric vector with covariate values for all variables in
-any covariate models in the object. If given, it overrides 'covariate_quantile'.
      
-
-
-
      covariate_quantile
      
-
      This argument only has an effect if the fitted
-object has covariate models. If so, the default is to show endpoints
-for the median of the covariate values (50th percentile).
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      A list with a matrix of dissipation times named distimes, and, if
-applicable, a vector of formation fractions named ff and, if the SFORB model
-was in use, a vector of eigenvalues of these SFORB models, equivalent to
-DFOP rate constants
      
-    
      
-    
      
-    
      Details
      
-    
      Additional DT50 values are calculated from the FOMC DT90 and k1 and k2 from
-HS and DFOP, as well as from Eigenvalues b1 and b2 of any SFORB models
      
-    
      
-    
      
-    
      Note
      
-    
      The function is used internally by summary.mkinfit,
-summary.nlme.mmkin and summary.saem.mmkin.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-  fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
-  endpoints(fit)
-#> $distimes
-#>            DT50    DT90 DT50back
-#> parent 1.785233 15.1479 4.559973
-#> 
-  # \dontrun{
-    fit_2 <- mkinfit("DFOP", FOCUS_2006_C, quiet = TRUE)
-    endpoints(fit_2)
-#> $distimes
-#>            DT50     DT90 DT50back  DT50_k1  DT50_k2
-#> parent 1.886925 21.25106 6.397207 1.508293 38.83438
-#> 
-    fit_3 <- mkinfit("SFORB", FOCUS_2006_C, quiet = TRUE)
-    endpoints(fit_3)
-#> $ff
-#> parent_free 
-#>           1 
-#> 
-#> $SFORB
-#> parent_b1 parent_b2  parent_g 
-#> 0.4595574 0.0178488 0.8539454 
-#> 
-#> $distimes
-#>            DT50     DT90 DT50back DT50_parent_b1 DT50_parent_b2
-#> parent 1.886925 21.25106 6.397208       1.508293       38.83438
-#> 
-  # }
-
-
      
-    
      
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-  
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-      
      
-  
      Developed by Johannes Ranke.
      
-
      
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-  
      Site built with pkgdown 2.0.7.
      
-
      
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diff --git a/docs/dev/reference/example_analysis/dlls/sforb_sfo2.so b/docs/dev/reference/example_analysis/dlls/sforb_sfo2.so
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diff --git a/docs/dev/reference/example_analysis/example_analysis.Rmd b/docs/dev/reference/example_analysis/example_analysis.Rmd
deleted file mode 100644
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----
-title: "Hierarchical kinetic modelling of degradation data"
-author:
-date:
-output: mkin::hierarchical_kinetics
-geometry: margin=2cm
----
-
-\clearpage
-
-# Setup
-
-```{r packages, cache = FALSE, message = FALSE}
-library(mkin)
-library(knitr)
-library(saemix)
-library(parallel)
-library(readxl)
-```
-
-```{r n_cores, cache = FALSE}
-n_cores <- detectCores()
-
-if (Sys.info()["sysname"] == "Windows") {
-  cl <- makePSOCKcluster(n_cores)
-} else {
-  cl <- makeForkCluster(n_cores)
-}
-```
-
-\clearpage
-
-# Introduction
-
-This report shows hierarchical kinetic modelling for ...
-The data were obtained from ...
-
-```{r ds}
-data_path <- system.file(
-  "testdata", "lambda-cyhalothrin_soil_efsa_2014.xlsx",
-  package = "mkin")
-ds <- read_spreadsheet(data_path, valid_datasets = c(1:4, 7:13))
-covariates <- attr(ds, "covariates")
-```
-
-The covariate data are shown below.
-
-```{r results = "asis", dependson = "ds", echo = FALSE}
-kable(covariates, caption = "Covariate data for all datasets")
-```
-
-\clearpage
-
-The datasets with the residue time series are shown in the tables below. Please
-refer to the spreadsheet for details like data sources, treatment of values
-below reporting limits and time step normalisation factors.
-
-```{r results = "asis", dependson = "ds", echo = FALSE}
-for (ds_name in names(ds)) {
-  print(
-    kable(mkin_long_to_wide(ds[[ds_name]]),
-      caption = paste("Dataset", ds_name),
-      booktabs = TRUE, row.names = FALSE))
-  cat("\n\\clearpage\n")
-}
-```
-
-# Parent only evaluations
-
-The following code performs separate fits of the candidate degradation models
-to all datasets using constant variance and the two-component error model.
-
-```{r parent-sep, dependson = "ds"}
-parent_deg_mods <- c("SFO", "FOMC", "DFOP", "SFORB")
-errmods <- c(const = "constant variance", tc = "two-component error")
-parent_sep_const <- mmkin(
-  parent_deg_mods, ds,
-  error_model = "const",
-  cluster = cl, quiet = TRUE)
-parent_sep_tc <- update(parent_sep_const, error_model = "tc")
-```
-
-To select the parent model, the corresponding hierarchical fits are performed below.
-
-```{r parent-mhmkin, dependson = "parent-sep"}
-parent_mhmkin <- mhmkin(list(parent_sep_const, parent_sep_tc), cluster = cl)
-status(parent_mhmkin) |> kable()
-```
-
-All fits terminate without errors (status OK). The check for ill-defined
-parameters shows that not all random effect parameters can be robustly
-quantified.
-
-```{r dependson = "parent_mhmkin"}
-illparms(parent_mhmkin) |> kable()
-```
-
-Therefore, the fits are updated, excluding random effects that were
-ill-defined according to the `illparms` function. The status of the fits
-is checked.
-
-```{r parent-mhmkin-refined}
-parent_mhmkin_refined <- update(parent_mhmkin,
-  no_random_effect = illparms(parent_mhmkin))
-status(parent_mhmkin_refined) |> kable()
-```
-
-Also, it is checked if the AIC values of the refined fits are actually smaller
-than the AIC values of the original fits.
-
-```{r dependson = "parent-mhmkin-refined"}
-(AIC(parent_mhmkin_refined) < AIC(parent_mhmkin)) |> kable()
-```
-
-From the refined fits, the most suitable model is selected using the AIC.
-
-```{r parent-best, dependson = "parent-mhmkin"}
-aic_parent <- AIC(parent_mhmkin_refined)
-min_aic <- which(aic_parent == min(aic_parent), arr.ind = TRUE)
-best_degmod_parent <- rownames(aic_parent)[min_aic[1]]
-best_errmod_parent <- colnames(aic_parent)[min_aic[2]]
-anova(parent_mhmkin_refined) |> kable(digits = 1)
-parent_best <- parent_mhmkin_refined[[best_degmod_parent, best_errmod_parent]]
-```
-
-Based on the AIC, the combination of the `r best_degmod_parent` degradation
-model with the error model `r errmods[best_errmod_parent]` is identified to
-be most suitable for the degradation of the parent. The check below
-confirms that no ill-defined parameters remain for this combined model.
-
-```{r dependson = "parent-best"}
-illparms(parent_best)
-```
-
-The corresponding fit is plotted below.
-
-```{r dependson = "parent-best"}
-plot(parent_best)
-```
-The fitted parameters, together with approximate confidence
-intervals are listed below.
-
-```{r dependson = "parent-best"}
-parms(parent_best, ci = TRUE) |> kable(digits = 3)
-```
-
-To investigate a potential covariate influence on degradation parameters, a
-covariate model is added to the hierarchical model for each of the degradation
-parameters with well-defined random effects. Also, a version with covariate
-models for both of them is fitted.
-
-```{r parent-best-pH}
-parent_best_pH_1 <- update(parent_best, covariates = covariates,
-  covariate_models = list(log_k_lambda_free ~ pH))
-parent_best_pH_2 <- update(parent_best, covariates = covariates,
-  covariate_models = list(log_k_lambda_bound_free ~ pH))
-parent_best_pH_3 <- update(parent_best, covariates = covariates,
-  covariate_models = list(log_k_lambda_free ~ pH, log_k_lambda_bound_free ~ pH))
-```
-
-The resulting models are compared.
-
-```{r dependson = "parent-best-pH"}
-anova(parent_best, parent_best_pH_1, parent_best_pH_2, parent_best_pH_3) |>
-  kable(digits = 1)
-```
-
-The model fit with the lowest AIC is the one with a pH correlation of the
-desorption rate constant `k_lambda_bound_free`. Plot and parameter listing
-of this fit are shown below. Also, it is confirmed that no ill-defined
-variance parameters are found.
-
-```{r dependson = "parent-best-pH"}
-plot(parent_best_pH_2)
-```
-
-```{r dependson = "parent-best-pH"}
-illparms(parent_best_pH_2)
-parms(parent_best_pH_2, ci = TRUE) |> kable(digits = 3)
-```
-
-\clearpage
-
-# Pathway fits
-
-As an example of a pathway fit, a model with SFORB for the parent compound and
-parallel formation of two metabolites is set up.
-
-```{r path-1-degmod}
-if (!dir.exists("dlls")) dir.create("dlls")
-
-m_sforb_sfo2 = mkinmod(
-  lambda = mkinsub("SFORB", to = c("c_V", "c_XV")),
-  c_V = mkinsub("SFO"),
-  c_XV = mkinsub("SFO"),
-  name = "sforb_sfo2",
-  dll_dir = "dlls",
-  overwrite = TRUE, quiet = TRUE
-)
-```
-
-Separate evaluations of all datasets are performed with constant variance
-and using two-component error.
-
-```{r path-1-sep, dependson = c("path-1-degmod", "ds")}
-sforb_sep_const <- mmkin(list(sforb_path = m_sforb_sfo2), ds,
-  cluster = cl, quiet = TRUE)
-sforb_sep_tc <- update(sforb_sep_const, error_model = "tc")
-```
-
-The separate fits with constant variance are plotted.
-
-```{r dependson = "path-1-sep", fig.height = 9}
-plot(mixed(sforb_sep_const))
-```
-
-The two corresponding hierarchical fits, with the random effects for the parent
-degradation parameters excluded as discussed above, and including the covariate
-model that was identified for the parent degradation, are attempted below.
-
-```{r path-1, dependson = "path-1-sep"}
-path_1 <- mhmkin(list(sforb_sep_const, sforb_sep_tc),
-  no_random_effect = c("lambda_free_0", "log_k_lambda_free_bound"),
-  covariates = covariates, covariate_models = list(log_k_lambda_bound_free ~ pH),
-  cluster = cl)
-```
-
-```{r dependson = "path-1"}
-status(path_1) |> kable()
-```
-
-The status information shows that both fits were successfully completed.
-
-```{r dependson = "path-1"}
-anova(path_1) |> kable(digits = 1)
-```
-Model comparison shows that the two-component error model provides a much
-better fit.
-
-```{r dependson = "path-1"}
-illparms(path_1[["sforb_path", "tc"]])
-```
-
-Two ill-defined variance components are found. Therefore, the fit is
-repeated with the corresponding random effects removed.
-
-```{r path-1-refined, dependson = "path-1"}
-path_1_refined <- update(path_1[["sforb_path", "tc"]],
-  no_random_effect = c("lambda_free_0", "log_k_lambda_free_bound",
-    "log_k_c_XV", "f_lambda_ilr_2"))
-```
-
-The empty output of the illparms function indicates that there are no
-ill-defined parameters remaining in the refined fit.
-
-```{r dependson = "path-1-refined"}
-illparms(path_1_refined)
-```
-
-Below, the refined fit is plotted and the fitted parameters are shown together
-with their 95% confidence intervals.
-
-```{r dependson = "path-1-refined", fig.height = 9}
-plot(path_1_refined)
-```
-
-```{r dependson = "path-1-refined", fig.height = 9}
-parms(path_1_refined, ci = TRUE) |> kable(digits = 3)
-```
-
-\clearpage
-
-# Appendix
-
-## Listings of initial parent fits
-
-```{r listings-parent, results = "asis", echo = FALSE, dependson = "parent_mhmkin"}
-for (deg_mod in parent_deg_mods) {
-  for (err_mod in c("const", "tc")) {
-    caption <- paste("Hierarchical", deg_mod, "fit with", errmods[err_mod])
-    tex_listing(parent_mhmkin[[deg_mod, err_mod]], caption)
-  }
-}
-```
-
-## Listings of refined parent fits
-
-```{r listings-parent-refined, results = "asis", echo = FALSE, dependson = "parent_mhmkin_refined"}
-for (deg_mod in parent_deg_mods) {
-  for (err_mod in c("const", "tc")) {
-    caption <- paste("Refined hierarchical", deg_mod, "fit with", errmods[err_mod])
-    tex_listing(parent_mhmkin_refined[[deg_mod, err_mod]], caption)
-  }
-}
-```
-
-## Listings of pathway fits
-
-```{r listings-path-1, results = "asis", echo = FALSE, dependson = "path-1-refined"}
-tex_listing(path_1[["sforb_path", "const"]],
-  caption = "Hierarchical fit of SFORB-SFO2 with constant variance")
-tex_listing(path_1[["sforb_path", "tc"]],
-  caption = "Hierarchical fit of SFORB-SFO2 with two-component error")
-tex_listing(path_1_refined,
-  caption = "Refined hierarchical fit of SFORB-SFO2 with two-component error")
-```
-
-## Session info
-
-```{r echo = FALSE, cache = FALSE}
-parallel::stopCluster(cl)
-sessionInfo()
-```
-
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-
-Experimental datasets used for development and testing of error models — experimental_data_for_UBA_2019 • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Experimental datasets used for development and testing of error models
      
-    
-    
-    
      
-
-    
      
-    
      The 12 datasets were extracted from active substance evaluation dossiers published
- by EFSA. Kinetic evaluations shown for these datasets are intended to illustrate
- and advance error model specifications. The fact that these data and some
- results are shown here do not imply a license to use them in the context of
- pesticide registrations, as the use of the data may be constrained by
- data protection regulations.
      
-
      Preprocessing of data was performed based on the recommendations of the FOCUS
- kinetics workgroup (FOCUS, 2014) as described below.
      
-
      Datasets 1 and 2 are from the Renewal Assessment Report (RAR) for imazamox
- (France, 2015, p. 15). For setting values reported as zero, an LOQ of 0.1
- was assumed. Metabolite residues reported for day zero were added to the
- parent compound residues.
      
-
      Datasets 3 and 4 are from the Renewal Assessment Report (RAR) for isofetamid
- (Belgium, 2014, p. 8) and show the data for two different radiolabels. For
- dataset 4, the value given for the metabolite in the day zero sampling
- in replicate B was added to the parent compound, following the respective
- FOCUS recommendation.
      
-
      Dataset 5 is from the Renewal Assessment Report (RAR) for ethofumesate
- (Austria, 2015, p. 16).
      
-
      Datasets 6 to 10 are from the Renewal Assessment Report (RAR) for glyphosate
- (Germany, 2013, pages 8, 28, 50, 51). For the initial sampling,
- the residues given for the metabolite were added to the parent
- value, following the recommendation of the FOCUS kinetics workgroup.
      
-
      Dataset 11 is from the Renewal Assessment Report (RAR) for 2,4-D
- (Hellas, 2013, p. 644). Values reported as zero were set to NA, with
- the exception of the day three sampling of metabolite A2, which was set
- to one half of the LOD reported to be 1% AR.
      
-
      Dataset 12 is from the Renewal Assessment Report (RAR) for thifensulfuron-methyl
- (United Kingdom, 2014, p. 81).
      
-    
      
-
-    
      
-    
      experimental_data_for_UBA_2019
      
-    
      
-
-    
      
-    
      Format
      
-    
      A list containing twelve datasets as an R6 class defined by mkinds,
-  each containing, among others, the following components
      title
      
-
      The name of the dataset, e.g. Soil 1
      
-
-    
      data
      
-
      A data frame with the data in the form expected by mkinfit
      
-
-  
-
      
-    
      
-    
      Source
      
-    
-
-
      Austria (2015). Ethofumesate Renewal Assessment Report Volume 3 Annex B.8 (AS)
      
-
      Belgium (2014). Isofetamid (IKF-5411) Draft Assessment Report Volume 3 Annex B.8 (AS)
      
-
      France (2015). Imazamox Draft Renewal Assessment Report Volume 3 Annex B.8 (AS)
      
-
      FOCUS (2014) “Generic guidance for Estimating Persistence and
-  Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
-  Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-  Version 1.1, 18 December 2014
-  http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-
      Germany (2013). Renewal Assessment Report Glyphosate Volume 3 Annex B.8: Environmental Fate
-  and Behaviour
      
-
      Hellas (2013). Renewal Assessment Report 2,4-D Volume 3 Annex B.8: Fate and behaviour in the
-  environment
      
-
      Ranke (2019) Documentation of results obtained for the error model expertise
-  written for the German Umweltbundesamt.
      
-
      United Kingdom (2014). Thifensulfuron-methyl - Annex B.8 (Volume 3) to the Report and Proposed
-  Decision of the United Kingdom made to the European Commission under Regulation (EC) No.
-  1141/2010 for renewal of an active substance
      
-    
      
-
-    
      
-    
      Examples
      
-    
      # \dontrun{
-
-# Model definitions
-sfo_sfo <- mkinmod(
-  parent = mkinsub("SFO", to = "A1"),
-  A1 = mkinsub("SFO"),
-  use_of_ff = "max"
-)
-#> Temporary DLL for differentials generated and loaded
-
-dfop_sfo <- mkinmod(
-  parent = mkinsub("DFOP", to = "A1"),
-  A1 = mkinsub("SFO"),
-  use_of_ff = "max"
-)
-#> Temporary DLL for differentials generated and loaded
-
-sfo_sfo_sfo <- mkinmod(
-  parent = mkinsub("SFO", to = "A1"),
-  A1 = mkinsub("SFO", to = "A2"),
-  A2 = mkinsub("SFO"),
-  use_of_ff = "max"
-)
-#> Temporary DLL for differentials generated and loaded
-
-dfop_sfo_sfo <- mkinmod(
-  parent = mkinsub("DFOP", to = "A1"),
-  A1 = mkinsub("SFO", to = "A2"),
-  A2 = mkinsub("SFO"),
-  use_of_ff = "max"
-)
-#> Temporary DLL for differentials generated and loaded
-d_1_2 <- lapply(experimental_data_for_UBA_2019[1:2], function(x) x$data)
-names(d_1_2) <- paste("Soil", 1:2)
-
-
-f_1_2_tc <- mmkin(list("DFOP-SFO-SFO" = dfop_sfo_sfo), d_1_2, error_model = "tc")
-
-plot(f_1_2_tc, resplot = "errmod")
-
-
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/f_time_norm_focus.html b/docs/dev/reference/f_time_norm_focus.html
deleted file mode 100644
index b0722bc6..00000000
--- a/docs/dev/reference/f_time_norm_focus.html
+++ /dev/null
@@ -1,248 +0,0 @@
-
-Normalisation factors for aerobic soil degradation according to FOCUS guidance — f_time_norm_focus • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Normalisation factors for aerobic soil degradation according to FOCUS guidance
      
-    Source: R/f_time_norm_focus.R
-    
-    
      
-
-    
      
-    
      Time step normalisation factors for aerobic soil degradation as described
-in Appendix 8 to the FOCUS kinetics guidance (FOCUS 2014, p. 369).
      
-    
      
-
-    
      
-    
      f_time_norm_focus(object, ...)
-
-# S3 method for numeric
-f_time_norm_focus(
-  object,
-  moisture = NA,
-  field_moisture = NA,
-  temperature = object,
-  Q10 = 2.58,
-  walker = 0.7,
-  f_na = NA,
-  ...
-)
-
-# S3 method for mkindsg
-f_time_norm_focus(
-  object,
-  study_moisture_ref_source = c("auto", "meta", "focus"),
-  Q10 = 2.58,
-  walker = 0.7,
-  f_na = NA,
-  ...
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      An object containing information used for the calculations
      
-
-
-
      ...
      
-
      Currently not used
      
-
-
-
      moisture
      
-
      Numeric vector of moisture contents in \% w/w
      
-
-
-
      field_moisture
      
-
      Numeric vector of moisture contents at field capacity
-(pF2) in \% w/w
      
-
-
-
      temperature
      
-
      Numeric vector of temperatures in °C
      
-
-
-
      Q10
      
-
      The Q10 value used for temperature normalisation
      
-
-
-
      walker
      
-
      The Walker exponent used for moisture normalisation
      
-
-
-
      f_na
      
-
      The factor to use for NA values. If set to NA, only factors
-for complete cases will be returned.
      
-
-
-
      study_moisture_ref_source
      
-
      Source for the reference value
-used to calculate the study moisture. If 'auto', preference is given
-to a reference moisture given in the meta information, otherwise
-the focus soil moisture for the soil class is used
      
-
-
      
-    
      
-    
      References
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
-FOCUS (2014) “Generic guidance for Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-Version 1.1, 18 December 2014
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-    
      
-    
      
-    
      See also
      
-    
      focus_soil_moisture
      
-    
      
-
-    
      
-    
      Examples
      
-    
      f_time_norm_focus(25, 20, 25) # 1.37, compare FOCUS 2014 p. 184
-#> [1] 1.373956
-
-D24_2014$meta
-#>                                 study usda_soil_type study_moisture_ref_type
-#> Mississippi                Cohen 1991      Silt loam                    <NA>
-#> Fayette     Liu and Adelfinskaya 2011      Silt loam                     pF1
-#> RefSol 03-G Liu and Adelfinskaya 2011           Loam                     pF1
-#> Site E1     Liu and Adelfinskaya 2011           Loam                     pF1
-#> Site I2     Liu and Adelfinskaya 2011     Loamy sand                     pF1
-#>             rel_moisture temperature
-#> Mississippi           NA          25
-#> Fayette              0.5          20
-#> RefSol 03-G          0.5          20
-#> Site E1              0.5          20
-#> Site I2              0.5          20
-# No moisture normalisation in the first dataset, so we use f_na = 1 to get
-# temperature only normalisation as in the EU evaluation
-f_time_norm_focus(D24_2014, study_moisture_ref_source = "focus", f_na = 1)
-#> $f_time_norm was (re)set to normalised values
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/focus_soil_moisture.html b/docs/dev/reference/focus_soil_moisture.html
deleted file mode 100644
index cb4a035a..00000000
--- a/docs/dev/reference/focus_soil_moisture.html
+++ /dev/null
@@ -1,170 +0,0 @@
-
-FOCUS default values for soil moisture contents at field capacity, MWHC and 1/3 bar — focus_soil_moisture • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      FOCUS default values for soil moisture contents at field capacity, MWHC and 1/3 bar
      
-    Source: R/focus_soil_moisture.R
-    
-    
      
-
-    
      
-    
      The value were transcribed from p. 36. The table assumes field capacity
-corresponds to pF2, MWHC to pF 1 and 1/3 bar to pF 2.5.
      
-    
      
-
-    
      
-    
      focus_soil_moisture
      
-    
      
-
-    
      
-    
      Format
      
-    
      A matrix with upper case USDA soil classes as row names, and water tension
-('pF1', 'pF2', 'pF 2.5') as column names
      
-    
      
-    
      
-    
      Source
      
-    
      Anonymous (2014) Generic Guidance for Tier 1 FOCUS Ground Water Assessment
-Version 2.2, May 2014 https://esdac.jrc.ec.europa.eu/projects/ground-water
      
-    
      
-
-    
      
-    
      Examples
      
-    
      focus_soil_moisture
-#>                 pF1 pF2 pF2.5
-#> Sand             24  12     7
-#> Loamy sand       24  14     9
-#> Sandy loam       27  19    15
-#> Sandy clay loam  28  22    18
-#> Clay loam        32  28    25
-#> Loam             31  25    21
-#> Silt loam        32  26    21
-#> Silty clay loam  34  30    27
-#> Silt             31  27    21
-#> Sandy clay       41  35    31
-#> Silty clay       44  40    36
-#> Clay             53  48    43
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/get_deg_func.html b/docs/dev/reference/get_deg_func.html
deleted file mode 100644
index cf81a591..00000000
--- a/docs/dev/reference/get_deg_func.html
+++ /dev/null
@@ -1,147 +0,0 @@
-
-Retrieve a degradation function from the mmkin namespace — get_deg_func • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Retrieve a degradation function from the mmkin namespace
      
-    Source: R/nlme.mmkin.R
-    
-    
      
-
-    
      
-    
      Retrieve a degradation function from the mmkin namespace
      
-    
      
-
-    
      
-    
      get_deg_func()
      
-    
      
-
-    
      
-    
      Value
      
-    
-
-
      A function that was likely previously assigned from within
-nlme.mmkin
      
-    
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/hierarchical_kinetics.html b/docs/dev/reference/hierarchical_kinetics.html
deleted file mode 100644
index 7ece90cc..00000000
--- a/docs/dev/reference/hierarchical_kinetics.html
+++ /dev/null
@@ -1,197 +0,0 @@
-
-Hierarchical kinetics template — hierarchical_kinetics • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Hierarchical kinetics template
      
-    Source: R/hierarchical_kinetics.R
-    
-    
      
-
-    
      
-    
      R markdown format for setting up hierarchical kinetics based on a template
-provided with the mkin package. This format is based on rmarkdown::pdf_document.
-Chunk options are adapted. Echoing R code from code chunks and caching are
-turned on per default. character for prepending output from code chunks is
-set to the empty string, code tidying is off, figure alignment defaults to
-centering, and positioning of figures is set to "H", which means that
-figures will not move around in the document, but stay where the user
-includes them.
      
-    
      
-
-    
      
-    
      hierarchical_kinetics(..., keep_tex = FALSE)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      ...
      
-
      Arguments to rmarkdown::pdf_document
      
-
-
-
      keep_tex
      
-
      Keep the intermediate tex file used in the conversion to PDF
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      R Markdown output format to pass to
-render
      
-
-
-    
      
-    
      
-    
      Details
      
-    
      The latter feature (positioning the figures with "H") depends on the LaTeX
-package 'float'. In addition, the LaTeX package 'listing' is used in the
-template for showing model fit summaries in the Appendix. This means that
-the LaTeX packages 'float' and 'listing' need to be installed in the TeX
-distribution used.
      
-
      On Windows, the easiest way to achieve this (if no TeX distribution
-is present before) is to install the 'tinytex' R package, to run
-'tinytex::install_tinytex()' to get the basic tiny Tex distribution,
-and then to run 'tinytex::tlmgr_install(c("float", "listing"))'.
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-# \dontrun{
-library(rmarkdown)
-# The following is now commented out after the relase of v1.2.3 for the generation
-# of online docs, as the command creates a directory and opens an editor
-#draft("example_analysis.rmd", template = "hierarchical_kinetics", package = "mkin")
-# }
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/illparms.html b/docs/dev/reference/illparms.html
deleted file mode 100644
index 7bf6c1fe..00000000
--- a/docs/dev/reference/illparms.html
+++ /dev/null
@@ -1,253 +0,0 @@
-
-Method to get the names of ill-defined parameters — illparms • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Method to get the names of ill-defined parameters
      
-    Source: R/illparms.R
-    
-    
      
-
-    
      
-    
      The method for generalised nonlinear regression fits as obtained
-with mkinfit and mmkin checks if the degradation parameters
-pass the Wald test (in degradation kinetics often simply called t-test) for
-significant difference from zero. For this test, the parameterisation
-without parameter transformations is used.
      
-    
      
-
-    
      
-    
      illparms(object, ...)
-
-# S3 method for mkinfit
-illparms(object, conf.level = 0.95, ...)
-
-# S3 method for illparms.mkinfit
-print(x, ...)
-
-# S3 method for mmkin
-illparms(object, conf.level = 0.95, ...)
-
-# S3 method for illparms.mmkin
-print(x, ...)
-
-# S3 method for saem.mmkin
-illparms(
-  object,
-  conf.level = 0.95,
-  random = TRUE,
-  errmod = TRUE,
-  slopes = TRUE,
-  ...
-)
-
-# S3 method for illparms.saem.mmkin
-print(x, ...)
-
-# S3 method for mhmkin
-illparms(object, conf.level = 0.95, random = TRUE, errmod = TRUE, ...)
-
-# S3 method for illparms.mhmkin
-print(x, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      The object to investigate
      
-
-
-
      ...
      
-
      For potential future extensions
      
-
-
-
      conf.level
      
-
      The confidence level for checking p values
      
-
-
-
      x
      
-
      The object to be printed
      
-
-
-
      random
      
-
      For hierarchical fits, should random effects be tested?
      
-
-
-
      errmod
      
-
      For hierarchical fits, should error model parameters be
-tested?
      
-
-
-
      slopes
      
-
      For hierarchical saem fits using saemix as backend,
-should slope parameters in the covariate model(starting with 'beta_') be
-tested?
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      For mkinfit or saem objects, a character vector of parameter
-names. For mmkin or mhmkin objects, a matrix like object of class
-'illparms.mmkin' or 'illparms.mhmkin'.
      
-    
      
-    
      
-    
      Details
      
-    
      The method for hierarchical model fits, also known as nonlinear
-mixed-effects model fits as obtained with saem and mhmkin
-checks if any of the confidence intervals for the random
-effects expressed as standard deviations include zero, and if
-the confidence intervals for the error model parameters include
-zero.
      
-    
      
-    
      
-    
      Note
      
-    
      All return objects have printing methods. For the single fits, printing
-does not output anything in the case no ill-defined parameters are found.
      
-    
      
-
-    
      
-    
      Examples
      
-    
      fit <- mkinfit("FOMC", FOCUS_2006_A, quiet = TRUE)
-illparms(fit)
-#> [1] "parent_0" "alpha"    "beta"     "sigma"   
-# \dontrun{
-fits <- mmkin(
-  c("SFO", "FOMC"),
-  list("FOCUS A" = FOCUS_2006_A,
-       "FOCUS C" = FOCUS_2006_C),
-  quiet = TRUE)
-illparms(fits)
-#>       dataset
-#> model  FOCUS A                      FOCUS C
-#>   SFO                                      
-#>   FOMC parent_0, alpha, beta, sigma        
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/ilr.html b/docs/dev/reference/ilr.html
deleted file mode 100644
index 94b23a76..00000000
--- a/docs/dev/reference/ilr.html
+++ /dev/null
@@ -1,210 +0,0 @@
-
-Function to perform isometric log-ratio transformation — ilr • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Function to perform isometric log-ratio transformation
      
-    Source: R/ilr.R
-    
-    
      
-
-    
      
-    
      This implementation is a special case of the class of isometric log-ratio
-transformations.
      
-    
      
-
-    
      
-    
      ilr(x)
-
-invilr(x)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      x
      
-
      A numeric vector. Naturally, the forward transformation is only
-sensible for vectors with all elements being greater than zero.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The result of the forward or backward transformation. The returned
-components always sum to 1 for the case of the inverse log-ratio
-transformation.
      
-    
      
-    
      
-    
      References
      
-    
      Peter Filzmoser, Karel Hron (2008) Outlier Detection for
-Compositional Data Using Robust Methods. Math Geosci 40 233-248
      
-    
      
-    
      
-    
      See also
      
-    
      Another implementation can be found in R package
-robCompositions.
      
-    
      
-    
      
-    
      Author
      
-    
      René Lehmann and Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-# Order matters
-ilr(c(0.1, 1, 10))
-#> [1] -1.628174 -2.820079
-ilr(c(10, 1, 0.1))
-#> [1] 1.628174 2.820079
-# Equal entries give ilr transformations with zeros as elements
-ilr(c(3, 3, 3))
-#> [1] 0 0
-# Almost equal entries give small numbers
-ilr(c(0.3, 0.4, 0.3))
-#> [1] -0.2034219  0.1174457
-# Only the ratio between the numbers counts, not their sum
-invilr(ilr(c(0.7, 0.29, 0.01)))
-#> [1] 0.70 0.29 0.01
-invilr(ilr(2.1 * c(0.7, 0.29, 0.01)))
-#> [1] 0.70 0.29 0.01
-# Inverse transformation of larger numbers gives unequal elements
-invilr(-10)
-#> [1] 7.213536e-07 9.999993e-01
-invilr(c(-10, 0))
-#> [1] 7.207415e-07 9.991507e-01 8.486044e-04
-# The sum of the elements of the inverse ilr is 1
-sum(invilr(c(-10, 0)))
-#> [1] 1
-# This is why we do not need all elements of the inverse transformation to go back:
-a <- c(0.1, 0.3, 0.5)
-b <- invilr(a)
-length(b) # Four elements
-#> [1] 4
-ilr(c(b[1:3], 1 - sum(b[1:3]))) # Gives c(0.1, 0.3, 0.5)
-#> [1] 0.1 0.3 0.5
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/index.html b/docs/dev/reference/index.html
deleted file mode 100644
index d1b789c3..00000000
--- a/docs/dev/reference/index.html
+++ /dev/null
@@ -1,528 +0,0 @@
-
-Function reference • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-      
      Reference
      
-    
      
-
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-      
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-        
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-      
-      
-        
-      
      
-          
      Main functions 
      
-          
      Essential functionality
      
-        
      
-          
      mkinmod() print(<mkinmod>) mkinsub() 
      
-        
      Function to set up a kinetic model with one or more state variables
      
-          
      mkinfit() 
      
-        
      Fit a kinetic model to data with one or more state variables
      
-          
      mmkin() print(<mmkin>) 
      
-        
      Fit one or more kinetic models with one or more state variables to one or
-more datasets
      
-          
      mhmkin() `[`(<mhmkin>) print(<mhmkin>) 
      
-        
      Fit nonlinear mixed-effects models built from one or more kinetic
-degradation models and one or more error models
      
-          
      Generics 
      
-          
      Generic functions introduced by the package
      
-        
      
-          
      parms() 
      
-        
      Extract model parameters
      
-          
      status() print(<status.mmkin>) print(<status.mhmkin>) 
      
-        
      Method to get status information for fit array objects
      
-          
      illparms() print(<illparms.mkinfit>) print(<illparms.mmkin>) print(<illparms.saem.mmkin>) print(<illparms.mhmkin>) 
      
-        
      Method to get the names of ill-defined parameters
      
-          
      endpoints() 
      
-        
      Function to calculate endpoints for further use from kinetic models fitted
-with mkinfit
      
-          
      aw() 
      
-        
      Calculate Akaike weights for model averaging
      
-          
      Show results 
      
-          
      Functions working with mkinfit objects
      
-        
      
-          
      plot(<mkinfit>) plot_sep() plot_res() plot_err() 
      
-        
      Plot the observed data and the fitted model of an mkinfit object
      
-          
      summary(<mkinfit>) print(<summary.mkinfit>) 
      
-        
      Summary method for class "mkinfit"
      
-          
      confint(<mkinfit>) 
      
-        
      Confidence intervals for parameters of mkinfit objects
      
-          
      update(<mkinfit>) 
      
-        
      Update an mkinfit model with different arguments
      
-          
      lrtest(<mkinfit>) lrtest(<mmkin>) 
      
-        
      Likelihood ratio test for mkinfit models
      
-          
      loftest() 
      
-        
      Lack-of-fit test for models fitted to data with replicates
      
-          
      mkinerrmin() 
      
-        
      Calculate the minimum error to assume in order to pass the variance test
      
-          
      CAKE_export() 
      
-        
      Export a list of datasets format to a CAKE study file
      
-          
      Work with mmkin objects 
      
-          
      Functions working with aggregated results
      
-        
      
-          
      `[`(<mmkin>) 
      
-        
      Subsetting method for mmkin objects
      
-          
      plot(<mmkin>) 
      
-        
      Plot model fits (observed and fitted) and the residuals for a row or column
-of an mmkin object
      
-          
      AIC(<mmkin>) BIC(<mmkin>) 
      
-        
      Calculate the AIC for a column of an mmkin object
      
-          
      summary(<mmkin>) print(<summary.mmkin>) 
      
-        
      Summary method for class "mmkin"
      
-          
      Mixed models 
      
-          
      Create and work with nonlinear hierarchical models
      
-        
      
-          
      hierarchical_kinetics() 
      
-        
      Hierarchical kinetics template
      
-          
      read_spreadsheet() 
      
-        
      Read datasets and relevant meta information from a spreadsheet file
      
-          
      nlme(<mmkin>) print(<nlme.mmkin>) update(<nlme.mmkin>) 
      
-        
      Create an nlme model for an mmkin row object
      
-          
      saem() print(<saem.mmkin>) saemix_model() saemix_data() 
      
-        
      Fit nonlinear mixed models with SAEM
      
-          
      mhmkin() `[`(<mhmkin>) print(<mhmkin>) 
      
-        
      Fit nonlinear mixed-effects models built from one or more kinetic
-degradation models and one or more error models
      
-          
      plot(<mixed.mmkin>) 
      
-        
      Plot predictions from a fitted nonlinear mixed model obtained via an mmkin row object
      
-          
      summary(<nlme.mmkin>) print(<summary.nlme.mmkin>) 
      
-        
      Summary method for class "nlme.mmkin"
      
-          
      summary(<saem.mmkin>) print(<summary.saem.mmkin>) 
      
-        
      Summary method for class "saem.mmkin"
      
-          
      anova(<saem.mmkin>) 
      
-        
      Anova method for saem.mmkin objects
      
-          
      logLik(<saem.mmkin>) 
      
-        
      logLik method for saem.mmkin objects
      
-          
      nlme_function() nlme_data() 
      
-        
      Helper functions to create nlme models from mmkin row objects
      
-          
      get_deg_func() 
      
-        
      Retrieve a degradation function from the mmkin namespace
      
-          
      mixed() print(<mixed.mmkin>) 
      
-        
      Create a mixed effects model from an mmkin row object
      
-          
      reexports intervals lrtest nlme 
      
-        
      Objects exported from other packages
      
-          
      intervals(<saem.mmkin>) 
      
-        
      Confidence intervals for parameters in saem.mmkin objects
      
-          
      multistart() print(<multistart>) best() which.best() 
      
-        
      Perform a hierarchical model fit with multiple starting values
      
-          
      llhist() 
      
-        
      Plot the distribution of log likelihoods from multistart objects
      
-          
      parplot() 
      
-        
      Plot parameter variability of multistart objects
      
-          
      Datasets and known results 
      
-          
      
-        
      
-          
      ds_mixed ds_sfo ds_fomc ds_dfop ds_hs ds_dfop_sfo 
      
-        
      Synthetic data for hierarchical kinetic degradation models
      
-          
      D24_2014 
      
-        
      Aerobic soil degradation data on 2,4-D from the EU assessment in 2014
      
-          
      dimethenamid_2018 
      
-        
      Aerobic soil degradation data on dimethenamid and dimethenamid-P from the EU assessment in 2018
      
-          
      FOCUS_2006_A FOCUS_2006_B FOCUS_2006_C FOCUS_2006_D FOCUS_2006_E FOCUS_2006_F 
      
-        
      Datasets A to F from the FOCUS Kinetics report from 2006
      
-          
      FOCUS_2006_SFO_ref_A_to_F 
      
-        
      Results of fitting the SFO model to Datasets A to F of FOCUS (2006)
      
-          
      FOCUS_2006_FOMC_ref_A_to_F 
      
-        
      Results of fitting the FOMC model to Datasets A to F of FOCUS (2006)
      
-          
      FOCUS_2006_HS_ref_A_to_F 
      
-        
      Results of fitting the HS model to Datasets A to F of FOCUS (2006)
      
-          
      FOCUS_2006_DFOP_ref_A_to_B 
      
-        
      Results of fitting the DFOP model to Datasets A to B of FOCUS (2006)
      
-          
      NAFTA_SOP_Appendix_B NAFTA_SOP_Appendix_D 
      
-        
      Example datasets from the NAFTA SOP published 2015
      
-          
      NAFTA_SOP_Attachment 
      
-        
      Example datasets from Attachment 1 to the NAFTA SOP published 2015
      
-          
      mccall81_245T 
      
-        
      Datasets on aerobic soil metabolism of 2,4,5-T in six soils
      
-          
      schaefer07_complex_case 
      
-        
      Metabolism data set used for checking the software quality of KinGUI
      
-          
      synthetic_data_for_UBA_2014 
      
-        
      Synthetic datasets for one parent compound with two metabolites
      
-          
      experimental_data_for_UBA_2019 
      
-        
      Experimental datasets used for development and testing of error models
      
-          
      test_data_from_UBA_2014 
      
-        
      Three experimental datasets from two water sediment systems and one soil
      
-          
      focus_soil_moisture 
      
-        
      FOCUS default values for soil moisture contents at field capacity, MWHC and 1/3 bar
      
-          
      print(<mkinds>) 
      
-        
      A dataset class for mkin
      
-          
      print(<mkindsg>) 
      
-        
      A class for dataset groups for mkin
      
-          
      NAFTA guidance 
      
-          
      
-        
      
-          
      nafta() print(<nafta>) 
      
-        
      Evaluate parent kinetics using the NAFTA guidance
      
-          
      plot(<nafta>) 
      
-        
      Plot the results of the three models used in the NAFTA scheme.
      
-          
      Utility functions 
      
-          
      
-        
      
-          
      summary_listing() tex_listing() html_listing() 
      
-        
      Display the output of a summary function according to the output format
      
-          
      f_time_norm_focus() 
      
-        
      Normalisation factors for aerobic soil degradation according to FOCUS guidance
      
-          
      set_nd_nq() set_nd_nq_focus() 
      
-        
      Set non-detects and unquantified values in residue series without replicates
      
-          
      max_twa_parent() max_twa_sfo() max_twa_fomc() max_twa_dfop() max_twa_hs() 
      
-        
      Function to calculate maximum time weighted average concentrations from
-kinetic models fitted with mkinfit
      
-          
      mkin_wide_to_long() 
      
-        
      Convert a dataframe with observations over time into long format
      
-          
      mkin_long_to_wide() 
      
-        
      Convert a dataframe from long to wide format
      
-          
      Helper functions mainly used internally 
      
-          
      
-        
      
-          
      mkinpredict() 
      
-        
      Produce predictions from a kinetic model using specific parameters
      
-          
      transform_odeparms() backtransform_odeparms() 
      
-        
      Functions to transform and backtransform kinetic parameters for fitting
      
-          
      ilr() invilr() 
      
-        
      Function to perform isometric log-ratio transformation
      
-          
      logLik(<mkinfit>) 
      
-        
      Calculated the log-likelihood of a fitted mkinfit object
      
-          
      residuals(<mkinfit>) 
      
-        
      Extract residuals from an mkinfit model
      
-          
      nobs(<mkinfit>) 
      
-        
      Number of observations on which an mkinfit object was fitted
      
-          
      mkinresplot() 
      
-        
      Function to plot residuals stored in an mkin object
      
-          
      mkinparplot() 
      
-        
      Function to plot the confidence intervals obtained using mkinfit
      
-          
      mkinerrplot() 
      
-        
      Function to plot squared residuals and the error model for an mkin object
      
-          
      mean_degparms() 
      
-        
      Calculate mean degradation parameters for an mmkin row object
      
-          
      create_deg_func() 
      
-        
      Create degradation functions for known analytical solutions
      
-          
      Analytical solutions 
      
-          
      Parent only model solutions
      
-        
      
-          
      SFO.solution() 
      
-        
      Single First-Order kinetics
      
-          
      FOMC.solution() 
      
-        
      First-Order Multi-Compartment kinetics
      
-          
      DFOP.solution() 
      
-        
      Double First-Order in Parallel kinetics
      
-          
      SFORB.solution() 
      
-        
      Single First-Order Reversible Binding kinetics
      
-          
      HS.solution() 
      
-        
      Hockey-Stick kinetics
      
-          
      IORE.solution() 
      
-        
      Indeterminate order rate equation kinetics
      
-          
      logistic.solution() 
      
-        
      Logistic kinetics
      
-          
      Generate synthetic datasets 
      
-          
      
-        
      
-          
      add_err() 
      
-        
      Add normally distributed errors to simulated kinetic degradation data
      
-          
      sigma_twocomp() 
      
-        
      Two-component error model
      
-          
      Deprecated functions 
      
-          
      Functions that have been superseded
      
-        
      
-          
      mkinplot() 
      
-        
      Plot the observed data and the fitted model of an mkinfit object
      
-
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/intervals.nlmixr.mmkin.html b/docs/dev/reference/intervals.nlmixr.mmkin.html
deleted file mode 100644
index 14f11c0c..00000000
--- a/docs/dev/reference/intervals.nlmixr.mmkin.html
+++ /dev/null
@@ -1,132 +0,0 @@
-
-Confidence intervals for parameters in nlmixr.mmkin objects — intervals.nlmixr.mmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Confidence intervals for parameters in nlmixr.mmkin objects
      
-    Source: R/intervals.R
-    
-    
      
-
-    
      
-    
      Confidence intervals for parameters in nlmixr.mmkin objects
      
-    
      
-
-    
      
-    
      # S3 method for nlmixr.mmkin
-intervals(object, level = 0.95, backtransform = TRUE, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      The fitted saem.mmkin object
      
-
      level
      
-
      The confidence level.
      
-
      backtransform
      
-
      Should we backtransform the parameters where a one to
-one correlation between transformed and backtransformed parameters exists?
      
-
      ...
      
-
      For compatibility with the generic method
      
-
      
-    
      
-    
      Value
      
-    
      An object with 'intervals.saem.mmkin' and 'intervals.lme' in the
-class attribute
      
-    
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.2.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/intervals.saem.mmkin.html b/docs/dev/reference/intervals.saem.mmkin.html
deleted file mode 100644
index a566ee8d..00000000
--- a/docs/dev/reference/intervals.saem.mmkin.html
+++ /dev/null
@@ -1,169 +0,0 @@
-
-Confidence intervals for parameters in saem.mmkin objects — intervals.saem.mmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Confidence intervals for parameters in saem.mmkin objects
      
-    Source: R/intervals.R
-    
-    
      
-
-    
      
-    
      Confidence intervals for parameters in saem.mmkin objects
      
-    
      
-
-    
      
-    
      # S3 method for saem.mmkin
-intervals(object, level = 0.95, backtransform = TRUE, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      The fitted saem.mmkin object
      
-
-
-
      level
      
-
      The confidence level. Must be the default of 0.95 as this is what
-is available in the saemix object
      
-
-
-
      backtransform
      
-
      In case the model was fitted with mkin transformations,
-should we backtransform the parameters where a one to one correlation
-between transformed and backtransformed parameters exists?
      
-
-
-
      ...
      
-
      For compatibility with the generic method
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      An object with 'intervals.saem.mmkin' and 'intervals.lme' in the
-class attribute
      
-    
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/llhist.html b/docs/dev/reference/llhist.html
deleted file mode 100644
index 2b5afa25..00000000
--- a/docs/dev/reference/llhist.html
+++ /dev/null
@@ -1,168 +0,0 @@
-
-Plot the distribution of log likelihoods from multistart objects — llhist • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Plot the distribution of log likelihoods from multistart objects
      
-    Source: R/llhist.R
-    
-    
      
-
-    
      
-    
      Produces a histogram of log-likelihoods. In addition, the likelihood of the
-original fit is shown as a red vertical line.
      
-    
      
-
-    
      
-    
      llhist(object, breaks = "Sturges", lpos = "topleft", main = "", ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      The multistart object
      
-
-
-
      breaks
      
-
      Passed to hist
      
-
-
-
      lpos
      
-
      Positioning of the legend.
      
-
-
-
      main
      
-
      Title of the plot
      
-
-
-
      ...
      
-
      Passed to hist
      
-
-
      
-    
      
-    
      See also
      
-    
      multistart
      
-    
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/loftest-1.png b/docs/dev/reference/loftest-1.png
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deleted file mode 100644
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--- a/docs/dev/reference/loftest.html
+++ /dev/null
@@ -1,342 +0,0 @@
-
-Lack-of-fit test for models fitted to data with replicates — loftest • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Lack-of-fit test for models fitted to data with replicates
      
-    Source: R/loftest.R
-    
-    
      
-
-    
      
-    
      This is a generic function with a method currently only defined for mkinfit
-objects. It fits an anova model to the data contained in the object and
-compares the likelihoods using the likelihood ratio test
-lrtest.default from the lmtest package.
      
-    
      
-
-    
      
-    
      loftest(object, ...)
-
-# S3 method for mkinfit
-loftest(object, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      A model object with a defined loftest method
      
-
-
-
      ...
      
-
      Not used
      
-
-
      
-    
      
-    
      Details
      
-    
      The anova model is interpreted as the simplest form of an mkinfit model,
-assuming only a constant variance about the means, but not enforcing any
-structure of the means, so we have one model parameter for every mean
-of replicate samples.
      
-    
      
-    
      
-    
      See also
      
-    
      lrtest
      
-    
      
-
-    
      
-    
      Examples
      
-    
      # \dontrun{
-test_data <- subset(synthetic_data_for_UBA_2014[[12]]$data, name == "parent")
-sfo_fit <- mkinfit("SFO", test_data, quiet = TRUE)
-plot_res(sfo_fit) # We see a clear pattern in the residuals
-
-loftest(sfo_fit)  # We have a clear lack of fit
-#> Likelihood ratio test
-#> 
-#> Model 1: ANOVA with error model const
-#> Model 2: SFO with error model const
-#>   #Df  LogLik Df  Chisq Pr(>Chisq)    
-#> 1  10 -40.710                         
-#> 2   3 -63.954 -7 46.487  7.027e-08 ***
-#> ---
-#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
-#
-# We try a different model (the one that was used to generate the data)
-dfop_fit <- mkinfit("DFOP", test_data, quiet = TRUE)
-plot_res(dfop_fit) # We don't see systematic deviations, but heteroscedastic residuals
-
-# therefore we should consider adapting the error model, although we have
-loftest(dfop_fit) # no lack of fit
-#> Likelihood ratio test
-#> 
-#> Model 1: ANOVA with error model const
-#> Model 2: DFOP with error model const
-#>   #Df  LogLik Df Chisq Pr(>Chisq)
-#> 1  10 -40.710                    
-#> 2   5 -42.453 -5 3.485     0.6257
-#
-# This is the anova model used internally for the comparison
-test_data_anova <- test_data
-test_data_anova$time <- as.factor(test_data_anova$time)
-anova_fit <- lm(value ~ time, data = test_data_anova)
-summary(anova_fit)
-#> 
-#> Call:
-#> lm(formula = value ~ time, data = test_data_anova)
-#> 
-#> Residuals:
-#>     Min      1Q  Median      3Q     Max 
-#> -6.1000 -0.5625  0.0000  0.5625  6.1000 
-#> 
-#> Coefficients:
-#>             Estimate Std. Error t value Pr(>|t|)    
-#> (Intercept)  103.150      2.323  44.409 7.44e-12 ***
-#> time1        -19.950      3.285  -6.073 0.000185 ***
-#> time3        -50.800      3.285 -15.465 8.65e-08 ***
-#> time7        -68.500      3.285 -20.854 6.28e-09 ***
-#> time14       -79.750      3.285 -24.278 1.63e-09 ***
-#> time28       -86.000      3.285 -26.181 8.35e-10 ***
-#> time60       -94.900      3.285 -28.891 3.48e-10 ***
-#> time90       -98.500      3.285 -29.986 2.49e-10 ***
-#> time120     -100.450      3.285 -30.580 2.09e-10 ***
-#> ---
-#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
-#> 
-#> Residual standard error: 3.285 on 9 degrees of freedom
-#> Multiple R-squared:  0.9953,	Adjusted R-squared:  0.9912 
-#> F-statistic: 240.5 on 8 and 9 DF,  p-value: 1.417e-09
-#> 
-logLik(anova_fit) # We get the same likelihood and degrees of freedom
-#> 'log Lik.' -40.71015 (df=10)
-#
-test_data_2 <- synthetic_data_for_UBA_2014[[12]]$data
-m_synth_SFO_lin <- mkinmod(parent = list(type = "SFO", to = "M1"),
-  M1 = list(type = "SFO", to = "M2"),
-  M2 = list(type = "SFO"), use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-sfo_lin_fit <- mkinfit(m_synth_SFO_lin, test_data_2, quiet = TRUE)
-plot_res(sfo_lin_fit) # not a good model, we try parallel formation
-
-loftest(sfo_lin_fit)
-#> Likelihood ratio test
-#> 
-#> Model 1: ANOVA with error model const
-#> Model 2: m_synth_SFO_lin with error model const and fixed parameter(s) M1_0, M2_0
-#>   #Df   LogLik  Df  Chisq Pr(>Chisq)    
-#> 1  28  -93.606                          
-#> 2   7 -171.927 -21 156.64  < 2.2e-16 ***
-#> ---
-#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
-#
-m_synth_SFO_par <- mkinmod(parent = list(type = "SFO", to = c("M1", "M2")),
-  M1 = list(type = "SFO"),
-  M2 = list(type = "SFO"), use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-sfo_par_fit <- mkinfit(m_synth_SFO_par, test_data_2, quiet = TRUE)
-plot_res(sfo_par_fit) # much better for metabolites
-
-loftest(sfo_par_fit)
-#> Likelihood ratio test
-#> 
-#> Model 1: ANOVA with error model const
-#> Model 2: m_synth_SFO_par with error model const and fixed parameter(s) M1_0, M2_0
-#>   #Df   LogLik  Df  Chisq Pr(>Chisq)    
-#> 1  28  -93.606                          
-#> 2   7 -156.331 -21 125.45  < 2.2e-16 ***
-#> ---
-#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
-#
-m_synth_DFOP_par <- mkinmod(parent = list(type = "DFOP", to = c("M1", "M2")),
-  M1 = list(type = "SFO"),
-  M2 = list(type = "SFO"), use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-dfop_par_fit <- mkinfit(m_synth_DFOP_par, test_data_2, quiet = TRUE)
-plot_res(dfop_par_fit) # No visual lack of fit
-
-loftest(dfop_par_fit)  # no lack of fit found by the test
-#> Likelihood ratio test
-#> 
-#> Model 1: ANOVA with error model const
-#> Model 2: m_synth_DFOP_par with error model const and fixed parameter(s) M1_0, M2_0
-#>   #Df   LogLik  Df  Chisq Pr(>Chisq)
-#> 1  28  -93.606                      
-#> 2   9 -102.763 -19 18.313     0.5016
-#
-# The anova model used for comparison in the case of transformation products
-test_data_anova_2 <- dfop_par_fit$data
-test_data_anova_2$variable <- as.factor(test_data_anova_2$variable)
-test_data_anova_2$time <- as.factor(test_data_anova_2$time)
-anova_fit_2 <- lm(observed ~ time:variable - 1, data = test_data_anova_2)
-summary(anova_fit_2)
-#> 
-#> Call:
-#> lm(formula = observed ~ time:variable - 1, data = test_data_anova_2)
-#> 
-#> Residuals:
-#>     Min      1Q  Median      3Q     Max 
-#> -6.1000 -0.5875  0.0000  0.5875  6.1000 
-#> 
-#> Coefficients: (2 not defined because of singularities)
-#>                        Estimate Std. Error t value Pr(>|t|)    
-#> time0:variableparent    103.150      1.573  65.562  < 2e-16 ***
-#> time1:variableparent     83.200      1.573  52.882  < 2e-16 ***
-#> time3:variableparent     52.350      1.573  33.274  < 2e-16 ***
-#> time7:variableparent     34.650      1.573  22.024  < 2e-16 ***
-#> time14:variableparent    23.400      1.573  14.873 6.35e-14 ***
-#> time28:variableparent    17.150      1.573  10.901 5.47e-11 ***
-#> time60:variableparent     8.250      1.573   5.244 1.99e-05 ***
-#> time90:variableparent     4.650      1.573   2.956 0.006717 ** 
-#> time120:variableparent    2.700      1.573   1.716 0.098507 .  
-#> time0:variableM1             NA         NA      NA       NA    
-#> time1:variableM1         11.850      1.573   7.532 6.93e-08 ***
-#> time3:variableM1         22.700      1.573  14.428 1.26e-13 ***
-#> time7:variableM1         33.050      1.573  21.007  < 2e-16 ***
-#> time14:variableM1        31.250      1.573  19.863  < 2e-16 ***
-#> time28:variableM1        18.900      1.573  12.013 7.02e-12 ***
-#> time60:variableM1         7.550      1.573   4.799 6.28e-05 ***
-#> time90:variableM1         3.850      1.573   2.447 0.021772 *  
-#> time120:variableM1        2.050      1.573   1.303 0.204454    
-#> time0:variableM2             NA         NA      NA       NA    
-#> time1:variableM2          6.700      1.573   4.259 0.000254 ***
-#> time3:variableM2         16.750      1.573  10.646 8.93e-11 ***
-#> time7:variableM2         25.800      1.573  16.399 6.89e-15 ***
-#> time14:variableM2        28.600      1.573  18.178 6.35e-16 ***
-#> time28:variableM2        25.400      1.573  16.144 9.85e-15 ***
-#> time60:variableM2        21.600      1.573  13.729 3.81e-13 ***
-#> time90:variableM2        17.800      1.573  11.314 2.51e-11 ***
-#> time120:variableM2       14.100      1.573   8.962 2.79e-09 ***
-#> ---
-#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
-#> 
-#> Residual standard error: 2.225 on 25 degrees of freedom
-#> Multiple R-squared:  0.9979,	Adjusted R-squared:  0.9957 
-#> F-statistic: 469.2 on 25 and 25 DF,  p-value: < 2.2e-16
-#> 
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/logLik.mkinfit.html b/docs/dev/reference/logLik.mkinfit.html
deleted file mode 100644
index e51a52eb..00000000
--- a/docs/dev/reference/logLik.mkinfit.html
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@@ -1,204 +0,0 @@
-
-Calculated the log-likelihood of a fitted mkinfit object — logLik.mkinfit • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Calculated the log-likelihood of a fitted mkinfit object
      
-    Source: R/logLik.mkinfit.R
-    
-    
      
-
-    
      
-    
      This function returns the product of the likelihood densities of each
-observed value, as calculated as part of the fitting procedure using
-dnorm, i.e. assuming normal distribution, and with the means
-predicted by the degradation model, and the standard deviations predicted by
-the error model.
      
-    
      
-
-    
      
-    
      # S3 method for mkinfit
-logLik(object, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      An object of class mkinfit.
      
-
-
-
      ...
      
-
      For compatibility with the generic method
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      An object of class logLik with the number of estimated
-parameters (degradation model parameters plus variance model parameters)
-as attribute.
      
-    
      
-    
      
-    
      Details
      
-    
      The total number of estimated parameters returned with the value of the
-likelihood is calculated as the sum of fitted degradation model parameters
-and the fitted error model parameters.
      
-    
      
-    
      
-    
      See also
      
-    
      Compare the AIC of columns of mmkin objects using
-AIC.mmkin.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-  # \dontrun{
-  sfo_sfo <- mkinmod(
-    parent = mkinsub("SFO", to = "m1"),
-    m1 = mkinsub("SFO")
-  )
-#> Temporary DLL for differentials generated and loaded
-  d_t <- subset(FOCUS_2006_D, value != 0)
-  f_nw <- mkinfit(sfo_sfo, d_t, quiet = TRUE) # no weighting (weights are unity)
-  f_obs <- update(f_nw, error_model = "obs")
-  f_tc <- update(f_nw, error_model = "tc")
-  AIC(f_nw, f_obs, f_tc)
-#>       df      AIC
-#> f_nw   5 204.4486
-#> f_obs  6 205.8727
-#> f_tc   6 141.9656
-  # }
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/logLik.saem.mmkin.html b/docs/dev/reference/logLik.saem.mmkin.html
deleted file mode 100644
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-
-logLik method for saem.mmkin objects — logLik.saem.mmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      logLik method for saem.mmkin objects
      
-    Source: R/saem.R
-    
-    
      
-
-    
      
-    
      logLik method for saem.mmkin objects
      
-    
      
-
-    
      
-    
      # S3 method for saem.mmkin
-logLik(object, ..., method = c("is", "lin", "gq"))
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      The fitted saem.mmkin object
      
-
-
-
      ...
      
-
      Passed to saemix::logLik.SaemixObject
      
-
-
-
      method
      
-
      Passed to saemix::logLik.SaemixObject
      
-
-
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
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@@ -1,253 +0,0 @@
-
-Logistic kinetics — logistic.solution • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Logistic kinetics
      
-    Source: R/parent_solutions.R
-    
-    
      
-
-    
      
-    
      Function describing exponential decline from a defined starting value, with
-an increasing rate constant, supposedly caused by microbial growth
      
-    
      
-
-    
      
-    
      logistic.solution(t, parent_0, kmax, k0, r)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      t
      
-
      Time.
      
-
-
-
      parent_0
      
-
      Starting value for the response variable at time zero.
      
-
-
-
      kmax
      
-
      Maximum rate constant.
      
-
-
-
      k0
      
-
      Minimum rate constant effective at time zero.
      
-
-
-
      r
      
-
      Growth rate of the increase in the rate constant.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The value of the response variable at time t.
      
-    
      
-    
      
-    
      Note
      
-    
      The solution of the logistic model reduces to the
-SFO.solution if k0 is equal to kmax.
      
-    
      
-    
      
-    
      References
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
-FOCUS (2014) “Generic guidance for Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-Version 1.1, 18 December 2014
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-    
      
-    
      
-    
      See also
      
-    
      Other parent solutions: 
-DFOP.solution(),
-FOMC.solution(),
-HS.solution(),
-IORE.solution(),
-SFO.solution(),
-SFORB.solution()
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-  # Reproduce the plot on page 57 of FOCUS (2014)
-  plot(function(x) logistic.solution(x, 100, 0.08, 0.0001, 0.2),
-       from = 0, to = 100, ylim = c(0, 100),
-       xlab = "Time", ylab = "Residue")
-  plot(function(x) logistic.solution(x, 100, 0.08, 0.0001, 0.4),
-       from = 0, to = 100, add = TRUE, lty = 2, col = 2)
-  plot(function(x) logistic.solution(x, 100, 0.08, 0.0001, 0.8),
-       from = 0, to = 100, add = TRUE, lty = 3, col = 3)
-  plot(function(x) logistic.solution(x, 100, 0.08, 0.001, 0.2),
-       from = 0, to = 100, add = TRUE, lty = 4, col = 4)
-  plot(function(x) logistic.solution(x, 100, 0.08, 0.08, 0.2),
-       from = 0, to = 100, add = TRUE, lty = 5, col = 5)
-  legend("topright", inset = 0.05,
-         legend = paste0("k0 = ", c(0.0001, 0.0001, 0.0001, 0.001, 0.08),
-                         ", r = ", c(0.2, 0.4, 0.8, 0.2, 0.2)),
-         lty = 1:5, col = 1:5)
-
-
-  # Fit with synthetic data
-  logistic <- mkinmod(parent = mkinsub("logistic"))
-
-  sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-  parms_logistic <- c(kmax = 0.08, k0 = 0.0001, r = 0.2)
-  d_logistic <- mkinpredict(logistic,
-    parms_logistic, c(parent = 100),
-    sampling_times)
-  d_2_1 <- add_err(d_logistic,
-    sdfunc = function(x) sigma_twocomp(x, 0.5, 0.07),
-    n = 1, reps = 2, digits = 5, LOD = 0.1, seed = 123456)[[1]]
-
-  m <- mkinfit("logistic", d_2_1, quiet = TRUE)
-  plot_sep(m)
-
-  summary(m)$bpar
-#>              Estimate   se_notrans   t value       Pr(>t)        Lower
-#> parent_0 1.057896e+02 1.9023449590 55.610120 3.768360e-16 1.016451e+02
-#> kmax     6.398190e-02 0.0143201029  4.467978 3.841828e-04 3.929235e-02
-#> k0       1.612775e-04 0.0005866813  0.274898 3.940351e-01 5.846688e-08
-#> r        2.263946e-01 0.1718110662  1.317695 1.061043e-01 4.335843e-02
-#> sigma    5.332935e+00 0.9145907310  5.830952 4.036926e-05 3.340213e+00
-#>                Upper
-#> parent_0 109.9341588
-#> kmax       0.1041853
-#> k0         0.4448749
-#> r          1.1821120
-#> sigma      7.3256566
-  endpoints(m)$distimes
-#>            DT50     DT90  DT50_k0 DT50_kmax
-#> parent 36.86533 62.41511 4297.853  10.83349
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/lrtest.mkinfit.html b/docs/dev/reference/lrtest.mkinfit.html
deleted file mode 100644
index d59590c0..00000000
--- a/docs/dev/reference/lrtest.mkinfit.html
+++ /dev/null
@@ -1,233 +0,0 @@
-
-Likelihood ratio test for mkinfit models — lrtest.mkinfit • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Likelihood ratio test for mkinfit models
      
-    Source: R/lrtest.mkinfit.R
-    
-    
      
-
-    
      
-    
      Compare two mkinfit models based on their likelihood. If two fitted
-mkinfit objects are given as arguments, it is checked if they have been
-fitted to the same data. It is the responsibility of the user to make sure
-that the models are nested, i.e. one of them has less degrees of freedom
-and can be expressed by fixing the parameters of the other.
      
-    
      
-
-    
      
-    
      # S3 method for mkinfit
-lrtest(object, object_2 = NULL, ...)
-
-# S3 method for mmkin
-lrtest(object, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      An mkinfit object, or an mmkin column
-object containing two fits to the same data.
      
-
-
-
      object_2
      
-
      Optionally, another mkinfit object fitted to the same data.
      
-
-
-
      ...
      
-
      Argument to mkinfit, passed to
-update.mkinfit for creating the alternative fitted object.
      
-
-
      
-    
      
-    
      Details
      
-    
      Alternatively, an argument to mkinfit can be given which is then passed
-to update.mkinfit to obtain the alternative model.
      
-
      The comparison is then made by the lrtest.default
-method from the lmtest package. The model with the higher number of fitted
-parameters (alternative hypothesis) is listed first, then the model with the
-lower number of fitted parameters (null hypothesis).
      
-    
      
-
-    
      
-    
      Examples
      
-    
      # \dontrun{
-test_data <- subset(synthetic_data_for_UBA_2014[[12]]$data, name == "parent")
-sfo_fit <- mkinfit("SFO", test_data, quiet = TRUE)
-dfop_fit <- mkinfit("DFOP", test_data, quiet = TRUE)
-lrtest(dfop_fit, sfo_fit)
-#> Likelihood ratio test
-#> 
-#> Model 1: DFOP with error model const
-#> Model 2: SFO with error model const
-#>   #Df  LogLik Df  Chisq Pr(>Chisq)    
-#> 1   5 -42.453                         
-#> 2   3 -63.954 -2 43.002  4.594e-10 ***
-#> ---
-#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
-lrtest(sfo_fit, dfop_fit)
-#> Likelihood ratio test
-#> 
-#> Model 1: DFOP with error model const
-#> Model 2: SFO with error model const
-#>   #Df  LogLik Df  Chisq Pr(>Chisq)    
-#> 1   5 -42.453                         
-#> 2   3 -63.954 -2 43.002  4.594e-10 ***
-#> ---
-#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
-
-# The following two examples are commented out as they fail during
-# generation of the static help pages by pkgdown
-#lrtest(dfop_fit, error_model = "tc")
-#lrtest(dfop_fit, fixed_parms = c(k2 = 0))
-
-# However, this equivalent syntax also works for static help pages
-lrtest(dfop_fit, update(dfop_fit, error_model = "tc"))
-#> Likelihood ratio test
-#> 
-#> Model 1: DFOP with error model tc
-#> Model 2: DFOP with error model const
-#>   #Df  LogLik Df  Chisq Pr(>Chisq)    
-#> 1   6 -34.587                         
-#> 2   5 -42.453 -1 15.731  7.302e-05 ***
-#> ---
-#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
-lrtest(dfop_fit, update(dfop_fit, fixed_parms = c(k2 = 0)))
-#> Likelihood ratio test
-#> 
-#> Model 1: DFOP with error model const
-#> Model 2: DFOP with error model const and fixed parameter(s) k2
-#>   #Df  LogLik Df  Chisq Pr(>Chisq)    
-#> 1   5 -42.453                         
-#> 2   4 -57.340 -1 29.776  4.851e-08 ***
-#> ---
-#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/max_twa_parent.html b/docs/dev/reference/max_twa_parent.html
deleted file mode 100644
index 507a0758..00000000
--- a/docs/dev/reference/max_twa_parent.html
+++ /dev/null
@@ -1,239 +0,0 @@
-
-Function to calculate maximum time weighted average concentrations from
-kinetic models fitted with mkinfit — max_twa_parent • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Function to calculate maximum time weighted average concentrations from
-kinetic models fitted with mkinfit
      
-    Source: R/max_twa_parent.R
-    
-    
      
-
-    
      
-    
      This function calculates maximum moving window time weighted average
-concentrations (TWAs) for kinetic models fitted with mkinfit.
-Currently, only calculations for the parent are implemented for the SFO,
-FOMC, DFOP and HS models, using the analytical formulas given in the PEC
-soil section of the FOCUS guidance.
      
-    
      
-
-    
      
-    
      max_twa_parent(fit, windows)
-
-max_twa_sfo(M0 = 1, k, t)
-
-max_twa_fomc(M0 = 1, alpha, beta, t)
-
-max_twa_dfop(M0 = 1, k1, k2, g, t)
-
-max_twa_hs(M0 = 1, k1, k2, tb, t)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      fit
      
-
      An object of class mkinfit.
      
-
-
-
      windows
      
-
      The width of the time windows for which the TWAs should be
-calculated.
      
-
-
-
      M0
      
-
      The initial concentration for which the maximum time weighted
-average over the decline curve should be calculated. The default is to use
-a value of 1, which means that a relative maximum time weighted average
-factor (f_twa) is calculated.
      
-
-
-
      k
      
-
      The rate constant in the case of SFO kinetics.
      
-
-
-
      t
      
-
      The width of the time window.
      
-
-
-
      alpha
      
-
      Parameter of the FOMC model.
      
-
-
-
      beta
      
-
      Parameter of the FOMC model.
      
-
-
-
      k1
      
-
      The first rate constant of the DFOP or the HS kinetics.
      
-
-
-
      k2
      
-
      The second rate constant of the DFOP or the HS kinetics.
      
-
-
-
      g
      
-
      Parameter of the DFOP model.
      
-
-
-
      tb
      
-
      Parameter of the HS model.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      For max_twa_parent, a numeric vector, named using the
-windows argument.  For the other functions, a numeric vector of
-length one (also known as 'a number').
      
-    
      
-    
      
-    
      References
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-  fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
-  max_twa_parent(fit, c(7, 21))
-#>        7       21 
-#> 34.71343 18.22124 
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/mccall81_245T-1.png b/docs/dev/reference/mccall81_245T-1.png
deleted file mode 100644
index 5e4ea6ef..00000000
Binary files a/docs/dev/reference/mccall81_245T-1.png and /dev/null differ
diff --git a/docs/dev/reference/mccall81_245T.html b/docs/dev/reference/mccall81_245T.html
deleted file mode 100644
index c0e9cb37..00000000
--- a/docs/dev/reference/mccall81_245T.html
+++ /dev/null
@@ -1,247 +0,0 @@
-
-Datasets on aerobic soil metabolism of 2,4,5-T in six soils — mccall81_245T • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Datasets on aerobic soil metabolism of 2,4,5-T in six soils
      
-    
-    
-    
      
-
-    
      
-    
      Time course of 2,4,5-trichlorophenoxyacetic acid, and the corresponding
- 2,4,5-trichlorophenol and 2,4,5-trichloroanisole as recovered in diethylether
- extracts.
      
-    
      
-
-    
      
-    
      mccall81_245T
      
-    
      
-
-    
      
-    
      Format
      
-    
      A dataframe containing the following variables.
      name
      
-
      the name of the compound observed. Note that T245 is used as
-                       an acronym for 2,4,5-T. T245 is a legitimate object name
-                       in R, which is necessary for specifying models using
-                       mkinmod.
      
-
-    
      time
      
-
      a numeric vector containing sampling times in days after
-                       treatment
      
-
-    
      value
      
-
      a numeric vector containing concentrations in percent of applied radioactivity
      
-
-    
      soil
      
-
      a factor containing the name of the soil
      
-
-  
-
      
-    
      
-    
      Source
      
-    
      McCall P, Vrona SA, Kelley SS (1981) Fate of uniformly carbon-14 ring labelled 2,4,5-Trichlorophenoxyacetic acid and 2,4-dichlorophenoxyacetic acid. J Agric Chem 29, 100-107
-  doi:10.1021/jf00103a026
      
-    
      
-
-    
      
-    
      Examples
      
-    
        SFO_SFO_SFO <- mkinmod(T245 = list(type = "SFO", to = "phenol"),
-    phenol = list(type = "SFO", to = "anisole"),
-    anisole = list(type = "SFO"))
-#> Temporary DLL for differentials generated and loaded
-  # \dontrun{
-    fit.1 <- mkinfit(SFO_SFO_SFO, subset(mccall81_245T, soil == "Commerce"), quiet = TRUE)
-#> Warning: Observations with value of zero were removed from the data
-    summary(fit.1)$bpar
-#>                         Estimate   se_notrans   t value       Pr(>t)
-#> T245_0              1.038550e+02 2.1847074945 47.537272 4.472189e-18
-#> k_T245              4.337042e-02 0.0018983965 22.845818 2.276911e-13
-#> k_phenol            4.050581e-01 0.2986993563  1.356073 9.756989e-02
-#> k_anisole           6.678742e-03 0.0008021439  8.326114 2.623177e-07
-#> f_T245_to_phenol    6.227599e-01 0.3985340558  1.562627 6.949413e-02
-#> f_phenol_to_anisole 1.000000e+00 0.6718439825  1.488441 7.867789e-02
-#> sigma               2.514628e+00 0.4907558883  5.123989 6.233157e-05
-#>                            Lower        Upper
-#> T245_0              99.246061385 1.084640e+02
-#> k_T245               0.039631621 4.746194e-02
-#> k_phenol             0.218013879 7.525762e-01
-#> k_anisole            0.005370739 8.305299e-03
-#> f_T245_to_phenol     0.547559081 6.924813e-01
-#> f_phenol_to_anisole  0.000000000 1.000000e+00
-#> sigma                1.706607296 3.322649e+00
-    endpoints(fit.1)
-#> $ff
-#>    T245_phenol      T245_sink phenol_anisole    phenol_sink 
-#>   6.227599e-01   3.772401e-01   1.000000e+00   3.773626e-10 
-#> 
-#> $distimes
-#>               DT50      DT90
-#> T245     15.982025  53.09114
-#> phenol    1.711229   5.68458
-#> anisole 103.784093 344.76329
-#> 
-    # formation fraction from phenol to anisol is practically 1. As we cannot
-    # fix formation fractions when using the ilr transformation, we can turn of
-    # the sink in the model generation
-    SFO_SFO_SFO_2 <- mkinmod(T245 = list(type = "SFO", to = "phenol"),
-      phenol = list(type = "SFO", to = "anisole", sink = FALSE),
-      anisole = list(type = "SFO"))
-#> Temporary DLL for differentials generated and loaded
-    fit.2 <- mkinfit(SFO_SFO_SFO_2, subset(mccall81_245T, soil == "Commerce"),
-      quiet = TRUE)
-#> Warning: Observations with value of zero were removed from the data
-    summary(fit.2)$bpar
-#>                      Estimate   se_notrans   t value       Pr(>t)        Lower
-#> T245_0           1.038550e+02 2.1623653066 48.028439 4.993108e-19 99.271020284
-#> k_T245           4.337042e-02 0.0018343666 23.643268 3.573556e-14  0.039650976
-#> k_phenol         4.050582e-01 0.1177237473  3.440752 1.679254e-03  0.218746587
-#> k_anisole        6.678742e-03 0.0006829745  9.778903 1.872894e-08  0.005377083
-#> f_T245_to_phenol 6.227599e-01 0.0342197875 18.198824 2.039411e-12  0.547975637
-#> sigma            2.514628e+00 0.3790944250  6.633250 2.875782e-06  1.710983655
-#>                         Upper
-#> T245_0           108.43904074
-#> k_T245             0.04743877
-#> k_phenol           0.75005585
-#> k_anisole          0.00829550
-#> f_T245_to_phenol   0.69212308
-#> sigma              3.31827222
-    endpoints(fit.1)
-#> $ff
-#>    T245_phenol      T245_sink phenol_anisole    phenol_sink 
-#>   6.227599e-01   3.772401e-01   1.000000e+00   3.773626e-10 
-#> 
-#> $distimes
-#>               DT50      DT90
-#> T245     15.982025  53.09114
-#> phenol    1.711229   5.68458
-#> anisole 103.784093 344.76329
-#> 
-    plot_sep(fit.2)
-
-  # }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/mean_degparms.html b/docs/dev/reference/mean_degparms.html
deleted file mode 100644
index a374d532..00000000
--- a/docs/dev/reference/mean_degparms.html
+++ /dev/null
@@ -1,182 +0,0 @@
-
-Calculate mean degradation parameters for an mmkin row object — mean_degparms • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Calculate mean degradation parameters for an mmkin row object
      
-    Source: R/mean_degparms.R
-    
-    
      
-
-    
      
-    
      Calculate mean degradation parameters for an mmkin row object
      
-    
      
-
-    
      
-    
      mean_degparms(
-  object,
-  random = FALSE,
-  test_log_parms = FALSE,
-  conf.level = 0.6,
-  default_log_parms = NA
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      An mmkin row object containing several fits of the same model to different datasets
      
-
-
-
      random
      
-
      Should a list with fixed and random effects be returned?
      
-
-
-
      test_log_parms
      
-
      If TRUE, log parameters are only considered in
-the mean calculations if their untransformed counterparts (most likely
-rate constants) pass the t-test for significant difference from zero.
      
-
-
-
      conf.level
      
-
      Possibility to adjust the required confidence level
-for parameter that are tested if requested by 'test_log_parms'.
      
-
-
-
      default_log_parms
      
-
      If set to a numeric value, this is used
-as a default value for the tested log parameters that failed the
-t-test.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      If random is FALSE (default), a named vector containing mean values
-of the fitted degradation model parameters. If random is TRUE, a list with
-fixed and random effects, in the format required by the start argument of
-nlme for the case of a single grouping variable ds.
      
-    
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
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+++ /dev/null
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-
-Fit nonlinear mixed-effects models built from one or more kinetic
-degradation models and one or more error models — mhmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Fit nonlinear mixed-effects models built from one or more kinetic
-degradation models and one or more error models
      
-    Source: R/mhmkin.R
-    
-    
      
-
-    
      
-    
      The name of the methods expresses that (multiple) hierarchichal
-(also known as multilevel) multicompartment kinetic models are
-fitted. Our kinetic models are nonlinear, so we can use various nonlinear
-mixed-effects model fitting functions.
      
-    
      
-
-    
      
-    
      mhmkin(objects, ...)
-
-# S3 method for mmkin
-mhmkin(objects, ...)
-
-# S3 method for list
-mhmkin(
-  objects,
-  backend = "saemix",
-  algorithm = "saem",
-  no_random_effect = NULL,
-  ...,
-  cores = if (Sys.info()["sysname"] == "Windows") 1 else parallel::detectCores(),
-  cluster = NULL
-)
-
-# S3 method for mhmkin
-[(x, i, j, ..., drop = FALSE)
-
-# S3 method for mhmkin
-print(x, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      objects
      
-
      A list of mmkin objects containing fits of the same
-degradation models to the same data, but using different error models.
-Alternatively, a single mmkin object containing fits of several
-degradation models to the same data
      
-
-
-
      ...
      
-
      Further arguments that will be passed to the nonlinear mixed-effects
-model fitting function.
      
-
-
-
      backend
      
-
      The backend to be used for fitting. Currently, only saemix is
-supported
      
-
-
-
      algorithm
      
-
      The algorithm to be used for fitting (currently not used)
      
-
-
-
      no_random_effect
      
-
      Default is NULL and will be passed to saem. If a
-character vector is supplied, it will be passed to all calls to saem,
-which will exclude random effects for all matching parameters. Alternatively,
-a list of character vectors or an object of class illparms.mhmkin can be
-specified. They have to have the same dimensions that the return object of
-the current call will have, i.e. the number of rows must match the number
-of degradation models in the mmkin object(s), and the number of columns must
-match the number of error models used in the mmkin object(s).
      
-
-
-
      cores
      
-
      The number of cores to be used for multicore processing. This
-is only used when the cluster argument is NULL. On Windows
-machines, cores > 1 is not supported, you need to use the cluster
-argument to use multiple logical processors. Per default, all cores detected
-by parallel::detectCores() are used, except on Windows where the default
-is 1.
      
-
-
-
      cluster
      
-
      A cluster as returned by makeCluster to be used for
-parallel execution.
      
-
-
-
      x
      
-
      An mhmkin object.
      
-
-
-
      i
      
-
      Row index selecting the fits for specific models
      
-
-
-
      j
      
-
      Column index selecting the fits to specific datasets
      
-
-
-
      drop
      
-
      If FALSE, the method always returns an mhmkin object, otherwise
-either a list of fit objects or a single fit object.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      A two-dimensional array of fit objects and/or try-errors that can
-be indexed using the degradation model names for the first index (row index)
-and the error model names for the second index (column index), with class
-attribute 'mhmkin'.
      
-
-
-
      An object inheriting from mhmkin.
      
-    
      
-    
      
-    
      See also
      
-    
      [.mhmkin for subsetting mhmkin objects
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      # \dontrun{
-# We start with separate evaluations of all the first six datasets with two
-# degradation models and two error models
-f_sep_const <- mmkin(c("SFO", "FOMC"), ds_fomc[1:6], cores = 2, quiet = TRUE)
-f_sep_tc <- update(f_sep_const, error_model = "tc")
-# The mhmkin function sets up hierarchical degradation models aka
-# nonlinear mixed-effects models for all four combinations, specifying
-# uncorrelated random effects for all degradation parameters
-f_saem_1 <- mhmkin(list(f_sep_const, f_sep_tc), cores = 2)
-status(f_saem_1)
-#>            error
-#> degradation const tc
-#>        SFO  OK    OK
-#>        FOMC OK    OK
-#> 
-#> OK: Fit terminated successfully
-# The 'illparms' function shows that in all hierarchical fits, at least
-# one random effect is ill-defined (the confidence interval for the
-# random effect expressed as standard deviation includes zero)
-illparms(f_saem_1)
-#>            error
-#> degradation const        tc                        
-#>        SFO  sd(parent_0) sd(parent_0)              
-#>        FOMC sd(log_beta) sd(parent_0), sd(log_beta)
-# Therefore we repeat the fits, excluding the ill-defined random effects
-f_saem_2 <- update(f_saem_1, no_random_effect = illparms(f_saem_1))
-status(f_saem_2)
-#>            error
-#> degradation const tc
-#>        SFO  OK    OK
-#>        FOMC OK    OK
-#> 
-#> OK: Fit terminated successfully
-illparms(f_saem_2)
-#>            error
-#> degradation const tc
-#>        SFO          
-#>        FOMC         
-# Model comparisons show that FOMC with two-component error is preferable,
-# and confirms our reduction of the default parameter model
-anova(f_saem_1)
-#> Data: 95 observations of 1 variable(s) grouped in 6 datasets
-#> 
-#>            npar    AIC    BIC     Lik
-#> SFO const     5 574.40 573.35 -282.20
-#> SFO tc        6 543.72 542.47 -265.86
-#> FOMC const    7 489.67 488.22 -237.84
-#> FOMC tc       8 406.11 404.44 -195.05
-anova(f_saem_2)
-#> Data: 95 observations of 1 variable(s) grouped in 6 datasets
-#> 
-#>            npar    AIC    BIC     Lik
-#> SFO const     4 572.22 571.39 -282.11
-#> SFO tc        5 541.63 540.59 -265.81
-#> FOMC const    6 487.38 486.13 -237.69
-#> FOMC tc       6 402.12 400.88 -195.06
-# The convergence plot for the selected model looks fine
-saemix::plot(f_saem_2[["FOMC", "tc"]]$so, plot.type = "convergence")
-
-# The plot of predictions versus data shows that we have a pretty data-rich
-# situation with homogeneous distribution of residuals, because we used the
-# same degradation model, error model and parameter distribution model that
-# was used in the data generation.
-plot(f_saem_2[["FOMC", "tc"]])
-
-# We can specify the same parameter model reductions manually
-no_ranef <- list("parent_0", "log_beta", "parent_0", c("parent_0", "log_beta"))
-dim(no_ranef) <- c(2, 2)
-f_saem_2m <- update(f_saem_1, no_random_effect = no_ranef)
-anova(f_saem_2m)
-#> Data: 95 observations of 1 variable(s) grouped in 6 datasets
-#> 
-#>            npar    AIC    BIC     Lik
-#> SFO const     4 572.22 571.39 -282.11
-#> SFO tc        5 541.63 540.59 -265.81
-#> FOMC const    6 487.38 486.13 -237.69
-#> FOMC tc       6 402.12 400.88 -195.06
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/mixed-1.png b/docs/dev/reference/mixed-1.png
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diff --git a/docs/dev/reference/mixed.html b/docs/dev/reference/mixed.html
deleted file mode 100644
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--- a/docs/dev/reference/mixed.html
+++ /dev/null
@@ -1,245 +0,0 @@
-
-Create a mixed effects model from an mmkin row object — mixed • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Create a mixed effects model from an mmkin row object
      
-    Source: R/mixed.mmkin.R
-    
-    
      
-
-    
      
-    
      Create a mixed effects model from an mmkin row object
      
-    
      
-
-    
      
-    
      mixed(object, ...)
-
-# S3 method for mmkin
-mixed(object, method = c("none"), ...)
-
-# S3 method for mixed.mmkin
-print(x, digits = max(3, getOption("digits") - 3), ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      An mmkin row object
      
-
-
-
      ...
      
-
      Currently not used
      
-
-
-
      method
      
-
      The method to be used
      
-
-
-
      x
      
-
      A mixed.mmkin object to print
      
-
-
-
      digits
      
-
      Number of digits to use for printing.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      An object of class 'mixed.mmkin' which has the observed data in a
-single dataframe which is convenient for plotting
      
-    
      
-
-    
      
-    
      Examples
      
-    
      sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-n_biphasic <- 8
-err_1 = list(const = 1, prop = 0.07)
-
-DFOP_SFO <- mkinmod(
-  parent = mkinsub("DFOP", "m1"),
-  m1 = mkinsub("SFO"),
-  quiet = TRUE)
-
-set.seed(123456)
-log_sd <- 0.3
-syn_biphasic_parms <- as.matrix(data.frame(
-  k1 = rlnorm(n_biphasic, log(0.05), log_sd),
-  k2 = rlnorm(n_biphasic, log(0.01), log_sd),
-  g = plogis(rnorm(n_biphasic, 0, log_sd)),
-  f_parent_to_m1 = plogis(rnorm(n_biphasic, 0, log_sd)),
-  k_m1 = rlnorm(n_biphasic, log(0.002), log_sd)))
-
-ds_biphasic_mean <- lapply(1:n_biphasic,
-  function(i) {
-    mkinpredict(DFOP_SFO, syn_biphasic_parms[i, ],
-      c(parent = 100, m1 = 0), sampling_times)
-  }
-)
-
-set.seed(123456L)
-ds_biphasic <- lapply(ds_biphasic_mean, function(ds) {
-  add_err(ds,
-    sdfunc = function(value) sqrt(err_1$const^2 + value^2 * err_1$prop^2),
-    n = 1, secondary = "m1")[[1]]
-})
-
-# \dontrun{
-f_mmkin <- mmkin(list("DFOP-SFO" = DFOP_SFO), ds_biphasic, error_model = "tc", quiet = TRUE)
-
-f_mixed <- mixed(f_mmkin)
-print(f_mixed)
-#> Kinetic model fitted by nonlinear regression to each dataset
-#> Structural model:
-#> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-#>            time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-#>            * parent
-#> d_m1/dt = + f_parent_to_m1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)
-#>            * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-#>            exp(-k2 * time))) * parent - k_m1 * m1
-#> 
-#> Data:
-#> 271 observations of 2 variable(s) grouped in 8 datasets
-#> 
-#> <mmkin> object
-#> Status of individual fits:
-#> 
-#>           dataset
-#> model      1  2  3  4  5  6  7  8 
-#>   DFOP-SFO OK OK OK OK OK OK OK OK
-#> 
-#> OK: No warnings
-#> 
-#> Mean fitted parameters:
-#>        parent_0        log_k_m1 f_parent_qlogis          log_k1          log_k2 
-#>      100.674757       -8.761916       -0.004347       -3.348812       -3.986853 
-#>        g_qlogis 
-#>       -0.087392 
-plot(f_mixed)
-
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/mkin_long_to_wide.html b/docs/dev/reference/mkin_long_to_wide.html
deleted file mode 100644
index 990506b5..00000000
--- a/docs/dev/reference/mkin_long_to_wide.html
+++ /dev/null
@@ -1,201 +0,0 @@
-
-Convert a dataframe from long to wide format — mkin_long_to_wide • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Convert a dataframe from long to wide format
      
-    Source: R/mkin_long_to_wide.R
-    
-    
      
-
-    
      
-    
      This function takes a dataframe in the long form, i.e. with a row for each
-observed value, and converts it into a dataframe with one independent
-variable and several dependent variables as columns.
      
-    
      
-
-    
      
-    
      mkin_long_to_wide(long_data, time = "time", outtime = "time")
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      long_data
      
-
      The dataframe must contain one variable called "time" with
-the time values specified by the time argument, one column called
-"name" with the grouping of the observed values, and finally one column of
-observed values called "value".
      
-
-
-
      time
      
-
      The name of the time variable in the long input data.
      
-
-
-
      outtime
      
-
      The name of the time variable in the wide output data.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      Dataframe in wide format.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-mkin_long_to_wide(FOCUS_2006_D)
-#>    time parent    m1
-#> 1     0  99.46  0.00
-#> 2     0 102.04  0.00
-#> 3     1  93.50  4.84
-#> 4     1  92.50  5.64
-#> 5     3  63.23 12.91
-#> 6     3  68.99 12.96
-#> 7     7  52.32 22.97
-#> 8     7  55.13 24.47
-#> 9    14  27.27 41.69
-#> 10   14  26.64 33.21
-#> 11   21  11.50 44.37
-#> 12   21  11.64 46.44
-#> 13   35   2.85 41.22
-#> 14   35   2.91 37.95
-#> 15   50   0.69 41.19
-#> 16   50   0.63 40.01
-#> 17   75   0.05 40.09
-#> 18   75   0.06 33.85
-#> 19  100     NA 31.04
-#> 20  100     NA 33.13
-#> 21  120     NA 25.15
-#> 22  120     NA 33.31
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/mkin_wide_to_long.html b/docs/dev/reference/mkin_wide_to_long.html
deleted file mode 100644
index a324d3b8..00000000
--- a/docs/dev/reference/mkin_wide_to_long.html
+++ /dev/null
@@ -1,181 +0,0 @@
-
-Convert a dataframe with observations over time into long format — mkin_wide_to_long • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Convert a dataframe with observations over time into long format
      
-    Source: R/mkin_wide_to_long.R
-    
-    
      
-
-    
      
-    
      This function simply takes a dataframe with one independent variable and
-several dependent variable and converts it into the long form as required by
-mkinfit.
      
-    
      
-
-    
      
-    
      mkin_wide_to_long(wide_data, time = "t")
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      wide_data
      
-
      The dataframe must contain one variable with the time
-values specified by the time argument and usually more than one
-column of observed values.
      
-
-
-
      time
      
-
      The name of the time variable.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      Dataframe in long format as needed for mkinfit.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-wide <- data.frame(t = c(1,2,3), x = c(1,4,7), y = c(3,4,5))
-mkin_wide_to_long(wide)
-#>   name time value
-#> 1    x    1     1
-#> 2    x    2     4
-#> 3    x    3     7
-#> 4    y    1     3
-#> 5    y    2     4
-#> 6    y    3     5
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/mkinds.html b/docs/dev/reference/mkinds.html
deleted file mode 100644
index 6219766e..00000000
--- a/docs/dev/reference/mkinds.html
+++ /dev/null
@@ -1,262 +0,0 @@
-
-A dataset class for mkin — mkinds • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      A dataset class for mkin
      
-    Source: R/mkinds.R
-    
-    
      
-
-    
      
-    
      At the moment this dataset class is hardly used in mkin. For example,
-mkinfit does not take mkinds datasets as argument, but works with dataframes
-such as the on contained in the data field of mkinds objects. Some datasets
-provided by this package come as mkinds objects nevertheless.
      
-    
      
-
-    
      
-    
      # S3 method for mkinds
-print(x, data = FALSE, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      x
      
-
      An mkinds object.
      
-
-
-
      data
      
-
      Should the data be printed?
      
-
-
-
      ...
      
-
      Not used.
      
-
-
      
-    
      
-    
      Public fields
      
-    
      title
      
-
      A full title for the dataset
      
-
-
-
      sampling_times
      
-
      The sampling times
      
-
-
-
      time_unit
      
-
      The time unit
      
-
-
-
      observed
      
-
      Names of the observed variables
      
-
-
-
      unit
      
-
      The unit of the observations
      
-
-
-
      replicates
      
-
      The maximum number of replicates per sampling time
      
-
-
-
      data
      
-
      A data frame with at least the columns name, time
-and value in order to be compatible with mkinfit
      
-
-
-
      
-    
      
-    
      
-    
      Methods
      
-    
-
      
-
      Public methods
      
-
-
      
-
      Method new()
      
-
      Create a new mkinds object
      
-
      Usage
      
-
      mkinds$new(title = "", data, time_unit = NA, unit = NA)
      
-
      
-
-
      
-
      Arguments
      
-
      title
      
-
      The dataset title
      
-
-
-
      data
      
-
      The data
      
-
-
-
      time_unit
      
-
      The time unit
      
-
-
-
      unit
      
-
      The unit of the observations
      
-
-
-
      
-
      
-
-
      
-
      Method clone()
      
-
      The objects of this class are cloneable with this method.
      
-
      Usage
      
-
      mkinds$clone(deep = FALSE)
      
-
      
-
-
      
-
      Arguments
      
-
      deep
      
-
      Whether to make a deep clone.
      
-
-
-
      
-
      
-
-
      
-
-    
      
-
-    
      
-    
      Examples
      
-    
      
-mds <- mkinds$new("FOCUS A", FOCUS_2006_A)
-print(mds)
-#> <mkinds> with $title:  FOCUS A 
-#> Observed compounds $observed:  parent 
-#> Sampling times $sampling_times:
-#> 0, 3, 7, 14, 30, 62, 90, 118 
-#> With a maximum of  1  replicates
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/mkindsg.html b/docs/dev/reference/mkindsg.html
deleted file mode 100644
index 6e221a23..00000000
--- a/docs/dev/reference/mkindsg.html
+++ /dev/null
@@ -1,450 +0,0 @@
-
-A class for dataset groups for mkin — mkindsg • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      A class for dataset groups for mkin
      
-    Source: R/mkinds.R
-    
-    
      
-
-    
      
-    
      A container for working with datasets that share at least one compound,
-so that combined evaluations are desirable.
      
-
      Time normalisation factors are initialised with a value of 1 for each
-dataset if no data are supplied.
      
-    
      
-
-    
      
-    
      # S3 method for mkindsg
-print(x, data = FALSE, verbose = data, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      x
      
-
      An mkindsg object.
      
-
-
-
      data
      
-
      Should the mkinds objects be printed with their data?
      
-
-
-
      verbose
      
-
      Should the mkinds objects be printed?
      
-
-
-
      ...
      
-
      Not used.
      
-
-
      
-    
      
-    
      Public fields
      
-    
      title
      
-
      A title for the dataset group
      
-
-
-
      ds
      
-
      A list of mkinds objects
      
-
-
-
      observed_n
      
-
      Occurrence counts of compounds in datasets
      
-
-
-
      f_time_norm
      
-
      Time normalisation factors
      
-
-
-
      meta
      
-
      A data frame with a row for each dataset,
-containing additional information in the form
-of categorical data (factors) or numerical data
-(e.g. temperature, moisture,
-or covariates like soil pH).
      
-
-
-
      
-    
      
-    
      
-    
      Methods
      
-    
-
      
-
      Public methods
      
-
-
      
-
      Method new()
      
-
      Create a new mkindsg object
      
-
      Usage
      
-
      mkindsg$new(title = "", ds, f_time_norm = rep(1, length(ds)), meta)
      
-
      
-
-
      
-
      Arguments
      
-
      title
      
-
      The title
      
-
-
-
      ds
      
-
      A list of mkinds objects
      
-
-
-
      f_time_norm
      
-
      Time normalisation factors
      
-
-
-
      meta
      
-
      The meta data
      
-
-
-
      
-
      
-
-
      
-
      Method clone()
      
-
      The objects of this class are cloneable with this method.
      
-
      Usage
      
-
      mkindsg$clone(deep = FALSE)
      
-
      
-
-
      
-
      Arguments
      
-
      deep
      
-
      Whether to make a deep clone.
      
-
-
-
      
-
      
-
-
      
-
-    
      
-
-    
      
-    
      Examples
      
-    
      
-mdsg <- mkindsg$new("Experimental X", experimental_data_for_UBA_2019[6:10])
-print(mdsg)
-#> <mkindsg> holding 5 mkinds objects
-#> Title $title:  Experimental X 
-#> Occurrence of observed compounds $observed_n:
-#> parent     A1 
-#>      5      5 
-print(mdsg, verbose = TRUE)
-#> <mkindsg> holding 5 mkinds objects
-#> Title $title:  Experimental X 
-#> Occurrence of observed compounds $observed_n:
-#> parent     A1 
-#>      5      5 
-#> 
-#> Datasets $ds:
-#> <mkinds> with $title:  Soil 6 
-#> Observed compounds $observed:  parent, A1 
-#> Sampling times $sampling_times:
-#> 0, 3, 6, 10, 20, 34, 55, 90, 112, 132 
-#> With a maximum of  2  replicates
-#> Time unit:  days 
-#> Observation unit:  \%AR 
-#> 
-#> <mkinds> with $title:  Soil 7 
-#> Observed compounds $observed:  parent, A1 
-#> Sampling times $sampling_times:
-#> 0, 3, 7, 14, 30, 60, 90, 120, 180 
-#> With a maximum of  2  replicates
-#> Time unit:  days 
-#> Observation unit:  \%AR 
-#> 
-#> <mkinds> with $title:  Soil 8 
-#> Observed compounds $observed:  parent, A1 
-#> Sampling times $sampling_times:
-#> 0, 1, 3, 8, 14, 27, 48, 70 
-#> With a maximum of  2  replicates
-#> Time unit:  days 
-#> Observation unit:  \%AR 
-#> 
-#> <mkinds> with $title:  Soil 9 
-#> Observed compounds $observed:  parent, A1 
-#> Sampling times $sampling_times:
-#> 0, 1, 3, 8, 14, 27, 48, 70, 91, 120 
-#> With a maximum of  2  replicates
-#> Time unit:  days 
-#> Observation unit:  \%AR 
-#> 
-#> <mkinds> with $title:  Soil 10 
-#> Observed compounds $observed:  parent, A1 
-#> Sampling times $sampling_times:
-#> 0, 8, 14, 21, 41, 63, 91, 120 
-#> With a maximum of  2  replicates
-#> Time unit:  days 
-#> Observation unit:  \%AR 
-print(mdsg, verbose = TRUE, data = TRUE)
-#> <mkindsg> holding 5 mkinds objects
-#> Title $title:  Experimental X 
-#> Occurrence of observed compounds $observed_n:
-#> parent     A1 
-#>      5      5 
-#> 
-#> Datasets $ds:
-#> <mkinds> with $title:  Soil 6 
-#> Observed compounds $observed:  parent, A1 
-#> Sampling times $sampling_times:
-#> 0, 3, 6, 10, 20, 34, 55, 90, 112, 132 
-#> With a maximum of  2  replicates
-#> Time unit:  days 
-#> Observation unit:  \%AR 
-#>    time parent   A1
-#> 1     0   97.2   NA
-#> 2     0   96.4   NA
-#> 3     3   71.1  4.3
-#> 4     3   69.2  4.6
-#> 5     6   58.1  7.0
-#> 6     6   56.6  7.2
-#> 7    10   44.4  8.2
-#> 8    10   43.4  8.0
-#> 9    20   33.3 11.0
-#> 10   20   29.2 13.7
-#> 11   34   17.6 11.5
-#> 12   34   18.0 12.7
-#> 13   55   10.5 14.9
-#> 14   55    9.3 14.5
-#> 15   90    4.5 12.1
-#> 16   90    4.7 12.3
-#> 17  112    3.0  9.9
-#> 18  112    3.4 10.2
-#> 19  132    2.3  8.8
-#> 20  132    2.7  7.8
-#> 
-#> <mkinds> with $title:  Soil 7 
-#> Observed compounds $observed:  parent, A1 
-#> Sampling times $sampling_times:
-#> 0, 3, 7, 14, 30, 60, 90, 120, 180 
-#> With a maximum of  2  replicates
-#> Time unit:  days 
-#> Observation unit:  \%AR 
-#>    time parent   A1
-#> 1     0   93.6   NA
-#> 2     0   92.3   NA
-#> 3     3   87.0  3.9
-#> 4     3   82.2  3.1
-#> 5     7   74.0  6.9
-#> 6     7   73.9  6.6
-#> 7    14   64.2 10.4
-#> 8    14   69.5  8.3
-#> 9    30   54.0 14.4
-#> 10   30   54.6 13.7
-#> 11   60   41.1 22.1
-#> 12   60   38.4 22.3
-#> 13   90   32.5 27.5
-#> 14   90   35.5 25.4
-#> 15  120   28.1 28.0
-#> 16  120   29.0 26.6
-#> 17  180   26.5 25.8
-#> 18  180   27.6 25.3
-#> 
-#> <mkinds> with $title:  Soil 8 
-#> Observed compounds $observed:  parent, A1 
-#> Sampling times $sampling_times:
-#> 0, 1, 3, 8, 14, 27, 48, 70 
-#> With a maximum of  2  replicates
-#> Time unit:  days 
-#> Observation unit:  \%AR 
-#>    time parent   A1
-#> 1     0   91.9   NA
-#> 2     0   90.8   NA
-#> 3     1   64.9  9.6
-#> 4     1   66.2  7.7
-#> 5     3   43.5 15.0
-#> 6     3   44.1 15.1
-#> 7     8   18.3 21.2
-#> 8     8   18.1 21.1
-#> 9    14   10.2 19.7
-#> 10   14   10.8 18.9
-#> 11   27    4.9 17.5
-#> 12   27    3.3 15.9
-#> 13   48    1.6  9.5
-#> 14   48    1.5  9.8
-#> 15   70    1.1  6.2
-#> 16   70    0.9  6.1
-#> 
-#> <mkinds> with $title:  Soil 9 
-#> Observed compounds $observed:  parent, A1 
-#> Sampling times $sampling_times:
-#> 0, 1, 3, 8, 14, 27, 48, 70, 91, 120 
-#> With a maximum of  2  replicates
-#> Time unit:  days 
-#> Observation unit:  \%AR 
-#>    time parent   A1
-#> 1     0   99.8   NA
-#> 2     0   98.3   NA
-#> 3     1   77.1  4.2
-#> 4     1   77.2  3.9
-#> 5     3   59.0  7.4
-#> 6     3   58.1  7.9
-#> 7     8   27.4 14.5
-#> 8     8   29.2 13.7
-#> 9    14   19.1 14.2
-#> 10   14   29.6 12.2
-#> 11   27   10.1 13.7
-#> 12   27   18.2 13.2
-#> 13   48    4.5 13.6
-#> 14   48    9.1 15.4
-#> 15   70    2.3 10.4
-#> 16   70    2.9 11.6
-#> 17   91    2.0 10.0
-#> 18   91    1.8  9.5
-#> 19  120    2.0  9.1
-#> 20  120    2.2  9.0
-#> 
-#> <mkinds> with $title:  Soil 10 
-#> Observed compounds $observed:  parent, A1 
-#> Sampling times $sampling_times:
-#> 0, 8, 14, 21, 41, 63, 91, 120 
-#> With a maximum of  2  replicates
-#> Time unit:  days 
-#> Observation unit:  \%AR 
-#>    time parent   A1
-#> 1     0   96.1   NA
-#> 2     0   94.3   NA
-#> 3     8   73.9  3.3
-#> 4     8   73.9  3.4
-#> 5    14   69.4  3.9
-#> 6    14   73.1  2.9
-#> 7    21   65.6  6.4
-#> 8    21   65.3  7.2
-#> 9    41   55.9  9.1
-#> 10   41   54.4  8.5
-#> 11   63   47.0 11.7
-#> 12   63   49.3 12.0
-#> 13   91   44.7 13.3
-#> 14   91   46.7 13.2
-#> 15  120   42.1 14.3
-#> 16  120   41.3 12.1
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/mkinerrmin.html b/docs/dev/reference/mkinerrmin.html
deleted file mode 100644
index 3a8b9610..00000000
--- a/docs/dev/reference/mkinerrmin.html
+++ /dev/null
@@ -1,210 +0,0 @@
-
-Calculate the minimum error to assume in order to pass the variance test — mkinerrmin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Calculate the minimum error to assume in order to pass the variance test
      
-    Source: R/mkinerrmin.R
-    
-    
      
-
-    
      
-    
      This function finds the smallest relative error still resulting in passing
-the chi-squared test as defined in the FOCUS kinetics report from 2006.
      
-    
      
-
-    
      
-    
      mkinerrmin(fit, alpha = 0.05)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      fit
      
-
      an object of class mkinfit.
      
-
-
-
      alpha
      
-
      The confidence level chosen for the chi-squared test.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      A dataframe with the following components:
      
-
      err.min
      
-
      The
-relative error, expressed as a fraction.
      
- 
      n.optim
      
-
      The number of
-optimised parameters attributed to the data series.
      
- 
      df
      
-
      The number of
-remaining degrees of freedom for the chi2 error level calculations.  Note
-that mean values are used for the chi2 statistic and therefore every time
-point with observed values in the series only counts one time.
      
-
      The
-dataframe has one row for the total dataset and one further row for each
-observed state variable in the model.
      
-    
      
-    
      
-    
      Details
      
-    
      This function is used internally by summary.mkinfit.
      
-    
      
-    
      
-    
      References
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in EU
-Registration” Report of the FOCUS Work Group on Degradation Kinetics, EC
-Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-SFO_SFO = mkinmod(parent = mkinsub("SFO", to = "m1"),
-                  m1 = mkinsub("SFO"),
-                  use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-
-fit_FOCUS_D = mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
-#> Warning: Observations with value of zero were removed from the data
-round(mkinerrmin(fit_FOCUS_D), 4)
-#>          err.min n.optim df
-#> All data  0.0640       4 15
-#> parent    0.0646       2  7
-#> m1        0.0469       2  8
-# \dontrun{
-  fit_FOCUS_E = mkinfit(SFO_SFO, FOCUS_2006_E, quiet = TRUE)
-  round(mkinerrmin(fit_FOCUS_E), 4)
-#>          err.min n.optim df
-#> All data  0.1544       4 13
-#> parent    0.1659       2  7
-#> m1        0.1095       2  6
-# }
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/mkinerrplot-1.png b/docs/dev/reference/mkinerrplot-1.png
deleted file mode 100644
index 078614fc..00000000
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diff --git a/docs/dev/reference/mkinerrplot.html b/docs/dev/reference/mkinerrplot.html
deleted file mode 100644
index bc9b828a..00000000
--- a/docs/dev/reference/mkinerrplot.html
+++ /dev/null
@@ -1,245 +0,0 @@
-
-Function to plot squared residuals and the error model for an mkin object — mkinerrplot • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Function to plot squared residuals and the error model for an mkin object
      
-    Source: R/mkinerrplot.R
-    
-    
      
-
-    
      
-    
      This function plots the squared residuals for the specified subset of the
-observed variables from an mkinfit object. In addition, one or more dashed
-line(s) show the fitted error model.  A combined plot of the fitted model
-and this error model plot can be obtained with plot.mkinfit
-using the argument show_errplot = TRUE.
      
-    
      
-
-    
      
-    
      mkinerrplot(
-  object,
-  obs_vars = names(object$mkinmod$map),
-  xlim = c(0, 1.1 * max(object$data$predicted)),
-  xlab = "Predicted",
-  ylab = "Squared residual",
-  maxy = "auto",
-  legend = TRUE,
-  lpos = "topright",
-  col_obs = "auto",
-  pch_obs = "auto",
-  frame = TRUE,
-  ...
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      A fit represented in an mkinfit object.
      
-
-
-
      obs_vars
      
-
      A character vector of names of the observed variables for
-which residuals should be plotted. Defaults to all observed variables in
-the model
      
-
-
-
      xlim
      
-
      plot range in x direction.
      
-
-
-
      xlab
      
-
      Label for the x axis.
      
-
-
-
      ylab
      
-
      Label for the y axis.
      
-
-
-
      maxy
      
-
      Maximum value of the residuals. This is used for the scaling of
-the y axis and defaults to "auto".
      
-
-
-
      legend
      
-
      Should a legend be plotted?
      
-
-
-
      lpos
      
-
      Where should the legend be placed? Default is "topright". Will
-be passed on to legend.
      
-
-
-
      col_obs
      
-
      Colors for the observed variables.
      
-
-
-
      pch_obs
      
-
      Symbols to be used for the observed variables.
      
-
-
-
      frame
      
-
      Should a frame be drawn around the plots?
      
-
-
-
      ...
      
-
      further arguments passed to plot.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      Nothing is returned by this function, as it is called for its side
-effect, namely to produce a plot.
      
-    
      
-    
      
-    
      See also
      
-    
      mkinplot, for a way to plot the data and the fitted
-lines of the mkinfit object.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-# \dontrun{
-model <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
-#> Temporary DLL for differentials generated and loaded
-fit <- mkinfit(model, FOCUS_2006_D, error_model = "tc", quiet = TRUE)
-#> Warning: Observations with value of zero were removed from the data
-mkinerrplot(fit)
-
-# }
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
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-
diff --git a/docs/dev/reference/mkinfit-1.png b/docs/dev/reference/mkinfit-1.png
deleted file mode 100644
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diff --git a/docs/dev/reference/mkinfit.html b/docs/dev/reference/mkinfit.html
deleted file mode 100644
index 237d903e..00000000
--- a/docs/dev/reference/mkinfit.html
+++ /dev/null
@@ -1,719 +0,0 @@
-
-Fit a kinetic model to data with one or more state variables — mkinfit • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Fit a kinetic model to data with one or more state variables
      
-    Source: R/mkinfit.R
-    
-    
      
-
-    
      
-    
      This function maximises the likelihood of the observed data using the Port
-algorithm stats::nlminb(), and the specified initial or fixed
-parameters and starting values.  In each step of the optimisation, the
-kinetic model is solved using the function mkinpredict(), except
-if an analytical solution is implemented, in which case the model is solved
-using the degradation function in the mkinmod object. The
-parameters of the selected error model are fitted simultaneously with the
-degradation model parameters, as both of them are arguments of the
-likelihood function.
      
-    
      
-
-    
      
-    
      mkinfit(
-  mkinmod,
-  observed,
-  parms.ini = "auto",
-  state.ini = "auto",
-  err.ini = "auto",
-  fixed_parms = NULL,
-  fixed_initials = names(mkinmod$diffs)[-1],
-  from_max_mean = FALSE,
-  solution_type = c("auto", "analytical", "eigen", "deSolve"),
-  method.ode = "lsoda",
-  use_compiled = "auto",
-  control = list(eval.max = 300, iter.max = 200),
-  transform_rates = TRUE,
-  transform_fractions = TRUE,
-  quiet = FALSE,
-  atol = 1e-08,
-  rtol = 1e-10,
-  error_model = c("const", "obs", "tc"),
-  error_model_algorithm = c("auto", "d_3", "direct", "twostep", "threestep", "fourstep",
-    "IRLS", "OLS"),
-  reweight.tol = 1e-08,
-  reweight.max.iter = 10,
-  trace_parms = FALSE,
-  test_residuals = FALSE,
-  ...
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      mkinmod
      
-
      A list of class mkinmod, containing the kinetic
-model to be fitted to the data, or one of the shorthand names ("SFO",
-"FOMC", "DFOP", "HS", "SFORB", "IORE"). If a shorthand name is given, a
-parent only degradation model is generated for the variable with the
-highest value in observed.
      
-
-
-
      observed
      
-
      A dataframe with the observed data.  The first column called
-"name" must contain the name of the observed variable for each data point.
-The second column must contain the times of observation, named "time".
-The third column must be named "value" and contain the observed values.
-Zero values in the "value" column will be removed, with a warning, in
-order to avoid problems with fitting the two-component error model. This
-is not expected to be a problem, because in general, values of zero are
-not observed in degradation data, because there is a lower limit of
-detection.
      
-
-
-
      parms.ini
      
-
      A named vector of initial values for the parameters,
-including parameters to be optimised and potentially also fixed parameters
-as indicated by fixed_parms.  If set to "auto", initial values for
-rate constants are set to default values.  Using parameter names that are
-not in the model gives an error.
      
-
      It is possible to only specify a subset of the parameters that the model
-needs. You can use the parameter lists "bparms.ode" from a previously
-fitted model, which contains the differential equation parameters from
-this model.  This works nicely if the models are nested. An example is
-given below.
      
-
-
-
      state.ini
      
-
      A named vector of initial values for the state variables of
-the model. In case the observed variables are represented by more than one
-model variable, the names will differ from the names of the observed
-variables (see map component of mkinmod). The default
-is to set the initial value of the first model variable to the mean of the
-time zero values for the variable with the maximum observed value, and all
-others to 0.  If this variable has no time zero observations, its initial
-value is set to 100.
      
-
-
-
      err.ini
      
-
      A named vector of initial values for the error model
-parameters to be optimised.  If set to "auto", initial values are set to
-default values.  Otherwise, inital values for all error model parameters
-must be given.
      
-
-
-
      fixed_parms
      
-
      The names of parameters that should not be optimised but
-rather kept at the values specified in parms.ini. Alternatively,
-a named numeric vector of parameters to be fixed, regardless of the values
-in parms.ini.
      
-
-
-
      fixed_initials
      
-
      The names of model variables for which the initial
-state at time 0 should be excluded from the optimisation. Defaults to all
-state variables except for the first one.
      
-
-
-
      from_max_mean
      
-
      If this is set to TRUE, and the model has only one
-observed variable, then data before the time of the maximum observed value
-(after averaging for each sampling time) are discarded, and this time is
-subtracted from all remaining time values, so the time of the maximum
-observed mean value is the new time zero.
      
-
-
-
      solution_type
      
-
      If set to "eigen", the solution of the system of
-differential equations is based on the spectral decomposition of the
-coefficient matrix in cases that this is possible. If set to "deSolve", a
-numerical ode solver from package deSolve is used. If
-set to "analytical", an analytical solution of the model is used. This is
-only implemented for relatively simple degradation models.  The default is
-"auto", which uses "analytical" if possible, otherwise "deSolve" if a
-compiler is present, and "eigen" if no compiler is present and the model
-can be expressed using eigenvalues and eigenvectors.
      
-
-
-
      method.ode
      
-
      The solution method passed via mkinpredict()
-to deSolve::ode() in case the solution type is "deSolve". The default
-"lsoda" is performant, but sometimes fails to converge.
      
-
-
-
      use_compiled
      
-
      If set to FALSE, no compiled version of the
-mkinmod model is used in the calls to mkinpredict() even if a compiled
-version is present.
      
-
-
-
      control
      
-
      A list of control arguments passed to stats::nlminb().
      
-
-
-
      transform_rates
      
-
      Boolean specifying if kinetic rate constants should
-be transformed in the model specification used in the fitting for better
-compliance with the assumption of normal distribution of the estimator. If
-TRUE, also alpha and beta parameters of the FOMC model are
-log-transformed, as well as k1 and k2 rate constants for the DFOP and HS
-models and the break point tb of the HS model.  If FALSE, zero is used as
-a lower bound for the rates in the optimisation.
      
-
-
-
      transform_fractions
      
-
      Boolean specifying if formation fractions
-should be transformed in the model specification used in the fitting for
-better compliance with the assumption of normal distribution of the
-estimator. The default (TRUE) is to do transformations. If TRUE,
-the g parameter of the DFOP model is also transformed. Transformations
-are described in transform_odeparms.
      
-
-
-
      quiet
      
-
      Suppress printing out the current value of the negative
-log-likelihood after each improvement?
      
-
-
-
      atol
      
-
      Absolute error tolerance, passed to deSolve::ode(). Default
-is 1e-8, which is lower than the default in the deSolve::lsoda()
-function which is used per default.
      
-
-
-
      rtol
      
-
      Absolute error tolerance, passed to deSolve::ode(). Default
-is 1e-10, much lower than in deSolve::lsoda().
      
-
-
-
      error_model
      
-
      If the error model is "const", a constant standard
-deviation is assumed.
      
-
      If the error model is "obs", each observed variable is assumed to have its
-own variance.
      
-
      If the error model is "tc" (two-component error model), a two component
-error model similar to the one described by Rocke and Lorenzato (1995) is
-used for setting up the likelihood function.  Note that this model
-deviates from the model by Rocke and Lorenzato, as their model implies
-that the errors follow a lognormal distribution for large values, not a
-normal distribution as assumed by this method.
      
-
-
-
      error_model_algorithm
      
-
      If "auto", the selected algorithm depends on
-the error model.  If the error model is "const", unweighted nonlinear
-least squares fitting ("OLS") is selected. If the error model is "obs", or
-"tc", the "d_3" algorithm is selected.
      
-
      The algorithm "d_3" will directly minimize the negative log-likelihood
-and independently also use the three step algorithm described below.
-The fit with the higher likelihood is returned.
      
-
      The algorithm "direct" will directly minimize the negative log-likelihood.
      
-
      The algorithm "twostep" will minimize the negative log-likelihood after an
-initial unweighted least squares optimisation step.
      
-
      The algorithm "threestep" starts with unweighted least squares, then
-optimizes only the error model using the degradation model parameters
-found, and then minimizes the negative log-likelihood with free
-degradation and error model parameters.
      
-
      The algorithm "fourstep" starts with unweighted least squares, then
-optimizes only the error model using the degradation model parameters
-found, then optimizes the degradation model again with fixed error model
-parameters, and finally minimizes the negative log-likelihood with free
-degradation and error model parameters.
      
-
      The algorithm "IRLS" (Iteratively Reweighted Least Squares) starts with
-unweighted least squares, and then iterates optimization of the error
-model parameters and subsequent optimization of the degradation model
-using those error model parameters, until the error model parameters
-converge.
      
-
-
-
      reweight.tol
      
-
      Tolerance for the convergence criterion calculated from
-the error model parameters in IRLS fits.
      
-
-
-
      reweight.max.iter
      
-
      Maximum number of iterations in IRLS fits.
      
-
-
-
      trace_parms
      
-
      Should a trace of the parameter values be listed?
      
-
-
-
      test_residuals
      
-
      Should the residuals be tested for normal distribution?
      
-
-
-
      ...
      
-
      Further arguments that will be passed on to
-deSolve::ode().
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      A list with "mkinfit" in the class attribute.
      
-    
      
-    
      
-    
      Details
      
-    
      Per default, parameters in the kinetic models are internally transformed in
-order to better satisfy the assumption of a normal distribution of their
-estimators.
      
-    
      
-    
      
-    
      Note
      
-    
      When using the "IORE" submodel for metabolites, fitting with
-"transform_rates = TRUE" (the default) often leads to failures of the
-numerical ODE solver. In this situation it may help to switch off the
-internal rate transformation.
      
-    
      
-    
      
-    
      References
      
-    
      Rocke DM and Lorenzato S (1995) A two-component model
-for measurement error in analytical chemistry. Technometrics 37(2), 176-184.
      
-
      Ranke J and Meinecke S (2019) Error Models for the Kinetic Evaluation of Chemical
-Degradation Data. Environments 6(12) 124
-doi:10.3390/environments6120124
-.
      
-    
      
-    
      
-    
      See also
      
-    
      summary.mkinfit, plot.mkinfit, parms and lrtest.
      
-
      Comparisons of models fitted to the same data can be made using
-AIC by virtue of the method logLik.mkinfit.
      
-
      Fitting of several models to several datasets in a single call to
-mmkin.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-# Use shorthand notation for parent only degradation
-fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
-summary(fit)
-#> mkin version used for fitting:    1.2.3 
-#> R version used for fitting:       4.2.3 
-#> Date of fit:     Sun Apr 16 08:30:40 2023 
-#> Date of summary: Sun Apr 16 08:30:40 2023 
-#> 
-#> Equations:
-#> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
-#> 
-#> Model predictions using solution type analytical 
-#> 
-#> Fitted using 222 model solutions performed in 0.014 s
-#> 
-#> Error model: Constant variance 
-#> 
-#> Error model algorithm: OLS 
-#> 
-#> Starting values for parameters to be optimised:
-#>          value   type
-#> parent_0  85.1  state
-#> alpha      1.0 deparm
-#> beta      10.0 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>               value lower upper
-#> parent_0  85.100000  -Inf   Inf
-#> log_alpha  0.000000  -Inf   Inf
-#> log_beta   2.302585  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#> None
-#> 
-#> Results:
-#> 
-#>        AIC      BIC    logLik
-#>   44.68652 45.47542 -18.34326
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>           Estimate Std. Error    Lower   Upper
-#> parent_0  85.87000     1.8070 81.23000 90.5200
-#> log_alpha  0.05192     0.1353 -0.29580  0.3996
-#> log_beta   0.65100     0.2287  0.06315  1.2390
-#> sigma      1.85700     0.4378  0.73200  2.9830
-#> 
-#> Parameter correlation:
-#>             parent_0  log_alpha   log_beta     sigma
-#> parent_0   1.000e+00 -1.565e-01 -3.142e-01 4.772e-08
-#> log_alpha -1.565e-01  1.000e+00  9.564e-01 1.005e-07
-#> log_beta  -3.142e-01  9.564e-01  1.000e+00 8.541e-08
-#> sigma      4.772e-08  1.005e-07  8.541e-08 1.000e+00
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>          Estimate t value    Pr(>t)   Lower  Upper
-#> parent_0   85.870  47.530 3.893e-08 81.2300 90.520
-#> alpha       1.053   7.393 3.562e-04  0.7439  1.491
-#> beta        1.917   4.373 3.601e-03  1.0650  3.451
-#> sigma       1.857   4.243 4.074e-03  0.7320  2.983
-#> 
-#> FOCUS Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   6.657       3  6
-#> parent     6.657       3  6
-#> 
-#> Estimated disappearance times:
-#>         DT50  DT90 DT50back
-#> parent 1.785 15.15     4.56
-#> 
-#> Data:
-#>  time variable observed predicted residual
-#>     0   parent     85.1    85.875  -0.7749
-#>     1   parent     57.9    55.191   2.7091
-#>     3   parent     29.9    31.845  -1.9452
-#>     7   parent     14.6    17.012  -2.4124
-#>    14   parent      9.7     9.241   0.4590
-#>    28   parent      6.6     4.754   1.8460
-#>    63   parent      4.0     2.102   1.8977
-#>    91   parent      3.9     1.441   2.4590
-#>   119   parent      0.6     1.092  -0.4919
-
-# One parent compound, one metabolite, both single first order.
-# We remove zero values from FOCUS dataset D in order to avoid warnings
-FOCUS_D <- subset(FOCUS_2006_D, value != 0)
-# Use mkinsub for convenience in model formulation. Pathway to sink included per default.
-SFO_SFO <- mkinmod(
-  parent = mkinsub("SFO", "m1"),
-  m1 = mkinsub("SFO"))
-#> Temporary DLL for differentials generated and loaded
-
-# Fit the model quietly to the FOCUS example dataset D using defaults
-fit <- mkinfit(SFO_SFO, FOCUS_D, quiet = TRUE)
-plot_sep(fit)
-
-# As lower parent values appear to have lower variance, we try an alternative error model
-fit.tc <- mkinfit(SFO_SFO, FOCUS_D, quiet = TRUE, error_model = "tc")
-# This avoids the warning, and the likelihood ratio test confirms it is preferable
-lrtest(fit.tc, fit)
-#> Likelihood ratio test
-#> 
-#> Model 1: SFO_SFO with error model tc and fixed parameter(s) m1_0
-#> Model 2: SFO_SFO with error model const and fixed parameter(s) m1_0
-#>   #Df  LogLik Df  Chisq Pr(>Chisq)    
-#> 1   6 -64.983                         
-#> 2   5 -97.224 -1 64.483  9.737e-16 ***
-#> ---
-#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
-# We can also allow for different variances of parent and metabolite as error model
-fit.obs <- mkinfit(SFO_SFO, FOCUS_D, quiet = TRUE, error_model = "obs")
-# The two-component error model has significantly higher likelihood
-lrtest(fit.obs, fit.tc)
-#> Likelihood ratio test
-#> 
-#> Model 1: SFO_SFO with error model tc and fixed parameter(s) m1_0
-#> Model 2: SFO_SFO with error model obs and fixed parameter(s) m1_0
-#>   #Df  LogLik Df  Chisq Pr(>Chisq)    
-#> 1   6 -64.983                         
-#> 2   6 -96.936  0 63.907  < 2.2e-16 ***
-#> ---
-#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
-parms(fit.tc)
-#>       parent_0       k_parent           k_m1 f_parent_to_m1      sigma_low 
-#>   1.007343e+02   1.005562e-01   5.166712e-03   5.083933e-01   3.049883e-03 
-#>       rsd_high 
-#>   7.928118e-02 
-endpoints(fit.tc)
-#> $ff
-#>   parent_m1 parent_sink 
-#>   0.5083933   0.4916067 
-#> 
-#> $distimes
-#>             DT50      DT90
-#> parent   6.89313  22.89848
-#> m1     134.15634 445.65772
-#> 
-
-# We can show a quick (only one replication) benchmark for this case, as we
-# have several alternative solution methods for the model. We skip
-# uncompiled deSolve, as it is so slow. More benchmarks are found in the
-# benchmark vignette
-# \dontrun{
-if(require(rbenchmark)) {
-  benchmark(replications = 1, order = "relative", columns = c("test", "relative", "elapsed"),
-    deSolve_compiled = mkinfit(SFO_SFO, FOCUS_D, quiet = TRUE, error_model = "tc",
-      solution_type = "deSolve", use_compiled = TRUE),
-    eigen = mkinfit(SFO_SFO, FOCUS_D, quiet = TRUE, error_model = "tc",
-      solution_type = "eigen"),
-    analytical = mkinfit(SFO_SFO, FOCUS_D, quiet = TRUE, error_model = "tc",
-      solution_type = "analytical"))
-}
-#>               test relative elapsed
-#> 3       analytical    1.000   0.236
-#> 1 deSolve_compiled    1.263   0.298
-#> 2            eigen    2.373   0.560
-# }
-
-# Use stepwise fitting, using optimised parameters from parent only fit, FOMC-SFO
-# \dontrun{
-FOMC_SFO <- mkinmod(
-  parent = mkinsub("FOMC", "m1"),
-  m1 = mkinsub("SFO"))
-#> Temporary DLL for differentials generated and loaded
-fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_D, quiet = TRUE)
-# Again, we get a warning and try a more sophisticated error model
-fit.FOMC_SFO.tc <- mkinfit(FOMC_SFO, FOCUS_D, quiet = TRUE, error_model = "tc")
-# This model has a higher likelihood, but not significantly so
-lrtest(fit.tc, fit.FOMC_SFO.tc)
-#> Likelihood ratio test
-#> 
-#> Model 1: FOMC_SFO with error model tc and fixed parameter(s) m1_0
-#> Model 2: SFO_SFO with error model tc and fixed parameter(s) m1_0
-#>   #Df  LogLik Df  Chisq Pr(>Chisq)
-#> 1   7 -64.829                     
-#> 2   6 -64.983 -1 0.3075     0.5792
-# Also, the missing standard error for log_beta and the t-tests for alpha
-# and beta indicate overparameterisation
-summary(fit.FOMC_SFO.tc, data = FALSE)
-#> Warning: NaNs produced
-#> Warning: NaNs produced
-#> Warning: diag(.) had 0 or NA entries; non-finite result is doubtful
-#> mkin version used for fitting:    1.2.3 
-#> R version used for fitting:       4.2.3 
-#> Date of fit:     Sun Apr 16 08:30:44 2023 
-#> Date of summary: Sun Apr 16 08:30:44 2023 
-#> 
-#> Equations:
-#> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
-#> d_m1/dt = + f_parent_to_m1 * (alpha/beta) * 1/((time/beta) + 1) *
-#>            parent - k_m1 * m1
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted using 3729 model solutions performed in 0.688 s
-#> 
-#> Error model: Two-component variance function 
-#> 
-#> Error model algorithm: d_3 
-#> Direct fitting and three-step fitting yield approximately the same likelihood 
-#> 
-#> Starting values for parameters to be optimised:
-#>                 value   type
-#> parent_0       100.75  state
-#> alpha            1.00 deparm
-#> beta            10.00 deparm
-#> k_m1             0.10 deparm
-#> f_parent_to_m1   0.50 deparm
-#> sigma_low        0.10  error
-#> rsd_high         0.10  error
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                      value lower upper
-#> parent_0        100.750000  -Inf   Inf
-#> log_k_m1         -2.302585  -Inf   Inf
-#> f_parent_qlogis   0.000000  -Inf   Inf
-#> log_alpha         0.000000  -Inf   Inf
-#> log_beta          2.302585  -Inf   Inf
-#> sigma_low         0.100000     0   Inf
-#> rsd_high          0.100000     0   Inf
-#> 
-#> Fixed parameter values:
-#>      value  type
-#> m1_0     0 state
-#> 
-#> Results:
-#> 
-#>       AIC      BIC    logLik
-#>   143.658 155.1211 -64.82902
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>                   Estimate Std. Error     Lower      Upper
-#> parent_0        101.600000  2.6400000 96.240000 107.000000
-#> log_k_m1         -5.284000  0.0929100 -5.474000  -5.095000
-#> f_parent_qlogis   0.001426  0.0767000 -0.155000   0.157800
-#> log_alpha         5.522000  0.0077320  5.506000   5.538000
-#> log_beta          7.806000        NaN       NaN        NaN
-#> sigma_low         0.002488  0.0002431  0.001992   0.002984
-#> rsd_high          0.079210  0.0093280  0.060180   0.098230
-#> 
-#> Parameter correlation:
-#>                  parent_0  log_k_m1 f_parent_qlogis log_alpha log_beta
-#> parent_0         1.000000 -0.095226        -0.76678   0.70544      NaN
-#> log_k_m1        -0.095226  1.000000         0.51432  -0.14387      NaN
-#> f_parent_qlogis -0.766780  0.514321         1.00000  -0.61396      NaN
-#> log_alpha        0.705444 -0.143872        -0.61396   1.00000      NaN
-#> log_beta              NaN       NaN             NaN       NaN        1
-#> sigma_low        0.016073  0.001586         0.01548   5.87007      NaN
-#> rsd_high         0.006626 -0.011700        -0.05357   0.04849      NaN
-#>                 sigma_low  rsd_high
-#> parent_0         0.016073  0.006626
-#> log_k_m1         0.001586 -0.011700
-#> f_parent_qlogis  0.015476 -0.053566
-#> log_alpha        5.870075  0.048487
-#> log_beta              NaN       NaN
-#> sigma_low        1.000000 -0.652558
-#> rsd_high        -0.652558  1.000000
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>                 Estimate t value    Pr(>t)     Lower     Upper
-#> parent_0       1.016e+02 32.7800 6.311e-26 9.624e+01 1.070e+02
-#> k_m1           5.072e-03 10.1200 1.216e-11 4.196e-03 6.130e-03
-#> f_parent_to_m1 5.004e-01 20.8300 4.317e-20 4.613e-01 5.394e-01
-#> alpha          2.502e+02  0.5624 2.889e-01 2.463e+02 2.542e+02
-#> beta           2.455e+03  0.5549 2.915e-01        NA        NA
-#> sigma_low      2.488e-03  0.4843 3.158e-01 1.992e-03 2.984e-03
-#> rsd_high       7.921e-02  8.4300 8.001e-10 6.018e-02 9.823e-02
-#> 
-#> FOCUS Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   6.781       5 14
-#> parent     7.141       3  6
-#> m1         4.640       2  8
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_m1   0.5004
-#> parent_sink 0.4996
-#> 
-#> Estimated disappearance times:
-#>           DT50  DT90 DT50back
-#> parent   6.812  22.7    6.834
-#> m1     136.661 454.0       NA
-
-# We can easily use starting parameters from the parent only fit (only for illustration)
-fit.FOMC = mkinfit("FOMC", FOCUS_2006_D, quiet = TRUE, error_model = "tc")
-fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_D, quiet = TRUE,
-  parms.ini = fit.FOMC$bparms.ode, error_model = "tc")
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/mkinmod.html b/docs/dev/reference/mkinmod.html
deleted file mode 100644
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--- a/docs/dev/reference/mkinmod.html
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@@ -1,426 +0,0 @@
-
-Function to set up a kinetic model with one or more state variables — mkinmod • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Function to set up a kinetic model with one or more state variables
      
-    Source: R/mkinmod.R, R/mkinsub.R
-    
-    
      
-
-    
      
-    
      This function is usually called using a call to mkinsub() for each observed
-variable, specifying the corresponding submodel as well as outgoing pathways
-(see examples).
      
-
      Print mkinmod objects in a way that the user finds his way to get to its
-components.
      
-    
      
-
-    
      
-    
      mkinmod(
-  ...,
-  use_of_ff = "max",
-  name = NULL,
-  speclist = NULL,
-  quiet = FALSE,
-  verbose = FALSE,
-  dll_dir = NULL,
-  unload = FALSE,
-  overwrite = FALSE
-)
-
-# S3 method for mkinmod
-print(x, ...)
-
-mkinsub(submodel, to = NULL, sink = TRUE, full_name = NA)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      ...
      
-
      For each observed variable, a list as obtained by mkinsub()
-has to be specified as an argument (see examples).  Currently, single
-first order kinetics "SFO", indeterminate order rate equation kinetics
-"IORE", or single first order with reversible binding "SFORB" are
-implemented for all variables, while "FOMC", "DFOP", "HS" and "logistic"
-can additionally be chosen for the first variable which is assumed to be
-the source compartment.
-Additionally, mkinsub() has an argument to, specifying names of
-variables to which a transfer is to be assumed in the model.
-If the argument use_of_ff is set to "min"
-and the model for the compartment is "SFO" or "SFORB", an
-additional mkinsub() argument can be sink = FALSE, effectively
-fixing the flux to sink to zero.
-In print.mkinmod, this argument is currently not used.
      
-
-
-
      use_of_ff
      
-
      Specification of the use of formation fractions in the
-model equations and, if applicable, the coefficient matrix.  If "max",
-formation fractions are always used (default).  If "min", a minimum use of
-formation fractions is made, i.e. each first-order pathway to a metabolite
-has its own rate constant.
      
-
-
-
      name
      
-
      A name for the model. Should be a valid R object name.
      
-
-
-
      speclist
      
-
      The specification of the observed variables and their
-submodel types and pathways can be given as a single list using this
-argument. Default is NULL.
      
-
-
-
      quiet
      
-
      Should messages be suppressed?
      
-
-
-
      verbose
      
-
      If TRUE, passed to inline::cfunction() if
-applicable to give detailed information about the C function being built.
      
-
-
-
      dll_dir
      
-
      Directory where an DLL object, if generated internally by
-inline::cfunction(), should be saved.  The DLL will only be stored in a
-permanent location for use in future sessions, if 'dll_dir' and 'name'
-are specified. This is helpful if fit objects are cached e.g. by knitr,
-as the cache remains functional across sessions if the DLL is stored in
-a user defined location.
      
-
-
-
      unload
      
-
      If a DLL from the target location in 'dll_dir' is already
-loaded, should that be unloaded first?
      
-
-
-
      overwrite
      
-
      If a file exists at the target DLL location in 'dll_dir',
-should this be overwritten?
      
-
-
-
      x
      
-
      An mkinmod object.
      
-
-
-
      submodel
      
-
      Character vector of length one to specify the submodel type.
-See mkinmod for the list of allowed submodel names.
      
-
-
-
      to
      
-
      Vector of the names of the state variable to which a
-transformation shall be included in the model.
      
-
-
-
      sink
      
-
      Should a pathway to sink be included in the model in addition to
-the pathways to other state variables?
      
-
-
-
      full_name
      
-
      An optional name to be used e.g. for plotting fits
-performed with the model.  You can use non-ASCII characters here, but then
-your R code will not be portable, i.e. may produce unintended plot
-results on other operating systems or system configurations.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      A list of class mkinmod for use with mkinfit(),
-containing, among others,
      
-
      diffs
      
-
      A vector of string representations of differential equations, one for
-each modelling variable.
      
-
-
      map
      
-
      A list containing named character vectors for each observed variable,
-specifying the modelling variables by which it is represented.
      
-
-
      use_of_ff
      
-
      The content of use_of_ff is passed on in this list component.
      
-
-
      deg_func
      
-
      If generated, a function containing the solution of the degradation
-model.
      
-
-
      coefmat
      
-
      The coefficient matrix, if the system of differential equations can be
-represented by one.
      
-
-
      cf
      
-
      If generated, a compiled function calculating the derivatives as
-returned by cfunction.
      
-
-
-
      A list for use with mkinmod.
      
-    
      
-    
      
-    
      Details
      
-    
      For the definition of model types and their parameters, the equations given
-in the FOCUS and NAFTA guidance documents are used.
      
-
      For kinetic models with more than one observed variable, a symbolic solution
-of the system of differential equations is included in the resulting
-mkinmod object in some cases, speeding up the solution.
      
-
      If a C compiler is found by pkgbuild::has_compiler() and there
-is more than one observed variable in the specification, C code is generated
-for evaluating the differential equations, compiled using
-inline::cfunction() and added to the resulting mkinmod object.
      
-    
      
-    
      
-    
      Note
      
-    
      The IORE submodel is not well tested for metabolites. When using this
-model for metabolites, you may want to read the note in the help
-page to mkinfit.
      
-    
      
-    
      
-    
      References
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-
      NAFTA Technical Working Group on Pesticides (not dated) Guidance for
-Evaluating and Calculating Degradation Kinetics in Environmental Media
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-# Specify the SFO model (this is not needed any more, as we can now mkinfit("SFO", ...)
-SFO <- mkinmod(parent = mkinsub("SFO"))
-
-# One parent compound, one metabolite, both single first order
-SFO_SFO <- mkinmod(
-  parent = mkinsub("SFO", "m1"),
-  m1 = mkinsub("SFO"))
-#> Temporary DLL for differentials generated and loaded
-print(SFO_SFO)
-#> <mkinmod> model generated with
-#> Use of formation fractions $use_of_ff: max 
-#> Specification $spec:
-#> $parent
-#> $type: SFO; $to: m1; $sink: TRUE
-#> $m1
-#> $type: SFO; $sink: TRUE
-#> Coefficient matrix $coefmat available
-#> Compiled model $cf available
-#> Differential equations:
-#> d_parent/dt = - k_parent * parent
-#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1
-
-# \dontrun{
- fit_sfo_sfo <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE, solution_type = "deSolve")
-#> Warning: Observations with value of zero were removed from the data
-
- # Now supplying compound names used for plotting, and write to user defined location
- # We need to choose a path outside the session tempdir because this gets removed
- DLL_dir <- "~/.local/share/mkin"
- if (!dir.exists(DLL_dir)) dir.create(DLL_dir)
- SFO_SFO.2 <- mkinmod(
-   parent = mkinsub("SFO", "m1", full_name = "Test compound"),
-   m1 = mkinsub("SFO", full_name = "Metabolite M1"),
-   name = "SFO_SFO", dll_dir = DLL_dir, unload = TRUE, overwrite = TRUE)
-#> Temporary DLL for differentials generated and loaded
-#> Copied DLL from /tmp/RtmpiGRJ6t/file5c7f7365e02a0.so to /home/jranke/.local/share/mkin/SFO_SFO.so
-# Now we can save the model and restore it in a new session
-saveRDS(SFO_SFO.2, file = "~/SFO_SFO.rds")
-# Terminate the R session here if you would like to check, and then do
-library(mkin)
-SFO_SFO.3 <- readRDS("~/SFO_SFO.rds")
-fit_sfo_sfo <- mkinfit(SFO_SFO.3, FOCUS_2006_D, quiet = TRUE, solution_type = "deSolve")
-#> Warning: Observations with value of zero were removed from the data
-
-# Show details of creating the C function
-SFO_SFO <- mkinmod(
-  parent = mkinsub("SFO", "m1"),
-  m1 = mkinsub("SFO"), verbose = TRUE)
-#> Program source:
-#>   1: #include <R.h>
-#>   2: 
-#>   3: 
-#>   4: static double parms [3];
-#>   5: #define k_parent parms[0]
-#>   6: #define f_parent_to_m1 parms[1]
-#>   7: #define k_m1 parms[2]
-#>   8: 
-#>   9: void initpar(void (* odeparms)(int *, double *)) {
-#>  10:     int N = 3;
-#>  11:     odeparms(&N, parms);
-#>  12: }
-#>  13: 
-#>  14: 
-#>  15: void diffs ( int * n, double * t, double * y, double * f, double * rpar, int * ipar ) {
-#>  16: 
-#>  17: f[0] = - k_parent * y[0];
-#>  18: f[1] = + f_parent_to_m1 * k_parent * y[0] - k_m1 * y[1];
-#>  19: }
-#> Temporary DLL for differentials generated and loaded
-
-# The symbolic solution which is available in this case is not
-# made for human reading but for speed of computation
-SFO_SFO$deg_func
-#> function (observed, odeini, odeparms) 
-#> {
-#>     predicted <- numeric(0)
-#>     with(as.list(odeparms), {
-#>         t <- observed[observed$name == "parent", "time"]
-#>         predicted <<- c(predicted, SFO.solution(t, odeini["parent"], 
-#>             k_parent))
-#>         t <- observed[observed$name == "m1", "time"]
-#>         predicted <<- c(predicted, (((k_m1 - k_parent) * odeini["m1"] - 
-#>             f_parent_to_m1 * k_parent * odeini["parent"]) * exp(-k_m1 * 
-#>             t) + f_parent_to_m1 * k_parent * odeini["parent"] * 
-#>             exp(-k_parent * t))/(k_m1 - k_parent))
-#>     })
-#>     return(predicted)
-#> }
-#> <environment: 0x555558bd6708>
-
-# If we have several parallel metabolites
-# (compare tests/testthat/test_synthetic_data_for_UBA_2014.R)
-m_synth_DFOP_par <- mkinmod(
- parent = mkinsub("DFOP", c("M1", "M2")),
- M1 = mkinsub("SFO"),
- M2 = mkinsub("SFO"),
- quiet = TRUE)
-
-fit_DFOP_par_c <- mkinfit(m_synth_DFOP_par,
-  synthetic_data_for_UBA_2014[[12]]$data,
-  quiet = TRUE)
-# }
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/mkinparplot-1.png b/docs/dev/reference/mkinparplot-1.png
deleted file mode 100644
index 6e7bf34f..00000000
Binary files a/docs/dev/reference/mkinparplot-1.png and /dev/null differ
diff --git a/docs/dev/reference/mkinparplot.html b/docs/dev/reference/mkinparplot.html
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@@ -1,177 +0,0 @@
-
-Function to plot the confidence intervals obtained using mkinfit — mkinparplot • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Function to plot the confidence intervals obtained using mkinfit
      
-    Source: R/mkinparplot.R
-    
-    
      
-
-    
      
-    
      This function plots the confidence intervals for the parameters fitted using
-mkinfit.
      
-    
      
-
-    
      
-    
      mkinparplot(object)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      A fit represented in an mkinfit object.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      Nothing is returned by this function, as it is called for its side
-effect, namely to produce a plot.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-# \dontrun{
-model <- mkinmod(
-  T245 = mkinsub("SFO", to = c("phenol"), sink = FALSE),
-  phenol = mkinsub("SFO", to = c("anisole")),
-  anisole = mkinsub("SFO"), use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-fit <- mkinfit(model, subset(mccall81_245T, soil == "Commerce"), quiet = TRUE)
-#> Warning: Observations with value of zero were removed from the data
-#> Warning: Optimisation did not converge:
-#> false convergence (8)
-mkinparplot(fit)
-
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/mkinplot.html b/docs/dev/reference/mkinplot.html
deleted file mode 100644
index d83ea3f4..00000000
--- a/docs/dev/reference/mkinplot.html
+++ /dev/null
@@ -1,162 +0,0 @@
-
-Plot the observed data and the fitted model of an mkinfit object — mkinplot • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Plot the observed data and the fitted model of an mkinfit object
      
-    Source: R/plot.mkinfit.R
-    
-    
      
-
-    
      
-    
      Deprecated function. It now only calls the plot method
-plot.mkinfit.
      
-    
      
-
-    
      
-    
      mkinplot(fit, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      fit
      
-
      an object of class mkinfit.
      
-
-
-
      ...
      
-
      further arguments passed to plot.mkinfit.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The function is called for its side effect.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/mkinpredict.html b/docs/dev/reference/mkinpredict.html
deleted file mode 100644
index 7d8e7c26..00000000
--- a/docs/dev/reference/mkinpredict.html
+++ /dev/null
@@ -1,437 +0,0 @@
-
-Produce predictions from a kinetic model using specific parameters — mkinpredict • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Produce predictions from a kinetic model using specific parameters
      
-    Source: R/mkinpredict.R
-    
-    
      
-
-    
      
-    
      This function produces a time series for all the observed variables in a
-kinetic model as specified by mkinmod, using a specific set of
-kinetic parameters and initial values for the state variables.
      
-    
      
-
-    
      
-    
      mkinpredict(x, odeparms, odeini, outtimes, ...)
-
-# S3 method for mkinmod
-mkinpredict(
-  x,
-  odeparms = c(k_parent_sink = 0.1),
-  odeini = c(parent = 100),
-  outtimes = seq(0, 120, by = 0.1),
-  solution_type = "deSolve",
-  use_compiled = "auto",
-  use_symbols = FALSE,
-  method.ode = "lsoda",
-  atol = 1e-08,
-  rtol = 1e-10,
-  maxsteps = 20000L,
-  map_output = TRUE,
-  na_stop = TRUE,
-  ...
-)
-
-# S3 method for mkinfit
-mkinpredict(
-  x,
-  odeparms = x$bparms.ode,
-  odeini = x$bparms.state,
-  outtimes = seq(0, 120, by = 0.1),
-  solution_type = "deSolve",
-  use_compiled = "auto",
-  method.ode = "lsoda",
-  atol = 1e-08,
-  rtol = 1e-10,
-  map_output = TRUE,
-  ...
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      x
      
-
      A kinetic model as produced by mkinmod, or a kinetic fit as
-fitted by mkinfit. In the latter case, the fitted parameters are used for
-the prediction.
      
-
-
-
      odeparms
      
-
      A numeric vector specifying the parameters used in the
-kinetic model, which is generally defined as a set of ordinary differential
-equations.
      
-
-
-
      odeini
      
-
      A numeric vector containing the initial values of the state
-variables of the model. Note that the state variables can differ from the
-observed variables, for example in the case of the SFORB model.
      
-
-
-
      outtimes
      
-
      A numeric vector specifying the time points for which model
-predictions should be generated.
      
-
-
-
      ...
      
-
      Further arguments passed to the ode solver in case such a
-solver is used.
      
-
-
-
      solution_type
      
-
      The method that should be used for producing the
-predictions. This should generally be "analytical" if there is only one
-observed variable, and usually "deSolve" in the case of several observed
-variables. The third possibility "eigen" is fast in comparison to uncompiled
-ODE models, but not applicable to some models, e.g. using FOMC for the
-parent compound.
      
-
-
-
      use_compiled
      
-
      If set to FALSE, no compiled version of the
-mkinmod model is used, even if is present.
      
-
-
-
      use_symbols
      
-
      If set to TRUE (default), symbol info present in
-the mkinmod object is used if available for accessing compiled code
      
-
-
-
      method.ode
      
-
      The solution method passed via mkinpredict to ode] in
-case the solution type is "deSolve" and we are not using compiled code.
-When using compiled code, only lsoda is supported.
      
-
-
-
      atol
      
-
      Absolute error tolerance, passed to the ode solver.
      
-
-
-
      rtol
      
-
      Absolute error tolerance, passed to the ode solver.
      
-
-
-
      maxsteps
      
-
      Maximum number of steps, passed to the ode solver.
      
-
-
-
      map_output
      
-
      Boolean to specify if the output should list values for
-the observed variables (default) or for all state variables (if set to
-FALSE). Setting this to FALSE has no effect for analytical solutions,
-as these always return mapped output.
      
-
-
-
      na_stop
      
-
      Should it be an error if ode returns NaN values
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      A matrix with the numeric solution in wide format
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-SFO <- mkinmod(degradinol = mkinsub("SFO"))
-# Compare solution types
-mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20,
-      solution_type = "analytical")
-#>    time  degradinol
-#> 0     0 100.0000000
-#> 1     1  74.0818221
-#> 2     2  54.8811636
-#> 3     3  40.6569660
-#> 4     4  30.1194212
-#> 5     5  22.3130160
-#> 6     6  16.5298888
-#> 7     7  12.2456428
-#> 8     8   9.0717953
-#> 9     9   6.7205513
-#> 10   10   4.9787068
-#> 11   11   3.6883167
-#> 12   12   2.7323722
-#> 13   13   2.0241911
-#> 14   14   1.4995577
-#> 15   15   1.1108997
-#> 16   16   0.8229747
-#> 17   17   0.6096747
-#> 18   18   0.4516581
-#> 19   19   0.3345965
-#> 20   20   0.2478752
-mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20,
-      solution_type = "deSolve")
-#>    time  degradinol
-#> 0     0 100.0000000
-#> 1     1  74.0818221
-#> 2     2  54.8811636
-#> 3     3  40.6569660
-#> 4     4  30.1194212
-#> 5     5  22.3130160
-#> 6     6  16.5298888
-#> 7     7  12.2456428
-#> 8     8   9.0717953
-#> 9     9   6.7205513
-#> 10   10   4.9787068
-#> 11   11   3.6883167
-#> 12   12   2.7323722
-#> 13   13   2.0241911
-#> 14   14   1.4995577
-#> 15   15   1.1108996
-#> 16   16   0.8229747
-#> 17   17   0.6096747
-#> 18   18   0.4516581
-#> 19   19   0.3345965
-#> 20   20   0.2478752
-mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20,
-      solution_type = "deSolve", use_compiled = FALSE)
-#>    time  degradinol
-#> 0     0 100.0000000
-#> 1     1  74.0818221
-#> 2     2  54.8811636
-#> 3     3  40.6569660
-#> 4     4  30.1194212
-#> 5     5  22.3130160
-#> 6     6  16.5298888
-#> 7     7  12.2456428
-#> 8     8   9.0717953
-#> 9     9   6.7205513
-#> 10   10   4.9787068
-#> 11   11   3.6883167
-#> 12   12   2.7323722
-#> 13   13   2.0241911
-#> 14   14   1.4995577
-#> 15   15   1.1108996
-#> 16   16   0.8229747
-#> 17   17   0.6096747
-#> 18   18   0.4516581
-#> 19   19   0.3345965
-#> 20   20   0.2478752
-mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20,
-      solution_type = "eigen")
-#>    time  degradinol
-#> 0     0 100.0000000
-#> 1     1  74.0818221
-#> 2     2  54.8811636
-#> 3     3  40.6569660
-#> 4     4  30.1194212
-#> 5     5  22.3130160
-#> 6     6  16.5298888
-#> 7     7  12.2456428
-#> 8     8   9.0717953
-#> 9     9   6.7205513
-#> 10   10   4.9787068
-#> 11   11   3.6883167
-#> 12   12   2.7323722
-#> 13   13   2.0241911
-#> 14   14   1.4995577
-#> 15   15   1.1108997
-#> 16   16   0.8229747
-#> 17   17   0.6096747
-#> 18   18   0.4516581
-#> 19   19   0.3345965
-#> 20   20   0.2478752
-
-# Compare integration methods to analytical solution
-mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20,
-      solution_type = "analytical")[21,]
-#>       time degradinol 
-#> 20.0000000  0.2478752 
-mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20,
-      method = "lsoda", use_compiled = FALSE)[21,]
-#>       time degradinol 
-#> 20.0000000  0.2478752 
-mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20,
-      method = "ode45", use_compiled = FALSE)[21,]
-#>       time degradinol 
-#> 20.0000000  0.2478752 
-mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 0:20,
-      method = "rk4", use_compiled = FALSE)[21,]
-#>       time degradinol 
-#> 20.0000000  0.2480043 
-# rk4 is not as precise here
-
-# The number of output times used to make a lot of difference until the
-# default for atol was adjusted
-mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100),
-      seq(0, 20, by = 0.1))[201,]
-#>       time degradinol 
-#> 20.0000000  0.2478752 
-mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100),
-      seq(0, 20, by = 0.01))[2001,]
-#>       time degradinol 
-#> 20.0000000  0.2478752 
-
-# Comparison of the performance of solution types
-SFO_SFO = mkinmod(parent = list(type = "SFO", to = "m1"),
-                  m1 = list(type = "SFO"), use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-if(require(rbenchmark)) {
-  benchmark(replications = 10, order = "relative", columns = c("test", "relative", "elapsed"),
-    eigen = mkinpredict(SFO_SFO,
-      c(k_parent = 0.15, f_parent_to_m1 = 0.5, k_m1 = 0.01),
-      c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
-      solution_type = "eigen")[201,],
-    deSolve_compiled = mkinpredict(SFO_SFO,
-      c(k_parent = 0.15, f_parent_to_m1 = 0.5, k_m1 = 0.01),
-      c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
-      solution_type = "deSolve")[201,],
-    deSolve = mkinpredict(SFO_SFO,
-      c(k_parent = 0.15, f_parent_to_m1 = 0.5, k_m1 = 0.01),
-      c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
-      solution_type = "deSolve", use_compiled = FALSE)[201,],
-    analytical = mkinpredict(SFO_SFO,
-      c(k_parent = 0.15, f_parent_to_m1 = 0.5, k_m1 = 0.01),
-      c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
-      solution_type = "analytical", use_compiled = FALSE)[201,])
-}
-#> Loading required package: rbenchmark
-#>               test relative elapsed
-#> 2 deSolve_compiled     1.00   0.004
-#> 1            eigen     4.00   0.016
-#> 4       analytical     4.25   0.017
-#> 3          deSolve    40.75   0.163
-
-# \dontrun{
-  # Predict from a fitted model
-  f <- mkinfit(SFO_SFO, FOCUS_2006_C, quiet = TRUE)
-  f <- mkinfit(SFO_SFO, FOCUS_2006_C, quiet = TRUE, solution_type = "deSolve")
-  head(mkinpredict(f))
-#> Error in !is.null(x$symbols) & use_symbols: operations are possible only for numeric, logical or complex types
-# }
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/mkinresplot-1.png b/docs/dev/reference/mkinresplot-1.png
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-
-Function to plot residuals stored in an mkin object — mkinresplot • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Function to plot residuals stored in an mkin object
      
-    Source: R/mkinresplot.R
-    
-    
      
-
-    
      
-    
      This function plots the residuals for the specified subset of the observed
-variables from an mkinfit object. A combined plot of the fitted model and
-the residuals can be obtained using plot.mkinfit using the
-argument show_residuals = TRUE.
      
-    
      
-
-    
      
-    
      mkinresplot(
-  object,
-  obs_vars = names(object$mkinmod$map),
-  xlim = c(0, 1.1 * max(object$data$time)),
-  standardized = FALSE,
-  xlab = "Time",
-  ylab = ifelse(standardized, "Standardized residual", "Residual"),
-  maxabs = "auto",
-  legend = TRUE,
-  lpos = "topright",
-  col_obs = "auto",
-  pch_obs = "auto",
-  frame = TRUE,
-  ...
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      A fit represented in an mkinfit object.
      
-
-
-
      obs_vars
      
-
      A character vector of names of the observed variables for
-which residuals should be plotted. Defaults to all observed variables in
-the model
      
-
-
-
      xlim
      
-
      plot range in x direction.
      
-
-
-
      standardized
      
-
      Should the residuals be standardized by dividing by the
-standard deviation given by the error model of the fit?
      
-
-
-
      xlab
      
-
      Label for the x axis.
      
-
-
-
      ylab
      
-
      Label for the y axis.
      
-
-
-
      maxabs
      
-
      Maximum absolute value of the residuals. This is used for the
-scaling of the y axis and defaults to "auto".
      
-
-
-
      legend
      
-
      Should a legend be plotted?
      
-
-
-
      lpos
      
-
      Where should the legend be placed? Default is "topright". Will
-be passed on to legend.
      
-
-
-
      col_obs
      
-
      Colors for the observed variables.
      
-
-
-
      pch_obs
      
-
      Symbols to be used for the observed variables.
      
-
-
-
      frame
      
-
      Should a frame be drawn around the plots?
      
-
-
-
      ...
      
-
      further arguments passed to plot.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      Nothing is returned by this function, as it is called for its side
-effect, namely to produce a plot.
      
-    
      
-    
      
-    
      See also
      
-    
      mkinplot, for a way to plot the data and the fitted
-lines of the mkinfit object, and plot_res for a function
-combining the plot of the fit and the residual plot.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke and Katrin Lindenberger
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-model <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
-#> Temporary DLL for differentials generated and loaded
-fit <- mkinfit(model, FOCUS_2006_D, quiet = TRUE)
-#> Warning: Observations with value of zero were removed from the data
-mkinresplot(fit, "m1")
-
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
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-
-Fit one or more kinetic models with one or more state variables to one or
-more datasets — mmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Fit one or more kinetic models with one or more state variables to one or
-more datasets
      
-    Source: R/mmkin.R
-    
-    
      
-
-    
      
-    
      This function calls mkinfit on all combinations of models and
-datasets specified in its first two arguments.
      
-    
      
-
-    
      
-    
      mmkin(
-  models = c("SFO", "FOMC", "DFOP"),
-  datasets,
-  cores = if (Sys.info()["sysname"] == "Windows") 1 else parallel::detectCores(),
-  cluster = NULL,
-  ...
-)
-
-# S3 method for mmkin
-print(x, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      models
      
-
      Either a character vector of shorthand names like
-c("SFO", "FOMC", "DFOP", "HS", "SFORB"), or an optionally named
-list of mkinmod objects.
      
-
-
-
      datasets
      
-
      An optionally named list of datasets suitable as observed
-data for mkinfit.
      
-
-
-
      cores
      
-
      The number of cores to be used for multicore processing. This
-is only used when the cluster argument is NULL. On Windows
-machines, cores > 1 is not supported, you need to use the cluster
-argument to use multiple logical processors. Per default, all cores
-detected by parallel::detectCores() are used, except on Windows where
-the default is 1.
      
-
-
-
      cluster
      
-
      A cluster as returned by makeCluster to be used
-for parallel execution.
      
-
-
-
      ...
      
-
      Not used.
      
-
-
-
      x
      
-
      An mmkin object.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      A two-dimensional array of mkinfit
      
-
-
-
      objects and/or try-errors that can be indexed using the model names for the
-first index (row index) and the dataset names for the second index (column
-index).
      
-    
      
-    
      
-    
      See also
      
-    
      [.mmkin for subsetting, plot.mmkin for
-plotting.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-# \dontrun{
-m_synth_SFO_lin <- mkinmod(parent = mkinsub("SFO", "M1"),
-                           M1 = mkinsub("SFO", "M2"),
-                           M2 = mkinsub("SFO"), use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-
-m_synth_FOMC_lin <- mkinmod(parent = mkinsub("FOMC", "M1"),
-                            M1 = mkinsub("SFO", "M2"),
-                            M2 = mkinsub("SFO"), use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-
-models <- list(SFO_lin = m_synth_SFO_lin, FOMC_lin = m_synth_FOMC_lin)
-datasets <- lapply(synthetic_data_for_UBA_2014[1:3], function(x) x$data)
-names(datasets) <- paste("Dataset", 1:3)
-
-time_default <- system.time(fits.0 <- mmkin(models, datasets, quiet = TRUE))
-time_1 <- system.time(fits.4 <- mmkin(models, datasets, cores = 1, quiet = TRUE))
-
-time_default
-#>    user  system elapsed 
-#>   1.560   0.668   0.742 
-time_1
-#>    user  system elapsed 
-#>   2.033   0.004   2.037 
-
-endpoints(fits.0[["SFO_lin", 2]])
-#> $ff
-#>   parent_M1 parent_sink       M1_M2     M1_sink 
-#>   0.7340481   0.2659519   0.7505683   0.2494317 
-#> 
-#> $distimes
-#>             DT50       DT90
-#> parent  0.877769   2.915885
-#> M1      2.325744   7.725956
-#> M2     33.720100 112.015749
-#> 
-
-# plot.mkinfit handles rows or columns of mmkin result objects
-plot(fits.0[1, ])
-
-plot(fits.0[1, ], obs_var = c("M1", "M2"))
-
-plot(fits.0[, 1])
-
-# Use double brackets to extract a single mkinfit object, which will be plotted
-# by plot.mkinfit and can be plotted using plot_sep
-plot(fits.0[[1, 1]], sep_obs = TRUE, show_residuals = TRUE, show_errmin = TRUE)
-
-plot_sep(fits.0[[1, 1]])
-# Plotting with mmkin (single brackets, extracting an mmkin object) does not
-# allow to plot the observed variables separately
-plot(fits.0[1, 1])
-
-
-# On Windows, we can use multiple cores by making a cluster first
-cl <- parallel::makePSOCKcluster(12)
-f <- mmkin(c("SFO", "FOMC", "DFOP"),
-  list(A = FOCUS_2006_A, B = FOCUS_2006_B, C = FOCUS_2006_C, D = FOCUS_2006_D),
-  cluster = cl, quiet = TRUE)
-print(f)
-#> <mmkin> object
-#> Status of individual fits:
-#> 
-#>       dataset
-#> model  A  B  C  D 
-#>   SFO  OK OK OK OK
-#>   FOMC OK OK OK OK
-#>   DFOP OK OK OK OK
-#> 
-#> OK: No warnings
-# We get false convergence for the FOMC fit to FOCUS_2006_A because this
-# dataset is really SFO, and the FOMC fit is overparameterised
-parallel::stopCluster(cl)
-# }
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/multistart-1.png b/docs/dev/reference/multistart-1.png
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-
-Perform a hierarchical model fit with multiple starting values — multistart • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Perform a hierarchical model fit with multiple starting values
      
-    Source: R/multistart.R
-    
-    
      
-
-    
      
-    
      The purpose of this method is to check if a certain algorithm for fitting
-nonlinear hierarchical models (also known as nonlinear mixed-effects models)
-will reliably yield results that are sufficiently similar to each other, if
-started with a certain range of reasonable starting parameters. It is
-inspired by the article on practical identifiabiliy in the frame of nonlinear
-mixed-effects models by Duchesne et al (2021).
      
-    
      
-
-    
      
-    
      multistart(
-  object,
-  n = 50,
-  cores = if (Sys.info()["sysname"] == "Windows") 1 else parallel::detectCores(),
-  cluster = NULL,
-  ...
-)
-
-# S3 method for saem.mmkin
-multistart(object, n = 50, cores = 1, cluster = NULL, ...)
-
-# S3 method for multistart
-print(x, ...)
-
-best(object, ...)
-
-# S3 method for default
-best(object, ...)
-
-which.best(object, ...)
-
-# S3 method for default
-which.best(object, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      The fit object to work with
      
-
-
-
      n
      
-
      How many different combinations of starting parameters should be
-used?
      
-
-
-
      cores
      
-
      How many fits should be run in parallel (only on posix platforms)?
      
-
-
-
      cluster
      
-
      A cluster as returned by parallel::makeCluster to be used
-for parallel execution.
      
-
-
-
      ...
      
-
      Passed to the update function.
      
-
-
-
      x
      
-
      The multistart object to print
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      A list of saem.mmkin objects, with class attributes
-'multistart.saem.mmkin' and 'multistart'.
      
-
-
-
      The object with the highest likelihood
      
-
-
-
      The index of the object with the highest likelihood
      
-    
      
-    
      
-    
      References
      
-    
      Duchesne R, Guillemin A, Gandrillon O, Crauste F. Practical
-identifiability in the frame of nonlinear mixed effects models: the example
-of the in vitro erythropoiesis. BMC Bioinformatics. 2021 Oct 4;22(1):478.
-doi: 10.1186/s12859-021-04373-4.
      
-    
      
-    
      
-    
      See also
      
-    
      parplot, llhist
      
-    
      
-
-    
      
-    
      Examples
      
-    
      # \dontrun{
-library(mkin)
-dmta_ds <- lapply(1:7, function(i) {
-  ds_i <- dimethenamid_2018$ds[[i]]$data
-  ds_i[ds_i$name == "DMTAP", "name"] <-  "DMTA"
-  ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i]
-  ds_i
-})
-names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title)
-dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]])
-dmta_ds[["Elliot 1"]] <- dmta_ds[["Elliot 2"]] <- NULL
-
-f_mmkin <- mmkin("DFOP", dmta_ds, error_model = "tc", cores = 7, quiet = TRUE)
-f_saem_full <- saem(f_mmkin)
-f_saem_full_multi <- multistart(f_saem_full, n = 16, cores = 16)
-parplot(f_saem_full_multi, lpos = "topleft")
-
-illparms(f_saem_full)
-#> [1] "sd(log_k2)"
-
-f_saem_reduced <- update(f_saem_full, no_random_effect = "log_k2")
-illparms(f_saem_reduced)
-# On Windows, we need to create a PSOCK cluster first and refer to it
-# in the call to multistart()
-library(parallel)
-cl <- makePSOCKcluster(12)
-f_saem_reduced_multi <- multistart(f_saem_reduced, n = 16, cluster = cl)
-parplot(f_saem_reduced_multi, lpos = "topright", ylim = c(0.5, 2))
-
-stopCluster(cl)
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/nafta-1.png b/docs/dev/reference/nafta-1.png
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-
-Evaluate parent kinetics using the NAFTA guidance — nafta • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Evaluate parent kinetics using the NAFTA guidance
      
-    Source: R/nafta.R
-    
-    
      
-
-    
      
-    
      The function fits the SFO, IORE and DFOP models using mmkin
-and returns an object of class nafta that has methods for printing
-and plotting.
      
-
      Print nafta objects. The results for the three models are printed in the
-order of increasing model complexity, i.e. SFO, then IORE, and finally DFOP.
      
-    
      
-
-    
      
-    
      nafta(ds, title = NA, quiet = FALSE, ...)
-
-# S3 method for nafta
-print(x, quiet = TRUE, digits = 3, ...)
      
-    
      
-
-    
      
-    
      Source
      
-    
      NAFTA (2011) Guidance for evaluating and calculating degradation
-kinetics in environmental media. NAFTA Technical Working Group on
-Pesticides
-https://www.epa.gov/pesticide-science-and-assessing-pesticide-risks/guidance-evaluating-and-calculating-degradation
-accessed 2019-02-22
      
-
      US EPA (2015) Standard Operating Procedure for Using the NAFTA Guidance to
-Calculate Representative Half-life Values and Characterizing Pesticide
-Degradation
-https://www.epa.gov/pesticide-science-and-assessing-pesticide-risks/standard-operating-procedure-using-nafta-guidance
      
-    
      
-    
      
-    
      Arguments
      
-    
      ds
      
-
      A dataframe that must contain one variable called "time" with the
-time values specified by the time argument, one column called
-"name" with the grouping of the observed values, and finally one column of
-observed values called "value".
      
-
-
-
      title
      
-
      Optional title of the dataset
      
-
-
-
      quiet
      
-
      Should the evaluation text be shown?
      
-
-
-
      ...
      
-
      Further arguments passed to mmkin (not for the
-printing method).
      
-
-
-
      x
      
-
      An nafta object.
      
-
-
-
      digits
      
-
      Number of digits to be used for printing parameters and
-dissipation times.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      An list of class nafta. The list element named "mmkin" is the
-mmkin object containing the fits of the three models. The
-list element named "title" contains the title of the dataset used. The
-list element "data" contains the dataset used in the fits.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-  nafta_evaluation <- nafta(NAFTA_SOP_Appendix_D, cores = 1)
-#> The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
-#> The representative half-life of the IORE model is longer than the one corresponding
-#> to the terminal degradation rate found with the DFOP model.
-#> The representative half-life obtained from the DFOP model may be used
-  print(nafta_evaluation)
-#> Sums of squares:
-#>       SFO      IORE      DFOP 
-#> 1378.6832  615.7730  517.8836 
-#> 
-#> Critical sum of squares for checking the SFO model:
-#> [1] 717.4598
-#> 
-#> Parameters:
-#> $SFO
-#>          Estimate   Pr(>t)    Lower   Upper
-#> parent_0  83.7558 1.80e-14 77.18268 90.3288
-#> k_parent   0.0017 7.43e-05  0.00112  0.0026
-#> sigma      8.7518 1.22e-05  5.64278 11.8608
-#> 
-#> $IORE
-#>                Estimate Pr(>t)    Lower    Upper
-#> parent_0       9.69e+01     NA 8.88e+01 1.05e+02
-#> k__iore_parent 8.40e-14     NA 1.79e-18 3.94e-09
-#> N_parent       6.68e+00     NA 4.19e+00 9.17e+00
-#> sigma          5.85e+00     NA 3.76e+00 7.94e+00
-#> 
-#> $DFOP
-#>          Estimate   Pr(>t)    Lower    Upper
-#> parent_0 9.76e+01 1.94e-13 9.02e+01 1.05e+02
-#> k1       4.24e-02 5.92e-03 2.03e-02 8.88e-02
-#> k2       8.24e-04 6.48e-03 3.89e-04 1.75e-03
-#> g        2.88e-01 2.47e-05 1.95e-01 4.03e-01
-#> sigma    5.36e+00 2.22e-05 3.43e+00 7.30e+00
-#> 
-#> 
-#> DTx values:
-#>      DT50    DT90 DT50_rep
-#> SFO   407    1350      407
-#> IORE  541 5190000  1560000
-#> DFOP  429    2380      841
-#> 
-#> Representative half-life:
-#> [1] 841.41
-  plot(nafta_evaluation)
-
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
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-
-Helper functions to create nlme models from mmkin row objects — nlme_function • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Helper functions to create nlme models from mmkin row objects
      
-    Source: R/nlme.R
-    
-    
      
-
-    
      
-    
      These functions facilitate setting up a nonlinear mixed effects model for
-an mmkin row object. An mmkin row object is essentially a list of mkinfit
-objects that have been obtained by fitting the same model to a list of
-datasets. They are used internally by the nlme.mmkin() method.
      
-    
      
-
-    
      
-    
      nlme_function(object)
-
-nlme_data(object)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      An mmkin row object containing several fits of the same model to different datasets
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      A function that can be used with nlme
      
-
-
-
      A groupedData object
      
-    
      
-    
      
-    
      See also
      
-    
      nlme.mmkin
      
-    
      
-
-    
      
-    
      Examples
      
-    
      sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-m_SFO <- mkinmod(parent = mkinsub("SFO"))
-d_SFO_1 <- mkinpredict(m_SFO,
-  c(k_parent = 0.1),
-  c(parent = 98), sampling_times)
-d_SFO_1_long <- mkin_wide_to_long(d_SFO_1, time = "time")
-d_SFO_2 <- mkinpredict(m_SFO,
-  c(k_parent = 0.05),
-  c(parent = 102), sampling_times)
-d_SFO_2_long <- mkin_wide_to_long(d_SFO_2, time = "time")
-d_SFO_3 <- mkinpredict(m_SFO,
-  c(k_parent = 0.02),
-  c(parent = 103), sampling_times)
-d_SFO_3_long <- mkin_wide_to_long(d_SFO_3, time = "time")
-
-d1 <- add_err(d_SFO_1, function(value) 3, n = 1)
-d2 <- add_err(d_SFO_2, function(value) 2, n = 1)
-d3 <- add_err(d_SFO_3, function(value) 4, n = 1)
-ds <- c(d1 = d1, d2 = d2, d3 = d3)
-
-f <- mmkin("SFO", ds, cores = 1, quiet = TRUE)
-mean_dp <- mean_degparms(f)
-grouped_data <- nlme_data(f)
-nlme_f <- nlme_function(f)
-# These assignments are necessary for these objects to be
-# visible to nlme and augPred when evaluation is done by
-# pkgdown to generate the html docs.
-assign("nlme_f", nlme_f, globalenv())
-assign("grouped_data", grouped_data, globalenv())
-
-library(nlme)
-m_nlme <- nlme(value ~ nlme_f(name, time, parent_0, log_k_parent_sink),
-  data = grouped_data,
-  fixed = parent_0 + log_k_parent_sink ~ 1,
-  random = pdDiag(parent_0 + log_k_parent_sink ~ 1),
-  start = mean_dp)
-summary(m_nlme)
-#> Nonlinear mixed-effects model fit by maximum likelihood
-#>   Model: value ~ nlme_f(name, time, parent_0, log_k_parent_sink) 
-#>   Data: grouped_data 
-#>        AIC      BIC    logLik
-#>   266.6428 275.8935 -128.3214
-#> 
-#> Random effects:
-#>  Formula: list(parent_0 ~ 1, log_k_parent_sink ~ 1)
-#>  Level: ds
-#>  Structure: Diagonal
-#>             parent_0 log_k_parent_sink Residual
-#> StdDev: 0.0004253489         0.7058039 3.065183
-#> 
-#> Fixed effects:  parent_0 + log_k_parent_sink ~ 1 
-#>                       Value Std.Error DF   t-value p-value
-#> parent_0          101.18323 0.7900461 43 128.07256       0
-#> log_k_parent_sink  -3.08708 0.4171755 43  -7.39995       0
-#>  Correlation: 
-#>                   prnt_0
-#> log_k_parent_sink 0.031 
-#> 
-#> Standardized Within-Group Residuals:
-#>         Min          Q1         Med          Q3         Max 
-#> -2.38427071 -0.52059848  0.03593021  0.39987268  2.73188969 
-#> 
-#> Number of Observations: 47
-#> Number of Groups: 3 
-plot(augPred(m_nlme, level = 0:1), layout = c(3, 1))
-
-# augPred does not work on fits with more than one state
-# variable
-#
-# The procedure is greatly simplified by the nlme.mmkin function
-f_nlme <- nlme(f)
-plot(f_nlme)
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
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-
-Create an nlme model for an mmkin row object — nlme.mmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Create an nlme model for an mmkin row object
      
-    Source: R/nlme.mmkin.R
-    
-    
      
-
-    
      
-    
      This functions sets up a nonlinear mixed effects model for an mmkin row
-object. An mmkin row object is essentially a list of mkinfit objects that
-have been obtained by fitting the same model to a list of datasets.
      
-    
      
-
-    
      
-    
      # S3 method for mmkin
-nlme(
-  model,
-  data = "auto",
-  fixed = lapply(as.list(names(mean_degparms(model))), function(el) eval(parse(text =
-    paste(el, 1, sep = "~")))),
-  random = pdDiag(fixed),
-  groups,
-  start = mean_degparms(model, random = TRUE, test_log_parms = TRUE),
-  correlation = NULL,
-  weights = NULL,
-  subset,
-  method = c("ML", "REML"),
-  na.action = na.fail,
-  naPattern,
-  control = list(),
-  verbose = FALSE
-)
-
-# S3 method for nlme.mmkin
-print(x, digits = max(3, getOption("digits") - 3), ...)
-
-# S3 method for nlme.mmkin
-update(object, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      model
      
-
      An mmkin row object.
      
-
-
-
      data
      
-
      Ignored, data are taken from the mmkin model
      
-
-
-
      fixed
      
-
      Ignored, all degradation parameters fitted in the
-mmkin model are used as fixed parameters
      
-
-
-
      random
      
-
      If not specified, no correlations between random effects are
-set up for the optimised degradation model parameters. This is
-achieved by using the nlme::pdDiag method.
      
-
-
-
      groups
      
-
      See the documentation of nlme
      
-
-
-
      start
      
-
      If not specified, mean values of the fitted degradation
-parameters taken from the mmkin object are used
      
-
-
-
      correlation
      
-
      See the documentation of nlme
      
-
-
-
      weights
      
-
      passed to nlme
      
-
-
-
      subset
      
-
      passed to nlme
      
-
-
-
      method
      
-
      passed to nlme
      
-
-
-
      na.action
      
-
      passed to nlme
      
-
-
-
      naPattern
      
-
      passed to nlme
      
-
-
-
      control
      
-
      passed to nlme
      
-
-
-
      verbose
      
-
      passed to nlme
      
-
-
-
      x
      
-
      An nlme.mmkin object to print
      
-
-
-
      digits
      
-
      Number of digits to use for printing
      
-
-
-
      ...
      
-
      Update specifications passed to update.nlme
      
-
-
-
      object
      
-
      An nlme.mmkin object to update
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      Upon success, a fitted 'nlme.mmkin' object, which is an nlme object
-with additional elements. It also inherits from 'mixed.mmkin'.
      
-    
      
-    
      
-    
      Details
      
-    
      Note that the convergence of the nlme algorithms depends on the quality
-of the data. In degradation kinetics, we often only have few datasets
-(e.g. data for few soils) and complicated degradation models, which may
-make it impossible to obtain convergence with nlme.
      
-    
      
-    
      
-    
      Note
      
-    
      As the object inherits from nlme::nlme, there is a wealth of
-methods that will automatically work on 'nlme.mmkin' objects, such as
-nlme::intervals(), nlme::anova.lme() and nlme::coef.lme().
      
-    
      
-    
-
-    
      
-    
      Examples
      
-    
      ds <- lapply(experimental_data_for_UBA_2019[6:10],
- function(x) subset(x$data[c("name", "time", "value")], name == "parent"))
-
-# \dontrun{
-  f <- mmkin(c("SFO", "DFOP"), ds, quiet = TRUE, cores = 1)
-  library(nlme)
-  f_nlme_sfo <- nlme(f["SFO", ])
-  f_nlme_dfop <- nlme(f["DFOP", ])
-  anova(f_nlme_sfo, f_nlme_dfop)
-#>             Model df      AIC      BIC    logLik   Test  L.Ratio p-value
-#> f_nlme_sfo      1  5 625.0539 637.5529 -307.5269                        
-#> f_nlme_dfop     2  9 495.1270 517.6253 -238.5635 1 vs 2 137.9268  <.0001
-  print(f_nlme_dfop)
-#> Kinetic nonlinear mixed-effects model fit by maximum likelihood
-#> 
-#> Structural model:
-#> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-#>            time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-#>            * parent
-#> 
-#> Data:
-#> 90 observations of 1 variable(s) grouped in 5 datasets
-#> 
-#> Log-likelihood: -238.6
-#> 
-#> Fixed effects:
-#>  list(parent_0 ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1) 
-#> parent_0   log_k1   log_k2 g_qlogis 
-#>  94.1702  -1.8002  -4.1474   0.0324 
-#> 
-#> Random effects:
-#>  Formula: list(parent_0 ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1)
-#>  Level: ds
-#>  Structure: Diagonal
-#>         parent_0 log_k1 log_k2 g_qlogis Residual
-#> StdDev:    2.488 0.8447   1.33   0.4652    2.321
-#> 
-  plot(f_nlme_dfop)
-
-  endpoints(f_nlme_dfop)
-#> $distimes
-#>            DT50     DT90 DT50back  DT50_k1  DT50_k2
-#> parent 10.79857 100.7937 30.34192 4.193936 43.85441
-#> 
-
-  ds_2 <- lapply(experimental_data_for_UBA_2019[6:10],
-   function(x) x$data[c("name", "time", "value")])
-  m_sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"),
-    A1 = mkinsub("SFO"), use_of_ff = "min", quiet = TRUE)
-  m_sfo_sfo_ff <- mkinmod(parent = mkinsub("SFO", "A1"),
-    A1 = mkinsub("SFO"), use_of_ff = "max", quiet = TRUE)
-  m_dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
-    A1 = mkinsub("SFO"), quiet = TRUE)
-
-  f_2 <- mmkin(list("SFO-SFO" = m_sfo_sfo,
-   "SFO-SFO-ff" = m_sfo_sfo_ff,
-   "DFOP-SFO" = m_dfop_sfo),
-    ds_2, quiet = TRUE)
-
-  f_nlme_sfo_sfo <- nlme(f_2["SFO-SFO", ])
-  plot(f_nlme_sfo_sfo)
-
-
-  # With formation fractions this does not coverge with defaults
-  # f_nlme_sfo_sfo_ff <- nlme(f_2["SFO-SFO-ff", ])
-  #plot(f_nlme_sfo_sfo_ff)
-
-  # For the following, we need to increase pnlsMaxIter and the tolerance
-  # to get convergence
-  f_nlme_dfop_sfo <- nlme(f_2["DFOP-SFO", ],
-    control = list(pnlsMaxIter = 120, tolerance = 5e-4))
-
-  plot(f_nlme_dfop_sfo)
-
-
-  anova(f_nlme_dfop_sfo, f_nlme_sfo_sfo)
-#>                 Model df       AIC       BIC    logLik   Test  L.Ratio p-value
-#> f_nlme_dfop_sfo     1 13  843.8547  884.6201 -408.9274                        
-#> f_nlme_sfo_sfo      2  9 1085.1821 1113.4043 -533.5910 1 vs 2 249.3274  <.0001
-
-  endpoints(f_nlme_sfo_sfo)
-#> $ff
-#> parent_sink   parent_A1     A1_sink 
-#>   0.5912432   0.4087568   1.0000000 
-#> 
-#> $distimes
-#>            DT50     DT90
-#> parent 19.13518  63.5657
-#> A1     66.02155 219.3189
-#> 
-  endpoints(f_nlme_dfop_sfo)
-#> $ff
-#>   parent_A1 parent_sink 
-#>   0.2768575   0.7231425 
-#> 
-#> $distimes
-#>             DT50     DT90 DT50back  DT50_k1  DT50_k2
-#> parent  11.07091 104.6320 31.49737 4.462384 46.20825
-#> A1     162.30507 539.1658       NA       NA       NA
-#> 
-
-  if (length(findFunction("varConstProp")) > 0) { # tc error model for nlme available
-    # Attempts to fit metabolite kinetics with the tc error model are possible,
-    # but need tweeking of control values and sometimes do not converge
-
-    f_tc <- mmkin(c("SFO", "DFOP"), ds, quiet = TRUE, error_model = "tc")
-    f_nlme_sfo_tc <- nlme(f_tc["SFO", ])
-    f_nlme_dfop_tc <- nlme(f_tc["DFOP", ])
-    AIC(f_nlme_sfo, f_nlme_sfo_tc, f_nlme_dfop, f_nlme_dfop_tc)
-    print(f_nlme_dfop_tc)
-  }
-#> Kinetic nonlinear mixed-effects model fit by maximum likelihood
-#> 
-#> Structural model:
-#> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-#>            time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-#>            * parent
-#> 
-#> Data:
-#> 90 observations of 1 variable(s) grouped in 5 datasets
-#> 
-#> Log-likelihood: -238.4
-#> 
-#> Fixed effects:
-#>  list(parent_0 ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1) 
-#> parent_0   log_k1   log_k2 g_qlogis 
-#> 94.04773 -1.82340 -4.16716  0.05686 
-#> 
-#> Random effects:
-#>  Formula: list(parent_0 ~ 1, log_k1 ~ 1, log_k2 ~ 1, g_qlogis ~ 1)
-#>  Level: ds
-#>  Structure: Diagonal
-#>         parent_0 log_k1 log_k2 g_qlogis Residual
-#> StdDev:    2.474   0.85  1.337   0.4659        1
-#> 
-#> Variance function:
-#>  Structure: Constant plus proportion of variance covariate
-#>  Formula: ~fitted(.) 
-#>  Parameter estimates:
-#>      const       prop 
-#> 2.23223593 0.01262367 
-
-  f_2_obs <- update(f_2, error_model = "obs")
-  f_nlme_sfo_sfo_obs <- nlme(f_2_obs["SFO-SFO", ])
-  print(f_nlme_sfo_sfo_obs)
-#> Kinetic nonlinear mixed-effects model fit by maximum likelihood
-#> 
-#> Structural model:
-#> d_parent/dt = - k_parent_sink * parent - k_parent_A1 * parent
-#> d_A1/dt = + k_parent_A1 * parent - k_A1_sink * A1
-#> 
-#> Data:
-#> 170 observations of 2 variable(s) grouped in 5 datasets
-#> 
-#> Log-likelihood: -473
-#> 
-#> Fixed effects:
-#>  list(parent_0 ~ 1, log_k_parent_sink ~ 1, log_k_parent_A1 ~ 1,      log_k_A1_sink ~ 1) 
-#>          parent_0 log_k_parent_sink   log_k_parent_A1     log_k_A1_sink 
-#>            87.976            -3.670            -4.164            -4.645 
-#> 
-#> Random effects:
-#>  Formula: list(parent_0 ~ 1, log_k_parent_sink ~ 1, log_k_parent_A1 ~ 1,      log_k_A1_sink ~ 1)
-#>  Level: ds
-#>  Structure: Diagonal
-#>         parent_0 log_k_parent_sink log_k_parent_A1 log_k_A1_sink Residual
-#> StdDev:    3.992             1.777           1.055        0.4821    6.483
-#> 
-#> Variance function:
-#>  Structure: Different standard deviations per stratum
-#>  Formula: ~1 | name 
-#>  Parameter estimates:
-#>    parent        A1 
-#> 1.0000000 0.2049994 
-  f_nlme_dfop_sfo_obs <- nlme(f_2_obs["DFOP-SFO", ],
-    control = list(pnlsMaxIter = 120, tolerance = 5e-4))
-
-  f_2_tc <- update(f_2, error_model = "tc")
-  # f_nlme_sfo_sfo_tc <- nlme(f_2_tc["SFO-SFO", ]) # No convergence with 50 iterations
-  # f_nlme_dfop_sfo_tc <- nlme(f_2_tc["DFOP-SFO", ],
-  #  control = list(pnlsMaxIter = 120, tolerance = 5e-4)) # Error in X[, fmap[[nm]]] <- gradnm
-
-  anova(f_nlme_dfop_sfo, f_nlme_dfop_sfo_obs)
-#>                     Model df      AIC      BIC    logLik   Test  L.Ratio
-#> f_nlme_dfop_sfo         1 13 843.8547 884.6201 -408.9274                
-#> f_nlme_dfop_sfo_obs     2 14 817.5338 861.4350 -394.7669 1 vs 2 28.32093
-#>                     p-value
-#> f_nlme_dfop_sfo            
-#> f_nlme_dfop_sfo_obs  <.0001
-
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
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-
-Fit nonlinear mixed models using nlmixr — nlmixr.mmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Fit nonlinear mixed models using nlmixr
      
-    Source: R/nlmixr.R
-    
-    
      
-
-    
      
-    
      This function uses nlmixr::nlmixr() as a backend for fitting nonlinear mixed
-effects models created from mmkin row objects using the Stochastic Approximation
-Expectation Maximisation algorithm (SAEM) or First Order Conditional
-Estimation with Interaction (FOCEI).
      
-    
      
-
-    
      
-    
      # S3 method for mmkin
-nlmixr(
-  object,
-  data = NULL,
-  est = NULL,
-  control = list(),
-  table = tableControl(),
-  error_model = object[[1]]$err_mod,
-  test_log_parms = TRUE,
-  conf.level = 0.6,
-  degparms_start = "auto",
-  eta_start = "auto",
-  ...,
-  save = NULL,
-  envir = parent.frame()
-)
-
-# S3 method for nlmixr.mmkin
-print(x, digits = max(3, getOption("digits") - 3), ...)
-
-nlmixr_model(
-  object,
-  est = c("saem", "focei"),
-  degparms_start = "auto",
-  eta_start = "auto",
-  test_log_parms = TRUE,
-  conf.level = 0.6,
-  error_model = object[[1]]$err_mod,
-  add_attributes = FALSE
-)
-
-nlmixr_data(object, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      An mmkin row object containing several fits of the same
-mkinmod model to different datasets
      
-
      data
      
-
      Not used, as the data are extracted from the mmkin row object
      
-
      est
      
-
      Estimation method passed to nlmixr::nlmixr
      
-
      control
      
-
      Passed to nlmixr::nlmixr
      
-
      table
      
-
      Passed to nlmixr::nlmixr
      
-
      error_model
      
-
      Optional argument to override the error model which is
-being set based on the error model used in the mmkin row object.
      
-
      test_log_parms
      
-
      If TRUE, an attempt is made to use more robust starting
-values for population parameters fitted as log parameters in mkin (like
-rate constants) by only considering rate constants that pass the t-test
-when calculating mean degradation parameters using mean_degparms.
      
-
      conf.level
      
-
      Possibility to adjust the required confidence level
-for parameter that are tested if requested by 'test_log_parms'.
      
-
      degparms_start
      
-
      Parameter values given as a named numeric vector will
-be used to override the starting values obtained from the 'mmkin' object.
      
-
      eta_start
      
-
      Standard deviations on the transformed scale given as a
-named numeric vector will be used to override the starting values obtained
-from the 'mmkin' object.
      
-
      ...
      
-
      Passed to nlmixr_model
      
-
      save
      
-
      Passed to nlmixr::nlmixr
      
-
      envir
      
-
      Passed to nlmixr::nlmixr
      
-
      x
      
-
      An nlmixr.mmkin object to print
      
-
      digits
      
-
      Number of digits to use for printing
      
-
      add_attributes
      
-
      Should the starting values used for degradation model
-parameters and their distribution and for the error model parameters
-be returned as attributes?
      
-
      
-    
      
-    
      Value
      
-    
      An S3 object of class 'nlmixr.mmkin', containing the fitted
-nlmixr::nlmixr object as a list component named 'nm'. The
-object also inherits from 'mixed.mmkin'.
-An function defining a model suitable for fitting with nlmixr::nlmixr.
-An dataframe suitable for use with nlmixr::nlmixr
      
-    
      
-    
      
-    
      Details
      
-    
      An mmkin row object is essentially a list of mkinfit objects that have been
-obtained by fitting the same model to a list of datasets using mkinfit.
      
-    
      
-    
-
-    
      
-    
      Examples
      
-    
      # \dontrun{
-ds <- lapply(experimental_data_for_UBA_2019[6:10],
- function(x) subset(x$data[c("name", "time", "value")]))
-names(ds) <- paste("Dataset", 6:10)
-
-f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP", "HS"), ds, quiet = TRUE, cores = 1)
-f_mmkin_parent_tc <- mmkin(c("SFO", "FOMC", "DFOP"), ds, error_model = "tc",
-  cores = 1, quiet = TRUE)
-
-library(nlmixr)
-#> 
-#> Attaching package: ‘nlmixr’
-#> The following object is masked from ‘package:mkin’:
-#> 
-#>     saem
-f_nlmixr_sfo_saem <- nlmixr(f_mmkin_parent["SFO", ], est = "saem",
-  control = saemControl(print = 0))
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#>  
-#> → generate SAEM model
-#> ✔ done
-#> RxODE 1.1.4 using 8 threads (see ?getRxThreads)
-#>   no cache: create with `rxCreateCache()`
-#> Calculating covariance matrix
-#> 
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> Calculating residuals/tables
-#> done
-f_nlmixr_sfo_focei <- nlmixr(f_mmkin_parent["SFO", ], est = "focei",
-  control = foceiControl(print = 0))
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → calculate jacobian
-#> 
-#> → calculate sensitivities
-#> 
-#> → calculate ∂(f)/∂(η)
-#> 
-#> → calculate ∂(R²)/∂(η)
-#> 
-#> → finding duplicate expressions in inner model...
-#> 
-#> → optimizing duplicate expressions in inner model...
-#> 
-#> → finding duplicate expressions in EBE model...
-#> 
-#> → optimizing duplicate expressions in EBE model...
-#> 
-#> → compiling inner model...
-#>  
-#> ✔ done
-#> → finding duplicate expressions in FD model...
-#> 
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> → compiling events FD model...
-#>  
-#> ✔ done
-#> calculating covariance matrix
-#> done
-#> Calculating residuals/tables
-#> done
-
-f_nlmixr_fomc_saem <- nlmixr(f_mmkin_parent["FOMC", ], est = "saem",
-  control = saemControl(print = 0))
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#>  
-#> → generate SAEM model
-#> ✔ done
-#> Calculating covariance matrix
-#> 
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> Calculating residuals/tables
-#> done
-f_nlmixr_fomc_focei <- nlmixr(f_mmkin_parent["FOMC", ], est = "focei",
-  control = foceiControl(print = 0))
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → calculate jacobian
-#> 
-#> → calculate sensitivities
-#> 
-#> → calculate ∂(f)/∂(η)
-#> 
-#> → calculate ∂(R²)/∂(η)
-#> 
-#> → finding duplicate expressions in inner model...
-#> 
-#> → optimizing duplicate expressions in inner model...
-#> 
-#> → finding duplicate expressions in EBE model...
-#> 
-#> → optimizing duplicate expressions in EBE model...
-#> 
-#> → compiling inner model...
-#>  
-#> ✔ done
-#> → finding duplicate expressions in FD model...
-#> 
-#> → optimizing duplicate expressions in FD model...
-#> 
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> → compiling events FD model...
-#>  
-#> ✔ done
-#> calculating covariance matrix
-#> done
-#> Calculating residuals/tables
-#> done
-
-f_nlmixr_dfop_saem <- nlmixr(f_mmkin_parent["DFOP", ], est = "saem",
-  control = saemControl(print = 0))
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#>  
-#> → generate SAEM model
-#> ✔ done
-#> Calculating covariance matrix
-#> 
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> Calculating residuals/tables
-#> done
-f_nlmixr_dfop_focei <- nlmixr(f_mmkin_parent["DFOP", ], est = "focei",
-  control = foceiControl(print = 0))
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → calculate jacobian
-#> 
-#> → calculate sensitivities
-#> 
-#> → calculate ∂(f)/∂(η)
-#> 
-#> → calculate ∂(R²)/∂(η)
-#> 
-#> → finding duplicate expressions in inner model...
-#> 
-#> → optimizing duplicate expressions in inner model...
-#> 
-#> → finding duplicate expressions in EBE model...
-#> 
-#> → optimizing duplicate expressions in EBE model...
-#> 
-#> → compiling inner model...
-#>  
-#> ✔ done
-#> → finding duplicate expressions in FD model...
-#> 
-#> → optimizing duplicate expressions in FD model...
-#> 
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> → compiling events FD model...
-#>  
-#> ✔ done
-#> calculating covariance matrix
-#> done
-#> Calculating residuals/tables
-#> done
-
-f_nlmixr_hs_saem <- nlmixr(f_mmkin_parent["HS", ], est = "saem",
-  control = saemControl(print = 0))
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#>  
-#> → generate SAEM model
-#> ✔ done
-#> Calculating covariance matrix
-#> 
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> Calculating residuals/tables
-#> done
-f_nlmixr_hs_focei <- nlmixr(f_mmkin_parent["HS", ], est = "focei",
-  control = foceiControl(print = 0))
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → calculate jacobian
-#> 
-#> → calculate sensitivities
-#> 
-#> → calculate ∂(f)/∂(η)
-#> 
-#> → calculate ∂(R²)/∂(η)
-#> 
-#> → finding duplicate expressions in inner model...
-#> 
-#> → optimizing duplicate expressions in inner model...
-#> 
-#> → finding duplicate expressions in EBE model...
-#> 
-#> → optimizing duplicate expressions in EBE model...
-#> 
-#> → compiling inner model...
-#>  
-#> ✔ done
-#> → finding duplicate expressions in FD model...
-#> 
-#> → optimizing duplicate expressions in FD model...
-#> 
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> → compiling events FD model...
-#>  
-#> ✔ done
-#> calculating covariance matrix
-#> done
-#> Calculating residuals/tables
-#> done
-
-f_nlmixr_fomc_saem_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "saem",
-  control = saemControl(print = 0))
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#>  
-#> Calculating covariance matrix
-#> 
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> Calculating residuals/tables
-#> done
-f_nlmixr_fomc_focei_tc <- nlmixr(f_mmkin_parent_tc["FOMC", ], est = "focei",
-  control = foceiControl(print = 0))
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → calculate jacobian
-#> 
-#> → calculate sensitivities
-#> 
-#> → calculate ∂(f)/∂(η)
-#> 
-#> → calculate ∂(R²)/∂(η)
-#> 
-#> → finding duplicate expressions in inner model...
-#> 
-#> → optimizing duplicate expressions in inner model...
-#> 
-#> → finding duplicate expressions in EBE model...
-#> 
-#> → optimizing duplicate expressions in EBE model...
-#> 
-#> → compiling inner model...
-#>  
-#> ✔ done
-#> → finding duplicate expressions in FD model...
-#> 
-#> → optimizing duplicate expressions in FD model...
-#> 
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> → compiling events FD model...
-#>  
-#> ✔ done
-#> done
-#> Calculating residuals/tables
-#> done
-
-AIC(
-  f_nlmixr_sfo_saem$nm, f_nlmixr_sfo_focei$nm,
-  f_nlmixr_fomc_saem$nm, f_nlmixr_fomc_focei$nm,
-  f_nlmixr_dfop_saem$nm, f_nlmixr_dfop_focei$nm,
-  f_nlmixr_hs_saem$nm, f_nlmixr_hs_focei$nm,
-  f_nlmixr_fomc_saem_tc$nm, f_nlmixr_fomc_focei_tc$nm)
-#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
-#> 
-#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
-#> 
-#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
-#> 
-#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
-#> 
-#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
-#> 
-#>                           df      AIC
-#> f_nlmixr_sfo_saem$nm       5 624.9492
-#> f_nlmixr_sfo_focei$nm      5 625.0695
-#> f_nlmixr_fomc_saem$nm      7 463.7577
-#> f_nlmixr_fomc_focei$nm     7 468.0861
-#> f_nlmixr_dfop_saem$nm      9 495.1980
-#> f_nlmixr_dfop_focei$nm     9 495.1072
-#> f_nlmixr_hs_saem$nm        9 531.0689
-#> f_nlmixr_hs_focei$nm       9 545.6728
-#> f_nlmixr_fomc_saem_tc$nm   8 462.1411
-#> f_nlmixr_fomc_focei_tc$nm  8 470.0745
-
-AIC(nlme(f_mmkin_parent["FOMC", ]))
-#> [1] 468.0781
-AIC(nlme(f_mmkin_parent["HS", ]))
-#> [1] 535.609
-
-# The FOCEI fit of FOMC with constant variance or the tc error model is best
-plot(f_nlmixr_fomc_saem_tc)
-
-
-sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"),
-  A1 = mkinsub("SFO"), quiet = TRUE)
-fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"),
-  A1 = mkinsub("SFO"), quiet = TRUE)
-dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
-  A1 = mkinsub("SFO"), quiet = TRUE)
-
-f_mmkin_const <- mmkin(list(
-    "SFO-SFO" = sfo_sfo, "FOMC-SFO" = fomc_sfo, "DFOP-SFO" = dfop_sfo),
-  ds, quiet = TRUE, error_model = "const")
-f_mmkin_obs <- mmkin(list(
-    "SFO-SFO" = sfo_sfo, "FOMC-SFO" = fomc_sfo, "DFOP-SFO" = dfop_sfo),
-  ds, quiet = TRUE, error_model = "obs")
-f_mmkin_tc <- mmkin(list(
-    "SFO-SFO" = sfo_sfo, "FOMC-SFO" = fomc_sfo, "DFOP-SFO" = dfop_sfo),
-  ds, quiet = TRUE, error_model = "tc")
-
-nlmixr_model(f_mmkin_const["SFO-SFO", ])
-#> Constant variance for more than one variable is not supported for est = 'saem'
-#> Changing the error model to 'obs' (variance by observed variable)
-#> function () 
-#> {
-#>     ini({
-#>         parent_0 = 87
-#>         eta.parent_0 ~ 4.2
-#>         log_k_parent = -3.2
-#>         eta.log_k_parent ~ 1.5
-#>         log_k_A1 = -4.6
-#>         eta.log_k_A1 ~ 0.56
-#>         f_parent_qlogis = -0.33
-#>         eta.f_parent_qlogis ~ 1.1
-#>         sigma_parent = 4.3
-#>         sigma_A1 = 4.3
-#>     })
-#>     model({
-#>         parent_0_model = parent_0 + eta.parent_0
-#>         parent(0) = parent_0_model
-#>         k_parent = exp(log_k_parent + eta.log_k_parent)
-#>         k_A1 = exp(log_k_A1 + eta.log_k_A1)
-#>         f_parent_to_A1 = expit(f_parent_qlogis + eta.f_parent_qlogis)
-#>         d/dt(parent) = -k_parent * parent
-#>         d/dt(A1) = +f_parent_to_A1 * k_parent * parent - k_A1 * 
-#>             A1
-#>         parent ~ add(sigma_parent)
-#>         A1 ~ add(sigma_A1)
-#>     })
-#> }
-#> <environment: 0x55556c775068>
-
-# A single constant variance is currently only possible with est = 'focei' in nlmixr
-f_nlmixr_sfo_sfo_focei_const <- nlmixr(f_mmkin_const["SFO-SFO", ], est = "focei")
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → calculate jacobian
-#> 
-#> → calculate sensitivities
-#> 
-#> → calculate ∂(f)/∂(η)
-#> 
-#> → calculate ∂(R²)/∂(η)
-#> 
-#> → finding duplicate expressions in inner model...
-#> 
-#> → optimizing duplicate expressions in inner model...
-#> 
-#> → finding duplicate expressions in EBE model...
-#> 
-#> → optimizing duplicate expressions in EBE model...
-#> 
-#> → compiling inner model...
-#>  
-#> ✔ done
-#> → finding duplicate expressions in FD model...
-#> 
-#> → optimizing duplicate expressions in FD model...
-#> 
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> → compiling events FD model...
-#>  
-#> ✔ done
-#> Needed Covariates:
-#> [1] "CMT"
-#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> |    #| Objective Fun |  parent_0 |log_k_parent |  log_k_A1 |f_parent_qlogis |
-#> |.....................|     sigma |        o1 |        o2 |        o3 |
-#> |.....................|        o4 |...........|...........|...........|
-#> |    1|     756.61847 |     1.000 |   -0.9694 |    -1.000 |   -0.9068 |
-#> |.....................|   -0.8057 |   -0.8843 |   -0.8798 |   -0.8743 |
-#> |.....................|   -0.8782 |...........|...........|...........|
-#> |    U|     756.61847 |     87.00 |    -3.200 |    -4.600 |   -0.3300 |
-#> |.....................|     4.300 |    0.6985 |    0.9036 |     1.156 |
-#> |.....................|    0.9765 |...........|...........|...........|
-#> |    X|     756.61847 |     87.00 |   0.04076 |   0.01005 |    0.4182 |
-#> |.....................|     4.300 |    0.6985 |    0.9036 |     1.156 |
-#> |.....................|    0.9765 |...........|...........|...........|
-#> |    G|    Gill Diff. |     104.1 |   0.02915 |    0.3320 |    0.4427 |
-#> |.....................|    -29.46 |     6.499 |     3.260 |    -8.158 |
-#> |.....................|    -5.501 |...........|...........|...........|
-#> |    2|     4014.8405 |   0.04387 |   -0.9697 |    -1.003 |   -0.9108 |
-#> |.....................|   -0.5352 |   -0.9440 |   -0.9098 |   -0.7994 |
-#> |.....................|   -0.8277 |...........|...........|...........|
-#> |    U|     4014.8405 |     3.817 |    -3.200 |    -4.603 |   -0.3313 |
-#> |.....................|     4.882 |    0.6569 |    0.8766 |     1.243 |
-#> |.....................|     1.026 |...........|...........|...........|
-#> |    X|     4014.8405 |     3.817 |   0.04075 |   0.01002 |    0.4179 |
-#> |.....................|     4.882 |    0.6569 |    0.8766 |     1.243 |
-#> |.....................|     1.026 |...........|...........|...........|
-#> |    3|     784.09766 |    0.9044 |   -0.9695 |    -1.000 |   -0.9072 |
-#> |.....................|   -0.7786 |   -0.8903 |   -0.8828 |   -0.8668 |
-#> |.....................|   -0.8732 |...........|...........|...........|
-#> |    U|     784.09766 |     78.68 |    -3.200 |    -4.600 |   -0.3301 |
-#> |.....................|     4.358 |    0.6944 |    0.9009 |     1.165 |
-#> |.....................|    0.9814 |...........|...........|...........|
-#> |    X|     784.09766 |     78.68 |   0.04076 |   0.01005 |    0.4182 |
-#> |.....................|     4.358 |    0.6944 |    0.9009 |     1.165 |
-#> |.....................|    0.9814 |...........|...........|...........|
-#> |    4|     755.85897 |    0.9864 |   -0.9694 |    -1.000 |   -0.9068 |
-#> |.....................|   -0.8018 |   -0.8852 |   -0.8803 |   -0.8733 |
-#> |.....................|   -0.8775 |...........|...........|...........|
-#> |    U|     755.85897 |     85.82 |    -3.200 |    -4.600 |   -0.3300 |
-#> |.....................|     4.308 |    0.6979 |    0.9032 |     1.157 |
-#> |.....................|    0.9772 |...........|...........|...........|
-#> |    X|     755.85897 |     85.82 |   0.04076 |   0.01005 |    0.4182 |
-#> |.....................|     4.308 |    0.6979 |    0.9032 |     1.157 |
-#> |.....................|    0.9772 |...........|...........|...........|
-#> |    F| Forward Diff. |    -10.67 |    0.1182 |    0.2197 |    0.3686 |
-#> |.....................|    -28.82 |     3.860 |     3.200 |    -8.294 |
-#> |.....................|    -5.254 |...........|...........|...........|
-#> |    5|     755.50135 |    0.9911 |   -0.9695 |    -1.000 |   -0.9070 |
-#> |.....................|   -0.7893 |   -0.8868 |   -0.8816 |   -0.8697 |
-#> |.....................|   -0.8752 |...........|...........|...........|
-#> |    U|     755.50135 |     86.22 |    -3.200 |    -4.600 |   -0.3301 |
-#> |.....................|     4.335 |    0.6968 |    0.9020 |     1.161 |
-#> |.....................|    0.9794 |...........|...........|...........|
-#> |    X|     755.50135 |     86.22 |   0.04076 |   0.01005 |    0.4182 |
-#> |.....................|     4.335 |    0.6968 |    0.9020 |     1.161 |
-#> |.....................|    0.9794 |...........|...........|...........|
-#> |    6|     755.34910 |    0.9966 |   -0.9695 |    -1.000 |   -0.9072 |
-#> |.....................|   -0.7744 |   -0.8888 |   -0.8833 |   -0.8654 |
-#> |.....................|   -0.8725 |...........|...........|...........|
-#> |    U|      755.3491 |     86.70 |    -3.200 |    -4.600 |   -0.3301 |
-#> |.....................|     4.367 |    0.6954 |    0.9005 |     1.166 |
-#> |.....................|    0.9820 |...........|...........|...........|
-#> |    X|      755.3491 |     86.70 |   0.04076 |   0.01005 |    0.4182 |
-#> |.....................|     4.367 |    0.6954 |    0.9005 |     1.166 |
-#> |.....................|    0.9820 |...........|...........|...........|
-#> |    F| Forward Diff. |     73.92 |   0.04965 |    0.3063 |    0.4373 |
-#> |.....................|    -23.46 |     5.143 |     2.934 |    -7.746 |
-#> |.....................|    -5.165 |...........|...........|...........|
-#> |    7|     754.44379 |    0.9831 |   -0.9697 |    -1.001 |   -0.9076 |
-#> |.....................|   -0.7489 |   -0.8930 |   -0.8865 |   -0.8566 |
-#> |.....................|   -0.8669 |...........|...........|...........|
-#> |    U|     754.44379 |     85.53 |    -3.200 |    -4.601 |   -0.3303 |
-#> |.....................|     4.422 |    0.6925 |    0.8975 |     1.176 |
-#> |.....................|    0.9875 |...........|...........|...........|
-#> |    X|     754.44379 |     85.53 |   0.04075 |   0.01005 |    0.4182 |
-#> |.....................|     4.422 |    0.6925 |    0.8975 |     1.176 |
-#> |.....................|    0.9875 |...........|...........|...........|
-#> |    F| Forward Diff. |    -36.39 |    0.1354 |    0.1953 |    0.3724 |
-#> |.....................|    -19.20 |     3.020 |     2.621 |    -7.506 |
-#> |.....................|    -4.671 |...........|...........|...........|
-#> |    8|     753.82350 |    0.9908 |   -0.9699 |    -1.001 |   -0.9085 |
-#> |.....................|   -0.7249 |   -0.8992 |   -0.8910 |   -0.8427 |
-#> |.....................|   -0.8580 |...........|...........|...........|
-#> |    U|      753.8235 |     86.20 |    -3.200 |    -4.601 |   -0.3306 |
-#> |.....................|     4.474 |    0.6881 |    0.8935 |     1.193 |
-#> |.....................|    0.9962 |...........|...........|...........|
-#> |    X|      753.8235 |     86.20 |   0.04074 |   0.01004 |    0.4181 |
-#> |.....................|     4.474 |    0.6881 |    0.8935 |     1.193 |
-#> |.....................|    0.9962 |...........|...........|...........|
-#> |    F| Forward Diff. |     25.33 |   0.08213 |    0.2542 |    0.4339 |
-#> |.....................|    -14.89 |     3.322 |     2.230 |    -6.934 |
-#> |.....................|    -4.324 |...........|...........|...........|
-#> |    9|     753.42397 |    0.9836 |   -0.9702 |    -1.002 |   -0.9101 |
-#> |.....................|   -0.7094 |   -0.9058 |   -0.8962 |   -0.8215 |
-#> |.....................|   -0.8457 |...........|...........|...........|
-#> |    U|     753.42397 |     85.57 |    -3.201 |    -4.602 |   -0.3311 |
-#> |.....................|     4.507 |    0.6835 |    0.8888 |     1.217 |
-#> |.....................|     1.008 |...........|...........|...........|
-#> |    X|     753.42397 |     85.57 |   0.04073 |   0.01003 |    0.4180 |
-#> |.....................|     4.507 |    0.6835 |    0.8888 |     1.217 |
-#> |.....................|     1.008 |...........|...........|...........|
-#> |    F| Forward Diff. |    -31.38 |    0.1220 |    0.1752 |    0.4111 |
-#> |.....................|    -12.58 |     2.402 |     1.769 |    -6.044 |
-#> |.....................|    -3.541 |...........|...........|...........|
-#> |   10|     753.10125 |    0.9902 |   -0.9707 |    -1.003 |   -0.9128 |
-#> |.....................|   -0.7033 |   -0.9147 |   -0.8999 |   -0.7966 |
-#> |.....................|   -0.8328 |...........|...........|...........|
-#> |    U|     753.10125 |     86.15 |    -3.201 |    -4.603 |   -0.3320 |
-#> |.....................|     4.520 |    0.6773 |    0.8855 |     1.246 |
-#> |.....................|     1.021 |...........|...........|...........|
-#> |    X|     753.10125 |     86.15 |   0.04071 |   0.01002 |    0.4178 |
-#> |.....................|     4.520 |    0.6773 |    0.8855 |     1.246 |
-#> |.....................|     1.021 |...........|...........|...........|
-#> |    F| Forward Diff. |     18.19 |   0.07644 |    0.2005 |    0.4693 |
-#> |.....................|    -11.34 |     2.660 |     1.470 |    -4.866 |
-#> |.....................|    -2.908 |...........|...........|...........|
-#> |   11|     752.83558 |    0.9856 |   -0.9716 |    -1.004 |   -0.9194 |
-#> |.....................|   -0.6931 |   -0.9294 |   -0.8999 |   -0.7740 |
-#> |.....................|   -0.8246 |...........|...........|...........|
-#> |    U|     752.83558 |     85.75 |    -3.202 |    -4.604 |   -0.3342 |
-#> |.....................|     4.542 |    0.6671 |    0.8855 |     1.272 |
-#> |.....................|     1.029 |...........|...........|...........|
-#> |    X|     752.83558 |     85.75 |   0.04067 |   0.01001 |    0.4172 |
-#> |.....................|     4.542 |    0.6671 |    0.8855 |     1.272 |
-#> |.....................|     1.029 |...........|...........|...........|
-#> |    F| Forward Diff. |    -17.42 |   0.09700 |    0.1175 |    0.4453 |
-#> |.....................|    -9.793 |     1.829 |     1.489 |    -3.997 |
-#> |.....................|    -2.337 |...........|...........|...........|
-#> |   12|     752.64046 |    0.9898 |   -0.9731 |    -1.005 |   -0.9331 |
-#> |.....................|   -0.6718 |   -0.9413 |   -0.9101 |   -0.7759 |
-#> |.....................|   -0.8318 |...........|...........|...........|
-#> |    U|     752.64046 |     86.12 |    -3.204 |    -4.605 |   -0.3387 |
-#> |.....................|     4.588 |    0.6587 |    0.8763 |     1.270 |
-#> |.....................|     1.022 |...........|...........|...........|
-#> |    X|     752.64046 |     86.12 |   0.04061 |   0.01000 |    0.4161 |
-#> |.....................|     4.588 |    0.6587 |    0.8763 |     1.270 |
-#> |.....................|     1.022 |...........|...........|...........|
-#> |    F| Forward Diff. |     12.96 |   0.06018 |    0.1556 |    0.4415 |
-#> |.....................|    -6.445 |     1.822 |    0.6282 |    -4.092 |
-#> |.....................|    -2.761 |...........|...........|...........|
-#> |   13|     752.52461 |    0.9874 |   -0.9741 |    -1.006 |   -0.9430 |
-#> |.....................|   -0.6755 |   -0.9483 |   -0.9069 |   -0.7553 |
-#> |.....................|   -0.8127 |...........|...........|...........|
-#> |    U|     752.52461 |     85.90 |    -3.205 |    -4.606 |   -0.3420 |
-#> |.....................|     4.580 |    0.6538 |    0.8792 |     1.294 |
-#> |.....................|     1.040 |...........|...........|...........|
-#> |    X|     752.52461 |     85.90 |   0.04057 |  0.009996 |    0.4153 |
-#> |.....................|     4.580 |    0.6538 |    0.8792 |     1.294 |
-#> |.....................|     1.040 |...........|...........|...........|
-#> |    F| Forward Diff. |    -5.319 |   0.06758 |    0.1323 |    0.4528 |
-#> |.....................|    -7.018 |     1.348 |    0.9128 |    -3.312 |
-#> |.....................|    -1.706 |...........|...........|...........|
-#> |   14|     752.47650 |    0.9920 |   -0.9750 |    -1.008 |   -0.9578 |
-#> |.....................|   -0.6735 |   -0.9481 |   -0.9014 |   -0.7293 |
-#> |.....................|   -0.8100 |...........|...........|...........|
-#> |    U|      752.4765 |     86.30 |    -3.206 |    -4.608 |   -0.3468 |
-#> |.....................|     4.584 |    0.6539 |    0.8841 |     1.324 |
-#> |.....................|     1.043 |...........|...........|...........|
-#> |    X|      752.4765 |     86.30 |   0.04054 |  0.009974 |    0.4142 |
-#> |.....................|     4.584 |    0.6539 |    0.8841 |     1.324 |
-#> |.....................|     1.043 |...........|...........|...........|
-#> |    F| Forward Diff. |     26.38 |   0.03719 |   0.08701 |    0.4621 |
-#> |.....................|    -6.642 |     1.808 |     1.401 |    -2.463 |
-#> |.....................|    -1.595 |...........|...........|...........|
-#> |   15|     752.37074 |    0.9880 |   -0.9759 |    -1.009 |   -0.9778 |
-#> |.....................|   -0.6665 |   -0.9465 |   -0.9156 |   -0.7192 |
-#> |.....................|   -0.8239 |...........|...........|...........|
-#> |    U|     752.37074 |     85.96 |    -3.206 |    -4.609 |   -0.3534 |
-#> |.....................|     4.599 |    0.6551 |    0.8713 |     1.335 |
-#> |.....................|     1.030 |...........|...........|...........|
-#> |    X|     752.37074 |     85.96 |   0.04050 |  0.009963 |    0.4125 |
-#> |.....................|     4.599 |    0.6551 |    0.8713 |     1.335 |
-#> |.....................|     1.030 |...........|...........|...........|
-#> |    F| Forward Diff. |   -0.8866 |   0.05090 |  -0.01541 |    0.3812 |
-#> |.....................|    -5.712 |     1.436 |    0.1646 |    -2.191 |
-#> |.....................|    -2.247 |...........|...........|...........|
-#> |   16|     752.26949 |    0.9921 |   -0.9761 |    -1.009 |   -0.9796 |
-#> |.....................|   -0.6402 |   -0.9531 |   -0.9164 |   -0.7091 |
-#> |.....................|   -0.8135 |...........|...........|...........|
-#> |    U|     752.26949 |     86.31 |    -3.207 |    -4.609 |   -0.3540 |
-#> |.....................|     4.656 |    0.6505 |    0.8706 |     1.347 |
-#> |.....................|     1.040 |...........|...........|...........|
-#> |    X|     752.26949 |     86.31 |   0.04049 |  0.009963 |    0.4124 |
-#> |.....................|     4.656 |    0.6505 |    0.8706 |     1.347 |
-#> |.....................|     1.040 |...........|...........|...........|
-#> |    F| Forward Diff. |     26.82 |   0.02710 |   0.03892 |    0.4267 |
-#> |.....................|    -2.005 |     1.500 |    0.1022 |    -1.862 |
-#> |.....................|    -1.773 |...........|...........|...........|
-#> |   17|     752.20271 |    0.9873 |   -0.9768 |    -1.006 |   -0.9927 |
-#> |.....................|   -0.6361 |   -0.9677 |   -0.9007 |   -0.7162 |
-#> |.....................|   -0.7982 |...........|...........|...........|
-#> |    U|     752.20271 |     85.89 |    -3.207 |    -4.606 |   -0.3584 |
-#> |.....................|     4.664 |    0.6403 |    0.8848 |     1.339 |
-#> |.....................|     1.055 |...........|...........|...........|
-#> |    X|     752.20271 |     85.89 |   0.04046 |  0.009992 |    0.4114 |
-#> |.....................|     4.664 |    0.6403 |    0.8848 |     1.339 |
-#> |.....................|     1.055 |...........|...........|...........|
-#> |    F| Forward Diff. |    -7.259 |   0.05081 |    0.1320 |    0.4166 |
-#> |.....................|    -1.497 |    0.4663 |     1.471 |    -1.984 |
-#> |.....................|   -0.9590 |...........|...........|...........|
-#> |   18|     752.16826 |    0.9883 |   -0.9778 |    -1.006 |    -1.005 |
-#> |.....................|   -0.6437 |   -0.9795 |   -0.9210 |   -0.7076 |
-#> |.....................|   -0.7873 |...........|...........|...........|
-#> |    U|     752.16826 |     85.98 |    -3.208 |    -4.606 |   -0.3626 |
-#> |.....................|     4.648 |    0.6320 |    0.8664 |     1.349 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|     752.16826 |     85.98 |   0.04042 |  0.009989 |    0.4103 |
-#> |.....................|     4.648 |    0.6320 |    0.8664 |     1.349 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |    -1.732 |   0.03428 |    0.1666 |    0.4265 |
-#> |.....................|    -2.413 |    0.2526 |   -0.2557 |    -1.689 |
-#> |.....................|   -0.3553 |...........|...........|...........|
-#> |   19|     752.25223 |    0.9952 |   -0.9788 |    -1.010 |    -1.023 |
-#> |.....................|   -0.6370 |   -0.9826 |   -0.9156 |   -0.6853 |
-#> |.....................|   -0.7912 |...........|...........|...........|
-#> |    U|     752.25223 |     86.58 |    -3.209 |    -4.610 |   -0.3684 |
-#> |.....................|     4.663 |    0.6299 |    0.8713 |     1.374 |
-#> |.....................|     1.061 |...........|...........|...........|
-#> |    X|     752.25223 |     86.58 |   0.04038 |  0.009949 |    0.4089 |
-#> |.....................|     4.663 |    0.6299 |    0.8713 |     1.374 |
-#> |.....................|     1.061 |...........|...........|...........|
-#> |   20|     752.18605 |    0.9920 |   -0.9778 |    -1.007 |    -1.006 |
-#> |.....................|   -0.6387 |   -0.9801 |   -0.9204 |   -0.7040 |
-#> |.....................|   -0.7866 |...........|...........|...........|
-#> |    U|     752.18605 |     86.30 |    -3.208 |    -4.607 |   -0.3629 |
-#> |.....................|     4.659 |    0.6316 |    0.8669 |     1.353 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    X|     752.18605 |     86.30 |   0.04042 |  0.009985 |    0.4103 |
-#> |.....................|     4.659 |    0.6316 |    0.8669 |     1.353 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |   21|     752.16428 |    0.9894 |   -0.9778 |    -1.006 |    -1.006 |
-#> |.....................|   -0.6422 |   -0.9797 |   -0.9208 |   -0.7065 |
-#> |.....................|   -0.7871 |...........|...........|...........|
-#> |    U|     752.16428 |     86.08 |    -3.208 |    -4.606 |   -0.3627 |
-#> |.....................|     4.651 |    0.6319 |    0.8666 |     1.350 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|     752.16428 |     86.08 |   0.04042 |  0.009988 |    0.4103 |
-#> |.....................|     4.651 |    0.6319 |    0.8666 |     1.350 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |     5.144 |   0.02886 |    0.1726 |    0.4333 |
-#> |.....................|    -2.192 |    0.3285 |   -0.2407 |    -1.661 |
-#> |.....................|   -0.3568 |...........|...........|...........|
-#> |   22|     752.15919 |    0.9884 |   -0.9779 |    -1.007 |    -1.007 |
-#> |.....................|   -0.6420 |   -0.9798 |   -0.9206 |   -0.7051 |
-#> |.....................|   -0.7874 |...........|...........|...........|
-#> |    U|     752.15919 |     85.99 |    -3.208 |    -4.607 |   -0.3630 |
-#> |.....................|     4.652 |    0.6319 |    0.8668 |     1.352 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|     752.15919 |     85.99 |   0.04042 |  0.009985 |    0.4102 |
-#> |.....................|     4.652 |    0.6319 |    0.8668 |     1.352 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |    -1.486 |   0.03361 |    0.1549 |    0.4244 |
-#> |.....................|    -2.177 |    0.2364 |   -0.2213 |    -1.616 |
-#> |.....................|   -0.3570 |...........|...........|...........|
-#> |   23|     752.15545 |    0.9894 |   -0.9779 |    -1.007 |    -1.007 |
-#> |.....................|   -0.6405 |   -0.9799 |   -0.9204 |   -0.7040 |
-#> |.....................|   -0.7872 |...........|...........|...........|
-#> |    U|     752.15545 |     86.07 |    -3.208 |    -4.607 |   -0.3631 |
-#> |.....................|     4.655 |    0.6318 |    0.8669 |     1.353 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|     752.15545 |     86.07 |   0.04042 |  0.009984 |    0.4102 |
-#> |.....................|     4.655 |    0.6318 |    0.8669 |     1.353 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |     4.936 |   0.02854 |    0.1600 |    0.4306 |
-#> |.....................|    -1.962 |    0.3065 |   -0.2063 |    -1.586 |
-#> |.....................|   -0.3570 |...........|...........|...........|
-#> |   24|     752.15077 |    0.9884 |   -0.9779 |    -1.007 |    -1.008 |
-#> |.....................|   -0.6403 |   -0.9800 |   -0.9202 |   -0.7026 |
-#> |.....................|   -0.7875 |...........|...........|...........|
-#> |    U|     752.15077 |     85.99 |    -3.209 |    -4.607 |   -0.3635 |
-#> |.....................|     4.656 |    0.6317 |    0.8672 |     1.355 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|     752.15077 |     85.99 |   0.04042 |  0.009981 |    0.4101 |
-#> |.....................|     4.656 |    0.6317 |    0.8672 |     1.355 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |    -1.303 |   0.03292 |    0.1430 |    0.4220 |
-#> |.....................|    -1.955 |    0.2207 |   -0.1874 |    -1.542 |
-#> |.....................|   -0.3581 |...........|...........|...........|
-#> |   25|     752.14731 |    0.9893 |   -0.9780 |    -1.007 |    -1.009 |
-#> |.....................|   -0.6389 |   -0.9801 |   -0.9200 |   -0.7014 |
-#> |.....................|   -0.7873 |...........|...........|...........|
-#> |    U|     752.14731 |     86.07 |    -3.209 |    -4.607 |   -0.3637 |
-#> |.....................|     4.659 |    0.6316 |    0.8673 |     1.356 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|     752.14731 |     86.07 |   0.04042 |  0.009980 |    0.4101 |
-#> |.....................|     4.659 |    0.6316 |    0.8673 |     1.356 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |     4.764 |   0.02806 |    0.1473 |    0.4277 |
-#> |.....................|    -1.749 |    0.2865 |   -0.1727 |    -1.510 |
-#> |.....................|   -0.3572 |...........|...........|...........|
-#> |   26|     752.14299 |    0.9884 |   -0.9780 |    -1.007 |    -1.010 |
-#> |.....................|   -0.6388 |   -0.9801 |   -0.9198 |   -0.7000 |
-#> |.....................|   -0.7876 |...........|...........|...........|
-#> |    U|     752.14299 |     85.99 |    -3.209 |    -4.607 |   -0.3641 |
-#> |.....................|     4.659 |    0.6316 |    0.8675 |     1.358 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|     752.14299 |     85.99 |   0.04041 |  0.009978 |    0.4100 |
-#> |.....................|     4.659 |    0.6316 |    0.8675 |     1.358 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |    -1.130 |   0.03192 |    0.1311 |    0.4194 |
-#> |.....................|    -1.750 |    0.2064 |   -0.1542 |    -1.466 |
-#> |.....................|   -0.3587 |...........|...........|...........|
-#> |   27|     752.13982 |    0.9893 |   -0.9781 |    -1.008 |    -1.010 |
-#> |.....................|   -0.6374 |   -0.9803 |   -0.9196 |   -0.6987 |
-#> |.....................|   -0.7873 |...........|...........|...........|
-#> |    U|     752.13982 |     86.07 |    -3.209 |    -4.608 |   -0.3642 |
-#> |.....................|     4.662 |    0.6315 |    0.8676 |     1.359 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|     752.13982 |     86.07 |   0.04041 |  0.009977 |    0.4099 |
-#> |.....................|     4.662 |    0.6315 |    0.8676 |     1.359 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |     4.635 |   0.02760 |    0.1350 |    0.4248 |
-#> |.....................|    -1.550 |    0.2683 |   -0.1407 |    -1.433 |
-#> |.....................|   -0.3557 |...........|...........|...........|
-#> |   28|     752.13580 |    0.9884 |   -0.9782 |    -1.008 |    -1.012 |
-#> |.....................|   -0.6373 |   -0.9803 |   -0.9194 |   -0.6973 |
-#> |.....................|   -0.7876 |...........|...........|...........|
-#> |    U|      752.1358 |     85.99 |    -3.209 |    -4.608 |   -0.3647 |
-#> |.....................|     4.662 |    0.6315 |    0.8678 |     1.361 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|      752.1358 |     85.99 |   0.04041 |  0.009975 |    0.4098 |
-#> |.....................|     4.662 |    0.6315 |    0.8678 |     1.361 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |   -0.9657 |   0.03147 |    0.1207 |    0.4166 |
-#> |.....................|    -1.557 |    0.1931 |   -0.1227 |    -1.391 |
-#> |.....................|   -0.3574 |...........|...........|...........|
-#> |   29|     752.13295 |    0.9893 |   -0.9782 |    -1.008 |    -1.012 |
-#> |.....................|   -0.6359 |   -0.9805 |   -0.9193 |   -0.6961 |
-#> |.....................|   -0.7873 |...........|...........|...........|
-#> |    U|     752.13295 |     86.07 |    -3.209 |    -4.608 |   -0.3648 |
-#> |.....................|     4.665 |    0.6314 |    0.8679 |     1.362 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|     752.13295 |     86.07 |   0.04041 |  0.009973 |    0.4098 |
-#> |.....................|     4.665 |    0.6314 |    0.8679 |     1.362 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |     4.554 |   0.02702 |    0.1245 |    0.4220 |
-#> |.....................|    -1.357 |    0.2511 |   -0.1114 |    -1.356 |
-#> |.....................|   -0.3512 |...........|...........|...........|
-#> |   30|     752.12919 |    0.9885 |   -0.9783 |    -1.008 |    -1.014 |
-#> |.....................|   -0.6359 |   -0.9804 |   -0.9191 |   -0.6947 |
-#> |.....................|   -0.7876 |...........|...........|...........|
-#> |    U|     752.12919 |     86.00 |    -3.209 |    -4.608 |   -0.3653 |
-#> |.....................|     4.665 |    0.6314 |    0.8681 |     1.364 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|     752.12919 |     86.00 |   0.04040 |  0.009972 |    0.4097 |
-#> |.....................|     4.665 |    0.6314 |    0.8681 |     1.364 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |   -0.8077 |   0.03076 |    0.1104 |    0.4140 |
-#> |.....................|    -1.370 |    0.1799 |  -0.09417 |    -1.307 |
-#> |.....................|   -0.3529 |...........|...........|...........|
-#> |   31|     752.12656 |    0.9893 |   -0.9783 |    -1.008 |    -1.014 |
-#> |.....................|   -0.6345 |   -0.9806 |   -0.9190 |   -0.6934 |
-#> |.....................|   -0.7872 |...........|...........|...........|
-#> |    U|     752.12656 |     86.07 |    -3.209 |    -4.608 |   -0.3654 |
-#> |.....................|     4.668 |    0.6313 |    0.8682 |     1.365 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|     752.12656 |     86.07 |   0.04040 |  0.009970 |    0.4096 |
-#> |.....................|     4.668 |    0.6313 |    0.8682 |     1.365 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |     4.375 |   0.02651 |    0.1140 |    0.4191 |
-#> |.....................|    -1.173 |    0.2330 |  -0.08481 |    -1.281 |
-#> |.....................|   -0.3435 |...........|...........|...........|
-#> |   32|     752.12310 |    0.9885 |   -0.9784 |    -1.008 |    -1.016 |
-#> |.....................|   -0.6345 |   -0.9806 |   -0.9188 |   -0.6922 |
-#> |.....................|   -0.7875 |...........|...........|...........|
-#> |    U|      752.1231 |     86.00 |    -3.209 |    -4.608 |   -0.3659 |
-#> |.....................|     4.668 |    0.6313 |    0.8684 |     1.367 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|      752.1231 |     86.00 |   0.04040 |  0.009969 |    0.4095 |
-#> |.....................|     4.668 |    0.6313 |    0.8684 |     1.367 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |   -0.6515 |   0.02994 |    0.1012 |    0.4113 |
-#> |.....................|    -1.192 |    0.1669 |  -0.06829 |    -1.233 |
-#> |.....................|   -0.3455 |...........|...........|...........|
-#> |   33|     752.12055 |    0.9892 |   -0.9784 |    -1.008 |    -1.016 |
-#> |.....................|   -0.6332 |   -0.9808 |   -0.9187 |   -0.6908 |
-#> |.....................|   -0.7871 |...........|...........|...........|
-#> |    U|     752.12055 |     86.06 |    -3.209 |    -4.608 |   -0.3661 |
-#> |.....................|     4.671 |    0.6312 |    0.8685 |     1.368 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|     752.12055 |     86.06 |   0.04040 |  0.009968 |    0.4095 |
-#> |.....................|     4.671 |    0.6312 |    0.8685 |     1.368 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |     3.998 |   0.02610 |    0.1041 |    0.4159 |
-#> |.....................|    -1.002 |    0.2127 |  -0.06061 |    -1.206 |
-#> |.....................|   -0.3333 |...........|...........|...........|
-#> |   34|     752.11747 |    0.9885 |   -0.9785 |    -1.009 |    -1.018 |
-#> |.....................|   -0.6332 |   -0.9807 |   -0.9185 |   -0.6896 |
-#> |.....................|   -0.7874 |...........|...........|...........|
-#> |    U|     752.11747 |     86.00 |    -3.209 |    -4.609 |   -0.3666 |
-#> |.....................|     4.671 |    0.6312 |    0.8687 |     1.370 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|     752.11747 |     86.00 |   0.04039 |  0.009966 |    0.4094 |
-#> |.....................|     4.671 |    0.6312 |    0.8687 |     1.370 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |   -0.5772 |   0.02918 |   0.09258 |    0.4085 |
-#> |.....................|    -1.024 |    0.1535 |  -0.04467 |    -1.159 |
-#> |.....................|   -0.3360 |...........|...........|...........|
-#> |   35|     752.11522 |    0.9892 |   -0.9785 |    -1.009 |    -1.018 |
-#> |.....................|   -0.6319 |   -0.9809 |   -0.9185 |   -0.6881 |
-#> |.....................|   -0.7870 |...........|...........|...........|
-#> |    U|     752.11522 |     86.06 |    -3.209 |    -4.609 |   -0.3668 |
-#> |.....................|     4.674 |    0.6311 |    0.8687 |     1.371 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    X|     752.11522 |     86.06 |   0.04039 |  0.009965 |    0.4093 |
-#> |.....................|     4.674 |    0.6311 |    0.8687 |     1.371 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    F| Forward Diff. |     3.959 |   0.02535 |   0.09612 |    0.4130 |
-#> |.....................|   -0.8451 |    0.1980 |  -0.03883 |    -1.121 |
-#> |.....................|   -0.3219 |...........|...........|...........|
-#> |   36|     752.11234 |    0.9885 |   -0.9786 |    -1.009 |    -1.020 |
-#> |.....................|   -0.6320 |   -0.9808 |   -0.9183 |   -0.6870 |
-#> |.....................|   -0.7872 |...........|...........|...........|
-#> |    U|     752.11234 |     86.00 |    -3.209 |    -4.609 |   -0.3673 |
-#> |.....................|     4.673 |    0.6311 |    0.8689 |     1.373 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    X|     752.11234 |     86.00 |   0.04039 |  0.009964 |    0.4092 |
-#> |.....................|     4.673 |    0.6311 |    0.8689 |     1.373 |
-#> |.....................|     1.065 |...........|...........|...........|
-#> |    F| Forward Diff. |   -0.5042 |   0.02791 |   0.08363 |    0.4056 |
-#> |.....................|   -0.8741 |    0.1402 |  -0.02542 |    -1.088 |
-#> |.....................|   -0.3257 |...........|...........|...........|
-#> |   37|     752.11033 |    0.9892 |   -0.9787 |    -1.009 |    -1.020 |
-#> |.....................|   -0.6308 |   -0.9810 |   -0.9182 |   -0.6855 |
-#> |.....................|   -0.7868 |...........|...........|...........|
-#> |    U|     752.11033 |     86.06 |    -3.209 |    -4.609 |   -0.3675 |
-#> |.....................|     4.676 |    0.6310 |    0.8689 |     1.374 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    X|     752.11033 |     86.06 |   0.04039 |  0.009963 |    0.4091 |
-#> |.....................|     4.676 |    0.6310 |    0.8689 |     1.374 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    F| Forward Diff. |     3.874 |   0.02465 |   0.08719 |    0.4100 |
-#> |.....................|   -0.7032 |    0.1835 |  -0.01978 |    -1.047 |
-#> |.....................|   -0.3084 |...........|...........|...........|
-#> |   38|     752.10764 |    0.9885 |   -0.9787 |    -1.009 |    -1.022 |
-#> |.....................|   -0.6309 |   -0.9810 |   -0.9181 |   -0.6844 |
-#> |.....................|   -0.7870 |...........|...........|...........|
-#> |    U|     752.10764 |     86.00 |    -3.209 |    -4.609 |   -0.3681 |
-#> |.....................|     4.676 |    0.6310 |    0.8691 |     1.376 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    X|     752.10764 |     86.00 |   0.04038 |  0.009962 |    0.4090 |
-#> |.....................|     4.676 |    0.6310 |    0.8691 |     1.376 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    F| Forward Diff. |   -0.4131 |   0.02699 |   0.07721 |    0.4026 |
-#> |.....................|   -0.7354 |    0.1282 | -0.007503 |    -1.011 |
-#> |.....................|   -0.3125 |...........|...........|...........|
-#> |   39|     752.10572 |    0.9892 |   -0.9788 |    -1.009 |    -1.023 |
-#> |.....................|   -0.6298 |   -0.9812 |   -0.9181 |   -0.6829 |
-#> |.....................|   -0.7865 |...........|...........|...........|
-#> |    U|     752.10572 |     86.06 |    -3.209 |    -4.609 |   -0.3683 |
-#> |.....................|     4.678 |    0.6309 |    0.8691 |     1.377 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    X|     752.10572 |     86.06 |   0.04038 |  0.009960 |    0.4090 |
-#> |.....................|     4.678 |    0.6309 |    0.8691 |     1.377 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    F| Forward Diff. |     3.580 |   0.02411 |   0.07834 |    0.4067 |
-#> |.....................|   -0.5755 |    0.1666 | -0.003596 |   -0.9604 |
-#> |.....................|   -0.2924 |...........|...........|...........|
-#> |   40|     752.10333 |    0.9885 |   -0.9789 |    -1.009 |    -1.024 |
-#> |.....................|   -0.6300 |   -0.9811 |   -0.9179 |   -0.6819 |
-#> |.....................|   -0.7867 |...........|...........|...........|
-#> |    U|     752.10333 |     86.00 |    -3.209 |    -4.609 |   -0.3688 |
-#> |.....................|     4.678 |    0.6309 |    0.8692 |     1.378 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    X|     752.10333 |     86.00 |   0.04038 |  0.009959 |    0.4088 |
-#> |.....................|     4.678 |    0.6309 |    0.8692 |     1.378 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    F| Forward Diff. |   -0.3772 |   0.02648 |   0.06875 |    0.3997 |
-#> |.....................|   -0.6082 |    0.1162 |  0.008208 |   -0.9328 |
-#> |.....................|   -0.2962 |...........|...........|...........|
-#> |   41|     752.10169 |    0.9892 |   -0.9789 |    -1.009 |    -1.025 |
-#> |.....................|   -0.6289 |   -0.9813 |   -0.9179 |   -0.6803 |
-#> |.....................|   -0.7862 |...........|...........|...........|
-#> |    U|     752.10169 |     86.06 |    -3.209 |    -4.609 |   -0.3691 |
-#> |.....................|     4.680 |    0.6308 |    0.8692 |     1.380 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    X|     752.10169 |     86.06 |   0.04038 |  0.009958 |    0.4088 |
-#> |.....................|     4.680 |    0.6308 |    0.8692 |     1.380 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    F| Forward Diff. |     3.644 |   0.02338 |   0.07127 |    0.4037 |
-#> |.....................|   -0.4618 |    0.1554 |  0.009391 |   -0.8908 |
-#> |.....................|   -0.2755 |...........|...........|...........|
-#> |   42|     752.09938 |    0.9886 |   -0.9790 |    -1.009 |    -1.027 |
-#> |.....................|   -0.6291 |   -0.9812 |   -0.9178 |   -0.6794 |
-#> |.....................|   -0.7864 |...........|...........|...........|
-#> |    U|     752.09938 |     86.00 |    -3.210 |    -4.609 |   -0.3697 |
-#> |.....................|     4.680 |    0.6308 |    0.8693 |     1.381 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    X|     752.09938 |     86.00 |   0.04037 |  0.009958 |    0.4086 |
-#> |.....................|     4.680 |    0.6308 |    0.8693 |     1.381 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    F| Forward Diff. |   -0.2627 |   0.02548 |   0.06256 |    0.3967 |
-#> |.....................|   -0.4955 |    0.1055 |   0.02027 |   -0.8653 |
-#> |.....................|   -0.2789 |...........|...........|...........|
-#> |   43|     752.09757 |    0.9890 |   -0.9791 |    -1.010 |    -1.028 |
-#> |.....................|   -0.6281 |   -0.9814 |   -0.9178 |   -0.6778 |
-#> |.....................|   -0.7859 |...........|...........|...........|
-#> |    U|     752.09757 |     86.05 |    -3.210 |    -4.610 |   -0.3699 |
-#> |.....................|     4.682 |    0.6307 |    0.8693 |     1.383 |
-#> |.....................|     1.067 |...........|...........|...........|
-#> |    X|     752.09757 |     86.05 |   0.04037 |  0.009956 |    0.4086 |
-#> |.....................|     4.682 |    0.6307 |    0.8693 |     1.383 |
-#> |.....................|     1.067 |...........|...........|...........|
-#> |    F| Forward Diff. |     2.867 |   0.02296 |   0.06369 |    0.3997 |
-#> |.....................|   -0.3645 |    0.1327 |   0.01894 |   -0.8216 |
-#> |.....................|   -0.2549 |...........|...........|...........|
-#> |   44|     752.09570 |    0.9886 |   -0.9791 |    -1.010 |    -1.030 |
-#> |.....................|   -0.6283 |   -0.9814 |   -0.9177 |   -0.6770 |
-#> |.....................|   -0.7861 |...........|...........|...........|
-#> |    U|      752.0957 |     86.00 |    -3.210 |    -4.610 |   -0.3705 |
-#> |.....................|     4.681 |    0.6307 |    0.8694 |     1.384 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    X|      752.0957 |     86.00 |   0.04037 |  0.009956 |    0.4084 |
-#> |.....................|     4.681 |    0.6307 |    0.8694 |     1.384 |
-#> |.....................|     1.066 |...........|...........|...........|
-#> |    F| Forward Diff. |   -0.2846 |   0.02474 |   0.05675 |    0.3935 |
-#> |.....................|   -0.3960 |   0.09353 |   0.02976 |   -0.7961 |
-#> |.....................|   -0.2595 |...........|...........|...........|
-#> |   45|     752.09434 |    0.9891 |   -0.9792 |    -1.010 |    -1.030 |
-#> |.....................|   -0.6275 |   -0.9816 |   -0.9177 |   -0.6754 |
-#> |.....................|   -0.7856 |...........|...........|...........|
-#> |    U|     752.09434 |     86.05 |    -3.210 |    -4.610 |   -0.3708 |
-#> |.....................|     4.683 |    0.6306 |    0.8694 |     1.386 |
-#> |.....................|     1.067 |...........|...........|...........|
-#> |    X|     752.09434 |     86.05 |   0.04037 |  0.009955 |    0.4083 |
-#> |.....................|     4.683 |    0.6306 |    0.8694 |     1.386 |
-#> |.....................|     1.067 |...........|...........|...........|
-#> |    F| Forward Diff. |     3.348 |   0.02147 |   0.05816 |    0.3967 |
-#> |.....................|   -0.2833 |    0.1286 |   0.02562 |   -0.7529 |
-#> |.....................|   -0.2380 |...........|...........|...........|
-#> |   46|     752.09236 |    0.9886 |   -0.9793 |    -1.010 |    -1.032 |
-#> |.....................|   -0.6277 |   -0.9815 |   -0.9176 |   -0.6746 |
-#> |.....................|   -0.7858 |...........|...........|...........|
-#> |    U|     752.09236 |     86.01 |    -3.210 |    -4.610 |   -0.3715 |
-#> |.....................|     4.683 |    0.6306 |    0.8695 |     1.387 |
-#> |.....................|     1.067 |...........|...........|...........|
-#> |    X|     752.09236 |     86.01 |   0.04036 |  0.009954 |    0.4082 |
-#> |.....................|     4.683 |    0.6306 |    0.8695 |     1.387 |
-#> |.....................|     1.067 |...........|...........|...........|
-#> |    F| Forward Diff. |   -0.1856 |   0.02378 |   0.05144 |    0.3902 |
-#> |.....................|   -0.3147 |   0.08386 |   0.03545 |   -0.7433 |
-#> |.....................|   -0.2408 |...........|...........|...........|
-#> |   47|     752.09077 |    0.9890 |   -0.9793 |    -1.010 |    -1.033 |
-#> |.....................|   -0.6269 |   -0.9817 |   -0.9177 |   -0.6729 |
-#> |.....................|   -0.7852 |...........|...........|...........|
-#> |    U|     752.09077 |     86.04 |    -3.210 |    -4.610 |   -0.3717 |
-#> |.....................|     4.684 |    0.6305 |    0.8694 |     1.389 |
-#> |.....................|     1.067 |...........|...........|...........|
-#> |    X|     752.09077 |     86.04 |   0.04036 |  0.009953 |    0.4081 |
-#> |.....................|     4.684 |    0.6305 |    0.8694 |     1.389 |
-#> |.....................|     1.067 |...........|...........|...........|
-#> |   48|     752.08937 |    0.9892 |   -0.9795 |    -1.010 |    -1.036 |
-#> |.....................|   -0.6267 |   -0.9818 |   -0.9176 |   -0.6714 |
-#> |.....................|   -0.7852 |...........|...........|...........|
-#> |    U|     752.08937 |     86.06 |    -3.210 |    -4.610 |   -0.3725 |
-#> |.....................|     4.685 |    0.6304 |    0.8695 |     1.391 |
-#> |.....................|     1.067 |...........|...........|...........|
-#> |    X|     752.08937 |     86.06 |   0.04036 |  0.009952 |    0.4079 |
-#> |.....................|     4.685 |    0.6304 |    0.8695 |     1.391 |
-#> |.....................|     1.067 |...........|...........|...........|
-#> |    F| Forward Diff. |     3.945 |   0.01952 |   0.05064 |    0.3906 |
-#> |.....................|   -0.1866 |    0.1233 |   0.03740 |   -0.6554 |
-#> |.....................|   -0.2138 |...........|...........|...........|
-#> |   49|     752.08593 |    0.9886 |   -0.9796 |    -1.010 |    -1.040 |
-#> |.....................|   -0.6271 |   -0.9817 |   -0.9174 |   -0.6701 |
-#> |.....................|   -0.7856 |...........|...........|...........|
-#> |    U|     752.08593 |     86.01 |    -3.210 |    -4.610 |   -0.3740 |
-#> |.....................|     4.684 |    0.6305 |    0.8697 |     1.392 |
-#> |.....................|     1.067 |...........|...........|...........|
-#> |    X|     752.08593 |     86.01 |   0.04035 |  0.009951 |    0.4076 |
-#> |.....................|     4.684 |    0.6305 |    0.8697 |     1.392 |
-#> |.....................|     1.067 |...........|...........|...........|
-#> |    F| Forward Diff. |  -0.04707 |   0.02143 |   0.04311 |    0.3795 |
-#> |.....................|   -0.2514 |   0.07631 |   0.05739 |   -0.6184 |
-#> |.....................|   -0.2313 |...........|...........|...........|
-#> |   50|     752.08243 |    0.9889 |   -0.9798 |    -1.010 |    -1.042 |
-#> |.....................|   -0.6256 |   -0.9821 |   -0.9177 |   -0.6665 |
-#> |.....................|   -0.7842 |...........|...........|...........|
-#> |    U|     752.08243 |     86.03 |    -3.210 |    -4.610 |   -0.3748 |
-#> |.....................|     4.687 |    0.6302 |    0.8694 |     1.396 |
-#> |.....................|     1.068 |...........|...........|...........|
-#> |    X|     752.08243 |     86.03 |   0.04034 |  0.009949 |    0.4074 |
-#> |.....................|     4.687 |    0.6302 |    0.8694 |     1.396 |
-#> |.....................|     1.068 |...........|...........|...........|
-#> |   51|     752.07616 |    0.9895 |   -0.9803 |    -1.011 |    -1.054 |
-#> |.....................|   -0.6231 |   -0.9827 |   -0.9181 |   -0.6582 |
-#> |.....................|   -0.7817 |...........|...........|...........|
-#> |    U|     752.07616 |     86.08 |    -3.211 |    -4.611 |   -0.3786 |
-#> |.....................|     4.693 |    0.6298 |    0.8690 |     1.406 |
-#> |.....................|     1.071 |...........|...........|...........|
-#> |    X|     752.07616 |     86.08 |   0.04032 |  0.009942 |    0.4065 |
-#> |.....................|     4.693 |    0.6298 |    0.8690 |     1.406 |
-#> |.....................|     1.071 |...........|...........|...........|
-#> |    F| Forward Diff. |     5.128 |   0.01286 |   0.03023 |    0.3726 |
-#> |.....................|    0.2708 |   0.07184 |  -0.02487 |   -0.2959 |
-#> |.....................|  -0.03882 |...........|...........|...........|
-#> |   52|     752.06706 |    0.9888 |   -0.9810 |    -1.011 |    -1.073 |
-#> |.....................|   -0.6241 |   -0.9834 |   -0.9174 |   -0.6562 |
-#> |.....................|   -0.7830 |...........|...........|...........|
-#> |    U|     752.06706 |     86.03 |    -3.212 |    -4.611 |   -0.3848 |
-#> |.....................|     4.690 |    0.6293 |    0.8696 |     1.408 |
-#> |.....................|     1.069 |...........|...........|...........|
-#> |    X|     752.06706 |     86.03 |   0.04030 |  0.009938 |    0.4050 |
-#> |.....................|     4.690 |    0.6293 |    0.8696 |     1.408 |
-#> |.....................|     1.069 |...........|...........|...........|
-#> |   53|     752.05726 |    0.9892 |   -0.9821 |    -1.012 |    -1.106 |
-#> |.....................|   -0.6257 |   -0.9847 |   -0.9162 |   -0.6528 |
-#> |.....................|   -0.7853 |...........|...........|...........|
-#> |    U|     752.05726 |     86.06 |    -3.213 |    -4.612 |   -0.3958 |
-#> |.....................|     4.687 |    0.6284 |    0.8707 |     1.412 |
-#> |.....................|     1.067 |...........|...........|...........|
-#> |    X|     752.05726 |     86.06 |   0.04025 |  0.009929 |    0.4023 |
-#> |.....................|     4.687 |    0.6284 |    0.8707 |     1.412 |
-#> |.....................|     1.067 |...........|...........|...........|
-#> |   54|     752.04392 |    0.9898 |   -0.9854 |    -1.015 |    -1.200 |
-#> |.....................|   -0.6305 |   -0.9883 |   -0.9128 |   -0.6430 |
-#> |.....................|   -0.7918 |...........|...........|...........|
-#> |    U|     752.04392 |     86.11 |    -3.216 |    -4.615 |   -0.4269 |
-#> |.....................|     4.677 |    0.6259 |    0.8738 |     1.423 |
-#> |.....................|     1.061 |...........|...........|...........|
-#> |    X|     752.04392 |     86.11 |   0.04012 |  0.009906 |    0.3949 |
-#> |.....................|     4.677 |    0.6259 |    0.8738 |     1.423 |
-#> |.....................|     1.061 |...........|...........|...........|
-#> |    F| Forward Diff. |     5.566 |  -0.02004 |   0.02472 |    0.1678 |
-#> |.....................|   -0.6767 | -0.003606 |    0.4773 |   0.08205 |
-#> |.....................|   -0.6933 |...........|...........|...........|
-#> |   55|     752.05860 |    0.9880 |   -0.9900 |    -1.027 |    -1.486 |
-#> |.....................|   -0.6186 |   -0.9338 |   -0.9168 |   -0.6653 |
-#> |.....................|   -0.7443 |...........|...........|...........|
-#> |    U|      752.0586 |     85.96 |    -3.221 |    -4.627 |   -0.5212 |
-#> |.....................|     4.702 |    0.6640 |    0.8702 |     1.398 |
-#> |.....................|     1.107 |...........|...........|...........|
-#> |    X|      752.0586 |     85.96 |   0.03993 |  0.009780 |    0.3726 |
-#> |.....................|     4.702 |    0.6640 |    0.8702 |     1.398 |
-#> |.....................|     1.107 |...........|...........|...........|
-#> |   56|     752.02137 |    0.9885 |   -0.9874 |    -1.020 |    -1.325 |
-#> |.....................|   -0.6252 |   -0.9645 |   -0.9146 |   -0.6528 |
-#> |.....................|   -0.7710 |...........|...........|...........|
-#> |    U|     752.02137 |     86.00 |    -3.218 |    -4.620 |   -0.4681 |
-#> |.....................|     4.688 |    0.6425 |    0.8722 |     1.412 |
-#> |.....................|     1.081 |...........|...........|...........|
-#> |    X|     752.02137 |     86.00 |   0.04004 |  0.009850 |    0.3851 |
-#> |.....................|     4.688 |    0.6425 |    0.8722 |     1.412 |
-#> |.....................|     1.081 |...........|...........|...........|
-#> |    F| Forward Diff. |    -1.728 |  -0.02729 |   0.08518 |   0.04185 |
-#> |.....................|   -0.2367 |    0.4063 |    0.2432 |   0.01436 |
-#> |.....................|  -0.07563 |...........|...........|...........|
-#> |   57|     752.06656 |    0.9886 |   -0.9792 |    -1.053 |    -1.433 |
-#> |.....................|   -0.6165 |    -1.020 |   -0.9133 |   -0.6801 |
-#> |.....................|   -0.7607 |...........|...........|...........|
-#> |    U|     752.06656 |     86.01 |    -3.210 |    -4.653 |   -0.5037 |
-#> |.....................|     4.707 |    0.6037 |    0.8734 |     1.380 |
-#> |.....................|     1.091 |...........|...........|...........|
-#> |    X|     752.06656 |     86.01 |   0.04036 |  0.009533 |    0.3767 |
-#> |.....................|     4.707 |    0.6037 |    0.8734 |     1.380 |
-#> |.....................|     1.091 |...........|...........|...........|
-#> |   58|     752.02137 |    0.9885 |   -0.9874 |    -1.020 |    -1.325 |
-#> |.....................|   -0.6252 |   -0.9645 |   -0.9146 |   -0.6528 |
-#> |.....................|   -0.7710 |...........|...........|...........|
-#> |    U|     752.02137 |     86.00 |    -3.218 |    -4.620 |   -0.4681 |
-#> |.....................|     4.688 |    0.6425 |    0.8722 |     1.412 |
-#> |.....................|     1.081 |...........|...........|...........|
-#> |    X|     752.02137 |     86.00 |   0.04004 |  0.009850 |    0.3851 |
-#> |.....................|     4.688 |    0.6425 |    0.8722 |     1.412 |
-#> |.....................|     1.081 |...........|...........|...........|
-#> calculating covariance matrix
-#> done
-#> Calculating residuals/tables
-#> done
-f_nlmixr_fomc_sfo_focei_const <- nlmixr(f_mmkin_const["FOMC-SFO", ], est = "focei")
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → calculate jacobian
-#> 
-#> → calculate sensitivities
-#> 
-#> → calculate ∂(f)/∂(η)
-#> 
-#> → calculate ∂(R²)/∂(η)
-#> 
-#> → finding duplicate expressions in inner model...
-#> 
-#> → optimizing duplicate expressions in inner model...
-#> 
-#> → finding duplicate expressions in EBE model...
-#> 
-#> → optimizing duplicate expressions in EBE model...
-#> 
-#> → compiling inner model...
-#>  
-#> ✔ done
-#> → finding duplicate expressions in FD model...
-#> 
-#> → optimizing duplicate expressions in FD model...
-#> 
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> → compiling events FD model...
-#>  
-#> ✔ done
-#> Needed Covariates:
-#> [1] "CMT"
-#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> |    #| Objective Fun |  parent_0 |  log_k_A1 |f_parent_qlogis | log_alpha |
-#> |.....................|  log_beta |     sigma |        o1 |        o2 |
-#> |.....................|        o3 |        o4 |        o5 |...........|
-#> |    1|     494.78160 |     1.000 |    -1.000 |   -0.9115 |   -0.8954 |
-#> |.....................|   -0.8491 |   -0.8592 |   -0.8761 |   -0.8740 |
-#> |.....................|   -0.8674 |   -0.8694 |   -0.8683 |...........|
-#> |    U|      494.7816 |     94.00 |    -5.400 |    -1.000 |   -0.2000 |
-#> |.....................|     2.100 |     1.600 |    0.7598 |    0.8633 |
-#> |.....................|     1.189 |     1.089 |     1.146 |...........|
-#> |    X|      494.7816 |     94.00 |  0.004517 |    0.2689 |    0.8187 |
-#> |.....................|     8.166 |     1.600 |    0.7598 |    0.8633 |
-#> |.....................|     1.189 |     1.089 |     1.146 |...........|
-#> |    G|    Gill Diff. |    -28.01 |     1.933 |   -0.2086 |   0.01492 |
-#> |.....................|   -0.1687 |    -59.79 |     10.74 |     9.966 |
-#> |.....................|    -11.82 |    -8.862 |    -10.52 |...........|
-#> |    2|     1353.4477 |     1.400 |    -1.028 |   -0.9085 |   -0.8956 |
-#> |.....................|   -0.8467 | -0.005584 |    -1.029 |    -1.016 |
-#> |.....................|   -0.6987 |   -0.7429 |   -0.7181 |...........|
-#> |    U|     1353.4477 |     131.6 |    -5.428 |   -0.9970 |   -0.2002 |
-#> |.....................|     2.102 |     2.283 |    0.6433 |    0.7405 |
-#> |.....................|     1.390 |     1.227 |     1.318 |...........|
-#> |    X|     1353.4477 |     131.6 |  0.004394 |    0.2695 |    0.8186 |
-#> |.....................|     8.186 |     2.283 |    0.6433 |    0.7405 |
-#> |.....................|     1.390 |     1.227 |     1.318 |...........|
-#> |    3|     504.82409 |     1.040 |    -1.003 |   -0.9112 |   -0.8954 |
-#> |.....................|   -0.8489 |   -0.7738 |   -0.8914 |   -0.8882 |
-#> |.....................|   -0.8506 |   -0.8568 |   -0.8533 |...........|
-#> |    U|     504.82409 |     97.76 |    -5.403 |   -0.9997 |   -0.2000 |
-#> |.....................|     2.100 |     1.668 |    0.7482 |    0.8511 |
-#> |.....................|     1.209 |     1.103 |     1.163 |...........|
-#> |    X|     504.82409 |     97.76 |  0.004504 |    0.2690 |    0.8187 |
-#> |.....................|     8.168 |     1.668 |    0.7482 |    0.8511 |
-#> |.....................|     1.209 |     1.103 |     1.163 |...........|
-#> |    4|     494.10898 |     1.008 |    -1.001 |   -0.9114 |   -0.8954 |
-#> |.....................|   -0.8490 |   -0.8416 |   -0.8792 |   -0.8769 |
-#> |.....................|   -0.8640 |   -0.8668 |   -0.8652 |...........|
-#> |    U|     494.10898 |     94.77 |    -5.401 |   -0.9999 |   -0.2000 |
-#> |.....................|     2.100 |     1.614 |    0.7574 |    0.8608 |
-#> |.....................|     1.193 |     1.092 |     1.149 |...........|
-#> |    X|     494.10898 |     94.77 |  0.004514 |    0.2690 |    0.8187 |
-#> |.....................|     8.167 |     1.614 |    0.7574 |    0.8608 |
-#> |.....................|     1.193 |     1.092 |     1.149 |...........|
-#> |    F| Forward Diff. |     147.0 |     1.955 |  -0.08761 |   0.06834 |
-#> |.....................|   0.05948 |    -55.61 |     11.89 |     8.304 |
-#> |.....................|    -12.01 |    -8.510 |    -10.24 |...........|
-#> |    5|     492.58255 |    0.9992 |    -1.001 |   -0.9114 |   -0.8954 |
-#> |.....................|   -0.8490 |   -0.8245 |   -0.8825 |   -0.8797 |
-#> |.....................|   -0.8605 |   -0.8643 |   -0.8621 |...........|
-#> |    U|     492.58255 |     93.93 |    -5.401 |   -0.9999 |   -0.2000 |
-#> |.....................|     2.100 |     1.628 |    0.7550 |    0.8584 |
-#> |.....................|     1.197 |     1.095 |     1.153 |...........|
-#> |    X|     492.58255 |     93.93 |  0.004511 |    0.2690 |    0.8187 |
-#> |.....................|     8.167 |     1.628 |    0.7550 |    0.8584 |
-#> |.....................|     1.197 |     1.095 |     1.153 |...........|
-#> |    F| Forward Diff. |    -43.22 |     1.882 |   -0.2206 | -0.004719 |
-#> |.....................|   -0.1970 |    -51.78 |     10.22 |     6.620 |
-#> |.....................|    -11.81 |    -8.346 |    -10.04 |...........|
-#> |    6|     491.66702 |     1.006 |    -1.002 |   -0.9113 |   -0.8954 |
-#> |.....................|   -0.8490 |   -0.8063 |   -0.8860 |   -0.8822 |
-#> |.....................|   -0.8565 |   -0.8614 |   -0.8588 |...........|
-#> |    U|     491.66702 |     94.52 |    -5.402 |   -0.9998 |   -0.2000 |
-#> |.....................|     2.100 |     1.642 |    0.7523 |    0.8562 |
-#> |.....................|     1.202 |     1.098 |     1.157 |...........|
-#> |    X|     491.66702 |     94.52 |  0.004509 |    0.2690 |    0.8187 |
-#> |.....................|     8.167 |     1.642 |    0.7523 |    0.8562 |
-#> |.....................|     1.202 |     1.098 |     1.157 |...........|
-#> |    F| Forward Diff. |     87.79 |     1.893 |   -0.1269 |   0.04418 |
-#> |.....................|  -0.01699 |    -47.85 |     10.34 |     7.758 |
-#> |.....................|    -11.67 |    -8.213 |    -9.916 |...........|
-#> |    7|     490.57489 |    0.9987 |    -1.002 |   -0.9112 |   -0.8954 |
-#> |.....................|   -0.8489 |   -0.7885 |   -0.8895 |   -0.8851 |
-#> |.....................|   -0.8525 |   -0.8586 |   -0.8553 |...........|
-#> |    U|     490.57489 |     93.88 |    -5.402 |   -0.9998 |   -0.2000 |
-#> |.....................|     2.100 |     1.657 |    0.7496 |    0.8537 |
-#> |.....................|     1.207 |     1.101 |     1.161 |...........|
-#> |    X|     490.57489 |     93.88 |  0.004506 |    0.2690 |    0.8187 |
-#> |.....................|     8.168 |     1.657 |    0.7496 |    0.8537 |
-#> |.....................|     1.207 |     1.101 |     1.161 |...........|
-#> |    F| Forward Diff. |    -52.56 |     1.834 |   -0.2285 |  -0.01046 |
-#> |.....................|   -0.2159 |    -44.44 |     9.379 |     7.248 |
-#> |.....................|    -11.47 |    -8.044 |    -9.710 |...........|
-#> |    8|     489.67804 |     1.004 |    -1.003 |   -0.9112 |   -0.8954 |
-#> |.....................|   -0.8489 |   -0.7706 |   -0.8932 |   -0.8884 |
-#> |.....................|   -0.8482 |   -0.8554 |   -0.8516 |...........|
-#> |    U|     489.67804 |     94.42 |    -5.403 |   -0.9997 |   -0.2000 |
-#> |.....................|     2.100 |     1.671 |    0.7468 |    0.8509 |
-#> |.....................|     1.212 |     1.105 |     1.165 |...........|
-#> |    X|     489.67804 |     94.42 |  0.004503 |    0.2690 |    0.8187 |
-#> |.....................|     8.168 |     1.671 |    0.7468 |    0.8509 |
-#> |.....................|     1.212 |     1.105 |     1.165 |...........|
-#> |    F| Forward Diff. |     63.10 |     1.841 |   -0.1396 |   0.03713 |
-#> |.....................|  -0.05177 |    -40.65 |     9.345 |     6.018 |
-#> |.....................|    -11.29 |    -7.879 |    -9.567 |...........|
-#> |    9|     488.80457 |    0.9984 |    -1.004 |   -0.9111 |   -0.8954 |
-#> |.....................|   -0.8488 |   -0.7529 |   -0.8970 |   -0.8913 |
-#> |.....................|   -0.8435 |   -0.8521 |   -0.8475 |...........|
-#> |    U|     488.80457 |     93.85 |    -5.404 |   -0.9996 |   -0.2000 |
-#> |.....................|     2.100 |     1.685 |    0.7439 |    0.8484 |
-#> |.....................|     1.218 |     1.108 |     1.170 |...........|
-#> |    X|     488.80457 |     93.85 |  0.004499 |    0.2690 |    0.8187 |
-#> |.....................|     8.168 |     1.685 |    0.7439 |    0.8484 |
-#> |.....................|     1.218 |     1.108 |     1.170 |...........|
-#> |    F| Forward Diff. |    -56.52 |     1.788 |   -0.2313 |  -0.01570 |
-#> |.....................|   -0.2287 |    -37.43 |     8.740 |     5.512 |
-#> |.....................|    -11.08 |    -7.680 |    -9.353 |...........|
-#> |   10|     487.98244 |     1.004 |    -1.005 |   -0.9110 |   -0.8954 |
-#> |.....................|   -0.8487 |   -0.7356 |   -0.9012 |   -0.8939 |
-#> |.....................|   -0.8380 |   -0.8482 |   -0.8428 |...........|
-#> |    U|     487.98244 |     94.36 |    -5.405 |   -0.9995 |   -0.2000 |
-#> |.....................|     2.100 |     1.699 |    0.7407 |    0.8461 |
-#> |.....................|     1.224 |     1.112 |     1.175 |...........|
-#> |    X|     487.98244 |     94.36 |  0.004495 |    0.2690 |    0.8187 |
-#> |.....................|     8.169 |     1.699 |    0.7407 |    0.8461 |
-#> |.....................|     1.224 |     1.112 |     1.175 |...........|
-#> |    F| Forward Diff. |     49.57 |     1.794 |   -0.1466 |   0.03517 |
-#> |.....................|  -0.07178 |    -34.12 |     8.494 |     6.684 |
-#> |.....................|    -10.82 |    -7.482 |    -9.140 |...........|
-#> |   11|     487.23587 |    0.9987 |    -1.006 |   -0.9109 |   -0.8954 |
-#> |.....................|   -0.8487 |   -0.7192 |   -0.9058 |   -0.8980 |
-#> |.....................|   -0.8316 |   -0.8438 |   -0.8374 |...........|
-#> |    U|     487.23587 |     93.88 |    -5.406 |   -0.9994 |   -0.2001 |
-#> |.....................|     2.100 |     1.712 |    0.7372 |    0.8426 |
-#> |.....................|     1.232 |     1.117 |     1.181 |...........|
-#> |    X|     487.23587 |     93.88 |  0.004490 |    0.2691 |    0.8187 |
-#> |.....................|     8.170 |     1.712 |    0.7372 |    0.8426 |
-#> |.....................|     1.232 |     1.117 |     1.181 |...........|
-#> |    F| Forward Diff. |    -49.22 |     1.745 |   -0.2274 | -0.009194 |
-#> |.....................|   -0.2301 |    -31.48 |     7.992 |     6.132 |
-#> |.....................|    -10.64 |    -7.269 |    -8.903 |...........|
-#> |   12|     486.53337 |     1.004 |    -1.007 |   -0.9107 |   -0.8954 |
-#> |.....................|   -0.8485 |   -0.7047 |   -0.9109 |   -0.9037 |
-#> |.....................|   -0.8240 |   -0.8386 |   -0.8310 |...........|
-#> |    U|     486.53337 |     94.34 |    -5.407 |   -0.9993 |   -0.2001 |
-#> |.....................|     2.101 |     1.724 |    0.7334 |    0.8376 |
-#> |.....................|     1.241 |     1.123 |     1.189 |...........|
-#> |    X|     486.53337 |     94.34 |  0.004484 |    0.2691 |    0.8187 |
-#> |.....................|     8.171 |     1.724 |    0.7334 |    0.8376 |
-#> |.....................|     1.241 |     1.123 |     1.189 |...........|
-#> |    F| Forward Diff. |     43.47 |     1.742 |   -0.1424 |   0.02918 |
-#> |.....................|  -0.07089 |    -28.76 |     7.629 |     4.806 |
-#> |.....................|    -10.24 |    -6.953 |    -8.584 |...........|
-#> |   13|     485.91669 |    0.9989 |    -1.009 |   -0.9105 |   -0.8955 |
-#> |.....................|   -0.8484 |   -0.6920 |   -0.9165 |   -0.9072 |
-#> |.....................|   -0.8145 |   -0.8325 |   -0.8231 |...........|
-#> |    U|     485.91669 |     93.90 |    -5.409 |   -0.9991 |   -0.2001 |
-#> |.....................|     2.101 |     1.734 |    0.7291 |    0.8346 |
-#> |.....................|     1.252 |     1.130 |     1.198 |...........|
-#> |    X|     485.91669 |     93.90 |  0.004476 |    0.2691 |    0.8187 |
-#> |.....................|     8.172 |     1.734 |    0.7291 |    0.8346 |
-#> |.....................|     1.252 |     1.130 |     1.198 |...........|
-#> |    F| Forward Diff. |    -44.30 |     1.699 |   -0.2182 |  0.001936 |
-#> |.....................|   -0.2284 |    -26.86 |     7.286 |     5.487 |
-#> |.....................|    -9.898 |    -6.659 |    -8.234 |...........|
-#> |   14|     485.33976 |     1.003 |    -1.011 |   -0.9103 |   -0.8955 |
-#> |.....................|   -0.8481 |   -0.6819 |   -0.9228 |   -0.9110 |
-#> |.....................|   -0.8035 |   -0.8257 |   -0.8143 |...........|
-#> |    U|     485.33976 |     94.29 |    -5.411 |   -0.9988 |   -0.2001 |
-#> |.....................|     2.101 |     1.742 |    0.7243 |    0.8314 |
-#> |.....................|     1.265 |     1.137 |     1.208 |...........|
-#> |    X|     485.33976 |     94.29 |  0.004467 |    0.2692 |    0.8186 |
-#> |.....................|     8.174 |     1.742 |    0.7243 |    0.8314 |
-#> |.....................|     1.265 |     1.137 |     1.208 |...........|
-#> |   15|     484.77317 |     1.003 |    -1.014 |   -0.9100 |   -0.8956 |
-#> |.....................|   -0.8479 |   -0.6718 |   -0.9302 |   -0.9153 |
-#> |.....................|   -0.7902 |   -0.8175 |   -0.8035 |...........|
-#> |    U|     484.77317 |     94.32 |    -5.414 |   -0.9986 |   -0.2002 |
-#> |.....................|     2.101 |     1.750 |    0.7187 |    0.8276 |
-#> |.....................|     1.281 |     1.146 |     1.220 |...........|
-#> |    X|     484.77317 |     94.32 |  0.004455 |    0.2692 |    0.8186 |
-#> |.....................|     8.176 |     1.750 |    0.7187 |    0.8276 |
-#> |.....................|     1.281 |     1.146 |     1.220 |...........|
-#> |   16|     483.17588 |     1.004 |    -1.023 |   -0.9091 |   -0.8958 |
-#> |.....................|   -0.8469 |   -0.6384 |   -0.9549 |   -0.9296 |
-#> |.....................|   -0.7463 |   -0.7903 |   -0.7681 |...........|
-#> |    U|     483.17588 |     94.41 |    -5.423 |   -0.9976 |   -0.2004 |
-#> |.....................|     2.102 |     1.777 |    0.6999 |    0.8153 |
-#> |.....................|     1.333 |     1.176 |     1.261 |...........|
-#> |    X|     483.17588 |     94.41 |  0.004415 |    0.2694 |    0.8184 |
-#> |.....................|     8.184 |     1.777 |    0.6999 |    0.8153 |
-#> |.....................|     1.333 |     1.176 |     1.261 |...........|
-#> |   17|     481.21481 |     1.006 |    -1.040 |   -0.9072 |   -0.8961 |
-#> |.....................|   -0.8451 |   -0.5721 |    -1.004 |   -0.9579 |
-#> |.....................|   -0.6592 |   -0.7365 |   -0.6977 |...........|
-#> |    U|     481.21481 |     94.58 |    -5.440 |   -0.9958 |   -0.2008 |
-#> |.....................|     2.104 |     1.830 |    0.6628 |    0.7909 |
-#> |.....................|     1.437 |     1.234 |     1.341 |...........|
-#> |    X|     481.21481 |     94.58 |  0.004338 |    0.2698 |    0.8181 |
-#> |.....................|     8.199 |     1.830 |    0.6628 |    0.7909 |
-#> |.....................|     1.437 |     1.234 |     1.341 |...........|
-#> |    F| Forward Diff. |     62.86 |     1.476 |   0.06730 |   0.05792 |
-#> |.....................|    0.1123 |    -8.977 |     1.055 |     2.914 |
-#> |.....................|    -3.044 |    -1.094 |    -2.299 |...........|
-#> |   18|     481.29476 |     1.000 |    -1.145 |   -0.9129 |   -0.8997 |
-#> |.....................|   -0.8485 |   -0.5378 |   -0.8985 |    -1.168 |
-#> |.....................|   -0.6228 |   -0.8149 |   -0.6969 |...........|
-#> |    U|     481.29476 |     94.03 |    -5.545 |    -1.001 |   -0.2043 |
-#> |.....................|     2.101 |     1.857 |    0.7428 |    0.6099 |
-#> |.....................|     1.480 |     1.149 |     1.342 |...........|
-#> |    X|     481.29476 |     94.03 |  0.003907 |    0.2687 |    0.8152 |
-#> |.....................|     8.171 |     1.857 |    0.7428 |    0.6099 |
-#> |.....................|     1.480 |     1.149 |     1.342 |...........|
-#> |   19|     480.77138 |     1.000 |    -1.090 |   -0.9099 |   -0.8978 |
-#> |.....................|   -0.8467 |   -0.5555 |   -0.9542 |    -1.057 |
-#> |.....................|   -0.6419 |   -0.7733 |   -0.6972 |...........|
-#> |    U|     480.77138 |     94.01 |    -5.490 |   -0.9984 |   -0.2025 |
-#> |.....................|     2.102 |     1.843 |    0.7004 |    0.7055 |
-#> |.....................|     1.457 |     1.194 |     1.342 |...........|
-#> |    X|     480.77138 |     94.01 |  0.004129 |    0.2693 |    0.8167 |
-#> |.....................|     8.186 |     1.843 |    0.7004 |    0.7055 |
-#> |.....................|     1.457 |     1.194 |     1.342 |...........|
-#> |    F| Forward Diff. |    -25.72 |     1.151 |   0.08772 | -0.007897 |
-#> |.....................|  -0.07232 |    -6.930 |     3.330 |    -2.491 |
-#> |.....................|    -2.626 |    -3.111 |    -2.500 |...........|
-#> |   20|     480.61717 |     1.001 |    -1.203 |   -0.9227 |   -0.9002 |
-#> |.....................|   -0.8503 |   -0.5418 |   -0.9405 |    -1.001 |
-#> |.....................|   -0.6281 |   -0.7705 |   -0.6908 |...........|
-#> |    U|     480.61717 |     94.09 |    -5.603 |    -1.011 |   -0.2049 |
-#> |.....................|     2.099 |     1.854 |    0.7108 |    0.7537 |
-#> |.....................|     1.474 |     1.197 |     1.349 |...........|
-#> |    X|     480.61717 |     94.09 |  0.003688 |    0.2667 |    0.8147 |
-#> |.....................|     8.156 |     1.854 |    0.7108 |    0.7537 |
-#> |.....................|     1.474 |     1.197 |     1.349 |...........|
-#> |    F| Forward Diff. |    -10.61 |    0.9224 |   -0.5881 |  -0.06621 |
-#> |.....................|   -0.1838 |    -5.929 |     3.775 |     2.798 |
-#> |.....................|    -1.936 |    -2.993 |    -2.208 |...........|
-#> |   21|     480.72130 |     1.009 |    -1.314 |   -0.9169 |   -0.9003 |
-#> |.....................|   -0.8494 |   -0.5516 |   -0.9873 |    -1.003 |
-#> |.....................|   -0.6340 |   -0.7292 |   -0.6819 |...........|
-#> |    U|      480.7213 |     94.81 |    -5.714 |    -1.005 |   -0.2049 |
-#> |.....................|     2.100 |     1.846 |    0.6753 |    0.7523 |
-#> |.....................|     1.467 |     1.242 |     1.359 |...........|
-#> |    X|      480.7213 |     94.81 |  0.003299 |    0.2679 |    0.8147 |
-#> |.....................|     8.163 |     1.846 |    0.6753 |    0.7523 |
-#> |.....................|     1.467 |     1.242 |     1.359 |...........|
-#> |   22|     480.86254 |     1.009 |    -1.247 |   -0.9202 |   -0.9002 |
-#> |.....................|   -0.8499 |   -0.5429 |   -0.9605 |    -1.003 |
-#> |.....................|   -0.6295 |   -0.7530 |   -0.6863 |...........|
-#> |    U|     480.86254 |     94.84 |    -5.647 |    -1.009 |   -0.2048 |
-#> |.....................|     2.099 |     1.853 |    0.6957 |    0.7520 |
-#> |.....................|     1.472 |     1.216 |     1.354 |...........|
-#> |    X|     480.86254 |     94.84 |  0.003530 |    0.2672 |    0.8148 |
-#> |.....................|     8.160 |     1.853 |    0.6957 |    0.7520 |
-#> |.....................|     1.472 |     1.216 |     1.354 |...........|
-#> |   23|     480.98412 |     1.009 |    -1.209 |   -0.9220 |   -0.9002 |
-#> |.....................|   -0.8501 |   -0.5381 |   -0.9458 |    -1.003 |
-#> |.....................|   -0.6270 |   -0.7661 |   -0.6887 |...........|
-#> |    U|     480.98412 |     94.85 |    -5.609 |    -1.010 |   -0.2048 |
-#> |.....................|     2.099 |     1.857 |    0.7069 |    0.7519 |
-#> |.....................|     1.475 |     1.202 |     1.352 |...........|
-#> |    X|     480.98412 |     94.85 |  0.003664 |    0.2669 |    0.8148 |
-#> |.....................|     8.158 |     1.857 |    0.7069 |    0.7519 |
-#> |.....................|     1.475 |     1.202 |     1.352 |...........|
-#> |   24|     480.60990 |     1.003 |    -1.203 |   -0.9226 |   -0.9002 |
-#> |.....................|   -0.8503 |   -0.5410 |   -0.9411 |    -1.001 |
-#> |.....................|   -0.6278 |   -0.7701 |   -0.6905 |...........|
-#> |    U|      480.6099 |     94.24 |    -5.603 |    -1.011 |   -0.2049 |
-#> |.....................|     2.099 |     1.855 |    0.7104 |    0.7534 |
-#> |.....................|     1.474 |     1.198 |     1.350 |...........|
-#> |    X|      480.6099 |     94.24 |  0.003688 |    0.2668 |    0.8148 |
-#> |.....................|     8.156 |     1.855 |    0.7104 |    0.7534 |
-#> |.....................|     1.474 |     1.198 |     1.350 |...........|
-#> |    F| Forward Diff. |     15.29 |    0.9278 |   -0.5289 |  -0.04762 |
-#> |.....................|   -0.1043 |    -5.468 |     3.876 |    0.6273 |
-#> |.....................|    -1.897 |    -2.941 |    -2.183 |...........|
-#> |   25|     480.59557 |     1.001 |    -1.204 |   -0.9225 |   -0.9002 |
-#> |.....................|   -0.8503 |   -0.5407 |   -0.9419 |    -1.001 |
-#> |.....................|   -0.6277 |   -0.7694 |   -0.6902 |...........|
-#> |    U|     480.59557 |     94.13 |    -5.604 |    -1.011 |   -0.2049 |
-#> |.....................|     2.099 |     1.855 |    0.7098 |    0.7533 |
-#> |.....................|     1.474 |     1.198 |     1.350 |...........|
-#> |    X|     480.59557 |     94.13 |  0.003683 |    0.2668 |    0.8148 |
-#> |.....................|     8.157 |     1.855 |    0.7098 |    0.7533 |
-#> |.....................|     1.474 |     1.198 |     1.350 |...........|
-#> |    F| Forward Diff. |    -4.733 |    0.9212 |   -0.5619 |  -0.05855 |
-#> |.....................|   -0.1664 |    -5.388 |     3.833 |    0.5854 |
-#> |.....................|    -1.924 |    -2.927 |    -2.102 |...........|
-#> |   26|     480.58581 |     1.002 |    -1.204 |   -0.9224 |   -0.9002 |
-#> |.....................|   -0.8502 |   -0.5395 |   -0.9428 |    -1.002 |
-#> |.....................|   -0.6273 |   -0.7688 |   -0.6897 |...........|
-#> |    U|     480.58581 |     94.23 |    -5.604 |    -1.011 |   -0.2048 |
-#> |.....................|     2.099 |     1.856 |    0.7092 |    0.7532 |
-#> |.....................|     1.475 |     1.199 |     1.351 |...........|
-#> |    X|     480.58581 |     94.23 |  0.003683 |    0.2668 |    0.8148 |
-#> |.....................|     8.157 |     1.856 |    0.7092 |    0.7532 |
-#> |.....................|     1.475 |     1.199 |     1.351 |...........|
-#> |    F| Forward Diff. |     12.31 |    0.9226 |   -0.5246 |  -0.05019 |
-#> |.....................|   -0.1134 |    -5.293 |     3.771 |    0.5822 |
-#> |.....................|    -1.938 |    -2.904 |    -2.175 |...........|
-#> |   27|     480.57360 |     1.001 |    -1.205 |   -0.9222 |   -0.9002 |
-#> |.....................|   -0.8502 |   -0.5392 |   -0.9437 |    -1.002 |
-#> |.....................|   -0.6271 |   -0.7681 |   -0.6894 |...........|
-#> |    U|      480.5736 |     94.13 |    -5.605 |    -1.011 |   -0.2048 |
-#> |.....................|     2.099 |     1.856 |    0.7085 |    0.7532 |
-#> |.....................|     1.475 |     1.200 |     1.351 |...........|
-#> |    X|      480.5736 |     94.13 |  0.003678 |    0.2668 |    0.8148 |
-#> |.....................|     8.157 |     1.856 |    0.7085 |    0.7532 |
-#> |.....................|     1.475 |     1.200 |     1.351 |...........|
-#> |    F| Forward Diff. |    -4.864 |    0.9151 |   -0.5515 |  -0.06112 |
-#> |.....................|   -0.1679 |    -5.184 |     3.617 |    0.5746 |
-#> |.....................|    -1.832 |    -2.849 |    -2.141 |...........|
-#> |   28|     480.56429 |     1.002 |    -1.206 |   -0.9220 |   -0.9002 |
-#> |.....................|   -0.8502 |   -0.5382 |   -0.9446 |    -1.002 |
-#> |.....................|   -0.6268 |   -0.7674 |   -0.6889 |...........|
-#> |    U|     480.56429 |     94.23 |    -5.606 |    -1.011 |   -0.2048 |
-#> |.....................|     2.099 |     1.857 |    0.7078 |    0.7531 |
-#> |.....................|     1.475 |     1.201 |     1.351 |...........|
-#> |    X|     480.56429 |     94.23 |  0.003676 |    0.2669 |    0.8148 |
-#> |.....................|     8.158 |     1.857 |    0.7078 |    0.7531 |
-#> |.....................|     1.475 |     1.201 |     1.351 |...........|
-#> |    F| Forward Diff. |     12.18 |    0.9169 |   -0.5105 |  -0.05061 |
-#> |.....................|   -0.1125 |    -5.131 |     3.532 |    0.5638 |
-#> |.....................|    -1.931 |    -2.821 |    -2.132 |...........|
-#> |   29|     480.55246 |     1.001 |    -1.207 |   -0.9218 |   -0.9002 |
-#> |.....................|   -0.8501 |   -0.5380 |   -0.9454 |    -1.002 |
-#> |.....................|   -0.6266 |   -0.7667 |   -0.6886 |...........|
-#> |    U|     480.55246 |     94.13 |    -5.607 |    -1.010 |   -0.2048 |
-#> |.....................|     2.099 |     1.857 |    0.7071 |    0.7532 |
-#> |.....................|     1.476 |     1.201 |     1.352 |...........|
-#> |    X|     480.55246 |     94.13 |  0.003672 |    0.2669 |    0.8148 |
-#> |.....................|     8.158 |     1.857 |    0.7071 |    0.7532 |
-#> |.....................|     1.476 |     1.201 |     1.352 |...........|
-#> |    F| Forward Diff. |    -4.480 |    0.9098 |   -0.5353 |  -0.06055 |
-#> |.....................|   -0.1647 |    -5.053 |     3.625 |    0.5654 |
-#> |.....................|    -1.860 |    -2.782 |    -2.112 |...........|
-#> |   30|     480.54335 |     1.002 |    -1.207 |   -0.9217 |   -0.9002 |
-#> |.....................|   -0.8501 |   -0.5368 |   -0.9463 |    -1.002 |
-#> |.....................|   -0.6262 |   -0.7660 |   -0.6881 |...........|
-#> |    U|     480.54335 |     94.23 |    -5.607 |    -1.010 |   -0.2048 |
-#> |.....................|     2.099 |     1.858 |    0.7065 |    0.7530 |
-#> |.....................|     1.476 |     1.202 |     1.352 |...........|
-#> |    X|     480.54335 |     94.23 |  0.003671 |    0.2669 |    0.8148 |
-#> |.....................|     8.158 |     1.858 |    0.7065 |    0.7530 |
-#> |.....................|     1.476 |     1.202 |     1.352 |...........|
-#> |    F| Forward Diff. |     12.09 |    0.9120 |   -0.4955 |  -0.05014 |
-#> |.....................|   -0.1107 |    -4.912 |     3.583 |    0.5835 |
-#> |.....................|    -1.814 |    -2.702 |    -2.057 |...........|
-#> |   31|     480.53185 |     1.001 |    -1.209 |   -0.9215 |   -0.9002 |
-#> |.....................|   -0.8500 |   -0.5366 |   -0.9472 |    -1.002 |
-#> |.....................|   -0.6260 |   -0.7654 |   -0.6878 |...........|
-#> |    U|     480.53185 |     94.13 |    -5.609 |    -1.010 |   -0.2048 |
-#> |.....................|     2.099 |     1.858 |    0.7058 |    0.7531 |
-#> |.....................|     1.476 |     1.203 |     1.353 |...........|
-#> |    X|     480.53185 |     94.13 |  0.003666 |    0.2670 |    0.8148 |
-#> |.....................|     8.158 |     1.858 |    0.7058 |    0.7531 |
-#> |.....................|     1.476 |     1.203 |     1.353 |...........|
-#> |    F| Forward Diff. |    -4.509 |    0.9048 |   -0.5214 |  -0.06027 |
-#> |.....................|   -0.1665 |    -4.870 |     3.525 |    0.5641 |
-#> |.....................|    -1.813 |    -2.699 |    -2.069 |...........|
-#> |   32|     480.52276 |     1.002 |    -1.209 |   -0.9214 |   -0.9001 |
-#> |.....................|   -0.8500 |   -0.5356 |   -0.9481 |    -1.002 |
-#> |.....................|   -0.6256 |   -0.7647 |   -0.6873 |...........|
-#> |    U|     480.52276 |     94.22 |    -5.609 |    -1.010 |   -0.2048 |
-#> |.....................|     2.099 |     1.859 |    0.7051 |    0.7530 |
-#> |.....................|     1.477 |     1.203 |     1.353 |...........|
-#> |    X|     480.52276 |     94.22 |  0.003664 |    0.2670 |    0.8148 |
-#> |.....................|     8.159 |     1.859 |    0.7051 |    0.7530 |
-#> |.....................|     1.477 |     1.203 |     1.353 |...........|
-#> |    F| Forward Diff. |     11.38 |    0.9060 |   -0.4821 |  -0.05014 |
-#> |.....................|   -0.1110 |    -4.747 |     3.479 |    0.5798 |
-#> |.....................|    -1.777 |    -2.636 |    -2.020 |...........|
-#> |   33|     480.51194 |     1.001 |    -1.211 |   -0.9212 |   -0.9001 |
-#> |.....................|   -0.8500 |   -0.5355 |   -0.9490 |    -1.002 |
-#> |.....................|   -0.6255 |   -0.7641 |   -0.6869 |...........|
-#> |    U|     480.51194 |     94.13 |    -5.611 |    -1.010 |   -0.2048 |
-#> |.....................|     2.099 |     1.859 |    0.7044 |    0.7530 |
-#> |.....................|     1.477 |     1.204 |     1.354 |...........|
-#> |    X|     480.51194 |     94.13 |  0.003659 |    0.2670 |    0.8148 |
-#> |.....................|     8.159 |     1.859 |    0.7044 |    0.7530 |
-#> |.....................|     1.477 |     1.204 |     1.354 |...........|
-#> |    F| Forward Diff. |    -4.485 |    0.8991 |   -0.5064 |  -0.06148 |
-#> |.....................|   -0.1643 |    -4.758 |     3.403 |    0.5432 |
-#> |.....................|    -1.772 |    -2.633 |    -2.022 |...........|
-#> |   34|     480.50302 |     1.002 |    -1.211 |   -0.9210 |   -0.9001 |
-#> |.....................|   -0.8499 |   -0.5345 |   -0.9500 |    -1.002 |
-#> |.....................|   -0.6251 |   -0.7633 |   -0.6864 |...........|
-#> |    U|     480.50302 |     94.22 |    -5.611 |    -1.010 |   -0.2047 |
-#> |.....................|     2.099 |     1.860 |    0.7037 |    0.7529 |
-#> |.....................|     1.477 |     1.205 |     1.354 |...........|
-#> |    X|     480.50302 |     94.22 |  0.003656 |    0.2671 |    0.8149 |
-#> |.....................|     8.159 |     1.860 |    0.7037 |    0.7529 |
-#> |.....................|     1.477 |     1.205 |     1.354 |...........|
-#> |    F| Forward Diff. |     10.83 |    0.8997 |   -0.4680 |  -0.05021 |
-#> |.....................|   -0.1106 |    -4.703 |     3.332 |    0.5674 |
-#> |.....................|    -1.765 |    -2.559 |    -1.986 |...........|
-#> |   35|     480.49281 |     1.001 |    -1.213 |   -0.9209 |   -0.9001 |
-#> |.....................|   -0.8499 |   -0.5344 |   -0.9509 |    -1.002 |
-#> |.....................|   -0.6250 |   -0.7627 |   -0.6860 |...........|
-#> |    U|     480.49281 |     94.13 |    -5.613 |    -1.009 |   -0.2047 |
-#> |.....................|     2.099 |     1.860 |    0.7030 |    0.7529 |
-#> |.....................|     1.478 |     1.206 |     1.355 |...........|
-#> |    X|     480.49281 |     94.13 |  0.003652 |    0.2671 |    0.8149 |
-#> |.....................|     8.160 |     1.860 |    0.7030 |    0.7529 |
-#> |.....................|     1.478 |     1.206 |     1.355 |...........|
-#> |    F| Forward Diff. |    -4.447 |    0.8934 |   -0.4900 |  -0.06030 |
-#> |.....................|   -0.1577 |    -4.708 |     3.266 |    0.5080 |
-#> |.....................|    -1.782 |    -2.544 |    -1.983 |...........|
-#> |   36|     480.48415 |     1.002 |    -1.213 |   -0.9207 |   -0.9001 |
-#> |.....................|   -0.8498 |   -0.5335 |   -0.9518 |    -1.002 |
-#> |.....................|   -0.6246 |   -0.7620 |   -0.6855 |...........|
-#> |    U|     480.48415 |     94.22 |    -5.613 |    -1.009 |   -0.2047 |
-#> |.....................|     2.099 |     1.861 |    0.7023 |    0.7528 |
-#> |.....................|     1.478 |     1.206 |     1.355 |...........|
-#> |    X|     480.48415 |     94.22 |  0.003649 |    0.2671 |    0.8149 |
-#> |.....................|     8.160 |     1.861 |    0.7023 |    0.7528 |
-#> |.....................|     1.478 |     1.206 |     1.355 |...........|
-#> |    F| Forward Diff. |     10.47 |    0.8932 |   -0.4526 |  -0.04997 |
-#> |.....................|   -0.1093 |    -4.502 |     3.250 |    0.5653 |
-#> |.....................|    -1.769 |    -2.486 |    -1.944 |...........|
-#> |   37|     480.47437 |     1.001 |    -1.215 |   -0.9205 |   -0.9001 |
-#> |.....................|   -0.8498 |   -0.5334 |   -0.9527 |    -1.002 |
-#> |.....................|   -0.6244 |   -0.7613 |   -0.6852 |...........|
-#> |    U|     480.47437 |     94.13 |    -5.615 |    -1.009 |   -0.2047 |
-#> |.....................|     2.099 |     1.861 |    0.7016 |    0.7528 |
-#> |.....................|     1.478 |     1.207 |     1.356 |...........|
-#> |    X|     480.47437 |     94.13 |  0.003644 |    0.2672 |    0.8149 |
-#> |.....................|     8.161 |     1.861 |    0.7016 |    0.7528 |
-#> |.....................|     1.478 |     1.207 |     1.356 |...........|
-#> |    F| Forward Diff. |    -4.431 |    0.8869 |   -0.4735 |  -0.05983 |
-#> |.....................|   -0.1554 |    -4.492 |     3.189 |   -0.6996 |
-#> |.....................|    -1.700 |    -2.467 |    -1.937 |...........|
-#> |   38|     480.46651 |     1.002 |    -1.216 |   -0.9203 |   -0.9000 |
-#> |.....................|   -0.8497 |   -0.5326 |   -0.9537 |    -1.002 |
-#> |.....................|   -0.6240 |   -0.7606 |   -0.6847 |...........|
-#> |    U|     480.46651 |     94.21 |    -5.616 |    -1.009 |   -0.2047 |
-#> |.....................|     2.099 |     1.861 |    0.7009 |    0.7530 |
-#> |.....................|     1.479 |     1.208 |     1.356 |...........|
-#> |    X|     480.46651 |     94.21 |  0.003640 |    0.2672 |    0.8149 |
-#> |.....................|     8.161 |     1.861 |    0.7009 |    0.7530 |
-#> |.....................|     1.479 |     1.208 |     1.356 |...........|
-#> |    F| Forward Diff. |     9.502 |    0.8860 |   -0.4381 |  -0.05035 |
-#> |.....................|   -0.1103 |    -4.453 |     3.114 |    0.5384 |
-#> |.....................|    -1.770 |    -2.407 |    -1.897 |...........|
-#> |   39|     480.45755 |     1.001 |    -1.217 |   -0.9200 |   -0.9000 |
-#> |.....................|   -0.8497 |   -0.5325 |   -0.9546 |    -1.002 |
-#> |.....................|   -0.6238 |   -0.7600 |   -0.6843 |...........|
-#> |    U|     480.45755 |     94.13 |    -5.617 |    -1.009 |   -0.2047 |
-#> |.....................|     2.099 |     1.861 |    0.7002 |    0.7530 |
-#> |.....................|     1.479 |     1.209 |     1.357 |...........|
-#> |    X|     480.45755 |     94.13 |  0.003635 |    0.2673 |    0.8149 |
-#> |.....................|     8.162 |     1.861 |    0.7002 |    0.7530 |
-#> |.....................|     1.479 |     1.209 |     1.357 |...........|
-#> |    F| Forward Diff. |    -4.779 |    0.8798 |   -0.4544 |  -0.05816 |
-#> |.....................|   -0.1541 |    -4.432 |     3.060 |    0.5236 |
-#> |.....................|    -1.719 |    -2.365 |    -1.874 |...........|
-#> |   40|     480.44943 |     1.002 |    -1.218 |   -0.9199 |   -0.9000 |
-#> |.....................|   -0.8496 |   -0.5319 |   -0.9555 |    -1.002 |
-#> |.....................|   -0.6235 |   -0.7592 |   -0.6838 |...........|
-#> |    U|     480.44943 |     94.21 |    -5.618 |    -1.008 |   -0.2046 |
-#> |.....................|     2.099 |     1.862 |    0.6995 |    0.7529 |
-#> |.....................|     1.479 |     1.209 |     1.357 |...........|
-#> |    X|     480.44943 |     94.21 |  0.003631 |    0.2673 |    0.8149 |
-#> |.....................|     8.162 |     1.862 |    0.6995 |    0.7529 |
-#> |.....................|     1.479 |     1.209 |     1.357 |...........|
-#> |    F| Forward Diff. |     8.806 |    0.8785 |   -0.4202 |  -0.05024 |
-#> |.....................|   -0.1124 |    -4.289 |     3.039 |    0.5974 |
-#> |.....................|    -1.651 |    -2.322 |    -1.843 |...........|
-#> |   41|     480.44100 |     1.001 |    -1.220 |   -0.9197 |   -0.9000 |
-#> |.....................|   -0.8496 |   -0.5318 |   -0.9564 |    -1.002 |
-#> |.....................|   -0.6233 |   -0.7586 |   -0.6835 |...........|
-#> |    U|       480.441 |     94.13 |    -5.620 |    -1.008 |   -0.2046 |
-#> |.....................|     2.100 |     1.862 |    0.6988 |    0.7529 |
-#> |.....................|     1.480 |     1.210 |     1.358 |...........|
-#> |    X|       480.441 |     94.13 |  0.003626 |    0.2673 |    0.8150 |
-#> |.....................|     8.162 |     1.862 |    0.6988 |    0.7529 |
-#> |.....................|     1.480 |     1.210 |     1.358 |...........|
-#> |    F| Forward Diff. |    -4.662 |    0.8724 |   -0.4382 |  -0.05735 |
-#> |.....................|   -0.1541 |    -4.192 |     3.008 |    0.5718 |
-#> |.....................|    -1.633 |    -2.283 |    -1.828 |...........|
-#> |   42|     480.43316 |     1.002 |    -1.221 |   -0.9195 |   -0.9000 |
-#> |.....................|   -0.8495 |   -0.5313 |   -0.9573 |    -1.002 |
-#> |.....................|   -0.6230 |   -0.7579 |   -0.6830 |...........|
-#> |    U|     480.43316 |     94.21 |    -5.621 |    -1.008 |   -0.2046 |
-#> |.....................|     2.100 |     1.862 |    0.6981 |    0.7529 |
-#> |.....................|     1.480 |     1.211 |     1.358 |...........|
-#> |    X|     480.43316 |     94.21 |  0.003622 |    0.2674 |    0.8150 |
-#> |.....................|     8.163 |     1.862 |    0.6981 |    0.7529 |
-#> |.....................|     1.480 |     1.211 |     1.358 |...........|
-#> |    F| Forward Diff. |     8.374 |    0.8709 |   -0.4057 |  -0.04981 |
-#> |.....................|   -0.1077 |    -4.274 |     2.898 |    0.5670 |
-#> |.....................|    -1.709 |    -2.249 |    -1.806 |...........|
-#> |   43|     480.42514 |     1.001 |    -1.222 |   -0.9194 |   -0.8999 |
-#> |.....................|   -0.8495 |   -0.5312 |   -0.9582 |    -1.002 |
-#> |.....................|   -0.6227 |   -0.7573 |   -0.6826 |...........|
-#> |    U|     480.42514 |     94.13 |    -5.622 |    -1.008 |   -0.2046 |
-#> |.....................|     2.100 |     1.862 |    0.6974 |    0.7529 |
-#> |.....................|     1.480 |     1.212 |     1.359 |...........|
-#> |    X|     480.42514 |     94.13 |  0.003617 |    0.2674 |    0.8150 |
-#> |.....................|     8.163 |     1.862 |    0.6974 |    0.7529 |
-#> |.....................|     1.480 |     1.212 |     1.359 |...........|
-#> |    F| Forward Diff. |    -4.560 |    0.8648 |   -0.4238 |  -0.05673 |
-#> |.....................|   -0.1505 |    -4.130 |     2.894 |    0.5588 |
-#> |.....................|    -1.637 |    -2.210 |    -1.785 |...........|
-#> |   44|     480.41757 |     1.002 |    -1.223 |   -0.9192 |   -0.8999 |
-#> |.....................|   -0.8494 |   -0.5307 |   -0.9591 |    -1.002 |
-#> |.....................|   -0.6223 |   -0.7566 |   -0.6821 |...........|
-#> |    U|     480.41757 |     94.21 |    -5.623 |    -1.008 |   -0.2046 |
-#> |.....................|     2.100 |     1.863 |    0.6967 |    0.7528 |
-#> |.....................|     1.481 |     1.212 |     1.359 |...........|
-#> |    X|     480.41757 |     94.21 |  0.003613 |    0.2674 |    0.8150 |
-#> |.....................|     8.164 |     1.863 |    0.6967 |    0.7528 |
-#> |.....................|     1.481 |     1.212 |     1.359 |...........|
-#> |    F| Forward Diff. |     8.260 |    0.8632 |   -0.3905 |  -0.04898 |
-#> |.....................|   -0.1050 |    -4.163 |     2.793 |    0.5626 |
-#> |.....................|    -1.680 |    -2.170 |    -1.767 |...........|
-#> |   45|     480.40986 |     1.001 |    -1.225 |   -0.9190 |   -0.8999 |
-#> |.....................|   -0.8494 |   -0.5306 |   -0.9600 |    -1.002 |
-#> |.....................|   -0.6221 |   -0.7560 |   -0.6818 |...........|
-#> |    U|     480.40986 |     94.13 |    -5.625 |    -1.008 |   -0.2045 |
-#> |.....................|     2.100 |     1.863 |    0.6961 |    0.7528 |
-#> |.....................|     1.481 |     1.213 |     1.360 |...........|
-#> |    X|     480.40986 |     94.13 |  0.003607 |    0.2675 |    0.8150 |
-#> |.....................|     8.164 |     1.863 |    0.6961 |    0.7528 |
-#> |.....................|     1.481 |     1.213 |     1.360 |...........|
-#> |    F| Forward Diff. |    -4.433 |    0.8570 |   -0.4082 |  -0.05598 |
-#> |.....................|   -0.1439 |    -4.083 |     2.776 |   -0.7191 |
-#> |.....................|    -1.623 |    -2.134 |    -1.744 |...........|
-#> |   46|     480.40309 |     1.002 |    -1.226 |   -0.9188 |   -0.8999 |
-#> |.....................|   -0.8493 |   -0.5301 |   -0.9609 |    -1.002 |
-#> |.....................|   -0.6217 |   -0.7553 |   -0.6813 |...........|
-#> |    U|     480.40309 |     94.20 |    -5.626 |    -1.007 |   -0.2045 |
-#> |.....................|     2.100 |     1.863 |    0.6954 |    0.7529 |
-#> |.....................|     1.481 |     1.214 |     1.360 |...........|
-#> |    X|     480.40309 |     94.20 |  0.003603 |    0.2675 |    0.8151 |
-#> |.....................|     8.165 |     1.863 |    0.6954 |    0.7529 |
-#> |.....................|     1.481 |     1.214 |     1.360 |...........|
-#> |    F| Forward Diff. |     7.640 |    0.8551 |   -0.3719 |  -0.04853 |
-#> |.....................|   -0.1037 |    -4.111 |     2.689 |    0.5674 |
-#> |.....................|    -1.653 |    -2.095 |    -1.726 |...........|
-#> |   47|     480.39597 |     1.001 |    -1.227 |   -0.9185 |   -0.8998 |
-#> |.....................|   -0.8492 |   -0.5300 |   -0.9618 |    -1.002 |
-#> |.....................|   -0.6215 |   -0.7547 |   -0.6809 |...........|
-#> |    U|     480.39597 |     94.13 |    -5.627 |    -1.007 |   -0.2045 |
-#> |.....................|     2.100 |     1.863 |    0.6947 |    0.7530 |
-#> |.....................|     1.482 |     1.214 |     1.361 |...........|
-#> |    X|     480.39597 |     94.13 |  0.003598 |    0.2676 |    0.8151 |
-#> |.....................|     8.165 |     1.863 |    0.6947 |    0.7530 |
-#> |.....................|     1.482 |     1.214 |     1.361 |...........|
-#> |    F| Forward Diff. |    -4.827 |    0.8487 |   -0.3865 |  -0.05558 |
-#> |.....................|   -0.1453 |    -3.997 |     2.662 |    0.5449 |
-#> |.....................|    -1.580 |    -2.061 |    -1.701 |...........|
-#> |   48|     480.38900 |     1.002 |    -1.229 |   -0.9184 |   -0.8998 |
-#> |.....................|   -0.8491 |   -0.5297 |   -0.9626 |    -1.002 |
-#> |.....................|   -0.6211 |   -0.7540 |   -0.6805 |...........|
-#> |    U|       480.389 |     94.20 |    -5.629 |    -1.007 |   -0.2044 |
-#> |.....................|     2.100 |     1.864 |    0.6940 |    0.7529 |
-#> |.....................|     1.482 |     1.215 |     1.361 |...........|
-#> |    X|       480.389 |     94.20 |  0.003593 |    0.2676 |    0.8151 |
-#> |.....................|     8.166 |     1.864 |    0.6940 |    0.7529 |
-#> |.....................|     1.482 |     1.215 |     1.361 |...........|
-#> |    F| Forward Diff. |     7.052 |    0.8465 |   -0.3544 |  -0.04836 |
-#> |.....................|   -0.1022 |    -3.917 |     2.636 |    0.5926 |
-#> |.....................|    -1.553 |    -2.027 |    -1.689 |...........|
-#> |   49|     480.38219 |     1.001 |    -1.230 |   -0.9183 |   -0.8998 |
-#> |.....................|   -0.8491 |   -0.5296 |   -0.9634 |    -1.002 |
-#> |.....................|   -0.6209 |   -0.7534 |   -0.6801 |...........|
-#> |    U|     480.38219 |     94.13 |    -5.630 |    -1.007 |   -0.2044 |
-#> |.....................|     2.100 |     1.864 |    0.6934 |    0.7529 |
-#> |.....................|     1.482 |     1.216 |     1.362 |...........|
-#> |    X|     480.38219 |     94.13 |  0.003587 |    0.2676 |    0.8151 |
-#> |.....................|     8.166 |     1.864 |    0.6934 |    0.7529 |
-#> |.....................|     1.482 |     1.216 |     1.362 |...........|
-#> |    F| Forward Diff. |    -4.619 |    0.8406 |   -0.3725 |  -0.05439 |
-#> |.....................|   -0.1411 |    -3.915 |     2.594 |   -0.6808 |
-#> |.....................|    -1.519 |    -1.986 |    -1.659 |...........|
-#> |   50|     480.37598 |     1.002 |    -1.232 |   -0.9180 |   -0.8998 |
-#> |.....................|   -0.8490 |   -0.5292 |   -0.9644 |    -1.002 |
-#> |.....................|   -0.6206 |   -0.7528 |   -0.6796 |...........|
-#> |    U|     480.37598 |     94.20 |    -5.632 |    -1.007 |   -0.2044 |
-#> |.....................|     2.100 |     1.864 |    0.6927 |    0.7530 |
-#> |.....................|     1.483 |     1.216 |     1.362 |...........|
-#> |    X|     480.37598 |     94.20 |  0.003582 |    0.2677 |    0.8152 |
-#> |.....................|     8.167 |     1.864 |    0.6927 |    0.7530 |
-#> |.....................|     1.483 |     1.216 |     1.362 |...........|
-#> |    F| Forward Diff. |     6.566 |    0.8383 |   -0.3380 |  -0.04700 |
-#> |.....................|  -0.09943 |    -3.949 |     2.377 |    0.5751 |
-#> |.....................|    -1.561 |    -1.951 |    -1.641 |...........|
-#> |   51|     480.36982 |     1.001 |    -1.233 |   -0.9178 |   -0.8997 |
-#> |.....................|   -0.8489 |   -0.5291 |   -0.9651 |    -1.002 |
-#> |.....................|   -0.6204 |   -0.7522 |   -0.6792 |...........|
-#> |    U|     480.36982 |     94.12 |    -5.633 |    -1.006 |   -0.2043 |
-#> |.....................|     2.100 |     1.864 |    0.6922 |    0.7530 |
-#> |.....................|     1.483 |     1.217 |     1.363 |...........|
-#> |    X|     480.36982 |     94.12 |  0.003577 |    0.2677 |    0.8152 |
-#> |.....................|     8.167 |     1.864 |    0.6922 |    0.7530 |
-#> |.....................|     1.483 |     1.217 |     1.363 |...........|
-#> |    F| Forward Diff. |    -5.243 |    0.8317 |   -0.3515 |  -0.05392 |
-#> |.....................|   -0.1358 |    -3.830 |     2.493 |    0.5823 |
-#> |.....................|    -1.510 |    -1.918 |    -1.620 |...........|
-#> |   52|     480.36331 |     1.002 |    -1.235 |   -0.9176 |   -0.8997 |
-#> |.....................|   -0.8489 |   -0.5289 |   -0.9659 |    -1.002 |
-#> |.....................|   -0.6201 |   -0.7516 |   -0.6788 |...........|
-#> |    U|     480.36331 |     94.19 |    -5.635 |    -1.006 |   -0.2043 |
-#> |.....................|     2.100 |     1.864 |    0.6916 |    0.7530 |
-#> |.....................|     1.483 |     1.218 |     1.363 |...........|
-#> |    X|     480.36331 |     94.19 |  0.003572 |    0.2677 |    0.8152 |
-#> |.....................|     8.168 |     1.864 |    0.6916 |    0.7530 |
-#> |.....................|     1.483 |     1.218 |     1.363 |...........|
-#> |    F| Forward Diff. |     5.492 |    0.8288 |   -0.3226 |  -0.04732 |
-#> |.....................|  -0.09956 |    -3.829 |     2.435 |    0.5676 |
-#> |.....................|    -1.517 |    -1.882 |    -1.604 |...........|
-#> |   53|     480.35731 |     1.001 |    -1.236 |   -0.9175 |   -0.8996 |
-#> |.....................|   -0.8488 |   -0.5288 |   -0.9666 |    -1.002 |
-#> |.....................|   -0.6198 |   -0.7510 |   -0.6783 |...........|
-#> |    U|     480.35731 |     94.12 |    -5.636 |    -1.006 |   -0.2043 |
-#> |.....................|     2.100 |     1.864 |    0.6910 |    0.7529 |
-#> |.....................|     1.484 |     1.218 |     1.364 |...........|
-#> |    X|     480.35731 |     94.12 |  0.003566 |    0.2678 |    0.8152 |
-#> |.....................|     8.168 |     1.864 |    0.6910 |    0.7529 |
-#> |.....................|     1.484 |     1.218 |     1.364 |...........|
-#> |    F| Forward Diff. |    -5.442 |    0.8230 |   -0.3401 |  -0.05270 |
-#> |.....................|   -0.1329 |    -3.818 |     2.394 |   -0.6865 |
-#> |.....................|    -1.462 |    -1.826 |    -1.568 |...........|
-#> |   54|     480.35158 |     1.002 |    -1.238 |   -0.9173 |   -0.8996 |
-#> |.....................|   -0.8487 |   -0.5286 |   -0.9675 |    -1.002 |
-#> |.....................|   -0.6197 |   -0.7504 |   -0.6779 |...........|
-#> |    U|     480.35158 |     94.19 |    -5.638 |    -1.006 |   -0.2042 |
-#> |.....................|     2.100 |     1.864 |    0.6904 |    0.7530 |
-#> |.....................|     1.484 |     1.219 |     1.364 |...........|
-#> |    X|     480.35158 |     94.19 |  0.003561 |    0.2678 |    0.8153 |
-#> |.....................|     8.169 |     1.864 |    0.6904 |    0.7530 |
-#> |.....................|     1.484 |     1.219 |     1.364 |...........|
-#> |    F| Forward Diff. |     5.119 |    0.8198 |   -0.3066 |  -0.04724 |
-#> |.....................|   -0.1005 |    -3.787 |     2.338 |    0.5896 |
-#> |.....................|    -1.465 |    -1.812 |    -1.559 |...........|
-#> |   55|     480.34603 |     1.001 |    -1.239 |   -0.9170 |   -0.8996 |
-#> |.....................|   -0.8486 |   -0.5283 |   -0.9683 |    -1.002 |
-#> |.....................|   -0.6195 |   -0.7499 |   -0.6775 |...........|
-#> |    U|     480.34603 |     94.12 |    -5.639 |    -1.006 |   -0.2042 |
-#> |.....................|     2.100 |     1.865 |    0.6897 |    0.7530 |
-#> |.....................|     1.484 |     1.220 |     1.364 |...........|
-#> |    X|     480.34603 |     94.12 |  0.003555 |    0.2679 |    0.8153 |
-#> |.....................|     8.170 |     1.865 |    0.6897 |    0.7530 |
-#> |.....................|     1.484 |     1.220 |     1.364 |...........|
-#> |    F| Forward Diff. |    -5.669 |    0.8137 |   -0.3182 |  -0.05158 |
-#> |.....................|   -0.1292 |    -3.845 |     2.251 |    0.5349 |
-#> |.....................|    -1.532 |    -1.781 |    -1.537 |...........|
-#> |   56|     480.33997 |     1.002 |    -1.241 |   -0.9169 |   -0.8995 |
-#> |.....................|   -0.8486 |   -0.5282 |   -0.9690 |    -1.002 |
-#> |.....................|   -0.6192 |   -0.7493 |   -0.6772 |...........|
-#> |    U|     480.33997 |     94.19 |    -5.641 |    -1.005 |   -0.2041 |
-#> |.....................|     2.101 |     1.865 |    0.6892 |    0.7529 |
-#> |.....................|     1.484 |     1.220 |     1.365 |...........|
-#> |    X|     480.33997 |     94.19 |  0.003550 |    0.2679 |    0.8153 |
-#> |.....................|     8.170 |     1.865 |    0.6892 |    0.7529 |
-#> |.....................|     1.484 |     1.220 |     1.365 |...........|
-#> |    F| Forward Diff. |     4.944 |    0.8109 |   -0.2900 |  -0.04418 |
-#> |.....................|  -0.09220 |    -3.817 |     2.207 |    0.5423 |
-#> |.....................|    -1.530 |    -1.750 |    -1.524 |...........|
-#> |   57|     480.33440 |     1.001 |    -1.242 |   -0.9168 |   -0.8995 |
-#> |.....................|   -0.8485 |   -0.5280 |   -0.9697 |    -1.002 |
-#> |.....................|   -0.6188 |   -0.7487 |   -0.6768 |...........|
-#> |    U|      480.3344 |     94.12 |    -5.642 |    -1.005 |   -0.2041 |
-#> |.....................|     2.101 |     1.865 |    0.6887 |    0.7529 |
-#> |.....................|     1.485 |     1.221 |     1.365 |...........|
-#> |    X|      480.3344 |     94.12 |  0.003544 |    0.2679 |    0.8154 |
-#> |.....................|     8.171 |     1.865 |    0.6887 |    0.7529 |
-#> |.....................|     1.485 |     1.221 |     1.365 |...........|
-#> |    F| Forward Diff. |    -5.630 |    0.8048 |   -0.3070 |  -0.04965 |
-#> |.....................|   -0.1246 |    -3.770 |     2.179 |    0.5400 |
-#> |.....................|    -1.465 |    -1.710 |    -1.500 |...........|
-#> |   58|     480.32852 |     1.002 |    -1.244 |   -0.9167 |   -0.8994 |
-#> |.....................|   -0.8485 |   -0.5278 |   -0.9703 |    -1.002 |
-#> |.....................|   -0.6184 |   -0.7482 |   -0.6764 |...........|
-#> |    U|     480.32852 |     94.19 |    -5.644 |    -1.005 |   -0.2041 |
-#> |.....................|     2.101 |     1.865 |    0.6882 |    0.7528 |
-#> |.....................|     1.485 |     1.221 |     1.366 |...........|
-#> |    X|     480.32852 |     94.19 |  0.003538 |    0.2679 |    0.8154 |
-#> |.....................|     8.171 |     1.865 |    0.6882 |    0.7528 |
-#> |.....................|     1.485 |     1.221 |     1.366 |...........|
-#> |    F| Forward Diff. |     4.819 |    0.8018 |   -0.2789 |  -0.04260 |
-#> |.....................|  -0.08823 |    -3.653 |     2.177 |   -0.6593 |
-#> |.....................|    -1.384 |    -1.678 |    -1.478 |...........|
-#> |   59|     480.32382 |     1.001 |    -1.246 |   -0.9164 |   -0.8994 |
-#> |.....................|   -0.8484 |   -0.5276 |   -0.9711 |    -1.002 |
-#> |.....................|   -0.6183 |   -0.7477 |   -0.6761 |...........|
-#> |    U|     480.32382 |     94.12 |    -5.646 |    -1.005 |   -0.2040 |
-#> |.....................|     2.101 |     1.865 |    0.6876 |    0.7529 |
-#> |.....................|     1.486 |     1.222 |     1.366 |...........|
-#> |    X|     480.32382 |     94.12 |  0.003533 |    0.2680 |    0.8155 |
-#> |.....................|     8.172 |     1.865 |    0.6876 |    0.7529 |
-#> |.....................|     1.486 |     1.222 |     1.366 |...........|
-#> |    F| Forward Diff. |    -5.225 |    0.7951 |   -0.2896 |  -0.04843 |
-#> |.....................|   -0.1194 |    -3.720 |     2.091 |   -0.7072 |
-#> |.....................|    -1.430 |    -1.641 |    -1.454 |...........|
-#> |   60|     480.31902 |     1.002 |    -1.247 |   -0.9160 |   -0.8993 |
-#> |.....................|   -0.8482 |   -0.5273 |   -0.9719 |    -1.002 |
-#> |.....................|   -0.6182 |   -0.7473 |   -0.6757 |...........|
-#> |    U|     480.31902 |     94.19 |    -5.647 |    -1.005 |   -0.2039 |
-#> |.....................|     2.101 |     1.865 |    0.6870 |    0.7531 |
-#> |.....................|     1.486 |     1.222 |     1.367 |...........|
-#> |    X|     480.31902 |     94.19 |  0.003527 |    0.2681 |    0.8155 |
-#> |.....................|     8.173 |     1.865 |    0.6870 |    0.7531 |
-#> |.....................|     1.486 |     1.222 |     1.367 |...........|
-#> |    F| Forward Diff. |     4.904 |    0.7922 |   -0.2469 |  -0.04034 |
-#> |.....................|  -0.08539 |    -3.545 |     2.094 |   -0.6237 |
-#> |.....................|    -1.331 |    -1.619 |    -1.454 |...........|
-#> |   61|     480.31471 |     1.001 |    -1.249 |   -0.9156 |   -0.8993 |
-#> |.....................|   -0.8481 |   -0.5271 |   -0.9727 |    -1.001 |
-#> |.....................|   -0.6181 |   -0.7468 |   -0.6753 |...........|
-#> |    U|     480.31471 |     94.12 |    -5.649 |    -1.004 |   -0.2039 |
-#> |.....................|     2.101 |     1.866 |    0.6864 |    0.7533 |
-#> |.....................|     1.486 |     1.223 |     1.367 |...........|
-#> |    X|     480.31471 |     94.12 |  0.003522 |    0.2681 |    0.8156 |
-#> |.....................|     8.174 |     1.866 |    0.6864 |    0.7533 |
-#> |.....................|     1.486 |     1.223 |     1.367 |...........|
-#> |    F| Forward Diff. |    -5.295 |    0.7853 |   -0.2507 |  -0.04627 |
-#> |.....................|   -0.1126 |    -3.760 |     1.942 |   -0.7288 |
-#> |.....................|    -1.482 |    -1.617 |    -1.436 |...........|
-#> |   62|     480.31013 |     1.002 |    -1.250 |   -0.9152 |   -0.8992 |
-#> |.....................|   -0.8480 |   -0.5269 |   -0.9734 |    -1.001 |
-#> |.....................|   -0.6180 |   -0.7464 |   -0.6750 |...........|
-#> |    U|     480.31013 |     94.19 |    -5.650 |    -1.004 |   -0.2038 |
-#> |.....................|     2.101 |     1.866 |    0.6859 |    0.7535 |
-#> |.....................|     1.486 |     1.223 |     1.367 |...........|
-#> |    X|     480.31013 |     94.19 |  0.003516 |    0.2682 |    0.8156 |
-#> |.....................|     8.175 |     1.866 |    0.6859 |    0.7535 |
-#> |.....................|     1.486 |     1.223 |     1.367 |...........|
-#> |    F| Forward Diff. |     4.435 |    0.7821 |   -0.2118 |  -0.03855 |
-#> |.....................|  -0.07590 |    -3.495 |     2.000 |   -0.6027 |
-#> |.....................|    -1.382 |    -1.576 |    -1.413 |...........|
-#> |   63|     480.30581 |     1.001 |    -1.252 |   -0.9149 |   -0.8991 |
-#> |.....................|   -0.8479 |   -0.5266 |   -0.9741 |    -1.001 |
-#> |.....................|   -0.6178 |   -0.7459 |   -0.6746 |...........|
-#> |    U|     480.30581 |     94.12 |    -5.652 |    -1.003 |   -0.2037 |
-#> |.....................|     2.101 |     1.866 |    0.6854 |    0.7536 |
-#> |.....................|     1.486 |     1.224 |     1.368 |...........|
-#> |    X|     480.30581 |     94.12 |  0.003510 |    0.2683 |    0.8157 |
-#> |.....................|     8.176 |     1.866 |    0.6854 |    0.7536 |
-#> |.....................|     1.486 |     1.224 |     1.368 |...........|
-#> |    F| Forward Diff. |    -5.315 |    0.7789 |   -0.2090 |  -0.03720 |
-#> |.....................|  -0.09944 |    -3.577 |     1.911 |   -0.6518 |
-#> |.....................|    -1.378 |    -1.528 |    -1.376 |...........|
-#> |   64|     480.30125 |     1.002 |    -1.254 |   -0.9146 |   -0.8990 |
-#> |.....................|   -0.8478 |   -0.5264 |   -0.9748 |    -1.001 |
-#> |.....................|   -0.6176 |   -0.7454 |   -0.6743 |...........|
-#> |    U|     480.30125 |     94.19 |    -5.654 |    -1.003 |   -0.2037 |
-#> |.....................|     2.101 |     1.866 |    0.6848 |    0.7538 |
-#> |.....................|     1.486 |     1.224 |     1.368 |...........|
-#> |    X|     480.30125 |     94.19 |  0.003505 |    0.2683 |    0.8157 |
-#> |.....................|     8.177 |     1.866 |    0.6848 |    0.7538 |
-#> |.....................|     1.486 |     1.224 |     1.368 |...........|
-#> |    F| Forward Diff. |     4.353 |    0.7723 |   -0.1834 |  -0.03622 |
-#> |.....................|  -0.07047 |    -3.672 |     1.822 |   -0.6713 |
-#> |.....................|    -1.445 |    -1.532 |    -1.389 |...........|
-#> |   65|     480.29714 |     1.001 |    -1.255 |   -0.9143 |   -0.8990 |
-#> |.....................|   -0.8476 |   -0.5261 |   -0.9754 |    -1.001 |
-#> |.....................|   -0.6174 |   -0.7450 |   -0.6740 |...........|
-#> |    U|     480.29714 |     94.12 |    -5.655 |    -1.003 |   -0.2036 |
-#> |.....................|     2.101 |     1.866 |    0.6843 |    0.7539 |
-#> |.....................|     1.487 |     1.225 |     1.369 |...........|
-#> |    X|     480.29714 |     94.12 |  0.003499 |    0.2684 |    0.8158 |
-#> |.....................|     8.178 |     1.866 |    0.6843 |    0.7539 |
-#> |.....................|     1.487 |     1.225 |     1.369 |...........|
-#> |    F| Forward Diff. |    -5.435 |    0.7663 |   -0.1878 |  -0.03986 |
-#> |.....................|   -0.1019 |    -3.343 |     1.893 |    0.6711 |
-#> |.....................|    -1.269 |    -1.487 |    -1.354 |...........|
-#> |   66|     480.29215 |     1.002 |    -1.257 |   -0.9143 |   -0.8989 |
-#> |.....................|   -0.8476 |   -0.5260 |   -0.9760 |    -1.001 |
-#> |.....................|   -0.6172 |   -0.7444 |   -0.6736 |...........|
-#> |    U|     480.29215 |     94.18 |    -5.657 |    -1.003 |   -0.2036 |
-#> |.....................|     2.102 |     1.867 |    0.6839 |    0.7538 |
-#> |.....................|     1.487 |     1.226 |     1.369 |...........|
-#> |    X|     480.29215 |     94.18 |  0.003493 |    0.2684 |    0.8158 |
-#> |.....................|     8.179 |     1.867 |    0.6839 |    0.7538 |
-#> |.....................|     1.487 |     1.226 |     1.369 |...........|
-#> |    F| Forward Diff. |     4.161 |    0.7621 |   -0.1686 |  -0.03452 |
-#> |.....................|  -0.06632 |    -3.552 |     1.775 |    0.6057 |
-#> |.....................|    -1.379 |    -1.473 |    -1.364 |...........|
-#> |   67|     480.28721 |     1.001 |    -1.259 |   -0.9145 |   -0.8989 |
-#> |.....................|   -0.8476 |   -0.5257 |   -0.9765 |    -1.001 |
-#> |.....................|   -0.6170 |   -0.7439 |   -0.6732 |...........|
-#> |    U|     480.28721 |     94.12 |    -5.659 |    -1.003 |   -0.2035 |
-#> |.....................|     2.102 |     1.867 |    0.6836 |    0.7537 |
-#> |.....................|     1.487 |     1.226 |     1.369 |...........|
-#> |    X|     480.28721 |     94.12 |  0.003487 |    0.2684 |    0.8159 |
-#> |.....................|     8.179 |     1.867 |    0.6836 |    0.7537 |
-#> |.....................|     1.487 |     1.226 |     1.369 |...........|
-#> |    F| Forward Diff. |    -4.925 |    0.7584 |   -0.1913 |  -0.03513 |
-#> |.....................|  -0.09132 |    -3.418 |     1.781 |   -0.6203 |
-#> |.....................|    -1.349 |    -1.417 |    -1.313 |...........|
-#> |   68|     480.28278 |     1.002 |    -1.260 |   -0.9144 |   -0.8988 |
-#> |.....................|   -0.8475 |   -0.5255 |   -0.9770 |    -1.001 |
-#> |.....................|   -0.6167 |   -0.7434 |   -0.6728 |...........|
-#> |    U|     480.28278 |     94.19 |    -5.660 |    -1.003 |   -0.2035 |
-#> |.....................|     2.102 |     1.867 |    0.6832 |    0.7537 |
-#> |.....................|     1.487 |     1.227 |     1.370 |...........|
-#> |    X|     480.28278 |     94.19 |  0.003481 |    0.2684 |    0.8159 |
-#> |.....................|     8.179 |     1.867 |    0.6832 |    0.7537 |
-#> |.....................|     1.487 |     1.227 |     1.370 |...........|
-#> |    F| Forward Diff. |     4.442 |    0.7524 |   -0.1734 |  -0.03276 |
-#> |.....................|  -0.06267 |    -3.400 |     1.746 |   -0.5960 |
-#> |.....................|    -1.307 |    -1.411 |    -1.323 |...........|
-#> |   69|     480.27897 |     1.001 |    -1.262 |   -0.9141 |   -0.8988 |
-#> |.....................|   -0.8474 |   -0.5252 |   -0.9776 |    -1.001 |
-#> |.....................|   -0.6165 |   -0.7431 |   -0.6724 |...........|
-#> |    U|     480.27897 |     94.13 |    -5.662 |    -1.003 |   -0.2034 |
-#> |.....................|     2.102 |     1.867 |    0.6827 |    0.7539 |
-#> |.....................|     1.488 |     1.227 |     1.370 |...........|
-#> |    X|     480.27897 |     94.13 |  0.003475 |    0.2684 |    0.8159 |
-#> |.....................|     8.180 |     1.867 |    0.6827 |    0.7539 |
-#> |.....................|     1.488 |     1.227 |     1.370 |...........|
-#> |    F| Forward Diff. |    -4.732 |    0.7463 |   -0.1764 |  -0.03625 |
-#> |.....................|  -0.08933 |    -3.375 |     1.716 |    0.6486 |
-#> |.....................|    -1.273 |    -1.374 |    -1.283 |...........|
-#> |   70|     480.27440 |     1.002 |    -1.264 |   -0.9140 |   -0.8987 |
-#> |.....................|   -0.8473 |   -0.5250 |   -0.9782 |    -1.001 |
-#> |.....................|   -0.6164 |   -0.7427 |   -0.6721 |...........|
-#> |    U|      480.2744 |     94.19 |    -5.664 |    -1.003 |   -0.2034 |
-#> |.....................|     2.102 |     1.867 |    0.6823 |    0.7538 |
-#> |.....................|     1.488 |     1.227 |     1.371 |...........|
-#> |    X|      480.2744 |     94.19 |  0.003469 |    0.2684 |    0.8160 |
-#> |.....................|     8.181 |     1.867 |    0.6823 |    0.7538 |
-#> |.....................|     1.488 |     1.227 |     1.371 |...........|
-#> |    F| Forward Diff. |     4.305 |    0.7431 |   -0.1535 |  -0.02884 |
-#> |.....................|  -0.05624 |    -3.424 |     1.641 |   -0.6166 |
-#> |.....................|    -1.366 |    -1.368 |    -1.291 |...........|
-#> |   71|     480.27043 |     1.001 |    -1.266 |   -0.9140 |   -0.8987 |
-#> |.....................|   -0.8473 |   -0.5247 |   -0.9786 |    -1.001 |
-#> |.....................|   -0.6161 |   -0.7423 |   -0.6718 |...........|
-#> |    U|     480.27043 |     94.13 |    -5.666 |    -1.002 |   -0.2033 |
-#> |.....................|     2.102 |     1.868 |    0.6819 |    0.7539 |
-#> |.....................|     1.488 |     1.228 |     1.371 |...........|
-#> |    X|     480.27043 |     94.13 |  0.003463 |    0.2685 |    0.8160 |
-#> |.....................|     8.181 |     1.868 |    0.6819 |    0.7539 |
-#> |.....................|     1.488 |     1.228 |     1.371 |...........|
-#> |    F| Forward Diff. |    -4.306 |    0.7372 |   -0.1665 |  -0.03186 |
-#> |.....................|  -0.08221 |    -3.333 |     1.631 |   -0.6040 |
-#> |.....................|    -1.265 |    -1.322 |    -1.255 |...........|
-#> |   72|     480.26665 |     1.002 |    -1.267 |   -0.9136 |   -0.8986 |
-#> |.....................|   -0.8471 |   -0.5244 |   -0.9791 |    -1.001 |
-#> |.....................|   -0.6160 |   -0.7419 |   -0.6714 |...........|
-#> |    U|     480.26665 |     94.19 |    -5.667 |    -1.002 |   -0.2032 |
-#> |.....................|     2.102 |     1.868 |    0.6815 |    0.7540 |
-#> |.....................|     1.488 |     1.228 |     1.371 |...........|
-#> |    X|     480.26665 |     94.19 |  0.003457 |    0.2685 |    0.8161 |
-#> |.....................|     8.182 |     1.868 |    0.6815 |    0.7540 |
-#> |.....................|     1.488 |     1.228 |     1.371 |...........|
-#> |    F| Forward Diff. |     4.654 |    0.7327 |   -0.1326 |  -0.02617 |
-#> |.....................|  -0.04981 |    -3.394 |     1.559 |   -0.6139 |
-#> |.....................|    -1.358 |    -1.341 |    -1.268 |...........|
-#> |   73|     480.26300 |     1.001 |    -1.269 |   -0.9132 |   -0.8985 |
-#> |.....................|   -0.8470 |   -0.5241 |   -0.9796 |    -1.000 |
-#> |.....................|   -0.6158 |   -0.7416 |   -0.6711 |...........|
-#> |    U|       480.263 |     94.13 |    -5.669 |    -1.002 |   -0.2032 |
-#> |.....................|     2.102 |     1.868 |    0.6812 |    0.7542 |
-#> |.....................|     1.488 |     1.229 |     1.372 |...........|
-#> |    X|       480.263 |     94.13 |  0.003451 |    0.2686 |    0.8162 |
-#> |.....................|     8.183 |     1.868 |    0.6812 |    0.7542 |
-#> |.....................|     1.488 |     1.229 |     1.372 |...........|
-#> |    F| Forward Diff. |    -4.009 |    0.7258 |   -0.1343 |  -0.03035 |
-#> |.....................|  -0.07619 |    -3.164 |     1.609 |   -0.5397 |
-#> |.....................|    -1.251 |    -1.282 |    -1.219 |...........|
-#> |   74|     480.25930 |     1.002 |    -1.271 |   -0.9130 |   -0.8985 |
-#> |.....................|   -0.8469 |   -0.5239 |   -0.9802 |    -1.000 |
-#> |.....................|   -0.6155 |   -0.7412 |   -0.6708 |...........|
-#> |    U|      480.2593 |     94.19 |    -5.671 |    -1.002 |   -0.2031 |
-#> |.....................|     2.102 |     1.868 |    0.6807 |    0.7543 |
-#> |.....................|     1.489 |     1.229 |     1.372 |...........|
-#> |    X|      480.2593 |     94.19 |  0.003445 |    0.2686 |    0.8162 |
-#> |.....................|     8.184 |     1.868 |    0.6807 |    0.7543 |
-#> |.....................|     1.489 |     1.229 |     1.372 |...........|
-#> |    F| Forward Diff. |     4.851 |    0.7223 |   -0.1045 |  -0.02290 |
-#> |.....................|  -0.04316 |    -3.376 |     1.478 |    0.6193 |
-#> |.....................|    -1.343 |    -1.302 |    -1.232 |...........|
-#> |   75|     480.25486 |     1.001 |    -1.273 |   -0.9131 |   -0.8984 |
-#> |.....................|   -0.8469 |   -0.5237 |   -0.9805 |    -1.000 |
-#> |.....................|   -0.6152 |   -0.7408 |   -0.6705 |...........|
-#> |    U|     480.25486 |     94.14 |    -5.673 |    -1.002 |   -0.2030 |
-#> |.....................|     2.102 |     1.868 |    0.6805 |    0.7542 |
-#> |.....................|     1.489 |     1.230 |     1.373 |...........|
-#> |    X|     480.25486 |     94.14 |  0.003439 |    0.2686 |    0.8162 |
-#> |.....................|     8.184 |     1.868 |    0.6805 |    0.7542 |
-#> |.....................|     1.489 |     1.230 |     1.373 |...........|
-#> |    F| Forward Diff. |    -3.282 |    0.7167 |   -0.1236 |  -0.02586 |
-#> |.....................|  -0.06793 |    -3.294 |     1.470 |    0.6693 |
-#> |.....................|    -1.247 |    -1.242 |    -1.194 |...........|
-#> |   76|     480.25000 |     1.002 |    -1.274 |   -0.9134 |   -0.8984 |
-#> |.....................|   -0.8469 |   -0.5231 |   -0.9806 |    -1.001 |
-#> |.....................|   -0.6147 |   -0.7402 |   -0.6701 |...........|
-#> |    U|        480.25 |     94.20 |    -5.674 |    -1.002 |   -0.2030 |
-#> |.....................|     2.102 |     1.869 |    0.6804 |    0.7539 |
-#> |.....................|     1.490 |     1.230 |     1.373 |...........|
-#> |    X|        480.25 |     94.20 |  0.003434 |    0.2686 |    0.8163 |
-#> |.....................|     8.184 |     1.869 |    0.6804 |    0.7539 |
-#> |.....................|     1.490 |     1.230 |     1.373 |...........|
-#> |    F| Forward Diff. |     5.823 |    0.7134 |   -0.1173 |  -0.02040 |
-#> |.....................|  -0.04062 |    -3.151 |     1.491 |   -0.5685 |
-#> |.....................|    -1.243 |    -1.237 |    -1.210 |...........|
-#> |   77|     480.24598 |     1.001 |    -1.276 |   -0.9134 |   -0.8984 |
-#> |.....................|   -0.8469 |   -0.5229 |   -0.9809 |    -1.001 |
-#> |.....................|   -0.6145 |   -0.7399 |   -0.6698 |...........|
-#> |    U|     480.24598 |     94.13 |    -5.676 |    -1.002 |   -0.2030 |
-#> |.....................|     2.102 |     1.869 |    0.6802 |    0.7539 |
-#> |.....................|     1.490 |     1.231 |     1.373 |...........|
-#> |    X|     480.24598 |     94.13 |  0.003427 |    0.2686 |    0.8163 |
-#> |.....................|     8.184 |     1.869 |    0.6802 |    0.7539 |
-#> |.....................|     1.490 |     1.231 |     1.373 |...........|
-#> |    F| Forward Diff. |    -3.294 |    0.7076 |   -0.1362 |  -0.02383 |
-#> |.....................|  -0.06566 |    -3.147 |     1.461 |    0.6663 |
-#> |.....................|    -1.244 |    -1.185 |    -1.155 |...........|
-#> |   78|     480.24152 |     1.002 |    -1.278 |   -0.9134 |   -0.8983 |
-#> |.....................|   -0.8469 |   -0.5225 |   -0.9813 |    -1.001 |
-#> |.....................|   -0.6142 |   -0.7395 |   -0.6694 |...........|
-#> |    U|     480.24152 |     94.19 |    -5.678 |    -1.002 |   -0.2030 |
-#> |.....................|     2.102 |     1.869 |    0.6799 |    0.7538 |
-#> |.....................|     1.490 |     1.231 |     1.374 |...........|
-#> |    X|     480.24152 |     94.19 |  0.003421 |    0.2686 |    0.8163 |
-#> |.....................|     8.184 |     1.869 |    0.6799 |    0.7538 |
-#> |.....................|     1.490 |     1.231 |     1.374 |...........|
-#> |    F| Forward Diff. |     4.573 |    0.7031 |   -0.1214 |  -0.01999 |
-#> |.....................|  -0.04022 |    -3.129 |     1.425 |    0.6287 |
-#> |.....................|    -1.274 |    -1.197 |    -1.174 |...........|
-#> |   79|     480.23703 |     1.001 |    -1.280 |   -0.9136 |   -0.8983 |
-#> |.....................|   -0.8469 |   -0.5223 |   -0.9815 |    -1.001 |
-#> |.....................|   -0.6136 |   -0.7392 |   -0.6691 |...........|
-#> |    U|     480.23703 |     94.13 |    -5.680 |    -1.002 |   -0.2030 |
-#> |.....................|     2.102 |     1.869 |    0.6797 |    0.7536 |
-#> |.....................|     1.491 |     1.231 |     1.374 |...........|
-#> |    X|     480.23703 |     94.13 |  0.003415 |    0.2685 |    0.8163 |
-#> |.....................|     8.184 |     1.869 |    0.6797 |    0.7536 |
-#> |.....................|     1.491 |     1.231 |     1.374 |...........|
-#> |    F| Forward Diff. |    -3.496 |    0.6977 |   -0.1464 |  -0.02500 |
-#> |.....................|  -0.06997 |    -3.031 |     1.316 |    0.6455 |
-#> |.....................|    -1.198 |    -1.144 |    -1.124 |...........|
-#> |   80|     480.23246 |     1.002 |    -1.281 |   -0.9138 |   -0.8983 |
-#> |.....................|   -0.8469 |   -0.5219 |   -0.9816 |    -1.001 |
-#> |.....................|   -0.6131 |   -0.7387 |   -0.6687 |...........|
-#> |    U|     480.23246 |     94.19 |    -5.681 |    -1.002 |   -0.2030 |
-#> |.....................|     2.102 |     1.870 |    0.6796 |    0.7533 |
-#> |.....................|     1.492 |     1.232 |     1.375 |...........|
-#> |    X|     480.23246 |     94.19 |  0.003409 |    0.2685 |    0.8163 |
-#> |.....................|     8.184 |     1.870 |    0.6796 |    0.7533 |
-#> |.....................|     1.492 |     1.232 |     1.375 |...........|
-#> |    F| Forward Diff. |     4.825 |    0.6940 |   -0.1347 |  -0.01919 |
-#> |.....................|  -0.03939 |    -3.118 |     1.378 |    0.5922 |
-#> |.....................|    -1.219 |    -1.136 |    -1.127 |...........|
-#> |   81|     480.22809 |     1.001 |    -1.283 |   -0.9138 |   -0.8983 |
-#> |.....................|   -0.8469 |   -0.5217 |   -0.9816 |    -1.002 |
-#> |.....................|   -0.6127 |   -0.7384 |   -0.6684 |...........|
-#> |    U|     480.22809 |     94.14 |    -5.683 |    -1.002 |   -0.2029 |
-#> |.....................|     2.102 |     1.870 |    0.6796 |    0.7531 |
-#> |.....................|     1.492 |     1.232 |     1.375 |...........|
-#> |    X|     480.22809 |     94.14 |  0.003403 |    0.2685 |    0.8163 |
-#> |.....................|     8.184 |     1.870 |    0.6796 |    0.7531 |
-#> |.....................|     1.492 |     1.232 |     1.375 |...........|
-#> |    F| Forward Diff. |    -3.001 |    0.6885 |   -0.1518 |  -0.02256 |
-#> |.....................|  -0.06414 |    -2.892 |     1.443 |    0.6415 |
-#> |.....................|    -1.085 |    -1.098 |    -1.101 |...........|
-#> |   82|     480.22387 |     1.002 |    -1.285 |   -0.9139 |   -0.8983 |
-#> |.....................|   -0.8469 |   -0.5212 |   -0.9821 |    -1.002 |
-#> |.....................|   -0.6124 |   -0.7381 |   -0.6680 |...........|
-#> |    U|     480.22387 |     94.19 |    -5.685 |    -1.002 |   -0.2029 |
-#> |.....................|     2.102 |     1.870 |    0.6793 |    0.7529 |
-#> |.....................|     1.492 |     1.232 |     1.375 |...........|
-#> |    X|     480.22387 |     94.19 |  0.003397 |    0.2685 |    0.8163 |
-#> |.....................|     8.184 |     1.870 |    0.6793 |    0.7529 |
-#> |.....................|     1.492 |     1.232 |     1.375 |...........|
-#> |    F| Forward Diff. |     5.360 |    0.6846 |   -0.1392 |  -0.01938 |
-#> |.....................|  -0.04006 |    -2.853 |     1.421 |   -0.5715 |
-#> |.....................|    -1.064 |    -1.117 |    -1.118 |...........|
-#> |   83|     480.22054 |     1.001 |    -1.287 |   -0.9139 |   -0.8983 |
-#> |.....................|   -0.8469 |   -0.5210 |   -0.9826 |    -1.002 |
-#> |.....................|   -0.6125 |   -0.7380 |   -0.6676 |...........|
-#> |    U|     480.22054 |     94.14 |    -5.687 |    -1.002 |   -0.2029 |
-#> |.....................|     2.102 |     1.871 |    0.6789 |    0.7530 |
-#> |.....................|     1.492 |     1.233 |     1.376 |...........|
-#> |    X|     480.22054 |     94.14 |  0.003391 |    0.2685 |    0.8163 |
-#> |.....................|     8.184 |     1.871 |    0.6789 |    0.7530 |
-#> |.....................|     1.492 |     1.233 |     1.376 |...........|
-#> |    F| Forward Diff. |    -2.774 |    0.6781 |   -0.1521 |  -0.02419 |
-#> |.....................|  -0.06697 |    -2.800 |     1.392 |    0.6467 |
-#> |.....................|    -1.111 |    -1.074 |    -1.064 |...........|
-#> |   84|     480.21670 |     1.002 |    -1.288 |   -0.9138 |   -0.8983 |
-#> |.....................|   -0.8469 |   -0.5206 |   -0.9832 |    -1.002 |
-#> |.....................|   -0.6123 |   -0.7378 |   -0.6672 |...........|
-#> |    U|      480.2167 |     94.19 |    -5.688 |    -1.002 |   -0.2029 |
-#> |.....................|     2.102 |     1.871 |    0.6784 |    0.7529 |
-#> |.....................|     1.493 |     1.233 |     1.376 |...........|
-#> |    X|      480.2167 |     94.19 |  0.003385 |    0.2685 |    0.8163 |
-#> |.....................|     8.184 |     1.871 |    0.6784 |    0.7529 |
-#> |.....................|     1.493 |     1.233 |     1.376 |...........|
-#> |    F| Forward Diff. |     4.519 |    0.6730 |   -0.1351 |  -0.02088 |
-#> |.....................|  -0.04118 |    -2.856 |     1.311 |    0.6094 |
-#> |.....................|    -1.165 |    -1.062 |    -1.048 |...........|
-#> |   85|     480.21269 |     1.001 |    -1.290 |   -0.9139 |   -0.8983 |
-#> |.....................|   -0.8469 |   -0.5205 |   -0.9835 |    -1.002 |
-#> |.....................|   -0.6119 |   -0.7376 |   -0.6670 |...........|
-#> |    U|     480.21269 |     94.14 |    -5.690 |    -1.002 |   -0.2029 |
-#> |.....................|     2.102 |     1.871 |    0.6782 |    0.7527 |
-#> |.....................|     1.493 |     1.233 |     1.377 |...........|
-#> |    X|     480.21269 |     94.14 |  0.003379 |    0.2685 |    0.8163 |
-#> |.....................|     8.184 |     1.871 |    0.6782 |    0.7527 |
-#> |.....................|     1.493 |     1.233 |     1.377 |...........|
-#> |    F| Forward Diff. |    -2.933 |    0.6686 |   -0.1517 |  -0.01805 |
-#> |.....................|  -0.06304 |    -2.806 |     1.298 |    0.6045 |
-#> |.....................|    -1.073 |    -1.045 |    -1.026 |...........|
-#> |   86|     480.20865 |     1.002 |    -1.292 |   -0.9139 |   -0.8983 |
-#> |.....................|   -0.8469 |   -0.5201 |   -0.9839 |    -1.002 |
-#> |.....................|   -0.6115 |   -0.7373 |   -0.6667 |...........|
-#> |    U|     480.20865 |     94.19 |    -5.692 |    -1.002 |   -0.2029 |
-#> |.....................|     2.102 |     1.871 |    0.6779 |    0.7525 |
-#> |.....................|     1.494 |     1.233 |     1.377 |...........|
-#> |    X|     480.20865 |     94.19 |  0.003373 |    0.2685 |    0.8163 |
-#> |.....................|     8.184 |     1.871 |    0.6779 |    0.7525 |
-#> |.....................|     1.494 |     1.233 |     1.377 |...........|
-#> |    F| Forward Diff. |     4.802 |    0.6647 |   -0.1367 |  -0.01906 |
-#> |.....................|  -0.03994 |    -2.699 |     1.311 |   -0.5807 |
-#> |.....................|    -1.078 |    -1.030 |    -1.030 |...........|
-#> |   87|     480.20558 |     1.001 |    -1.294 |   -0.9137 |   -0.8983 |
-#> |.....................|   -0.8468 |   -0.5199 |   -0.9842 |    -1.002 |
-#> |.....................|   -0.6113 |   -0.7372 |   -0.6665 |...........|
-#> |    U|     480.20558 |     94.14 |    -5.694 |    -1.002 |   -0.2029 |
-#> |.....................|     2.102 |     1.871 |    0.6776 |    0.7525 |
-#> |.....................|     1.494 |     1.233 |     1.377 |...........|
-#> |    X|     480.20558 |     94.14 |  0.003367 |    0.2685 |    0.8163 |
-#> |.....................|     8.185 |     1.871 |    0.6776 |    0.7525 |
-#> |.....................|     1.494 |     1.233 |     1.377 |...........|
-#> |    F| Forward Diff. |    -2.911 |    0.6576 |   -0.1438 |  -0.02051 |
-#> |.....................|  -0.06613 |    -2.751 |     1.246 |   -0.6218 |
-#> |.....................|    -1.053 |    -1.017 |    -1.010 |...........|
-#> |   88|     480.20291 |     1.002 |    -1.296 |   -0.9132 |   -0.8982 |
-#> |.....................|   -0.8467 |   -0.5195 |   -0.9848 |    -1.002 |
-#> |.....................|   -0.6112 |   -0.7370 |   -0.6662 |...........|
-#> |    U|     480.20291 |     94.19 |    -5.696 |    -1.002 |   -0.2029 |
-#> |.....................|     2.102 |     1.872 |    0.6772 |    0.7527 |
-#> |.....................|     1.494 |     1.234 |     1.377 |...........|
-#> |    X|     480.20291 |     94.19 |  0.003361 |    0.2686 |    0.8164 |
-#> |.....................|     8.186 |     1.872 |    0.6772 |    0.7527 |
-#> |.....................|     1.494 |     1.234 |     1.377 |...........|
-#> |    F| Forward Diff. |     4.296 |    0.6533 |   -0.1055 |  -0.01383 |
-#> |.....................|  -0.03435 |    -2.750 |     1.192 |   -0.6155 |
-#> |.....................|    -1.121 |    -1.037 |    -1.054 |...........|
-#> |   89|     480.20010 |     1.001 |    -1.297 |   -0.9127 |   -0.8982 |
-#> |.....................|   -0.8466 |   -0.5193 |   -0.9850 |    -1.002 |
-#> |.....................|   -0.6110 |   -0.7368 |   -0.6658 |...........|
-#> |    U|      480.2001 |     94.14 |    -5.697 |    -1.001 |   -0.2028 |
-#> |.....................|     2.103 |     1.872 |    0.6771 |    0.7528 |
-#> |.....................|     1.494 |     1.234 |     1.378 |...........|
-#> |    X|      480.2001 |     94.14 |  0.003355 |    0.2687 |    0.8164 |
-#> |.....................|     8.187 |     1.872 |    0.6771 |    0.7528 |
-#> |.....................|     1.494 |     1.234 |     1.378 |...........|
-#> |    F| Forward Diff. |    -2.841 |    0.6461 |  -0.09617 |  -0.01892 |
-#> |.....................|  -0.05600 |    -2.503 |     1.255 |    0.6797 |
-#> |.....................|   -0.9587 |    -1.006 |   -0.9794 |...........|
-#> |   90|     480.19652 |     1.002 |    -1.299 |   -0.9127 |   -0.8982 |
-#> |.....................|   -0.8466 |   -0.5191 |   -0.9853 |    -1.002 |
-#> |.....................|   -0.6108 |   -0.7364 |   -0.6653 |...........|
-#> |    U|     480.19652 |     94.19 |    -5.699 |    -1.001 |   -0.2028 |
-#> |.....................|     2.103 |     1.872 |    0.6768 |    0.7526 |
-#> |.....................|     1.494 |     1.234 |     1.378 |...........|
-#> |    X|     480.19652 |     94.19 |  0.003349 |    0.2687 |    0.8164 |
-#> |.....................|     8.187 |     1.872 |    0.6768 |    0.7526 |
-#> |.....................|     1.494 |     1.234 |     1.378 |...........|
-#> |   91|     480.19461 |     1.002 |    -1.301 |   -0.9128 |   -0.8982 |
-#> |.....................|   -0.8466 |   -0.5193 |   -0.9855 |    -1.002 |
-#> |.....................|   -0.6107 |   -0.7361 |   -0.6650 |...........|
-#> |    U|     480.19461 |     94.18 |    -5.701 |    -1.001 |   -0.2028 |
-#> |.....................|     2.103 |     1.872 |    0.6767 |    0.7526 |
-#> |.....................|     1.494 |     1.235 |     1.379 |...........|
-#> |    X|     480.19461 |     94.18 |  0.003342 |    0.2687 |    0.8164 |
-#> |.....................|     8.187 |     1.872 |    0.6767 |    0.7526 |
-#> |.....................|     1.494 |     1.235 |     1.379 |...........|
-#> |   92|     480.18441 |     1.002 |    -1.313 |   -0.9134 |   -0.8983 |
-#> |.....................|   -0.8466 |   -0.5209 |   -0.9862 |    -1.003 |
-#> |.....................|   -0.6104 |   -0.7344 |   -0.6628 |...........|
-#> |    U|     480.18441 |     94.17 |    -5.713 |    -1.002 |   -0.2029 |
-#> |.....................|     2.103 |     1.871 |    0.6762 |    0.7522 |
-#> |.....................|     1.495 |     1.237 |     1.381 |...........|
-#> |    X|     480.18441 |     94.17 |  0.003303 |    0.2686 |    0.8164 |
-#> |.....................|     8.187 |     1.871 |    0.6762 |    0.7522 |
-#> |.....................|     1.495 |     1.237 |     1.381 |...........|
-#> |   93|     480.15712 |     1.001 |    -1.360 |   -0.9157 |   -0.8984 |
-#> |.....................|   -0.8466 |   -0.5271 |   -0.9890 |    -1.004 |
-#> |.....................|   -0.6089 |   -0.7277 |   -0.6540 |...........|
-#> |    U|     480.15712 |     94.12 |    -5.760 |    -1.004 |   -0.2031 |
-#> |.....................|     2.103 |     1.866 |    0.6740 |    0.7509 |
-#> |.....................|     1.497 |     1.244 |     1.391 |...........|
-#> |    X|     480.15712 |     94.12 |  0.003151 |    0.2681 |    0.8162 |
-#> |.....................|     8.187 |     1.866 |    0.6740 |    0.7509 |
-#> |.....................|     1.497 |     1.244 |     1.391 |...........|
-#> |   94|     480.23418 |    0.9997 |    -1.543 |   -0.9246 |   -0.8991 |
-#> |.....................|   -0.8465 |   -0.5509 |    -1.000 |    -1.011 |
-#> |.....................|   -0.6032 |   -0.7017 |   -0.6198 |...........|
-#> |    U|     480.23418 |     93.97 |    -5.943 |    -1.013 |   -0.2037 |
-#> |.....................|     2.103 |     1.847 |    0.6655 |    0.7454 |
-#> |.....................|     1.503 |     1.272 |     1.431 |...........|
-#> |    X|     480.23418 |     93.97 |  0.002624 |    0.2664 |    0.8157 |
-#> |.....................|     8.187 |     1.847 |    0.6655 |    0.7454 |
-#> |.....................|     1.503 |     1.272 |     1.431 |...........|
-#> |    F| Forward Diff. |    -6.048 |    0.4781 |   -0.2230 |  -0.02217 |
-#> |.....................|  -0.05480 |    -3.577 |    0.9301 |    0.6494 |
-#> |.....................|    -1.028 |   -0.4525 |   -0.4232 |...........|
-#> |   95|     480.10748 |     1.002 |    -1.612 |   -0.8919 |   -0.8955 |
-#> |.....................|   -0.8419 |   -0.5057 |    -1.005 |    -1.011 |
-#> |.....................|   -0.6089 |   -0.7402 |   -0.6757 |...........|
-#> |    U|     480.10748 |     94.20 |    -6.012 |   -0.9804 |   -0.2001 |
-#> |.....................|     2.107 |     1.883 |    0.6618 |    0.7449 |
-#> |.....................|     1.497 |     1.230 |     1.367 |...........|
-#> |    X|     480.10748 |     94.20 |  0.002450 |    0.2728 |    0.8186 |
-#> |.....................|     8.225 |     1.883 |    0.6618 |    0.7449 |
-#> |.....................|     1.497 |     1.230 |     1.367 |...........|
-#> |    F| Forward Diff. |     5.588 |   -0.2032 |     1.050 |   0.05863 |
-#> |.....................|    0.1556 |    -1.013 |   -0.1797 |    0.1430 |
-#> |.....................|    -1.088 |    -1.192 |    -1.504 |...........|
-#> |   96|     480.44664 |     1.003 |    -1.804 |   -0.9880 |   -0.8940 |
-#> |.....................|   -0.8524 |   -0.4601 |   -0.9127 |    -1.040 |
-#> |.....................|   -0.5485 |   -0.7099 |   -0.6226 |...........|
-#> |    U|     480.44664 |     94.31 |    -6.204 |    -1.077 |   -0.1987 |
-#> |.....................|     2.097 |     1.919 |    0.7320 |    0.7196 |
-#> |.....................|     1.568 |     1.263 |     1.427 |...........|
-#> |    X|     480.44664 |     94.31 |  0.002022 |    0.2542 |    0.8198 |
-#> |.....................|     8.139 |     1.919 |    0.7320 |    0.7196 |
-#> |.....................|     1.568 |     1.263 |     1.427 |...........|
-#> |   97|     480.05051 |     1.002 |    -1.657 |   -0.9147 |   -0.8952 |
-#> |.....................|   -0.8444 |   -0.4949 |   -0.9832 |    -1.018 |
-#> |.....................|   -0.5946 |   -0.7329 |   -0.6630 |...........|
-#> |    U|     480.05051 |     94.19 |    -6.057 |    -1.003 |   -0.1998 |
-#> |.....................|     2.105 |     1.891 |    0.6784 |    0.7389 |
-#> |.....................|     1.514 |     1.238 |     1.381 |...........|
-#> |    X|     480.05051 |     94.19 |  0.002341 |    0.2683 |    0.8189 |
-#> |.....................|     8.205 |     1.891 |    0.6784 |    0.7389 |
-#> |.....................|     1.514 |     1.238 |     1.381 |...........|
-#> |    F| Forward Diff. |     3.048 |   -0.2764 |  -0.02525 |   0.07726 |
-#> |.....................|    0.1002 |    0.1555 |     1.072 |    0.1458 |
-#> |.....................|   -0.5013 |   -0.7465 |   -0.9442 |...........|
-#> |   98|     480.05873 |     1.002 |    -1.641 |   -0.9145 |   -0.9051 |
-#> |.....................|   -0.8597 |   -0.5017 |   -0.9961 |    -1.019 |
-#> |.....................|   -0.5552 |   -0.7600 |   -0.6392 |...........|
-#> |    U|     480.05873 |     94.21 |    -6.041 |    -1.003 |   -0.2097 |
-#> |.....................|     2.089 |     1.886 |    0.6686 |    0.7381 |
-#> |.....................|     1.561 |     1.209 |     1.408 |...........|
-#> |    X|     480.05873 |     94.21 |  0.002380 |    0.2684 |    0.8108 |
-#> |.....................|     8.080 |     1.886 |    0.6686 |    0.7381 |
-#> |.....................|     1.561 |     1.209 |     1.408 |...........|
-#> |   99|     480.03299 |     1.002 |    -1.650 |   -0.9146 |   -0.8993 |
-#> |.....................|   -0.8508 |   -0.4977 |   -0.9887 |    -1.018 |
-#> |.....................|   -0.5780 |   -0.7442 |   -0.6529 |...........|
-#> |    U|     480.03299 |     94.17 |    -6.050 |    -1.003 |   -0.2040 |
-#> |.....................|     2.098 |     1.889 |    0.6742 |    0.7386 |
-#> |.....................|     1.533 |     1.226 |     1.393 |...........|
-#> |    X|     480.03299 |     94.17 |  0.002357 |    0.2683 |    0.8155 |
-#> |.....................|     8.152 |     1.889 |    0.6742 |    0.7386 |
-#> |.....................|     1.533 |     1.226 |     1.393 |...........|
-#> |    F| Forward Diff. |  -0.07884 |   -0.2508 |  -0.03233 |  -0.02314 |
-#> |.....................|   -0.1302 |   0.06288 |    0.7629 |    0.2261 |
-#> |.....................|    0.3850 |    -1.277 |   -0.6610 |...........|
-#> |  100|     480.00970 |     1.003 |    -1.641 |   -0.9125 |   -0.9005 |
-#> |.....................|   -0.8500 |   -0.4980 |   -0.9983 |    -1.021 |
-#> |.....................|   -0.5841 |   -0.7275 |   -0.6414 |...........|
-#> |    U|      480.0097 |     94.26 |    -6.041 |    -1.001 |   -0.2051 |
-#> |.....................|     2.099 |     1.889 |    0.6670 |    0.7367 |
-#> |.....................|     1.526 |     1.244 |     1.406 |...........|
-#> |    X|      480.0097 |     94.26 |  0.002380 |    0.2687 |    0.8145 |
-#> |.....................|     8.159 |     1.889 |    0.6670 |    0.7367 |
-#> |.....................|     1.526 |     1.244 |     1.406 |...........|
-#> |    F| Forward Diff. |     12.51 |   -0.2151 |    0.1066 |  -0.04414 |
-#> |.....................|  -0.06212 |   -0.2557 |   0.09002 |  -0.09728 |
-#> |.....................|   0.06582 |   -0.3883 |   0.07016 |...........|
-#> |  101|     480.02569 |     1.000 |    -1.627 |   -0.9257 |   -0.9015 |
-#> |.....................|   -0.8496 |   -0.4974 |    -1.010 |    -1.023 |
-#> |.....................|   -0.5876 |   -0.7200 |   -0.6493 |...........|
-#> |    U|     480.02569 |     94.03 |    -6.027 |    -1.014 |   -0.2061 |
-#> |.....................|     2.099 |     1.889 |    0.6581 |    0.7348 |
-#> |.....................|     1.522 |     1.252 |     1.397 |...........|
-#> |    X|     480.02569 |     94.03 |  0.002413 |    0.2662 |    0.8138 |
-#> |.....................|     8.162 |     1.889 |    0.6581 |    0.7348 |
-#> |.....................|     1.522 |     1.252 |     1.397 |...........|
-#> |  102|     480.01783 |     1.000 |    -1.636 |   -0.9171 |   -0.9008 |
-#> |.....................|   -0.8499 |   -0.4978 |    -1.002 |    -1.021 |
-#> |.....................|   -0.5853 |   -0.7249 |   -0.6441 |...........|
-#> |    U|     480.01783 |     94.03 |    -6.036 |    -1.006 |   -0.2055 |
-#> |.....................|     2.099 |     1.889 |    0.6639 |    0.7361 |
-#> |.....................|     1.525 |     1.247 |     1.403 |...........|
-#> |    X|     480.01783 |     94.03 |  0.002392 |    0.2678 |    0.8143 |
-#> |.....................|     8.160 |     1.889 |    0.6639 |    0.7361 |
-#> |.....................|     1.525 |     1.247 |     1.403 |...........|
-#> |  103|     480.01762 |     1.000 |    -1.639 |   -0.9140 |   -0.9006 |
-#> |.....................|   -0.8500 |   -0.4979 |   -0.9995 |    -1.021 |
-#> |.....................|   -0.5844 |   -0.7266 |   -0.6422 |...........|
-#> |    U|     480.01762 |     94.04 |    -6.039 |    -1.002 |   -0.2052 |
-#> |.....................|     2.099 |     1.889 |    0.6660 |    0.7365 |
-#> |.....................|     1.526 |     1.245 |     1.405 |...........|
-#> |    X|     480.01762 |     94.04 |  0.002384 |    0.2685 |    0.8145 |
-#> |.....................|     8.159 |     1.889 |    0.6660 |    0.7365 |
-#> |.....................|     1.526 |     1.245 |     1.405 |...........|
-#> |  104|     480.00603 |     1.001 |    -1.641 |   -0.9125 |   -0.9005 |
-#> |.....................|   -0.8500 |   -0.4980 |   -0.9983 |    -1.021 |
-#> |.....................|   -0.5841 |   -0.7275 |   -0.6414 |...........|
-#> |    U|     480.00603 |     94.12 |    -6.041 |    -1.001 |   -0.2051 |
-#> |.....................|     2.099 |     1.889 |    0.6670 |    0.7367 |
-#> |.....................|     1.526 |     1.244 |     1.406 |...........|
-#> |    X|     480.00603 |     94.12 |  0.002380 |    0.2687 |    0.8145 |
-#> |.....................|     8.159 |     1.889 |    0.6670 |    0.7367 |
-#> |.....................|     1.526 |     1.244 |     1.406 |...........|
-#> |    F| Forward Diff. |    -6.885 |   -0.2187 |   0.06031 |  -0.05864 |
-#> |.....................|   -0.1316 |   -0.6942 |  -0.07940 |    0.7419 |
-#> |.....................|   -0.2628 |   -0.6303 |   -0.1748 |...........|
-#> |  105|     480.00355 |     1.002 |    -1.640 |   -0.9125 |   -0.9004 |
-#> |.....................|   -0.8497 |   -0.4981 |   -0.9983 |    -1.021 |
-#> |.....................|   -0.5835 |   -0.7267 |   -0.6420 |...........|
-#> |    U|     480.00355 |     94.17 |    -6.040 |    -1.001 |   -0.2050 |
-#> |.....................|     2.099 |     1.889 |    0.6669 |    0.7366 |
-#> |.....................|     1.527 |     1.245 |     1.405 |...........|
-#> |    X|     480.00355 |     94.17 |  0.002382 |    0.2687 |    0.8147 |
-#> |.....................|     8.162 |     1.889 |    0.6669 |    0.7366 |
-#> |.....................|     1.527 |     1.245 |     1.405 |...........|
-#> |    F| Forward Diff. |   -0.1332 |   -0.2152 |   0.07761 |  -0.04946 |
-#> |.....................|  -0.09731 |  -0.07704 |    0.1258 |    0.9492 |
-#> |.....................|   0.08309 |   -0.3432 |   0.03979 |...........|
-#> |  106|     480.00003 |     1.002 |    -1.640 |   -0.9126 |   -0.9003 |
-#> |.....................|   -0.8495 |   -0.4980 |   -0.9985 |    -1.022 |
-#> |.....................|   -0.5836 |   -0.7262 |   -0.6420 |...........|
-#> |    U|     480.00003 |     94.19 |    -6.040 |    -1.001 |   -0.2049 |
-#> |.....................|     2.100 |     1.889 |    0.6668 |    0.7355 |
-#> |.....................|     1.527 |     1.245 |     1.405 |...........|
-#> |    X|     480.00003 |     94.19 |  0.002382 |    0.2687 |    0.8147 |
-#> |.....................|     8.163 |     1.889 |    0.6668 |    0.7355 |
-#> |.....................|     1.527 |     1.245 |     1.405 |...........|
-#> |    F| Forward Diff. |     2.294 |   -0.2073 |   0.08146 |  -0.04541 |
-#> |.....................|  -0.07807 |   -0.2293 |   0.05730 |    0.8075 |
-#> |.....................| -0.008164 |   -0.3171 |   0.03808 |...........|
-#> |  107|     479.99578 |     1.002 |    -1.638 |   -0.9109 |   -0.8997 |
-#> |.....................|   -0.8483 |   -0.4984 |   -0.9975 |    -1.023 |
-#> |.....................|   -0.5809 |   -0.7230 |   -0.6440 |...........|
-#> |    U|     479.99578 |     94.17 |    -6.038 |   -0.9994 |   -0.2043 |
-#> |.....................|     2.101 |     1.889 |    0.6675 |    0.7343 |
-#> |.....................|     1.530 |     1.249 |     1.403 |...........|
-#> |    X|     479.99578 |     94.17 |  0.002387 |    0.2691 |    0.8152 |
-#> |.....................|     8.172 |     1.889 |    0.6675 |    0.7343 |
-#> |.....................|     1.530 |     1.249 |     1.403 |...........|
-#> |  108|     479.99301 |     1.002 |    -1.632 |   -0.9055 |   -0.8980 |
-#> |.....................|   -0.8447 |   -0.4999 |   -0.9947 |    -1.027 |
-#> |.....................|   -0.5728 |   -0.7134 |   -0.6498 |...........|
-#> |    U|     479.99301 |     94.16 |    -6.032 |   -0.9941 |   -0.2026 |
-#> |.....................|     2.104 |     1.887 |    0.6697 |    0.7310 |
-#> |.....................|     1.540 |     1.259 |     1.396 |...........|
-#> |    X|     479.99301 |     94.16 |  0.002402 |    0.2701 |    0.8166 |
-#> |.....................|     8.202 |     1.887 |    0.6697 |    0.7310 |
-#> |.....................|     1.540 |     1.259 |     1.396 |...........|
-#> |    F| Forward Diff. |   -0.5972 |   -0.1625 |    0.4650 |  0.009686 |
-#> |.....................|   0.08636 |    -1.694 |   -0.1652 |    -1.042 |
-#> |.....................|   -0.1517 |    0.4204 |   -0.3659 |...........|
-#> |  109|     479.98697 |     1.002 |    -1.611 |   -0.9101 |   -0.8945 |
-#> |.....................|   -0.8385 |   -0.4966 |   -0.9980 |    -1.027 |
-#> |.....................|   -0.5750 |   -0.7140 |   -0.6459 |...........|
-#> |    U|     479.98697 |     94.17 |    -6.011 |   -0.9986 |   -0.1991 |
-#> |.....................|     2.111 |     1.890 |    0.6672 |    0.7309 |
-#> |.....................|     1.537 |     1.259 |     1.401 |...........|
-#> |    X|     479.98697 |     94.17 |  0.002451 |    0.2692 |    0.8195 |
-#> |.....................|     8.253 |     1.890 |    0.6672 |    0.7309 |
-#> |.....................|     1.537 |     1.259 |     1.401 |...........|
-#> |    F| Forward Diff. | -0.005684 |   -0.1115 |    0.2082 |   0.08938 |
-#> |.....................|    0.3008 |   0.01411 |    0.1052 |   -0.7061 |
-#> |.....................|    0.4111 |    0.4010 |   -0.1199 |...........|
-#> |  110|     479.98697 |     1.002 |    -1.611 |   -0.9101 |   -0.8945 |
-#> |.....................|   -0.8385 |   -0.4966 |   -0.9980 |    -1.027 |
-#> |.....................|   -0.5750 |   -0.7140 |   -0.6459 |...........|
-#> |    U|     479.98697 |     94.17 |    -6.011 |   -0.9986 |   -0.1991 |
-#> |.....................|     2.111 |     1.890 |    0.6672 |    0.7309 |
-#> |.....................|     1.537 |     1.259 |     1.401 |...........|
-#> |    X|     479.98697 |     94.17 |  0.002451 |    0.2692 |    0.8195 |
-#> |.....................|     8.253 |     1.890 |    0.6672 |    0.7309 |
-#> |.....................|     1.537 |     1.259 |     1.401 |...........|
-#> calculating covariance matrix
-#> done
-#> Calculating residuals/tables
-#> done
-f_nlmixr_dfop_sfo_focei_const <- nlmixr(f_mmkin_const["DFOP-SFO", ], est = "focei")
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → calculate jacobian
-#> 
-#> → calculate sensitivities
-#> 
-#> → calculate ∂(f)/∂(η)
-#> 
-#> → calculate ∂(R²)/∂(η)
-#> 
-#> → finding duplicate expressions in inner model...
-#> 
-#> → optimizing duplicate expressions in inner model...
-#> 
-#> → finding duplicate expressions in EBE model...
-#> 
-#> → optimizing duplicate expressions in EBE model...
-#> 
-#> → compiling inner model...
-#>  
-#> ✔ done
-#> → finding duplicate expressions in FD model...
-#> 
-#> → optimizing duplicate expressions in FD model...
-#> 
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> → compiling events FD model...
-#>  
-#> ✔ done
-#> Needed Covariates:
-#> [1] "CMT"
-#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> |    #| Objective Fun |  parent_0 |  log_k_A1 |f_parent_qlogis |    log_k1 |
-#> |.....................|    log_k2 |  g_qlogis |     sigma |        o1 |
-#> |.....................|        o2 |        o3 |        o4 |        o5 |
-#> |.....................|        o6 |...........|...........|...........|
-#> |    1|     517.20934 |     1.000 |    -1.000 |   -0.9109 |   -0.9296 |
-#> |.....................|   -0.9779 |   -0.8885 |   -0.8592 |   -0.8766 |
-#> |.....................|   -0.8740 |   -0.8675 |   -0.8712 |   -0.8735 |
-#> |.....................|   -0.8680 |...........|...........|...........|
-#> |    U|     517.20934 |     94.00 |    -5.400 |   -0.9700 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    X|     517.20934 |     94.00 |  0.004517 |    0.2749 |    0.1496 |
-#> |.....................|   0.01357 |    0.5349 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    G|    Gill Diff. |     64.43 |     1.648 |  -0.07882 |   -0.2050 |
-#> |.....................|   -0.4304 |   0.05992 |    -56.51 |     17.73 |
-#> |.....................|     9.983 |    -11.00 |    -3.771 |     3.593 |
-#> |.....................|    -10.58 |...........|...........|...........|
-#> |    2|     2737.3115 |    0.2806 |    -1.018 |   -0.9100 |   -0.9273 |
-#> |.....................|   -0.9731 |   -0.8892 |   -0.2282 |    -1.075 |
-#> |.....................|   -0.9854 |   -0.7447 |   -0.8291 |   -0.9136 |
-#> |.....................|   -0.7499 |...........|...........|...........|
-#> |    U|     2737.3115 |     26.38 |    -5.418 |   -0.9691 |    -1.898 |
-#> |.....................|    -4.295 |    0.1399 |     2.105 |    0.5864 |
-#> |.....................|    0.7671 |     1.329 |     1.042 |    0.8535 |
-#> |.....................|     1.298 |...........|...........|...........|
-#> |    X|     2737.3115 |     26.38 |  0.004434 |    0.2751 |    0.1499 |
-#> |.....................|   0.01363 |    0.5349 |     2.105 |    0.5864 |
-#> |.....................|    0.7671 |     1.329 |     1.042 |    0.8535 |
-#> |.....................|     1.298 |...........|...........|...........|
-#> |    3|     569.57476 |    0.9281 |    -1.002 |   -0.9108 |   -0.9293 |
-#> |.....................|   -0.9774 |   -0.8886 |   -0.7961 |   -0.8964 |
-#> |.....................|   -0.8851 |   -0.8553 |   -0.8670 |   -0.8775 |
-#> |.....................|   -0.8562 |...........|...........|...........|
-#> |    U|     569.57476 |     87.24 |    -5.402 |   -0.9699 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.650 |    0.7166 |
-#> |.....................|    0.8537 |     1.198 |     1.004 |    0.8856 |
-#> |.....................|     1.175 |...........|...........|...........|
-#> |    X|     569.57476 |     87.24 |  0.004508 |    0.2749 |    0.1496 |
-#> |.....................|   0.01358 |    0.5349 |     1.650 |    0.7166 |
-#> |.....................|    0.8537 |     1.198 |     1.004 |    0.8856 |
-#> |.....................|     1.175 |...........|...........|...........|
-#> |    4|     531.41065 |    0.9928 |    -1.000 |   -0.9109 |   -0.9296 |
-#> |.....................|   -0.9778 |   -0.8885 |   -0.8528 |   -0.8786 |
-#> |.....................|   -0.8751 |   -0.8663 |   -0.8708 |   -0.8739 |
-#> |.....................|   -0.8668 |...........|...........|...........|
-#> |    U|     531.41065 |     93.32 |    -5.400 |   -0.9700 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.605 |    0.7297 |
-#> |.....................|    0.8624 |     1.185 |     1.000 |    0.8888 |
-#> |.....................|     1.163 |...........|...........|...........|
-#> |    X|     531.41065 |     93.32 |  0.004516 |    0.2749 |    0.1496 |
-#> |.....................|   0.01357 |    0.5349 |     1.605 |    0.7297 |
-#> |.....................|    0.8624 |     1.185 |     1.000 |    0.8888 |
-#> |.....................|     1.163 |...........|...........|...........|
-#> |    5|     531.74000 |    0.9993 |    -1.000 |   -0.9109 |   -0.9296 |
-#> |.....................|   -0.9779 |   -0.8885 |   -0.8585 |   -0.8768 |
-#> |.....................|   -0.8741 |   -0.8674 |   -0.8712 |   -0.8735 |
-#> |.....................|   -0.8679 |...........|...........|...........|
-#> |    U|        531.74 |     93.93 |    -5.400 |   -0.9700 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.601 |    0.7310 |
-#> |.....................|    0.8632 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    X|        531.74 |     93.93 |  0.004516 |    0.2749 |    0.1496 |
-#> |.....................|   0.01357 |    0.5349 |     1.601 |    0.7310 |
-#> |.....................|    0.8632 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    6|     531.81753 |    0.9999 |    -1.000 |   -0.9109 |   -0.9296 |
-#> |.....................|   -0.9779 |   -0.8885 |   -0.8591 |   -0.8767 |
-#> |.....................|   -0.8740 |   -0.8675 |   -0.8712 |   -0.8735 |
-#> |.....................|   -0.8680 |...........|...........|...........|
-#> |    U|     531.81753 |     93.99 |    -5.400 |   -0.9700 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    X|     531.81753 |     93.99 |  0.004517 |    0.2749 |    0.1496 |
-#> |.....................|   0.01357 |    0.5349 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    7|     531.82573 |     1.000 |    -1.000 |   -0.9109 |   -0.9296 |
-#> |.....................|   -0.9779 |   -0.8885 |   -0.8591 |   -0.8766 |
-#> |.....................|   -0.8740 |   -0.8675 |   -0.8712 |   -0.8735 |
-#> |.....................|   -0.8680 |...........|...........|...........|
-#> |    U|     531.82573 |     94.00 |    -5.400 |   -0.9700 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    X|     531.82573 |     94.00 |  0.004517 |    0.2749 |    0.1496 |
-#> |.....................|   0.01357 |    0.5349 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    8|     531.82668 |     1.000 |    -1.000 |   -0.9109 |   -0.9296 |
-#> |.....................|   -0.9779 |   -0.8885 |   -0.8592 |   -0.8766 |
-#> |.....................|   -0.8740 |   -0.8675 |   -0.8712 |   -0.8735 |
-#> |.....................|   -0.8680 |...........|...........|...........|
-#> |    U|     531.82668 |     94.00 |    -5.400 |   -0.9700 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    X|     531.82668 |     94.00 |  0.004517 |    0.2749 |    0.1496 |
-#> |.....................|   0.01357 |    0.5349 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    9|     531.82678 |     1.000 |    -1.000 |   -0.9109 |   -0.9296 |
-#> |.....................|   -0.9779 |   -0.8885 |   -0.8592 |   -0.8766 |
-#> |.....................|   -0.8740 |   -0.8675 |   -0.8712 |   -0.8735 |
-#> |.....................|   -0.8680 |...........|...........|...........|
-#> |    U|     531.82678 |     94.00 |    -5.400 |   -0.9700 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    X|     531.82678 |     94.00 |  0.004517 |    0.2749 |    0.1496 |
-#> |.....................|   0.01357 |    0.5349 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |   10|     531.82679 |     1.000 |    -1.000 |   -0.9109 |   -0.9296 |
-#> |.....................|   -0.9779 |   -0.8885 |   -0.8592 |   -0.8766 |
-#> |.....................|   -0.8740 |   -0.8675 |   -0.8712 |   -0.8735 |
-#> |.....................|   -0.8680 |...........|...........|...........|
-#> |    U|     531.82679 |     94.00 |    -5.400 |   -0.9700 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    X|     531.82679 |     94.00 |  0.004517 |    0.2749 |    0.1496 |
-#> |.....................|   0.01357 |    0.5349 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |   11|     531.82679 |     1.000 |    -1.000 |   -0.9109 |   -0.9296 |
-#> |.....................|   -0.9779 |   -0.8885 |   -0.8592 |   -0.8766 |
-#> |.....................|   -0.8740 |   -0.8675 |   -0.8712 |   -0.8735 |
-#> |.....................|   -0.8680 |...........|...........|...........|
-#> |    U|     531.82679 |     94.00 |    -5.400 |   -0.9700 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    X|     531.82679 |     94.00 |  0.004517 |    0.2749 |    0.1496 |
-#> |.....................|   0.01357 |    0.5349 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |   12|     531.82678 |     1.000 |    -1.000 |   -0.9109 |   -0.9296 |
-#> |.....................|   -0.9779 |   -0.8885 |   -0.8592 |   -0.8766 |
-#> |.....................|   -0.8740 |   -0.8675 |   -0.8712 |   -0.8735 |
-#> |.....................|   -0.8680 |...........|...........|...........|
-#> |    U|     531.82678 |     94.00 |    -5.400 |   -0.9700 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    X|     531.82678 |     94.00 |  0.004517 |    0.2749 |    0.1496 |
-#> |.....................|   0.01357 |    0.5349 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |   13|     531.82679 |     1.000 |    -1.000 |   -0.9109 |   -0.9296 |
-#> |.....................|   -0.9779 |   -0.8885 |   -0.8592 |   -0.8766 |
-#> |.....................|   -0.8740 |   -0.8675 |   -0.8712 |   -0.8735 |
-#> |.....................|   -0.8680 |...........|...........|...........|
-#> |    U|     531.82679 |     94.00 |    -5.400 |   -0.9700 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    X|     531.82679 |     94.00 |  0.004517 |    0.2749 |    0.1496 |
-#> |.....................|   0.01357 |    0.5349 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |   14|     531.82679 |     1.000 |    -1.000 |   -0.9109 |   -0.9296 |
-#> |.....................|   -0.9779 |   -0.8885 |   -0.8592 |   -0.8766 |
-#> |.....................|   -0.8740 |   -0.8675 |   -0.8712 |   -0.8735 |
-#> |.....................|   -0.8680 |...........|...........|...........|
-#> |    U|     531.82679 |     94.00 |    -5.400 |   -0.9700 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    X|     531.82679 |     94.00 |  0.004517 |    0.2749 |    0.1496 |
-#> |.....................|   0.01357 |    0.5349 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |   15|     531.82679 |     1.000 |    -1.000 |   -0.9109 |   -0.9296 |
-#> |.....................|   -0.9779 |   -0.8885 |   -0.8592 |   -0.8766 |
-#> |.....................|   -0.8740 |   -0.8675 |   -0.8712 |   -0.8735 |
-#> |.....................|   -0.8680 |...........|...........|...........|
-#> |    U|     531.82679 |     94.00 |    -5.400 |   -0.9700 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    X|     531.82679 |     94.00 |  0.004517 |    0.2749 |    0.1496 |
-#> |.....................|   0.01357 |    0.5349 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |   16|     531.82679 |     1.000 |    -1.000 |   -0.9109 |   -0.9296 |
-#> |.....................|   -0.9779 |   -0.8885 |   -0.8592 |   -0.8766 |
-#> |.....................|   -0.8740 |   -0.8675 |   -0.8712 |   -0.8735 |
-#> |.....................|   -0.8680 |...........|...........|...........|
-#> |    U|     531.82679 |     94.00 |    -5.400 |   -0.9700 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    X|     531.82679 |     94.00 |  0.004517 |    0.2749 |    0.1496 |
-#> |.....................|   0.01357 |    0.5349 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |   17|     531.82679 |     1.000 |    -1.000 |   -0.9109 |   -0.9296 |
-#> |.....................|   -0.9779 |   -0.8885 |   -0.8592 |   -0.8766 |
-#> |.....................|   -0.8740 |   -0.8675 |   -0.8712 |   -0.8735 |
-#> |.....................|   -0.8680 |...........|...........|...........|
-#> |    U|     531.82679 |     94.00 |    -5.400 |   -0.9700 |    -1.900 |
-#> |.....................|    -4.300 |    0.1400 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> |    X|     531.82679 |     94.00 |  0.004517 |    0.2749 |    0.1496 |
-#> |.....................|   0.01357 |    0.5349 |     1.600 |    0.7311 |
-#> |.....................|    0.8633 |     1.183 |     1.000 |    0.8891 |
-#> |.....................|     1.161 |...........|...........|...........|
-#> calculating covariance matrix
-#> done
-#> Calculating residuals/tables
-#> done
-
-# Variance by variable is supported by 'saem' and 'focei'
-f_nlmixr_fomc_sfo_saem_obs <- nlmixr(f_mmkin_obs["FOMC-SFO", ], est = "saem")
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#>  
-#> → generate SAEM model
-#> ✔ done
-#> 1:    93.4067   -5.7935   -0.0604    2.2993   -1.1624    2.9450    1.7342    0.6650    0.5890    0.4750   14.5215    9.1023
-#> 2:    93.8811   -5.7873   -0.0289    2.3640   -1.0762    2.7977    2.0710    0.6317    0.5595    0.4512   11.1033    4.6425
-#> 3:    94.0397   -5.9934    0.0119    2.4035   -1.0703    3.0693    2.4524    0.6124    0.5316    0.4287   10.0698    3.4243
-#> 4:    93.8834   -6.0401    0.0041    2.3944   -1.0097    2.9159    3.1645    0.6120    0.5050    0.4073    9.2013    3.2162
-#> 5:    94.0163   -5.8381   -0.0267    2.3580   -1.0239    2.7701    3.0063    0.5814    0.4797    0.3869    9.0330    3.0330
-#> 6:    93.9753   -5.8371   -0.0315    2.3598   -1.0052    2.6316    2.8559    0.5708    0.4558    0.3675    8.6051    2.6518
-#> 7:    93.6109   -5.8741   -0.0401    2.3570   -1.0025    2.5000    2.7131    0.5691    0.4330    0.3492    8.4407    2.4701
-#> 8:    93.2480   -6.0361   -0.0523    2.3504   -1.0028    2.3750    3.1584    0.5407    0.4113    0.3317    8.6121    2.2437
-#> 9:    93.2245   -6.0431   -0.0503    2.3552   -0.9828    2.2562    3.9790    0.5395    0.3908    0.3151    8.6609    2.1129
-#> 10:    93.3040   -6.1080   -0.0503    2.3613   -0.9784    2.1434    4.8606    0.5401    0.3712    0.2994    8.6497    2.0865
-#> 11:    93.4509   -5.9532   -0.0503    2.3444   -0.9823    3.0948    4.6176    0.5679    0.3527    0.2844    8.1651    2.0310
-#> 12:    93.5099   -6.1699   -0.0503    2.3408   -0.9746    3.2814    4.3867    0.5679    0.3350    0.2702    8.1716    1.9862
-#> 13:    93.8052   -6.1984   -0.0474    2.3233   -0.9922    3.1173    4.6967    0.5644    0.3183    0.2567    8.2982    2.0040
-#> 14:    93.6510   -6.0090   -0.0429    2.3601   -0.9885    2.9615    4.4618    0.5526    0.3024    0.2438    8.3254    2.0605
-#> 15:    93.8952   -6.3354   -0.0394    2.3580   -0.9792    2.8134    5.2117    0.5657    0.2872    0.2316    8.1329    2.0520
-#> 16:    93.4703   -6.0722   -0.0434    2.3386   -1.0026    2.6727    4.9512    0.5781    0.2729    0.2201    8.0866    2.0994
-#> 17:    93.4238   -6.2132   -0.0755    2.3120   -1.0119    2.5391    4.7036    0.5495    0.2592    0.2091    7.5958    2.2864
-#> 18:    93.5288   -6.2747   -0.0616    2.3223   -1.0105    2.4121    4.4684    0.5467    0.2463    0.1986    7.1910    1.9828
-#> 19:    93.2607   -6.3635   -0.0631    2.3206   -1.0045    3.6271    4.8142    0.5405    0.2340    0.1928    7.3672    1.8187
-#> 20:    93.3918   -6.3241   -0.0742    2.2941   -1.0140    3.4457    4.9242    0.5596    0.2223    0.1950    7.1427    1.8754
-#> 21:    93.6794   -6.1336   -0.0758    2.3000   -1.0048    3.2734    4.6780    0.5565    0.2111    0.1852    7.0989    1.9232
-#> 22:    94.0006   -6.1882   -0.0800    2.3099   -1.0252    3.1098    4.4441    0.5354    0.2006    0.1870    7.0038    1.9920
-#> 23:    93.6433   -6.2626   -0.0841    2.2791   -1.0183    4.8893    4.4476    0.5276    0.1906    0.1798    6.3698    1.8787
-#> 24:    93.9545   -6.3772   -0.0816    2.2887   -1.0019    4.6448    5.1698    0.5293    0.1810    0.1779    6.5903    1.9474
-#> 25:    94.2280   -6.3235   -0.0839    2.2600   -0.9932    5.2801    4.9113    0.5262    0.1720    0.1806    6.5267    1.9807
-#> 26:    94.2022   -6.2830   -0.0883    2.2643   -1.0012    5.9595    4.6658    0.5225    0.1634    0.1795    6.3678    1.9659
-#> 27:    94.4398   -6.1769   -0.0894    2.2564   -1.0177    9.0771    4.4325    0.5207    0.1552    0.1880    6.4522    1.8590
-#> 28:    94.2586   -6.1652   -0.0882    2.2574   -1.0226    8.6233    4.2108    0.5158    0.1475    0.1881    6.3701    1.7882
-#> 29:    94.3490   -6.1505   -0.0854    2.2615   -1.0081    9.6333    4.0003    0.5109    0.1423    0.1833    6.3601    1.8485
-#> 30:    94.6929   -6.0285   -0.0909    2.2610   -1.0082    9.1517    3.8003    0.5117    0.1401    0.2097    6.2461    1.8606
-#> 31:    94.2553   -6.0390   -0.0896    2.2625   -1.0078    8.6941    3.6103    0.5072    0.1378    0.2088    6.3337    1.8220
-#> 32:    94.3096   -5.7252   -0.0886    2.2677   -0.9967    9.0244    3.4298    0.5051    0.1325    0.2015    6.4601    1.8880
-#> 33:    94.8327   -5.8775   -0.0865    2.2684   -0.9976    8.6305    3.2583    0.4920    0.1333    0.1993    6.4804    1.8203
-#> 34:    94.3527   -5.9488   -0.0826    2.2879   -0.9989    8.1989    3.1538    0.4969    0.1388    0.1984    6.4201    1.7696
-#> 35:    94.4411   -6.1171   -0.0826    2.2913   -0.9964    8.4377    3.7937    0.4969    0.1387    0.1972    6.3878    1.7612
-#> 36:    94.2058   -6.1151   -0.0844    2.2920   -1.0069    8.0158    3.7963    0.4962    0.1395    0.1938    6.2469    1.6680
-#> 37:    93.7449   -6.1251   -0.0925    2.2736   -1.0019    7.6150    3.8477    0.5101    0.1325    0.1841    6.1375    1.7472
-#> 38:    93.6861   -6.0575   -0.0934    2.2803   -1.0097    7.2343    3.6553    0.5119    0.1259    0.1862    6.0729    1.7608
-#> 39:    93.9767   -6.0314   -0.0999    2.2548   -1.0231    6.8726    3.4725    0.5195    0.1234    0.1951    6.1947    1.8276
-#> 40:    94.0297   -6.1559   -0.0989    2.2440   -1.0374    6.5290    3.8559    0.5199    0.1279    0.1891    6.0195    1.8906
-#> 41:    94.2069   -6.3055   -0.0820    2.2710   -1.0275    6.2025    4.7866    0.5304    0.1215    0.1858    6.1777    1.8541
-#> 42:    94.2400   -6.3179   -0.0790    2.2783   -1.0379    5.8924    4.6915    0.5253    0.1154    0.1794    6.0530    1.8960
-#> 43:    93.9851   -6.4096   -0.0784    2.2832   -1.0341    5.5978    5.0608    0.5163    0.1097    0.1773    6.0057    1.8136
-#> 44:    94.1440   -6.2214   -0.0746    2.2969   -1.0262    5.3179    4.8077    0.5130    0.1079    0.1851    6.1182    1.8390
-#> 45:    93.8847   -6.3883   -0.0745    2.3059   -1.0132    6.8202    5.1378    0.5130    0.1174    0.1769    6.1000    1.8391
-#> 46:    93.7228   -6.3305   -0.0794    2.3033   -1.0107    6.4792    4.8809    0.5095    0.1196    0.1783    6.2794    1.7304
-#> 47:    93.7031   -6.4232   -0.0796    2.3006   -1.0028    6.1552    5.5756    0.5092    0.1243    0.1887    6.1716    1.7279
-#> 48:    93.5210   -6.2770   -0.0794    2.2948   -1.0122    5.8475    5.2968    0.5098    0.1247    0.1863    5.9847    1.7994
-#> 49:    93.3676   -6.4486   -0.0754    2.3079   -1.0061    5.5551    5.4356    0.5018    0.1198    0.1858    6.1108    1.7598
-#> 50:    93.8573   -6.3944   -0.0755    2.3057   -1.0038    5.2773    5.2487    0.5063    0.1193    0.1843    6.0935    1.7725
-#> 51:    93.7004   -6.2783   -0.0854    2.2836   -1.0074    5.0135    4.9863    0.4932    0.1269    0.1858    6.1630    1.8063
-#> 52:    93.4843   -6.3763   -0.0962    2.2731   -1.0073    4.7628    5.0969    0.4815    0.1345    0.1924    6.0823    1.8013
-#> 53:    93.6971   -6.5002   -0.0887    2.2774   -1.0111    4.5246    5.7428    0.4726    0.1346    0.1982    6.1744    1.7695
-#> 54:    93.6176   -6.4928   -0.0917    2.2648   -1.0220    4.2984    5.4557    0.4765    0.1419    0.2017    6.3732    1.8195
-#> 55:    93.7072   -6.5760   -0.0833    2.2865   -1.0282    4.0835    5.9775    0.4732    0.1434    0.1963    6.3653    1.7028
-#> 56:    94.1360   -6.6854   -0.0901    2.2941   -1.0244    3.8793    7.2562    0.4637    0.1393    0.1935    6.3001    1.7878
-#> 57:    93.4627   -6.6255   -0.1049    2.2502   -1.0233    3.6854    6.8934    0.4847    0.1323    0.1878    6.2357    1.8480
-#> 58:    93.8066   -6.6603   -0.1049    2.2362   -1.0280    3.5011    6.9334    0.4847    0.1397    0.1872    6.3582    1.7787
-#> 59:    93.8599   -6.7837   -0.1046    2.2450   -1.0274    3.3260    8.4672    0.4853    0.1332    0.1833    6.1248    1.8066
-#> 60:    93.6190   -6.5618   -0.1055    2.2381   -1.0244    3.1597    8.0438    0.4742    0.1390    0.1858    6.2589    1.7881
-#> 61:    93.7045   -6.6482   -0.1159    2.2413   -1.0272    3.2942    7.8485    0.4655    0.1406    0.1827    5.8425    1.7744
-#> 62:    93.5232   -6.5027   -0.1168    2.2418   -1.0187    3.3810    7.4560    0.4766    0.1414    0.1790    5.9349    1.7717
-#> 63:    93.4884   -6.4221   -0.1164    2.2505   -1.0062    3.2119    7.0832    0.4768    0.1422    0.1752    6.0193    1.7434
-#> 64:    93.2305   -6.4456   -0.1153    2.2573   -1.0062    4.1468    6.7291    0.4776    0.1395    0.1753    5.8355    1.7529
-#> 65:    93.3743   -6.3237   -0.1227    2.2484   -1.0102    3.9395    6.3926    0.4864    0.1374    0.1800    5.6731    1.7808
-#> 66:    93.7132   -6.3178   -0.1186    2.2389   -0.9894    4.0557    6.0730    0.4909    0.1426    0.1807    5.7099    1.7283
-#> 67:    93.7490   -6.3514   -0.1155    2.2445   -0.9946    3.8529    5.7693    0.4938    0.1379    0.1830    5.7366    1.7847
-#> 68:    93.7617   -6.1181   -0.1251    2.2487   -0.9841    3.7650    5.4809    0.4816    0.1549    0.1769    5.6569    1.7415
-#> 69:    93.4342   -6.3588   -0.1301    2.2350   -0.9813    4.5688    5.2068    0.4745    0.1624    0.1736    5.5771    1.7091
-#> 70:    93.5303   -6.3266   -0.1330    2.2384   -0.9753    4.3404    4.9465    0.4734    0.1563    0.1699    5.5332    1.7256
-#> 71:    93.4733   -6.2859   -0.1364    2.2170   -0.9781    4.1234    4.6992    0.4701    0.1604    0.1649    5.6661    1.7335
-#> 72:    93.3055   -6.2502   -0.1462    2.2156   -0.9724    3.9172    4.7693    0.4519    0.1607    0.1582    5.4776    1.7679
-#> 73:    93.3010   -6.6844   -0.1490    2.2262   -0.9777    3.7213    6.9975    0.4426    0.1848    0.1640    5.7066    1.7588
-#> 74:    93.1104   -6.6720   -0.1484    2.2079   -0.9982    3.5353    6.7811    0.4436    0.1807    0.1732    5.7700    1.7343
-#> 75:    93.4534   -6.9644   -0.1480    2.2078   -0.9930    3.3585    8.7027    0.4497    0.1717    0.1708    5.5371    1.7098
-#> 76:    93.5886   -6.3503   -0.1491    2.1958   -0.9884    3.7136    8.2676    0.4509    0.1731    0.1706    5.3943    1.7340
-#> 77:    93.4345   -6.4976   -0.1531    2.1831   -0.9928    4.5945    7.8542    0.4592    0.1741    0.1703    5.5564    1.7164
-#> 78:    93.6007   -6.4885   -0.1538    2.1850   -0.9919    4.3647    7.4615    0.4607    0.1803    0.1692    5.4698    1.7354
-#> 79:    93.2897   -7.0329   -0.1518    2.1935   -0.9863    4.6922   10.9870    0.4569    0.1790    0.1608    5.3799    1.7484
-#> 80:    93.4130   -6.6634   -0.1531    2.1865   -0.9839    5.4720   10.4377    0.4585    0.1852    0.1543    5.4298    1.7237
-#> 81:    93.5828   -6.7204   -0.1563    2.1914   -0.9882    5.1984    9.9158    0.4548    0.1973    0.1600    5.4425    1.7741
-#> 82:    93.4450   -6.7357   -0.1537    2.1964   -0.9958    4.9384   10.1331    0.4577    0.1874    0.1632    5.6874    1.7789
-#> 83:    93.6109   -6.9249   -0.1493    2.2061   -0.9945    4.6915   11.1537    0.4474    0.1781    0.1686    5.4249    1.7317
-#> 84:    93.7133   -6.8029   -0.1493    2.2016   -0.9886    4.4569   10.9568    0.4474    0.1715    0.1689    5.5426    1.7227
-#> 85:    93.8040   -6.6434   -0.1483    2.2032   -0.9861    5.4991   10.4090    0.4330    0.1749    0.1726    5.4570    1.7332
-#> 86:    93.9029   -6.7750   -0.1472    2.2066   -0.9892    5.2241   11.7325    0.4352    0.1819    0.1644    5.5652    1.6802
-#> 87:    93.8127   -6.7015   -0.1499    2.2019   -0.9891    4.9629   11.1459    0.4292    0.1977    0.1661    5.7122    1.6713
-#> 88:    93.6777   -6.7044   -0.1440    2.2074   -1.0050    4.7148   10.5886    0.4379    0.1878    0.1750    5.6084    1.7096
-#> 89:    94.0481   -6.2990   -0.1443    2.2085   -0.9869    4.4790   10.0591    0.4355    0.1951    0.1688    5.4280    1.8093
-#> 90:    93.6399   -6.3965   -0.1429    2.2138   -0.9737    5.1306    9.5562    0.4367    0.1917    0.1604    5.5652    1.7458
-#> 91:    93.8670   -6.3075   -0.1426    2.2128   -0.9856    5.1368    9.0784    0.4427    0.1993    0.1546    5.3927    1.8246
-#> 92:    93.7332   -6.4793   -0.1426    2.2091   -0.9835    5.0102    8.6245    0.4427    0.1986    0.1585    5.4463    1.7343
-#> 93:    93.8211   -6.3270   -0.1416    2.2123   -0.9941    4.7597    8.1932    0.4431    0.1908    0.1689    5.5213    1.7093
-#> 94:    93.7499   -6.0880   -0.1390    2.2158   -0.9960    5.1992    7.7836    0.4444    0.1958    0.1733    5.5329    1.7880
-#> 95:    93.6253   -6.2196   -0.1436    2.2126   -1.0053    4.9392    7.3944    0.4383    0.2011    0.1717    5.6042    1.7460
-#> 96:    93.8862   -6.1475   -0.1408    2.2211   -0.9922    4.6923    7.0247    0.4347    0.2077    0.1669    5.6807    1.6943
-#> 97:    93.7610   -6.2409   -0.1368    2.2281   -0.9864    4.4576    6.6734    0.4313    0.2084    0.1723    5.5387    1.7075
-#> 98:    93.5362   -6.3378   -0.1368    2.2294   -0.9813    4.2348    6.3398    0.4313    0.2127    0.1877    5.5850    1.6627
-#> 99:    93.5044   -6.2557   -0.1311    2.2282   -0.9993    4.0230    6.0228    0.4461    0.2167    0.1879    5.6437    1.7076
-#> 100:    93.3102   -6.3602   -0.1311    2.2368   -1.0040    3.8219    5.7216    0.4461    0.2139    0.1875    5.8029    1.7592
-#> 101:    93.4687   -6.0385   -0.1241    2.2347   -1.0031    3.6308    5.4356    0.4483    0.2035    0.1816    6.0097    1.7002
-#> 102:    93.6536   -6.2867   -0.1299    2.2421   -1.0002    3.4492    5.1743    0.4434    0.1993    0.1872    5.8540    1.7162
-#> 103:    93.9532   -6.2261   -0.1277    2.2361   -0.9931    3.2768    5.0546    0.4450    0.2069    0.1884    5.6688    1.7324
-#> 104:    93.9839   -6.1980   -0.1287    2.2286   -1.0081    3.1129    5.0671    0.4475    0.1997    0.1985    5.7690    1.7636
-#> 105:    94.1682   -6.1671   -0.1283    2.2217   -1.0154    2.9573    4.8137    0.4481    0.1976    0.1965    5.9277    1.7386
-#> 106:    94.2778   -6.1839   -0.1243    2.2323   -1.0022    3.5381    4.5730    0.4707    0.1980    0.1932    5.7059    1.7184
-#> 107:    94.3667   -5.9941   -0.1182    2.2283   -1.0191    3.3612    4.3444    0.4753    0.1984    0.1986    5.7813    1.7446
-#> 108:    94.2722   -6.1869   -0.1171    2.2293   -1.0027    3.6659    4.6329    0.4742    0.1986    0.2011    5.7827    1.7074
-#> 109:    94.1997   -6.2385   -0.1172    2.2241   -1.0083    3.4826    4.7954    0.4721    0.2027    0.2020    5.8339    1.7650
-#> 110:    94.3017   -6.3774   -0.1291    2.2229   -0.9857    3.7634    5.8516    0.4810    0.2126    0.1984    5.7961    1.6706
-#> 111:    93.9803   -6.0240   -0.1258    2.2273   -0.9879    3.5752    5.5590    0.4749    0.2060    0.1976    5.6243    1.7082
-#> 112:    94.1307   -6.0036   -0.1253    2.2365   -0.9886    4.0368    5.2810    0.4760    0.2060    0.1975    5.5732    1.7063
-#> 113:    93.8676   -6.2496   -0.1118    2.2600   -1.0080    3.8350    5.0170    0.4855    0.2109    0.2006    5.6406    1.7357
-#> 114:    93.5949   -6.3200   -0.1044    2.2449   -1.0172    3.6472    4.7661    0.4868    0.2095    0.2131    5.7690    1.7428
-#> 115:    93.6997   -6.3282   -0.1046    2.2567   -1.0135    3.4648    4.8622    0.4876    0.2264    0.2134    5.8853    1.7823
-#> 116:    93.8191   -6.0802   -0.1087    2.2535   -1.0011    3.4347    4.6191    0.4786    0.2176    0.2108    5.6553    1.7802
-#> 117:    93.8575   -6.0930   -0.1022    2.2498   -0.9898    3.3071    4.3881    0.4822    0.2163    0.2075    5.7806    1.8150
-#> 118:    93.9164   -5.9787   -0.1133    2.2535   -0.9861    4.2578    4.1687    0.4687    0.2198    0.2088    5.4441    1.8411
-#> 119:    93.8748   -6.0108   -0.1165    2.2488   -0.9775    4.0449    3.9603    0.4653    0.2271    0.2032    5.6119    1.7501
-#> 120:    93.6001   -6.0447   -0.1144    2.2477   -0.9821    3.8426    3.7623    0.4641    0.2223    0.2055    5.6454    1.7244
-#> 121:    93.6712   -5.9851   -0.1195    2.2484   -0.9917    3.6505    3.5742    0.4600    0.2143    0.2010    5.4083    1.7965
-#> 122:    93.6859   -6.0390   -0.1145    2.2497   -0.9888    3.4680    3.5595    0.4618    0.2136    0.1986    5.4111    1.7519
-#> 123:    93.6014   -5.8383   -0.1145    2.2584   -0.9893    3.6047    3.3815    0.4618    0.2155    0.2045    5.3624    1.7023
-#> 124:    93.6333   -5.7861   -0.1131    2.2556   -0.9872    3.4245    3.2125    0.4621    0.2153    0.2025    5.3930    1.7036
-#> 125:    93.4504   -5.9483   -0.1154    2.2531   -0.9924    3.2533    3.0518    0.4640    0.2175    0.2030    5.5097    1.6830
-#> 126:    93.5693   -5.8818   -0.1120    2.2506   -0.9960    3.0906    2.8992    0.4606    0.2267    0.2016    5.4583    1.6650
-#> 127:    93.7074   -5.8191   -0.1178    2.2412   -0.9891    2.9361    2.7543    0.4688    0.2234    0.2039    5.4861    1.8125
-#> 128:    93.5959   -5.8842   -0.1179    2.2544   -0.9985    3.0224    2.6166    0.4700    0.2237    0.2019    5.6417    1.8454
-#> 129:    93.5600   -5.8683   -0.1161    2.2365   -0.9987    3.4186    2.4857    0.4721    0.2182    0.1918    5.4391    1.8145
-#> 130:    93.4104   -5.8226   -0.1126    2.2355   -0.9892    3.3648    2.4231    0.4763    0.2212    0.1873    5.3999    1.7457
-#> 131:    93.5045   -5.7255   -0.1118    2.2486   -0.9918    4.1951    2.3020    0.4776    0.2121    0.1927    5.4342    1.7744
-#> 132:    93.2626   -5.8379   -0.1097    2.2510   -0.9933    3.9853    2.5572    0.4763    0.2114    0.1966    5.2979    1.7239
-#> 133:    93.4370   -5.9097   -0.1049    2.2578   -0.9939    4.2190    2.8246    0.4738    0.2036    0.2020    5.2853    1.6765
-#> 134:    93.8665   -5.9439   -0.1035    2.2654   -0.9832    4.0081    3.1228    0.4756    0.2102    0.1961    5.3467    1.7177
-#> 135:    93.6301   -5.8062   -0.1031    2.2702   -0.9737    3.9024    2.9667    0.4748    0.2101    0.2003    5.3053    1.6977
-#> 136:    93.7744   -5.9328   -0.1055    2.2685   -0.9764    3.7072    2.9952    0.4721    0.2096    0.1949    5.4319    1.6864
-#> 137:    93.6734   -5.9886   -0.1107    2.2517   -0.9732    3.8811    3.4962    0.4642    0.2204    0.1924    5.4294    1.6684
-#> 138:    93.7128   -5.9927   -0.1119    2.2517   -0.9775    3.6870    3.4543    0.4667    0.2204    0.1953    5.3912    1.7060
-#> 139:    93.6530   -6.1296   -0.1210    2.2456   -0.9929    3.5027    4.6472    0.4527    0.2296    0.1855    5.4953    1.7242
-#> 140:    93.9344   -6.2519   -0.1384    2.2304   -0.9970    3.6814    4.4707    0.4337    0.2182    0.1762    5.5643    1.7596
-#> 141:    93.7356   -6.2804   -0.1296    2.2549   -0.9921    3.9811    4.4876    0.4218    0.2361    0.1674    5.3531    1.7175
-#> 142:    93.7399   -6.0023   -0.1098    2.2611   -0.9815    3.7821    4.2632    0.4395    0.2421    0.1807    5.3139    1.7191
-#> 143:    93.4732   -6.0376   -0.1108    2.2689   -0.9734    3.5930    4.0500    0.4396    0.2541    0.1718    5.2930    1.6229
-#> 144:    93.4900   -5.9517   -0.1093    2.2876   -0.9675    3.4133    3.8475    0.4337    0.2542    0.1711    5.4258    1.5660
-#> 145:    93.4090   -5.9596   -0.1000    2.2942   -0.9756    3.2426    3.6551    0.4274    0.2422    0.1671    5.3539    1.6971
-#> 146:    93.4142   -5.9549   -0.0982    2.2846   -0.9704    3.0805    3.6092    0.4226    0.2339    0.1745    5.5092    1.6696
-#> 147:    93.4409   -6.0720   -0.0971    2.2942   -0.9891    2.9265    3.9922    0.4224    0.2373    0.1781    5.5599    1.6080
-#> 148:    93.4504   -6.2201   -0.0980    2.2855   -0.9832    2.7802    4.6985    0.4104    0.2464    0.1856    5.5016    1.5877
-#> 149:    93.4240   -6.2122   -0.1005    2.2728   -0.9881    3.7659    4.7755    0.4082    0.2642    0.1885    5.4942    1.5534
-#> 150:    93.5094   -6.1295   -0.1087    2.2717   -0.9941    3.5776    4.5367    0.4109    0.2611    0.1928    5.3468    1.5585
-#> 151:    93.4038   -6.2751   -0.1130    2.2643   -0.9892    3.3987    4.9866    0.4172    0.2638    0.1905    5.4955    1.6256
-#> 152:    93.5072   -6.3361   -0.1147    2.2627   -0.9988    2.3580    5.3824    0.4175    0.2656    0.1819    5.7685    1.6126
-#> 153:    93.3582   -6.2019   -0.1227    2.2526   -0.9929    2.5874    4.7052    0.4348    0.2621    0.1810    5.5149    1.6181
-#> 154:    93.1890   -6.3537   -0.1263    2.2446   -0.9871    2.4073    5.7070    0.4351    0.2586    0.1829    5.3136    1.6272
-#> 155:    93.1706   -6.4117   -0.1260    2.2484   -0.9845    2.3035    6.0004    0.4463    0.2586    0.1781    5.4260    1.6494
-#> 156:    93.3240   -6.3931   -0.1259    2.2469   -0.9824    2.5659    5.7375    0.4466    0.2781    0.1754    5.6202    1.6591
-#> 157:    93.3239   -6.1812   -0.1242    2.2541   -0.9743    1.6054    4.5906    0.4478    0.2657    0.1758    5.6806    1.6367
-#> 158:    93.3756   -6.2562   -0.1264    2.2706   -0.9888    1.5329    4.6790    0.4458    0.2532    0.1728    5.7756    1.6248
-#> 159:    93.3034   -6.3291   -0.1217    2.2524   -0.9954    1.7774    5.7204    0.4532    0.2642    0.1715    5.8189    1.6830
-#> 160:    93.4387   -6.5115   -0.1196    2.2488   -0.9846    2.2219    6.4960    0.4555    0.2728    0.1689    5.5273    1.6332
-#> 161:    93.7646   -6.3820   -0.1231    2.2520   -0.9837    2.8322    5.7269    0.4498    0.2712    0.1730    5.3659    1.5787
-#> 162:    93.6252   -6.4563   -0.1243    2.2472   -0.9867    2.8322    5.9119    0.4502    0.2671    0.1726    5.4519    1.5819
-#> 163:    93.6787   -6.6444   -0.1292    2.2366   -0.9899    2.0520    7.4835    0.4556    0.2705    0.1689    5.4095    1.5883
-#> 164:    93.7458   -6.9330   -0.1257    2.2430   -0.9872    1.7825    9.4340    0.4495    0.2701    0.1593    5.4517    1.6116
-#> 165:    93.7370   -6.9118   -0.1250    2.2421   -0.9832    1.9949   10.6549    0.4499    0.2685    0.1622    5.6272    1.6075
-#> 166:    94.0889   -6.8704   -0.1276    2.2409   -0.9872    1.5618   10.4435    0.4482    0.2608    0.1648    5.5891    1.6208
-#> 167:    94.1319   -7.2779   -0.1206    2.2505   -0.9894    1.5063   13.4312    0.4393    0.2549    0.1661    5.6013    1.6043
-#> 168:    93.8341   -6.9310   -0.1140    2.2495   -0.9844    1.7329   11.3224    0.4463    0.2540    0.1629    5.8366    1.6765
-#> 169:    93.8923   -6.6547   -0.1173    2.2620   -0.9872    1.4531    8.4608    0.4419    0.2414    0.1666    5.8784    1.6268
-#> 170:    94.0072   -6.3970   -0.1173    2.2606   -0.9861    1.4164    6.9237    0.4419    0.2468    0.1656    5.8793    1.6387
-#> 171:    93.8690   -6.5151   -0.1079    2.2482   -0.9880    1.9225    7.7681    0.4547    0.2404    0.1523    6.0158    1.6281
-#> 172:    93.6847   -6.3416   -0.1095    2.2438   -0.9849    2.0143    5.5739    0.4498    0.2450    0.1534    6.1355    1.6422
-#> 173:    93.4817   -6.3165   -0.1115    2.2573   -0.9885    1.6855    5.5626    0.4440    0.2471    0.1542    6.1343    1.6337
-#> 174:    93.6781   -6.2722   -0.1113    2.2521   -0.9958    1.9186    5.3383    0.4471    0.2427    0.1565    6.1081    1.6358
-#> 175:    93.7764   -6.1664   -0.1113    2.2468   -0.9864    1.6286    4.6233    0.4471    0.2426    0.1596    5.8892    1.6375
-#> 176:    93.9246   -6.2164   -0.1160    2.2529   -0.9853    1.0357    4.8013    0.4422    0.2471    0.1756    5.7340    1.6016
-#> 177:    93.9711   -6.1274   -0.1112    2.2540   -0.9883    1.2079    4.1536    0.4415    0.2492    0.1783    5.8399    1.6291
-#> 178:    93.9212   -6.0532   -0.1116    2.2593   -0.9742    1.2409    3.6443    0.4489    0.2458    0.1683    5.8422    1.6290
-#> 179:    94.0137   -6.0739   -0.1095    2.2664   -0.9778    1.5060    3.9878    0.4506    0.2370    0.1746    6.0349    1.6326
-#> 180:    93.9247   -6.0681   -0.1130    2.2660   -0.9934    1.9619    3.9582    0.4474    0.2328    0.1773    5.8082    1.6740
-#> 181:    93.7150   -6.0191   -0.1153    2.2558   -0.9915    2.6849    3.7075    0.4491    0.2283    0.1759    5.7187    1.6842
-#> 182:    93.5908   -6.1098   -0.1111    2.2769   -0.9942    3.0096    3.9325    0.4643    0.2275    0.1736    5.9243    1.6466
-#> 183:    93.3386   -6.0987   -0.1131    2.2630   -0.9962    3.5457    4.1285    0.4693    0.2373    0.1751    5.6948    1.7222
-#> 184:    93.4889   -6.3097   -0.1134    2.2660   -0.9720    3.0855    5.2642    0.4648    0.2255    0.1585    5.6827    1.7444
-#> 185:    93.6387   -6.1883   -0.1188    2.2622   -0.9603    3.3568    4.8291    0.4554    0.2223    0.1681    5.7089    1.8164
-#> 186:    93.3420   -6.2909   -0.1195    2.2656   -0.9835    3.2124    4.8317    0.4541    0.2286    0.1531    5.7574    1.7708
-#> 187:    93.4395   -6.0358   -0.1165    2.2528   -0.9917    3.8299    3.3301    0.4518    0.2370    0.1593    5.8508    1.6988
-#> 188:    93.5358   -6.0105   -0.1161    2.2540   -0.9813    5.1249    3.3448    0.4522    0.2361    0.1660    5.8700    1.6525
-#> 189:    93.4932   -6.1199   -0.1129    2.2636   -0.9812    4.5430    4.3213    0.4428    0.2359    0.1907    5.6970    1.7268
-#> 190:    93.4754   -5.9088   -0.1171    2.2564   -0.9614    4.6253    3.2590    0.4410    0.2399    0.1864    5.7116    1.8140
-#> 191:    93.4709   -5.9676   -0.1171    2.2568   -0.9748    4.8326    3.6704    0.4410    0.2428    0.1812    5.5925    1.7267
-#> 192:    93.3895   -5.9940   -0.1191    2.2523   -0.9691    4.3019    3.5174    0.4360    0.2484    0.1591    5.4631    1.7057
-#> 193:    93.4904   -6.0400   -0.1173    2.2519   -0.9697    4.6476    3.6255    0.4389    0.2388    0.1694    5.5362    1.7174
-#> 194:    93.4591   -5.9642   -0.1245    2.2626   -0.9559    5.3125    3.8133    0.4297    0.2550    0.1660    5.7591    1.7344
-#> 195:    93.6610   -6.2211   -0.1226    2.2580   -0.9669    5.2051    4.9271    0.4318    0.2414    0.1811    5.7010    1.7710
-#> 196:    93.4249   -5.9570   -0.1068    2.2735   -0.9727    5.1049    3.4872    0.4442    0.2429    0.1815    5.7753    1.7379
-#> 197:    93.4082   -6.0568   -0.1054    2.2754   -0.9865    5.2827    3.9305    0.4554    0.2408    0.1925    5.7514    1.7163
-#> 198:    93.3856   -5.8616   -0.1087    2.2708   -0.9686    4.1369    3.0197    0.4530    0.2473    0.1878    5.6920    1.7043
-#> 199:    93.5488   -6.0494   -0.1167    2.2682   -0.9719    3.8010    3.8897    0.4600    0.2445    0.1860    5.7126    1.6605
-#> 200:    93.3779   -5.9779   -0.1110    2.2761   -0.9780    3.5955    3.4721    0.4595    0.2468    0.1941    5.7539    1.6736
-#> 201:    93.4946   -6.0259   -0.1102    2.2676   -0.9755    3.0583    3.7305    0.4592    0.2554    0.1921    5.8877    1.6730
-#> 202:    93.4698   -6.0522   -0.1110    2.2685   -0.9703    2.9421    3.8718    0.4579    0.2595    0.1906    5.8527    1.6701
-#> 203:    93.4625   -6.0744   -0.1132    2.2642   -0.9696    3.1854    4.0983    0.4589    0.2596    0.1886    5.7532    1.6655
-#> 204:    93.4984   -6.0853   -0.1138    2.2589   -0.9718    3.2826    4.1667    0.4581    0.2588    0.1851    5.7274    1.6694
-#> 205:    93.5279   -6.1054   -0.1151    2.2562   -0.9742    3.3257    4.2680    0.4569    0.2584    0.1832    5.6976    1.6777
-#> 206:    93.6025   -6.1087   -0.1174    2.2518   -0.9767    3.2399    4.2443    0.4582    0.2589    0.1822    5.6809    1.6775
-#> 207:    93.6382   -6.0990   -0.1204    2.2481   -0.9801    3.2768    4.1473    0.4579    0.2591    0.1823    5.6460    1.6819
-#> 208:    93.6250   -6.0878   -0.1224    2.2438   -0.9812    3.1815    4.0872    0.4579    0.2577    0.1818    5.6256    1.6887
-#> 209:    93.6102   -6.0740   -0.1255    2.2394   -0.9803    3.1716    3.9968    0.4561    0.2573    0.1812    5.6063    1.6886
-#> 210:    93.6005   -6.0571   -0.1277    2.2348   -0.9799    3.2408    3.8923    0.4548    0.2572    0.1798    5.5849    1.6912
-#> 211:    93.6270   -6.0425   -0.1306    2.2292   -0.9807    3.3500    3.8267    0.4538    0.2586    0.1792    5.5578    1.6992
-#> 212:    93.6641   -6.0403   -0.1331    2.2253   -0.9806    3.4487    3.8366    0.4529    0.2596    0.1786    5.5422    1.7022
-#> 213:    93.6743   -6.0344   -0.1354    2.2214   -0.9800    3.5484    3.8260    0.4518    0.2606    0.1781    5.5250    1.7069
-#> 214:    93.6719   -6.0405   -0.1377    2.2179   -0.9804    3.5538    3.8785    0.4506    0.2612    0.1769    5.5148    1.7087
-#> 215:    93.6743   -6.0403   -0.1396    2.2146   -0.9801    3.5578    3.9180    0.4496    0.2615    0.1761    5.5118    1.7094
-#> 216:    93.6666   -6.0436   -0.1413    2.2115   -0.9796    3.5848    3.9484    0.4488    0.2624    0.1755    5.5015    1.7116
-#> 217:    93.6715   -6.0438   -0.1430    2.2086   -0.9794    3.6188    3.9603    0.4478    0.2631    0.1748    5.4884    1.7132
-#> 218:    93.6765   -6.0488   -0.1441    2.2060   -0.9796    3.6126    3.9885    0.4471    0.2632    0.1746    5.4714    1.7156
-#> 219:    93.6714   -6.0557   -0.1453    2.2038   -0.9798    3.6603    4.0118    0.4463    0.2632    0.1735    5.4593    1.7235
-#> 220:    93.6728   -6.0711   -0.1462    2.2027   -0.9794    3.7244    4.0910    0.4457    0.2639    0.1730    5.4531    1.7241
-#> 221:    93.6723   -6.0822   -0.1470    2.2015   -0.9788    3.7754    4.1554    0.4450    0.2647    0.1724    5.4511    1.7247
-#> 222:    93.6789   -6.0745   -0.1480    2.1998   -0.9780    3.8735    4.1186    0.4442    0.2662    0.1718    5.4419    1.7258
-#> 223:    93.6891   -6.0700   -0.1488    2.1984   -0.9778    3.9353    4.0998    0.4434    0.2681    0.1715    5.4375    1.7251
-#> 224:    93.7125   -6.0705   -0.1496    2.1976   -0.9774    4.0220    4.0861    0.4427    0.2697    0.1711    5.4378    1.7230
-#> 225:    93.7332   -6.0695   -0.1502    2.1966   -0.9775    4.0553    4.0669    0.4422    0.2712    0.1711    5.4355    1.7205
-#> 226:    93.7631   -6.0712   -0.1508    2.1951   -0.9779    4.0755    4.0572    0.4417    0.2728    0.1712    5.4347    1.7190
-#> 227:    93.7912   -6.0687   -0.1512    2.1938   -0.9785    4.0621    4.0439    0.4409    0.2742    0.1716    5.4325    1.7189
-#> 228:    93.8077   -6.0644   -0.1517    2.1927   -0.9791    4.0246    4.0190    0.4400    0.2755    0.1722    5.4269    1.7193
-#> 229:    93.8255   -6.0661   -0.1521    2.1909   -0.9796    3.9958    4.0166    0.4392    0.2769    0.1725    5.4214    1.7214
-#> 230:    93.8403   -6.0766   -0.1530    2.1895   -0.9802    4.0152    4.0548    0.4380    0.2788    0.1730    5.4214    1.7232
-#> 231:    93.8549   -6.0768   -0.1541    2.1877   -0.9810    4.0690    4.0542    0.4368    0.2803    0.1734    5.4157    1.7236
-#> 232:    93.8666   -6.0728   -0.1550    2.1858   -0.9816    4.0852    4.0337    0.4356    0.2818    0.1736    5.4136    1.7224
-#> 233:    93.8728   -6.0672   -0.1557    2.1844   -0.9820    4.1001    4.0000    0.4346    0.2828    0.1738    5.4028    1.7243
-#> 234:    93.8862   -6.0646   -0.1563    2.1830   -0.9825    4.1303    3.9850    0.4337    0.2838    0.1737    5.3924    1.7222
-#> 235:    93.8862   -6.0632   -0.1570    2.1819   -0.9827    4.1149    3.9735    0.4329    0.2847    0.1737    5.3846    1.7225
-#> 236:    93.8827   -6.0639   -0.1577    2.1814   -0.9834    4.1004    3.9711    0.4322    0.2852    0.1739    5.3838    1.7220
-#> 237:    93.8729   -6.0680   -0.1582    2.1808   -0.9840    4.0606    3.9866    0.4316    0.2857    0.1741    5.3806    1.7213
-#> 238:    93.8739   -6.0733   -0.1587    2.1806   -0.9845    4.0331    4.0011    0.4311    0.2859    0.1742    5.3775    1.7199
-#> 239:    93.8732   -6.0729   -0.1591    2.1802   -0.9853    3.9850    3.9892    0.4307    0.2859    0.1744    5.3782    1.7216
-#> 240:    93.8760   -6.0754   -0.1595    2.1796   -0.9854    3.9349    3.9867    0.4303    0.2858    0.1747    5.3781    1.7232
-#> 241:    93.8779   -6.0749   -0.1599    2.1791   -0.9853    3.9241    3.9801    0.4299    0.2858    0.1748    5.3757    1.7228
-#> 242:    93.8842   -6.0716   -0.1602    2.1786   -0.9852    3.9394    3.9651    0.4297    0.2859    0.1749    5.3726    1.7224
-#> 243:    93.8884   -6.0719   -0.1606    2.1778   -0.9851    3.9310    3.9741    0.4295    0.2857    0.1750    5.3705    1.7224
-#> 244:    93.8910   -6.0712   -0.1610    2.1771   -0.9850    3.9173    3.9819    0.4294    0.2856    0.1749    5.3700    1.7222
-#> 245:    93.9054   -6.0736   -0.1614    2.1764   -0.9854    3.9106    3.9984    0.4293    0.2856    0.1748    5.3711    1.7217
-#> 246:    93.9209   -6.0753   -0.1617    2.1757   -0.9859    3.9080    4.0071    0.4291    0.2852    0.1746    5.3711    1.7215
-#> 247:    93.9273   -6.0846   -0.1621    2.1752   -0.9861    3.8790    4.0580    0.4286    0.2851    0.1745    5.3755    1.7206
-#> 248:    93.9265   -6.0884   -0.1625    2.1749   -0.9865    3.8613    4.0784    0.4286    0.2848    0.1744    5.3760    1.7198
-#> 249:    93.9286   -6.0926   -0.1627    2.1746   -0.9872    3.8663    4.1008    0.4287    0.2845    0.1745    5.3755    1.7195
-#> 250:    93.9287   -6.0968   -0.1629    2.1744   -0.9878    3.8822    4.1269    0.4289    0.2844    0.1743    5.3755    1.7201
-#> 251:    93.9314   -6.1017   -0.1630    2.1739   -0.9882    3.8878    4.1495    0.4291    0.2843    0.1744    5.3729    1.7200
-#> 252:    93.9351   -6.1036   -0.1632    2.1734   -0.9885    3.8908    4.1545    0.4293    0.2843    0.1746    5.3684    1.7191
-#> 253:    93.9415   -6.1053   -0.1634    2.1729   -0.9889    3.8727    4.1602    0.4294    0.2842    0.1747    5.3650    1.7196
-#> 254:    93.9473   -6.1088   -0.1636    2.1723   -0.9891    3.8657    4.1769    0.4296    0.2843    0.1749    5.3666    1.7190
-#> 255:    93.9505   -6.1087   -0.1639    2.1717   -0.9888    3.8457    4.1720    0.4298    0.2841    0.1749    5.3617    1.7191
-#> 256:    93.9497   -6.1054   -0.1642    2.1715   -0.9885    3.8395    4.1559    0.4299    0.2839    0.1749    5.3598    1.7192
-#> 257:    93.9477   -6.1008   -0.1643    2.1713   -0.9882    3.8383    4.1360    0.4299    0.2836    0.1749    5.3567    1.7196
-#> 258:    93.9402   -6.0998   -0.1645    2.1713   -0.9880    3.8516    4.1288    0.4300    0.2832    0.1749    5.3565    1.7190
-#> 259:    93.9318   -6.0979   -0.1646    2.1711   -0.9879    3.8396    4.1182    0.4301    0.2829    0.1750    5.3583    1.7188
-#> 260:    93.9277   -6.1002   -0.1646    2.1713   -0.9879    3.8173    4.1273    0.4304    0.2826    0.1751    5.3611    1.7186
-#> 261:    93.9251   -6.0973   -0.1646    2.1714   -0.9879    3.8140    4.1105    0.4306    0.2822    0.1750    5.3588    1.7192
-#> 262:    93.9186   -6.1009   -0.1647    2.1715   -0.9880    3.8177    4.1303    0.4308    0.2822    0.1750    5.3604    1.7194
-#> 263:    93.9130   -6.1033   -0.1646    2.1715   -0.9880    3.8029    4.1529    0.4309    0.2822    0.1748    5.3647    1.7188
-#> 264:    93.9040   -6.1077   -0.1645    2.1717   -0.9879    3.7950    4.1820    0.4310    0.2822    0.1747    5.3699    1.7184
-#> 265:    93.9012   -6.1071   -0.1645    2.1714   -0.9879    3.7834    4.1895    0.4310    0.2822    0.1746    5.3755    1.7191
-#> 266:    93.8988   -6.1051   -0.1644    2.1714   -0.9879    3.7788    4.1822    0.4311    0.2822    0.1745    5.3765    1.7203
-#> 267:    93.8964   -6.1059   -0.1643    2.1714   -0.9877    3.7774    4.1896    0.4311    0.2822    0.1744    5.3792    1.7197
-#> 268:    93.8901   -6.1092   -0.1643    2.1715   -0.9876    3.7790    4.2198    0.4310    0.2822    0.1742    5.3811    1.7200
-#> 269:    93.8842   -6.1105   -0.1643    2.1717   -0.9875    3.7620    4.2336    0.4310    0.2823    0.1742    5.3838    1.7193
-#> 270:    93.8760   -6.1125   -0.1643    2.1721   -0.9874    3.7668    4.2483    0.4308    0.2823    0.1741    5.3852    1.7181
-#> 271:    93.8705   -6.1149   -0.1643    2.1722   -0.9873    3.7785    4.2625    0.4306    0.2823    0.1742    5.3853    1.7172
-#> 272:    93.8674   -6.1149   -0.1643    2.1723   -0.9871    3.7829    4.2581    0.4304    0.2823    0.1743    5.3836    1.7162
-#> 273:    93.8644   -6.1159   -0.1642    2.1725   -0.9870    3.7910    4.2631    0.4303    0.2825    0.1743    5.3818    1.7154
-#> 274:    93.8585   -6.1158   -0.1640    2.1728   -0.9869    3.7926    4.2612    0.4302    0.2825    0.1743    5.3816    1.7147
-#> 275:    93.8564   -6.1151   -0.1639    2.1732   -0.9867    3.8053    4.2581    0.4301    0.2826    0.1743    5.3804    1.7143
-#> 276:    93.8564   -6.1132   -0.1638    2.1736   -0.9866    3.7958    4.2486    0.4300    0.2827    0.1745    5.3810    1.7144
-#> 277:    93.8564   -6.1120   -0.1637    2.1741   -0.9867    3.7952    4.2426    0.4298    0.2829    0.1747    5.3808    1.7148
-#> 278:    93.8528   -6.1113   -0.1636    2.1743   -0.9867    3.7922    4.2352    0.4297    0.2832    0.1750    5.3819    1.7144
-#> 279:    93.8503   -6.1124   -0.1636    2.1744   -0.9867    3.7930    4.2390    0.4298    0.2834    0.1753    5.3826    1.7144
-#> 280:    93.8466   -6.1146   -0.1636    2.1743   -0.9867    3.7946    4.2470    0.4299    0.2838    0.1755    5.3832    1.7142
-#> 281:    93.8435   -6.1165   -0.1638    2.1743   -0.9867    3.7994    4.2552    0.4298    0.2840    0.1756    5.3828    1.7140
-#> 282:    93.8421   -6.1162   -0.1639    2.1741   -0.9868    3.7967    4.2496    0.4296    0.2843    0.1758    5.3816    1.7137
-#> 283:    93.8382   -6.1146   -0.1641    2.1740   -0.9866    3.7957    4.2387    0.4294    0.2845    0.1760    5.3796    1.7135
-#> 284:    93.8356   -6.1131   -0.1641    2.1740   -0.9865    3.7904    4.2263    0.4292    0.2848    0.1762    5.3776    1.7127
-#> 285:    93.8349   -6.1113   -0.1642    2.1740   -0.9865    3.7841    4.2129    0.4291    0.2850    0.1765    5.3763    1.7130
-#> 286:    93.8372   -6.1095   -0.1643    2.1741   -0.9864    3.7801    4.2035    0.4289    0.2853    0.1769    5.3779    1.7130
-#> 287:    93.8393   -6.1077   -0.1643    2.1741   -0.9864    3.7804    4.1908    0.4287    0.2857    0.1771    5.3785    1.7132
-#> 288:    93.8395   -6.1071   -0.1644    2.1740   -0.9866    3.7714    4.1834    0.4284    0.2859    0.1772    5.3798    1.7120
-#> 289:    93.8398   -6.1065   -0.1645    2.1738   -0.9865    3.7635    4.1765    0.4282    0.2861    0.1774    5.3821    1.7111
-#> 290:    93.8376   -6.1089   -0.1647    2.1737   -0.9865    3.7495    4.1853    0.4281    0.2863    0.1776    5.3852    1.7106
-#> 291:    93.8341   -6.1091   -0.1647    2.1738   -0.9863    3.7340    4.1854    0.4278    0.2865    0.1776    5.3868    1.7098
-#> 292:    93.8329   -6.1080   -0.1647    2.1741   -0.9863    3.7189    4.1760    0.4275    0.2868    0.1777    5.3885    1.7091
-#> 293:    93.8312   -6.1065   -0.1647    2.1743   -0.9862    3.7091    4.1651    0.4272    0.2871    0.1778    5.3896    1.7086
-#> 294:    93.8310   -6.1042   -0.1647    2.1745   -0.9861    3.6946    4.1521    0.4269    0.2874    0.1780    5.3908    1.7077
-#> 295:    93.8299   -6.1033   -0.1648    2.1747   -0.9861    3.6968    4.1433    0.4265    0.2880    0.1781    5.3904    1.7066
-#> 296:    93.8276   -6.1027   -0.1648    2.1749   -0.9862    3.7072    4.1361    0.4261    0.2885    0.1782    5.3910    1.7056
-#> 297:    93.8212   -6.1015   -0.1647    2.1750   -0.9859    3.7253    4.1278    0.4256    0.2891    0.1783    5.3927    1.7051
-#> 298:    93.8173   -6.0980   -0.1647    2.1751   -0.9858    3.7552    4.1115    0.4251    0.2897    0.1784    5.3932    1.7045
-#> 299:    93.8168   -6.0984   -0.1646    2.1754   -0.9856    3.7687    4.1143    0.4246    0.2902    0.1786    5.3949    1.7037
-#> 300:    93.8154   -6.0967   -0.1646    2.1756   -0.9855    3.7888    4.1072    0.4241    0.2906    0.1788    5.3962    1.7030
-#> 301:    93.8129   -6.0946   -0.1646    2.1757   -0.9852    3.8097    4.1006    0.4236    0.2911    0.1791    5.3971    1.7026
-#> 302:    93.8120   -6.0932   -0.1646    2.1759   -0.9849    3.8403    4.0955    0.4231    0.2917    0.1792    5.3971    1.7021
-#> 303:    93.8115   -6.0942   -0.1646    2.1762   -0.9850    3.8602    4.1004    0.4227    0.2922    0.1795    5.3976    1.7020
-#> 304:    93.8106   -6.0979   -0.1645    2.1765   -0.9850    3.8898    4.1217    0.4222    0.2926    0.1798    5.3975    1.7024
-#> 305:    93.8091   -6.1009   -0.1644    2.1767   -0.9851    3.9165    4.1374    0.4218    0.2931    0.1801    5.3989    1.7024
-#> 306:    93.8090   -6.1043   -0.1644    2.1770   -0.9850    3.9485    4.1617    0.4214    0.2936    0.1803    5.3998    1.7021
-#> 307:    93.8082   -6.1063   -0.1644    2.1772   -0.9850    3.9730    4.1797    0.4210    0.2940    0.1803    5.3998    1.7017
-#> 308:    93.8093   -6.1090   -0.1644    2.1775   -0.9850    3.9874    4.2026    0.4205    0.2945    0.1804    5.3996    1.7006
-#> 309:    93.8092   -6.1122   -0.1643    2.1777   -0.9849    3.9948    4.2297    0.4201    0.2948    0.1804    5.4001    1.6998
-#> 310:    93.8080   -6.1142   -0.1642    2.1780   -0.9850    3.9976    4.2436    0.4197    0.2951    0.1803    5.4016    1.6989
-#> 311:    93.8094   -6.1164   -0.1641    2.1784   -0.9851    4.0015    4.2552    0.4194    0.2952    0.1803    5.4033    1.6978
-#> 312:    93.8107   -6.1184   -0.1640    2.1788   -0.9851    4.0006    4.2628    0.4190    0.2954    0.1802    5.4042    1.6972
-#> 313:    93.8118   -6.1190   -0.1640    2.1789   -0.9851    3.9991    4.2638    0.4186    0.2955    0.1802    5.4053    1.6967
-#> 314:    93.8139   -6.1188   -0.1639    2.1791   -0.9851    4.0019    4.2619    0.4183    0.2956    0.1802    5.4049    1.6966
-#> 315:    93.8152   -6.1173   -0.1639    2.1792   -0.9851    4.0111    4.2553    0.4179    0.2957    0.1802    5.4052    1.6966
-#> 316:    93.8178   -6.1158   -0.1639    2.1792   -0.9851    4.0073    4.2498    0.4175    0.2957    0.1802    5.4050    1.6966
-#> 317:    93.8205   -6.1155   -0.1639    2.1792   -0.9851    3.9999    4.2491    0.4172    0.2957    0.1802    5.4048    1.6963
-#> 318:    93.8216   -6.1145   -0.1639    2.1792   -0.9850    3.9961    4.2438    0.4168    0.2957    0.1802    5.4031    1.6961
-#> 319:    93.8241   -6.1143   -0.1639    2.1792   -0.9849    4.0009    4.2412    0.4164    0.2958    0.1801    5.4004    1.6956
-#> 320:    93.8257   -6.1142   -0.1639    2.1792   -0.9849    4.0018    4.2380    0.4160    0.2958    0.1801    5.3986    1.6952
-#> 321:    93.8280   -6.1134   -0.1639    2.1792   -0.9849    4.0055    4.2339    0.4156    0.2959    0.1802    5.3966    1.6950
-#> 322:    93.8299   -6.1122   -0.1639    2.1793   -0.9848    4.0075    4.2274    0.4152    0.2959    0.1802    5.3969    1.6948
-#> 323:    93.8318   -6.1123   -0.1639    2.1794   -0.9848    4.0087    4.2257    0.4149    0.2960    0.1802    5.3980    1.6941
-#> 324:    93.8352   -6.1098   -0.1639    2.1795   -0.9848    4.0123    4.2136    0.4145    0.2960    0.1802    5.3988    1.6936
-#> 325:    93.8374   -6.1072   -0.1638    2.1796   -0.9848    4.0230    4.2005    0.4142    0.2961    0.1802    5.3991    1.6933
-#> 326:    93.8410   -6.1050   -0.1637    2.1796   -0.9849    4.0327    4.1891    0.4139    0.2963    0.1802    5.4004    1.6927
-#> 327:    93.8457   -6.1023   -0.1637    2.1796   -0.9849    4.0327    4.1767    0.4135    0.2964    0.1802    5.4013    1.6922
-#> 328:    93.8493   -6.1017   -0.1637    2.1797   -0.9850    4.0440    4.1730    0.4131    0.2964    0.1802    5.4019    1.6915
-#> 329:    93.8515   -6.1001   -0.1637    2.1799   -0.9851    4.0556    4.1648    0.4128    0.2963    0.1803    5.4017    1.6912
-#> 330:    93.8541   -6.1001   -0.1636    2.1800   -0.9852    4.0606    4.1631    0.4124    0.2962    0.1804    5.4025    1.6912
-#> 331:    93.8539   -6.0994   -0.1635    2.1801   -0.9854    4.0654    4.1584    0.4120    0.2961    0.1805    5.4025    1.6907
-#> 332:    93.8536   -6.0999   -0.1634    2.1803   -0.9854    4.0696    4.1601    0.4116    0.2960    0.1808    5.4027    1.6904
-#> 333:    93.8531   -6.1002   -0.1633    2.1806   -0.9853    4.0682    4.1646    0.4112    0.2960    0.1810    5.4038    1.6893
-#> 334:    93.8543   -6.1005   -0.1632    2.1809   -0.9852    4.0771    4.1690    0.4108    0.2960    0.1812    5.4040    1.6883
-#> 335:    93.8552   -6.1010   -0.1631    2.1813   -0.9851    4.0888    4.1775    0.4104    0.2960    0.1813    5.4044    1.6878
-#> 336:    93.8555   -6.1016   -0.1630    2.1817   -0.9850    4.0969    4.1858    0.4099    0.2961    0.1814    5.4046    1.6873
-#> 337:    93.8553   -6.1025   -0.1628    2.1820   -0.9849    4.1152    4.1921    0.4094    0.2962    0.1815    5.4070    1.6863
-#> 338:    93.8553   -6.1018   -0.1626    2.1824   -0.9848    4.1314    4.1904    0.4090    0.2963    0.1816    5.4080    1.6852
-#> 339:    93.8567   -6.1004   -0.1625    2.1828   -0.9847    4.1449    4.1855    0.4087    0.2964    0.1817    5.4087    1.6841
-#> 340:    93.8582   -6.0987   -0.1623    2.1832   -0.9846    4.1603    4.1799    0.4083    0.2965    0.1819    5.4086    1.6832
-#> 341:    93.8589   -6.0962   -0.1620    2.1836   -0.9844    4.1692    4.1694    0.4079    0.2965    0.1820    5.4102    1.6828
-#> 342:    93.8583   -6.0932   -0.1618    2.1841   -0.9844    4.1729    4.1563    0.4075    0.2966    0.1821    5.4117    1.6821
-#> 343:    93.8590   -6.0906   -0.1615    2.1845   -0.9844    4.1840    4.1447    0.4071    0.2966    0.1822    5.4125    1.6819
-#> 344:    93.8582   -6.0890   -0.1613    2.1851   -0.9845    4.1860    4.1347    0.4068    0.2968    0.1826    5.4135    1.6814
-#> 345:    93.8576   -6.0876   -0.1610    2.1857   -0.9846    4.1889    4.1252    0.4064    0.2969    0.1829    5.4143    1.6810
-#> 346:    93.8549   -6.0853   -0.1608    2.1862   -0.9845    4.1925    4.1121    0.4061    0.2969    0.1832    5.4157    1.6803
-#> 347:    93.8540   -6.0829   -0.1605    2.1867   -0.9845    4.2031    4.0990    0.4058    0.2970    0.1834    5.4158    1.6803
-#> 348:    93.8516   -6.0814   -0.1602    2.1873   -0.9845    4.2169    4.0885    0.4055    0.2971    0.1836    5.4174    1.6801
-#> 349:    93.8505   -6.0797   -0.1600    2.1879   -0.9845    4.2253    4.0779    0.4052    0.2971    0.1837    5.4190    1.6799
-#> 350:    93.8512   -6.0773   -0.1597    2.1885   -0.9845    4.2268    4.0657    0.4049    0.2972    0.1839    5.4209    1.6797
-#> 351:    93.8507   -6.0754   -0.1595    2.1890   -0.9845    4.2245    4.0559    0.4046    0.2972    0.1840    5.4230    1.6794
-#> 352:    93.8490   -6.0736   -0.1592    2.1896   -0.9845    4.2296    4.0474    0.4044    0.2973    0.1841    5.4252    1.6790
-#> 353:    93.8460   -6.0718   -0.1589    2.1901   -0.9845    4.2356    4.0374    0.4042    0.2973    0.1843    5.4272    1.6790
-#> 354:    93.8437   -6.0695   -0.1586    2.1906   -0.9845    4.2408    4.0255    0.4041    0.2973    0.1844    5.4303    1.6787
-#> 355:    93.8420   -6.0679   -0.1584    2.1912   -0.9844    4.2428    4.0166    0.4040    0.2973    0.1845    5.4342    1.6785
-#> 356:    93.8413   -6.0666   -0.1581    2.1916   -0.9843    4.2418    4.0072    0.4040    0.2973    0.1845    5.4348    1.6792
-#> 357:    93.8406   -6.0650   -0.1578    2.1921   -0.9844    4.2531    3.9973    0.4040    0.2973    0.1846    5.4350    1.6798
-#> 358:    93.8404   -6.0639   -0.1575    2.1926   -0.9844    4.2596    3.9901    0.4040    0.2973    0.1846    5.4357    1.6805
-#> 359:    93.8373   -6.0630   -0.1572    2.1931   -0.9845    4.2724    3.9820    0.4039    0.2973    0.1848    5.4368    1.6816
-#> 360:    93.8347   -6.0622   -0.1569    2.1936   -0.9845    4.2788    3.9747    0.4039    0.2973    0.1849    5.4377    1.6824
-#> 361:    93.8327   -6.0626   -0.1566    2.1942   -0.9846    4.2919    3.9749    0.4038    0.2973    0.1850    5.4382    1.6831
-#> 362:    93.8326   -6.0629   -0.1562    2.1947   -0.9846    4.2989    3.9737    0.4038    0.2973    0.1850    5.4408    1.6838
-#> 363:    93.8316   -6.0629   -0.1559    2.1953   -0.9846    4.3007    3.9725    0.4037    0.2972    0.1850    5.4420    1.6842
-#> 364:    93.8317   -6.0629   -0.1556    2.1957   -0.9846    4.2910    3.9739    0.4038    0.2971    0.1850    5.4430    1.6840
-#> 365:    93.8317   -6.0629   -0.1553    2.1962   -0.9846    4.2878    3.9759    0.4040    0.2967    0.1849    5.4441    1.6839
-#> 366:    93.8319   -6.0633   -0.1549    2.1966   -0.9845    4.2870    3.9823    0.4042    0.2963    0.1849    5.4461    1.6839
-#> 367:    93.8320   -6.0636   -0.1546    2.1971   -0.9845    4.2828    3.9850    0.4042    0.2959    0.1849    5.4479    1.6843
-#> 368:    93.8312   -6.0635   -0.1544    2.1975   -0.9844    4.2781    3.9859    0.4043    0.2955    0.1849    5.4475    1.6841
-#> 369:    93.8301   -6.0640   -0.1541    2.1979   -0.9844    4.2760    3.9891    0.4043    0.2953    0.1850    5.4472    1.6835
-#> 370:    93.8306   -6.0651   -0.1539    2.1983   -0.9844    4.2690    3.9967    0.4042    0.2950    0.1850    5.4484    1.6829
-#> 371:    93.8312   -6.0669   -0.1536    2.1988   -0.9845    4.2613    4.0111    0.4042    0.2947    0.1851    5.4494    1.6822
-#> 372:    93.8312   -6.0681   -0.1533    2.1992   -0.9845    4.2585    4.0252    0.4042    0.2945    0.1852    5.4513    1.6817
-#> 373:    93.8307   -6.0681   -0.1531    2.1996   -0.9846    4.2605    4.0284    0.4042    0.2943    0.1853    5.4523    1.6815
-#> 374:    93.8305   -6.0678   -0.1529    2.1999   -0.9846    4.2676    4.0279    0.4040    0.2942    0.1853    5.4533    1.6816
-#> 375:    93.8313   -6.0673   -0.1528    2.2002   -0.9846    4.2708    4.0232    0.4038    0.2940    0.1854    5.4543    1.6813
-#> 376:    93.8310   -6.0672   -0.1527    2.2004   -0.9846    4.2775    4.0214    0.4037    0.2938    0.1855    5.4538    1.6809
-#> 377:    93.8298   -6.0666   -0.1526    2.2007   -0.9846    4.2787    4.0166    0.4035    0.2937    0.1856    5.4532    1.6806
-#> 378:    93.8276   -6.0664   -0.1525    2.2009   -0.9846    4.2781    4.0135    0.4033    0.2935    0.1857    5.4538    1.6801
-#> 379:    93.8262   -6.0671   -0.1524    2.2012   -0.9846    4.2800    4.0157    0.4031    0.2932    0.1857    5.4530    1.6803
-#> 380:    93.8243   -6.0675   -0.1523    2.2015   -0.9846    4.2735    4.0168    0.4029    0.2929    0.1857    5.4523    1.6803
-#> 381:    93.8233   -6.0677   -0.1522    2.2017   -0.9845    4.2670    4.0189    0.4027    0.2926    0.1858    5.4517    1.6798
-#> 382:    93.8229   -6.0674   -0.1521    2.2019   -0.9845    4.2655    4.0211    0.4025    0.2924    0.1858    5.4510    1.6794
-#> 383:    93.8196   -6.0681   -0.1521    2.2021   -0.9843    4.2696    4.0291    0.4023    0.2922    0.1859    5.4504    1.6788
-#> 384:    93.8174   -6.0688   -0.1520    2.2023   -0.9842    4.2851    4.0333    0.4021    0.2919    0.1860    5.4500    1.6783
-#> 385:    93.8156   -6.0682   -0.1518    2.2028   -0.9840    4.3056    4.0305    0.4019    0.2920    0.1862    5.4503    1.6774
-#> 386:    93.8145   -6.0684   -0.1516    2.2032   -0.9838    4.3195    4.0302    0.4016    0.2920    0.1863    5.4499    1.6765
-#> 387:    93.8121   -6.0679   -0.1514    2.2036   -0.9837    4.3290    4.0272    0.4014    0.2920    0.1864    5.4501    1.6756
-#> 388:    93.8105   -6.0676   -0.1513    2.2040   -0.9835    4.3393    4.0267    0.4011    0.2920    0.1865    5.4509    1.6751
-#> 389:    93.8089   -6.0664   -0.1510    2.2045   -0.9833    4.3458    4.0224    0.4009    0.2920    0.1865    5.4512    1.6746
-#> 390:    93.8080   -6.0658   -0.1508    2.2049   -0.9832    4.3422    4.0199    0.4007    0.2920    0.1866    5.4514    1.6744
-#> 391:    93.8077   -6.0669   -0.1507    2.2053   -0.9831    4.3500    4.0277    0.4007    0.2920    0.1867    5.4511    1.6740
-#> 392:    93.8069   -6.0676   -0.1505    2.2056   -0.9831    4.3525    4.0326    0.4006    0.2920    0.1868    5.4500    1.6733
-#> 393:    93.8072   -6.0678   -0.1504    2.2059   -0.9830    4.3562    4.0344    0.4005    0.2920    0.1868    5.4491    1.6725
-#> 394:    93.8083   -6.0684   -0.1503    2.2061   -0.9829    4.3577    4.0386    0.4004    0.2920    0.1869    5.4493    1.6716
-#> 395:    93.8086   -6.0685   -0.1501    2.2064   -0.9828    4.3574    4.0394    0.4003    0.2920    0.1869    5.4493    1.6709
-#> 396:    93.8078   -6.0677   -0.1500    2.2067   -0.9827    4.3591    4.0355    0.4002    0.2921    0.1870    5.4493    1.6707
-#> 397:    93.8064   -6.0668   -0.1499    2.2071   -0.9825    4.3621    4.0317    0.4000    0.2922    0.1871    5.4495    1.6704
-#> 398:    93.8058   -6.0661   -0.1499    2.2073   -0.9823    4.3701    4.0285    0.3999    0.2923    0.1872    5.4491    1.6699
-#> 399:    93.8057   -6.0651   -0.1498    2.2075   -0.9822    4.3803    4.0243    0.3997    0.2924    0.1872    5.4485    1.6699
-#> 400:    93.8057   -6.0647   -0.1498    2.2076   -0.9820    4.3854    4.0225    0.3996    0.2924    0.1872    5.4488    1.6699
-#> 401:    93.8059   -6.0635   -0.1498    2.2078   -0.9819    4.3939    4.0178    0.3995    0.2925    0.1873    5.4491    1.6702
-#> 402:    93.8063   -6.0621   -0.1498    2.2079   -0.9818    4.4033    4.0120    0.3993    0.2926    0.1875    5.4492    1.6704
-#> 403:    93.8055   -6.0609   -0.1498    2.2080   -0.9816    4.4098    4.0069    0.3992    0.2926    0.1876    5.4494    1.6703
-#> 404:    93.8040   -6.0608   -0.1499    2.2081   -0.9815    4.4153    4.0050    0.3991    0.2927    0.1877    5.4494    1.6701
-#> 405:    93.8030   -6.0604   -0.1499    2.2082   -0.9814    4.4181    4.0047    0.3990    0.2928    0.1879    5.4491    1.6700
-#> 406:    93.8002   -6.0597   -0.1499    2.2083   -0.9812    4.4257    4.0025    0.3989    0.2928    0.1880    5.4498    1.6702
-#> 407:    93.7969   -6.0593   -0.1500    2.2085   -0.9810    4.4343    3.9994    0.3988    0.2928    0.1881    5.4514    1.6703
-#> 408:    93.7947   -6.0582   -0.1499    2.2087   -0.9809    4.4509    3.9936    0.3987    0.2927    0.1882    5.4526    1.6704
-#> 409:    93.7929   -6.0579   -0.1499    2.2088   -0.9807    4.4584    3.9918    0.3987    0.2926    0.1882    5.4537    1.6707
-#> 410:    93.7896   -6.0593   -0.1499    2.2089   -0.9807    4.4664    4.0002    0.3987    0.2925    0.1883    5.4560    1.6705
-#> 411:    93.7875   -6.0601   -0.1499    2.2090   -0.9807    4.4626    4.0057    0.3987    0.2924    0.1883    5.4567    1.6705
-#> 412:    93.7862   -6.0602   -0.1499    2.2091   -0.9808    4.4574    4.0095    0.3986    0.2923    0.1884    5.4565    1.6706
-#> 413:    93.7858   -6.0606   -0.1498    2.2092   -0.9808    4.4527    4.0146    0.3986    0.2922    0.1885    5.4561    1.6708
-#> 414:    93.7859   -6.0615   -0.1498    2.2093   -0.9808    4.4451    4.0211    0.3987    0.2921    0.1885    5.4574    1.6708
-#> 415:    93.7864   -6.0629   -0.1498    2.2092   -0.9808    4.4443    4.0298    0.3986    0.2921    0.1885    5.4576    1.6707
-#> 416:    93.7851   -6.0639   -0.1498    2.2092   -0.9808    4.4462    4.0362    0.3985    0.2920    0.1884    5.4575    1.6706
-#> 417:    93.7820   -6.0644   -0.1499    2.2092   -0.9808    4.4425    4.0387    0.3985    0.2920    0.1884    5.4577    1.6703
-#> 418:    93.7801   -6.0652   -0.1499    2.2093   -0.9808    4.4365    4.0420    0.3985    0.2920    0.1883    5.4589    1.6702
-#> 419:    93.7799   -6.0648   -0.1499    2.2094   -0.9807    4.4303    4.0418    0.3984    0.2921    0.1883    5.4596    1.6703
-#> 420:    93.7797   -6.0641   -0.1498    2.2095   -0.9807    4.4216    4.0383    0.3983    0.2921    0.1884    5.4607    1.6702
-#> 421:    93.7803   -6.0641   -0.1498    2.2096   -0.9808    4.4120    4.0396    0.3983    0.2922    0.1885    5.4621    1.6702
-#> 422:    93.7806   -6.0638   -0.1498    2.2097   -0.9809    4.4017    4.0373    0.3981    0.2923    0.1885    5.4635    1.6702
-#> 423:    93.7800   -6.0636   -0.1498    2.2098   -0.9810    4.3948    4.0339    0.3981    0.2923    0.1885    5.4640    1.6701
-#> 424:    93.7789   -6.0638   -0.1498    2.2099   -0.9810    4.3884    4.0336    0.3980    0.2924    0.1885    5.4651    1.6700
-#> 425:    93.7774   -6.0628   -0.1498    2.2101   -0.9810    4.3814    4.0271    0.3978    0.2925    0.1884    5.4666    1.6699
-#> 426:    93.7755   -6.0619   -0.1498    2.2102   -0.9811    4.3841    4.0221    0.3977    0.2925    0.1884    5.4693    1.6697
-#> 427:    93.7753   -6.0612   -0.1498    2.2103   -0.9810    4.3785    4.0167    0.3975    0.2926    0.1883    5.4712    1.6696
-#> 428:    93.7741   -6.0613   -0.1498    2.2104   -0.9810    4.3767    4.0161    0.3973    0.2926    0.1882    5.4729    1.6696
-#> 429:    93.7717   -6.0613   -0.1498    2.2105   -0.9810    4.3744    4.0158    0.3971    0.2926    0.1880    5.4743    1.6694
-#> 430:    93.7690   -6.0619   -0.1498    2.2106   -0.9809    4.3744    4.0189    0.3969    0.2926    0.1879    5.4753    1.6692
-#> 431:    93.7668   -6.0615   -0.1498    2.2107   -0.9809    4.3709    4.0174    0.3967    0.2925    0.1878    5.4762    1.6691
-#> 432:    93.7656   -6.0619   -0.1498    2.2108   -0.9809    4.3710    4.0173    0.3966    0.2926    0.1878    5.4770    1.6688
-#> 433:    93.7632   -6.0625   -0.1498    2.2108   -0.9809    4.3689    4.0204    0.3964    0.2926    0.1877    5.4774    1.6687
-#> 434:    93.7624   -6.0621   -0.1498    2.2109   -0.9808    4.3687    4.0178    0.3962    0.2926    0.1876    5.4774    1.6683
-#> 435:    93.7608   -6.0622   -0.1497    2.2111   -0.9808    4.3714    4.0182    0.3961    0.2927    0.1875    5.4777    1.6679
-#> 436:    93.7586   -6.0622   -0.1498    2.2112   -0.9808    4.3695    4.0178    0.3959    0.2928    0.1874    5.4784    1.6679
-#> 437:    93.7558   -6.0622   -0.1498    2.2114   -0.9809    4.3658    4.0167    0.3957    0.2928    0.1873    5.4795    1.6678
-#> 438:    93.7519   -6.0627   -0.1499    2.2115   -0.9808    4.3601    4.0183    0.3955    0.2928    0.1872    5.4807    1.6674
-#> 439:    93.7478   -6.0618   -0.1499    2.2115   -0.9807    4.3538    4.0133    0.3952    0.2928    0.1871    5.4814    1.6672
-#> 440:    93.7449   -6.0612   -0.1499    2.2117   -0.9805    4.3504    4.0103    0.3951    0.2928    0.1870    5.4820    1.6669
-#> 441:    93.7433   -6.0608   -0.1499    2.2117   -0.9805    4.3438    4.0077    0.3949    0.2928    0.1869    5.4818    1.6666
-#> 442:    93.7417   -6.0604   -0.1500    2.2118   -0.9805    4.3354    4.0058    0.3947    0.2927    0.1868    5.4824    1.6666
-#> 443:    93.7407   -6.0604   -0.1500    2.2119   -0.9805    4.3281    4.0046    0.3946    0.2927    0.1867    5.4832    1.6667
-#> 444:    93.7397   -6.0608   -0.1500    2.2118   -0.9805    4.3180    4.0069    0.3944    0.2928    0.1866    5.4857    1.6664
-#> 445:    93.7387   -6.0613   -0.1501    2.2118   -0.9805    4.3092    4.0085    0.3942    0.2929    0.1866    5.4866    1.6663
-#> 446:    93.7376   -6.0612   -0.1502    2.2117   -0.9805    4.3022    4.0075    0.3939    0.2930    0.1865    5.4866    1.6660
-#> 447:    93.7375   -6.0613   -0.1503    2.2116   -0.9806    4.2981    4.0076    0.3937    0.2931    0.1865    5.4863    1.6658
-#> 448:    93.7388   -6.0617   -0.1504    2.2115   -0.9806    4.2970    4.0087    0.3935    0.2932    0.1864    5.4870    1.6658
-#> 449:    93.7400   -6.0617   -0.1504    2.2115   -0.9807    4.2904    4.0069    0.3933    0.2933    0.1864    5.4880    1.6655
-#> 450:    93.7414   -6.0623   -0.1505    2.2113   -0.9808    4.2829    4.0095    0.3930    0.2935    0.1863    5.4880    1.6653
-#> 451:    93.7426   -6.0634   -0.1506    2.2112   -0.9808    4.2797    4.0146    0.3928    0.2936    0.1863    5.4877    1.6655
-#> 452:    93.7447   -6.0642   -0.1507    2.2110   -0.9809    4.2770    4.0171    0.3926    0.2938    0.1862    5.4876    1.6657
-#> 453:    93.7465   -6.0644   -0.1508    2.2108   -0.9810    4.2698    4.0184    0.3924    0.2940    0.1862    5.4877    1.6652
-#> 454:    93.7478   -6.0645   -0.1509    2.2106   -0.9810    4.2657    4.0182    0.3922    0.2941    0.1861    5.4874    1.6648
-#> 455:    93.7486   -6.0650   -0.1511    2.2104   -0.9811    4.2656    4.0203    0.3921    0.2943    0.1861    5.4871    1.6644
-#> 456:    93.7485   -6.0659   -0.1512    2.2102   -0.9812    4.2646    4.0240    0.3920    0.2945    0.1860    5.4869    1.6641
-#> 457:    93.7487   -6.0668   -0.1514    2.2099   -0.9813    4.2613    4.0277    0.3919    0.2946    0.1860    5.4866    1.6640
-#> 458:    93.7484   -6.0667   -0.1515    2.2097   -0.9812    4.2586    4.0263    0.3918    0.2947    0.1859    5.4854    1.6639
-#> 459:    93.7468   -6.0661   -0.1517    2.2095   -0.9812    4.2565    4.0225    0.3917    0.2948    0.1858    5.4853    1.6639
-#> 460:    93.7458   -6.0652   -0.1518    2.2093   -0.9812    4.2548    4.0171    0.3916    0.2950    0.1858    5.4843    1.6638
-#> 461:    93.7435   -6.0645   -0.1519    2.2091   -0.9811    4.2554    4.0121    0.3914    0.2951    0.1858    5.4843    1.6637
-#> 462:    93.7421   -6.0637   -0.1521    2.2089   -0.9811    4.2509    4.0079    0.3913    0.2953    0.1857    5.4840    1.6638
-#> 463:    93.7406   -6.0630   -0.1522    2.2088   -0.9810    4.2534    4.0036    0.3912    0.2955    0.1857    5.4834    1.6640
-#> 464:    93.7406   -6.0622   -0.1524    2.2086   -0.9810    4.2548    3.9986    0.3911    0.2956    0.1857    5.4828    1.6639
-#> 465:    93.7404   -6.0617   -0.1525    2.2084   -0.9810    4.2511    3.9955    0.3910    0.2958    0.1857    5.4828    1.6638
-#> 466:    93.7414   -6.0610   -0.1527    2.2080   -0.9809    4.2468    3.9918    0.3910    0.2959    0.1857    5.4812    1.6640
-#> 467:    93.7419   -6.0606   -0.1529    2.2077   -0.9810    4.2446    3.9885    0.3909    0.2960    0.1858    5.4799    1.6642
-#> 468:    93.7427   -6.0604   -0.1531    2.2074   -0.9809    4.2473    3.9872    0.3909    0.2961    0.1858    5.4790    1.6643
-#> 469:    93.7435   -6.0608   -0.1532    2.2073   -0.9810    4.2457    3.9891    0.3907    0.2963    0.1858    5.4789    1.6641
-#> 470:    93.7442   -6.0611   -0.1533    2.2071   -0.9811    4.2443    3.9895    0.3905    0.2965    0.1858    5.4785    1.6640
-#> 471:    93.7443   -6.0618   -0.1534    2.2070   -0.9812    4.2415    3.9932    0.3903    0.2967    0.1858    5.4773    1.6639
-#> 472:    93.7433   -6.0624   -0.1535    2.2069   -0.9812    4.2414    3.9958    0.3901    0.2969    0.1858    5.4765    1.6637
-#> 473:    93.7421   -6.0621   -0.1536    2.2067   -0.9811    4.2330    3.9962    0.3899    0.2970    0.1858    5.4762    1.6637
-#> 474:    93.7415   -6.0621   -0.1537    2.2066   -0.9812    4.2263    3.9968    0.3897    0.2972    0.1858    5.4755    1.6638
-#> 475:    93.7396   -6.0621   -0.1538    2.2066   -0.9812    4.2261    3.9956    0.3895    0.2973    0.1859    5.4751    1.6637
-#> 476:    93.7373   -6.0626   -0.1539    2.2065   -0.9811    4.2265    3.9976    0.3893    0.2975    0.1859    5.4743    1.6634
-#> 477:    93.7357   -6.0623   -0.1540    2.2063   -0.9811    4.2222    3.9953    0.3891    0.2976    0.1859    5.4741    1.6635
-#> 478:    93.7345   -6.0620   -0.1541    2.2062   -0.9811    4.2165    3.9939    0.3889    0.2978    0.1860    5.4745    1.6638
-#> 479:    93.7341   -6.0615   -0.1542    2.2062   -0.9812    4.2122    3.9916    0.3887    0.2979    0.1860    5.4751    1.6637
-#> 480:    93.7338   -6.0619   -0.1543    2.2061   -0.9812    4.2084    3.9932    0.3885    0.2980    0.1860    5.4753    1.6635
-#> 481:    93.7336   -6.0618   -0.1544    2.2060   -0.9812    4.2066    3.9945    0.3883    0.2981    0.1860    5.4748    1.6637
-#> 482:    93.7340   -6.0622   -0.1545    2.2058   -0.9812    4.2069    3.9969    0.3882    0.2983    0.1860    5.4741    1.6636
-#> 483:    93.7328   -6.0627   -0.1547    2.2057   -0.9813    4.2062    3.9992    0.3879    0.2985    0.1861    5.4739    1.6636
-#> 484:    93.7323   -6.0629   -0.1547    2.2056   -0.9813    4.2075    3.9995    0.3877    0.2987    0.1861    5.4730    1.6638
-#> 485:    93.7326   -6.0634   -0.1548    2.2055   -0.9814    4.2045    4.0013    0.3875    0.2989    0.1862    5.4727    1.6637
-#> 486:    93.7320   -6.0632   -0.1549    2.2055   -0.9814    4.2084    3.9989    0.3872    0.2991    0.1863    5.4718    1.6635
-#> 487:    93.7321   -6.0625   -0.1549    2.2054   -0.9814    4.2105    3.9949    0.3870    0.2993    0.1864    5.4712    1.6634
-#> 488:    93.7326   -6.0623   -0.1550    2.2054   -0.9814    4.2104    3.9935    0.3868    0.2996    0.1865    5.4721    1.6635
-#> 489:    93.7342   -6.0615   -0.1551    2.2054   -0.9815    4.2103    3.9893    0.3866    0.2998    0.1866    5.4725    1.6635
-#> 490:    93.7360   -6.0610   -0.1551    2.2053   -0.9815    4.2116    3.9857    0.3864    0.3001    0.1867    5.4730    1.6636
-#> 491:    93.7374   -6.0601   -0.1551    2.2052   -0.9815    4.2128    3.9804    0.3862    0.3003    0.1868    5.4722    1.6638
-#> 492:    93.7386   -6.0597   -0.1552    2.2050   -0.9816    4.2171    3.9774    0.3861    0.3006    0.1869    5.4714    1.6642
-#> 493:    93.7399   -6.0597   -0.1553    2.2049   -0.9816    4.2262    3.9766    0.3859    0.3008    0.1869    5.4712    1.6643
-#> 494:    93.7404   -6.0596   -0.1553    2.2047   -0.9816    4.2347    3.9746    0.3857    0.3011    0.1870    5.4711    1.6646
-#> 495:    93.7406   -6.0590   -0.1554    2.2046   -0.9817    4.2395    3.9711    0.3855    0.3014    0.1871    5.4705    1.6650
-#> 496:    93.7416   -6.0582   -0.1554    2.2045   -0.9817    4.2456    3.9660    0.3853    0.3017    0.1871    5.4707    1.6656
-#> 497:    93.7433   -6.0575   -0.1555    2.2044   -0.9818    4.2511    3.9631    0.3851    0.3020    0.1871    5.4714    1.6658
-#> 498:    93.7444   -6.0574   -0.1556    2.2042   -0.9817    4.2516    3.9632    0.3848    0.3023    0.1871    5.4721    1.6660
-#> 499:    93.7457   -6.0576   -0.1557    2.2041   -0.9817    4.2518    3.9660    0.3846    0.3025    0.1871    5.4728    1.6660
-#> 500:    93.7469   -6.0586   -0.1557    2.2040   -0.9817    4.2481    3.9757    0.3844    0.3028    0.1871    5.4738    1.6661
-#> Calculating covariance matrix
-#> 
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> Needed Covariates:
-#> [1] "CMT"
-#> Calculating residuals/tables
-#> done
-f_nlmixr_fomc_sfo_focei_obs <- nlmixr(f_mmkin_obs["FOMC-SFO", ], est = "focei")
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → calculate jacobian
-#> 
-#> → calculate sensitivities
-#> 
-#> → calculate ∂(f)/∂(η)
-#> 
-#> → calculate ∂(R²)/∂(η)
-#> 
-#> → finding duplicate expressions in inner model...
-#> 
-#> → optimizing duplicate expressions in inner model...
-#> 
-#> → finding duplicate expressions in EBE model...
-#> 
-#> → optimizing duplicate expressions in EBE model...
-#> 
-#> → compiling inner model...
-#>  
-#> ✔ done
-#> → finding duplicate expressions in FD model...
-#> 
-#> → optimizing duplicate expressions in FD model...
-#> 
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> → compiling events FD model...
-#>  
-#> ✔ done
-#> Needed Covariates:
-#> [1] "CMT"
-#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> |    #| Objective Fun |  parent_0 |  log_k_A1 |f_parent_qlogis | log_alpha |
-#> |.....................|  log_beta |sigma_parent |  sigma_A1 |        o1 |
-#> |.....................|        o2 |        o3 |        o4 |        o5 |
-#> |    1|     468.02617 |     1.000 |    -1.000 |   -0.9113 |   -0.8954 |
-#> |.....................|   -0.8491 |   -0.8511 |   -0.8672 |   -0.8762 |
-#> |.....................|   -0.8737 |   -0.8674 |   -0.8694 |   -0.8687 |
-#> |    U|     468.02617 |     94.00 |    -5.400 |   -0.9900 |   -0.2000 |
-#> |.....................|     2.100 |     2.000 |     1.200 |    0.7536 |
-#> |.....................|    0.8758 |     1.189 |     1.093 |     1.127 |
-#> |    X|     468.02617 |     94.00 |  0.004517 |    0.2709 |    0.8187 |
-#> |.....................|     8.166 |     2.000 |     1.200 |    0.7536 |
-#> |.....................|    0.8758 |     1.189 |     1.093 |     1.127 |
-#> |    G|    Gill Diff. |     49.30 |     2.016 |   -0.2473 |   -0.3737 |
-#> |.....................|    -1.227 |    -27.89 |    -10.29 |     8.753 |
-#> |.....................|     11.17 |    -12.52 |    -9.819 |    -8.910 |
-#> |    2|     4021.4865 |    0.2059 |    -1.032 |   -0.9073 |   -0.8894 |
-#> |.....................|   -0.8293 |   -0.4019 |   -0.7014 |    -1.017 |
-#> |.....................|    -1.054 |   -0.6658 |   -0.7112 |   -0.7251 |
-#> |    U|     4021.4865 |     19.35 |    -5.432 |   -0.9861 |   -0.1940 |
-#> |.....................|     2.120 |     2.449 |     1.299 |    0.6474 |
-#> |.....................|    0.7182 |     1.429 |     1.266 |     1.289 |
-#> |    X|     4021.4865 |     19.35 |  0.004372 |    0.2717 |    0.8237 |
-#> |.....................|     8.329 |     2.449 |     1.299 |    0.6474 |
-#> |.....................|    0.7182 |     1.429 |     1.266 |     1.289 |
-#> |    3|     518.20369 |    0.9206 |    -1.003 |   -0.9109 |   -0.8948 |
-#> |.....................|   -0.8471 |   -0.8062 |   -0.8506 |   -0.8903 |
-#> |.....................|   -0.8917 |   -0.8473 |   -0.8535 |   -0.8543 |
-#> |    U|     518.20369 |     86.53 |    -5.403 |   -0.9896 |   -0.1994 |
-#> |.....................|     2.102 |     2.045 |     1.210 |    0.7430 |
-#> |.....................|    0.8600 |     1.213 |     1.111 |     1.143 |
-#> |    X|     518.20369 |     86.53 |  0.004502 |    0.2710 |    0.8192 |
-#> |.....................|     8.182 |     2.045 |     1.210 |    0.7430 |
-#> |.....................|    0.8600 |     1.213 |     1.111 |     1.143 |
-#> |    4|     467.99742 |    0.9921 |    -1.000 |   -0.9112 |   -0.8953 |
-#> |.....................|   -0.8489 |   -0.8466 |   -0.8655 |   -0.8776 |
-#> |.....................|   -0.8755 |   -0.8654 |   -0.8678 |   -0.8672 |
-#> |    U|     467.99742 |     93.25 |    -5.400 |   -0.9900 |   -0.1999 |
-#> |.....................|     2.100 |     2.004 |     1.201 |    0.7526 |
-#> |.....................|    0.8742 |     1.192 |     1.095 |     1.129 |
-#> |    X|     467.99742 |     93.25 |  0.004515 |    0.2709 |    0.8188 |
-#> |.....................|     8.168 |     2.004 |     1.201 |    0.7526 |
-#> |.....................|    0.8742 |     1.192 |     1.095 |     1.129 |
-#> |    F| Forward Diff. |    -98.28 |     1.929 |   -0.4044 |   -0.4503 |
-#> |.....................|    -1.484 |    -29.27 |    -9.987 |     8.922 |
-#> |.....................|     9.417 |    -11.79 |    -9.521 |    -8.343 |
-#> |    5|     467.67344 |    0.9967 |    -1.000 |   -0.9112 |   -0.8953 |
-#> |.....................|   -0.8488 |   -0.8452 |   -0.8651 |   -0.8780 |
-#> |.....................|   -0.8760 |   -0.8648 |   -0.8673 |   -0.8668 |
-#> |    U|     467.67344 |     93.69 |    -5.400 |   -0.9899 |   -0.1999 |
-#> |.....................|     2.100 |     2.006 |     1.201 |    0.7523 |
-#> |.....................|    0.8738 |     1.192 |     1.095 |     1.129 |
-#> |    X|     467.67344 |     93.69 |  0.004515 |    0.2709 |    0.8188 |
-#> |.....................|     8.168 |     2.006 |     1.201 |    0.7523 |
-#> |.....................|    0.8738 |     1.192 |     1.095 |     1.129 |
-#> |    F| Forward Diff. |    -11.92 |     1.963 |   -0.3242 |   -0.4184 |
-#> |.....................|    -1.350 |    -28.16 |    -10.02 |     8.541 |
-#> |.....................|     8.305 |    -11.80 |    -9.512 |    -8.408 |
-#> |    6|     467.50396 |    0.9983 |    -1.001 |   -0.9112 |   -0.8952 |
-#> |.....................|   -0.8487 |   -0.8416 |   -0.8638 |   -0.8791 |
-#> |.....................|   -0.8771 |   -0.8633 |   -0.8661 |   -0.8658 |
-#> |    U|     467.50396 |     93.84 |    -5.401 |   -0.9899 |   -0.1999 |
-#> |.....................|     2.100 |     2.010 |     1.202 |    0.7514 |
-#> |.....................|    0.8729 |     1.194 |     1.097 |     1.130 |
-#> |    X|     467.50396 |     93.84 |  0.004514 |    0.2709 |    0.8188 |
-#> |.....................|     8.170 |     2.010 |     1.202 |    0.7514 |
-#> |.....................|    0.8729 |     1.194 |     1.097 |     1.130 |
-#> |    7|     467.27231 |     1.003 |    -1.001 |   -0.9110 |   -0.8951 |
-#> |.....................|   -0.8481 |   -0.8306 |   -0.8599 |   -0.8825 |
-#> |.....................|   -0.8803 |   -0.8587 |   -0.8624 |   -0.8625 |
-#> |    U|     467.27231 |     94.27 |    -5.401 |   -0.9898 |   -0.1997 |
-#> |.....................|     2.101 |     2.021 |     1.204 |    0.7489 |
-#> |.....................|    0.8700 |     1.200 |     1.101 |     1.134 |
-#> |    X|     467.27231 |     94.27 |  0.004510 |    0.2710 |    0.8190 |
-#> |.....................|     8.174 |     2.021 |     1.204 |    0.7489 |
-#> |.....................|    0.8700 |     1.200 |     1.101 |     1.134 |
-#> |    F| Forward Diff. |     101.6 |     1.991 |   -0.1997 |   -0.3688 |
-#> |.....................|    -1.177 |    -25.72 |    -9.853 |     9.249 |
-#> |.....................|     8.335 |    -11.58 |    -9.288 |    -8.277 |
-#> |    8|     466.36087 |    0.9961 |    -1.002 |   -0.9109 |   -0.8949 |
-#> |.....................|   -0.8474 |   -0.8165 |   -0.8547 |   -0.8873 |
-#> |.....................|   -0.8853 |   -0.8526 |   -0.8575 |   -0.8582 |
-#> |    U|     466.36087 |     93.63 |    -5.402 |   -0.9896 |   -0.1995 |
-#> |.....................|     2.102 |     2.035 |     1.207 |    0.7453 |
-#> |.....................|    0.8657 |     1.207 |     1.106 |     1.139 |
-#> |    X|     466.36087 |     93.63 |  0.004506 |    0.2710 |    0.8191 |
-#> |.....................|     8.180 |     2.035 |     1.207 |    0.7453 |
-#> |.....................|    0.8657 |     1.207 |     1.106 |     1.139 |
-#> |    F| Forward Diff. |    -21.78 |     1.909 |   -0.3215 |   -0.4291 |
-#> |.....................|    -1.401 |    -25.38 |    -9.315 |     7.655 |
-#> |.....................|     10.17 |    -11.26 |    -9.035 |    -7.894 |
-#> |    9|     465.79764 |     1.000 |    -1.004 |   -0.9107 |   -0.8946 |
-#> |.....................|   -0.8467 |   -0.8024 |   -0.8495 |   -0.8920 |
-#> |.....................|   -0.8917 |   -0.8462 |   -0.8524 |   -0.8537 |
-#> |    U|     465.79764 |     94.04 |    -5.404 |   -0.9895 |   -0.1993 |
-#> |.....................|     2.102 |     2.049 |     1.211 |    0.7417 |
-#> |.....................|    0.8600 |     1.214 |     1.112 |     1.144 |
-#> |    X|     465.79764 |     94.04 |  0.004501 |    0.2710 |    0.8193 |
-#> |.....................|     8.186 |     2.049 |     1.211 |    0.7417 |
-#> |.....................|    0.8600 |     1.214 |     1.112 |     1.144 |
-#> |    F| Forward Diff. |     54.81 |     1.910 |   -0.2489 |   -0.4009 |
-#> |.....................|    -1.285 |    -22.17 |    -8.389 |     8.020 |
-#> |.....................|     7.340 |    -11.02 |    -8.786 |    -7.720 |
-#> |   10|     465.18897 |    0.9945 |    -1.005 |   -0.9105 |   -0.8943 |
-#> |.....................|   -0.8457 |   -0.7893 |   -0.8445 |   -0.8971 |
-#> |.....................|   -0.8975 |   -0.8390 |   -0.8467 |   -0.8487 |
-#> |    U|     465.18897 |     93.48 |    -5.405 |   -0.9893 |   -0.1990 |
-#> |.....................|     2.103 |     2.062 |     1.214 |    0.7379 |
-#> |.....................|    0.8549 |     1.223 |     1.118 |     1.149 |
-#> |    X|     465.18897 |     93.48 |  0.004495 |    0.2711 |    0.8196 |
-#> |.....................|     8.194 |     2.062 |     1.214 |    0.7379 |
-#> |.....................|    0.8549 |     1.223 |     1.118 |     1.149 |
-#> |    F| Forward Diff. |    -47.52 |     1.834 |   -0.3684 |   -0.4503 |
-#> |.....................|    -1.489 |    -22.39 |    -7.996 |     7.294 |
-#> |.....................|     9.249 |    -10.90 |    -8.741 |    -7.575 |
-#> |   11|     464.56229 |    0.9983 |    -1.006 |   -0.9102 |   -0.8940 |
-#> |.....................|   -0.8445 |   -0.7772 |   -0.8401 |   -0.9030 |
-#> |.....................|   -0.9029 |   -0.8305 |   -0.8400 |   -0.8430 |
-#> |    U|     464.56229 |     93.84 |    -5.406 |   -0.9890 |   -0.1986 |
-#> |.....................|     2.105 |     2.074 |     1.216 |    0.7334 |
-#> |.....................|    0.8503 |     1.233 |     1.125 |     1.156 |
-#> |    X|     464.56229 |     93.84 |  0.004488 |    0.2711 |    0.8199 |
-#> |.....................|     8.204 |     2.074 |     1.216 |    0.7334 |
-#> |.....................|    0.8503 |     1.233 |     1.125 |     1.156 |
-#> |   12|     463.71730 |    0.9982 |    -1.009 |   -0.9098 |   -0.8933 |
-#> |.....................|   -0.8424 |   -0.7583 |   -0.8332 |   -0.9128 |
-#> |.....................|   -0.9112 |   -0.8167 |   -0.8291 |   -0.8337 |
-#> |    U|      463.7173 |     93.83 |    -5.409 |   -0.9885 |   -0.1980 |
-#> |.....................|     2.107 |     2.093 |     1.220 |    0.7260 |
-#> |.....................|    0.8430 |     1.249 |     1.137 |     1.166 |
-#> |    X|      463.7173 |     93.83 |  0.004478 |    0.2712 |    0.8204 |
-#> |.....................|     8.221 |     2.093 |     1.220 |    0.7260 |
-#> |.....................|    0.8430 |     1.249 |     1.137 |     1.166 |
-#> |   13|     461.03699 |    0.9978 |    -1.018 |   -0.9080 |   -0.8909 |
-#> |.....................|   -0.8343 |   -0.6839 |   -0.8059 |   -0.9516 |
-#> |.....................|   -0.9441 |   -0.7622 |   -0.7862 |   -0.7969 |
-#> |    U|     461.03699 |     93.79 |    -5.418 |   -0.9868 |   -0.1955 |
-#> |.....................|     2.115 |     2.167 |     1.237 |    0.6968 |
-#> |.....................|    0.8141 |     1.314 |     1.184 |     1.208 |
-#> |    X|     461.03699 |     93.79 |  0.004435 |    0.2716 |    0.8224 |
-#> |.....................|     8.288 |     2.167 |     1.237 |    0.6968 |
-#> |.....................|    0.8141 |     1.314 |     1.184 |     1.208 |
-#> |   14|     458.83693 |    0.9972 |    -1.033 |   -0.9052 |   -0.8871 |
-#> |.....................|   -0.8218 |   -0.5692 |   -0.7639 |    -1.011 |
-#> |.....................|   -0.9948 |   -0.6782 |   -0.7201 |   -0.7403 |
-#> |    U|     458.83693 |     93.74 |    -5.433 |   -0.9840 |   -0.1917 |
-#> |.....................|     2.127 |     2.282 |     1.262 |    0.6519 |
-#> |.....................|    0.7697 |     1.414 |     1.256 |     1.272 |
-#> |    X|     458.83693 |     93.74 |  0.004371 |    0.2721 |    0.8255 |
-#> |.....................|     8.393 |     2.282 |     1.262 |    0.6519 |
-#> |.....................|    0.7697 |     1.414 |     1.256 |     1.272 |
-#> |    F| Forward Diff. |   0.05416 |     1.397 |   -0.2200 |   -0.5344 |
-#> |.....................|    -1.585 |    -3.387 |    -1.306 |   -0.2250 |
-#> |.....................|     1.392 |    -3.452 |    -2.065 |    -1.405 |
-#> |   15|     459.30045 |    0.9957 |    -1.166 |   -0.8845 |   -0.8313 |
-#> |.....................|   -0.6584 |   -0.5528 |   -0.7505 |   -0.8569 |
-#> |.....................|    -1.017 |   -0.4560 |   -0.6245 |   -0.7036 |
-#> |    U|     459.30045 |     93.60 |    -5.566 |   -0.9635 |   -0.1360 |
-#> |.....................|     2.291 |     2.298 |     1.270 |    0.7682 |
-#> |.....................|    0.7505 |     1.678 |     1.361 |     1.313 |
-#> |    X|     459.30045 |     93.60 |  0.003827 |    0.2762 |    0.8729 |
-#> |.....................|     9.881 |     2.298 |     1.270 |    0.7682 |
-#> |.....................|    0.7505 |     1.678 |     1.361 |     1.313 |
-#> |   16|     458.36319 |    0.9960 |    -1.071 |   -0.8992 |   -0.8719 |
-#> |.....................|   -0.7770 |   -0.5045 |   -0.7383 |   -0.9927 |
-#> |.....................|    -1.023 |   -0.5931 |   -0.6727 |   -0.7107 |
-#> |    U|     458.36319 |     93.63 |    -5.471 |   -0.9780 |   -0.1766 |
-#> |.....................|     2.172 |     2.347 |     1.277 |    0.6658 |
-#> |.....................|    0.7452 |     1.515 |     1.308 |     1.305 |
-#> |    X|     458.36319 |     93.63 |  0.004206 |    0.2733 |    0.8381 |
-#> |.....................|     8.777 |     2.347 |     1.277 |    0.6658 |
-#> |.....................|    0.7452 |     1.515 |     1.308 |     1.305 |
-#> |    F| Forward Diff. |    -12.30 |     1.214 |   0.06343 |   -0.2616 |
-#> |.....................|   -0.6069 |   0.08029 |    0.4273 |   0.07297 |
-#> |.....................|   -0.3937 |    0.3470 |    0.5201 |   0.09241 |
-#> |   17|     458.37724 |    0.9977 |    -1.183 |   -0.9046 |   -0.8476 |
-#> |.....................|   -0.7196 |   -0.4765 |   -0.7567 |    -1.014 |
-#> |.....................|   -0.9850 |   -0.5955 |   -0.6985 |   -0.7030 |
-#> |    U|     458.37724 |     93.79 |    -5.583 |   -0.9834 |   -0.1522 |
-#> |.....................|     2.229 |     2.375 |     1.266 |    0.6497 |
-#> |.....................|    0.7783 |     1.513 |     1.280 |     1.314 |
-#> |    X|     458.37724 |     93.79 |  0.003762 |    0.2722 |    0.8588 |
-#> |.....................|     9.295 |     2.375 |     1.266 |    0.6497 |
-#> |.....................|    0.7783 |     1.513 |     1.280 |     1.314 |
-#> |   18|     458.32800 |    0.9976 |    -1.124 |   -0.9017 |   -0.8605 |
-#> |.....................|   -0.7499 |   -0.4913 |   -0.7470 |    -1.003 |
-#> |.....................|    -1.005 |   -0.5943 |   -0.6849 |   -0.7071 |
-#> |    U|       458.328 |     93.78 |    -5.524 |   -0.9806 |   -0.1651 |
-#> |.....................|     2.199 |     2.360 |     1.272 |    0.6583 |
-#> |.....................|    0.7608 |     1.514 |     1.295 |     1.309 |
-#> |    X|       458.328 |     93.78 |  0.003990 |    0.2728 |    0.8478 |
-#> |.....................|     9.017 |     2.360 |     1.272 |    0.6583 |
-#> |.....................|    0.7608 |     1.514 |     1.295 |     1.309 |
-#> |    F| Forward Diff. |     9.757 |     1.093 |  -0.06310 |   0.02237 |
-#> |.....................|   0.09811 |    0.3115 |   -0.3381 |   -0.2098 |
-#> |.....................|    0.8196 |    0.7052 |   0.04425 |    0.2610 |
-#> |   19|     458.25889 |    0.9968 |    -1.183 |   -0.9011 |   -0.8543 |
-#> |.....................|   -0.7363 |   -0.4871 |   -0.7422 |    -1.003 |
-#> |.....................|    -1.023 |   -0.6115 |   -0.6911 |   -0.7106 |
-#> |    U|     458.25889 |     93.70 |    -5.583 |   -0.9799 |   -0.1589 |
-#> |.....................|     2.213 |     2.364 |     1.275 |    0.6583 |
-#> |.....................|    0.7450 |     1.494 |     1.288 |     1.305 |
-#> |    X|     458.25889 |     93.70 |  0.003760 |    0.2729 |    0.8531 |
-#> |.....................|     9.141 |     2.364 |     1.275 |    0.6583 |
-#> |.....................|    0.7450 |     1.494 |     1.288 |     1.305 |
-#> |    F| Forward Diff. |   -0.6125 |    0.8824 |  -0.01905 |    0.1697 |
-#> |.....................|    0.4368 |    0.4743 |   0.05191 |   -0.6440 |
-#> |.....................|   -0.4868 |   -0.9136 |   -0.3225 |  -0.06220 |
-#> |   20|     458.18570 |    0.9978 |    -1.246 |   -0.9006 |   -0.8585 |
-#> |.....................|   -0.7495 |   -0.4978 |   -0.7385 |   -0.9895 |
-#> |.....................|    -1.024 |   -0.6046 |   -0.6874 |   -0.7124 |
-#> |    U|      458.1857 |     93.79 |    -5.646 |   -0.9794 |   -0.1632 |
-#> |.....................|     2.200 |     2.353 |     1.277 |    0.6683 |
-#> |.....................|    0.7440 |     1.502 |     1.292 |     1.303 |
-#> |    X|      458.1857 |     93.79 |  0.003532 |    0.2730 |    0.8495 |
-#> |.....................|     9.022 |     2.353 |     1.277 |    0.6683 |
-#> |.....................|    0.7440 |     1.502 |     1.292 |     1.303 |
-#> |   21|     458.13464 |    0.9963 |    -1.435 |   -0.8992 |   -0.8705 |
-#> |.....................|   -0.7875 |   -0.5278 |   -0.7264 |   -0.9531 |
-#> |.....................|    -1.031 |   -0.5901 |   -0.6784 |   -0.7184 |
-#> |    U|     458.13464 |     93.65 |    -5.835 |   -0.9781 |   -0.1751 |
-#> |.....................|     2.162 |     2.323 |     1.284 |    0.6957 |
-#> |.....................|    0.7378 |     1.519 |     1.302 |     1.296 |
-#> |    X|     458.13464 |     93.65 |  0.002922 |    0.2733 |    0.8394 |
-#> |.....................|     8.685 |     2.323 |     1.284 |    0.6957 |
-#> |.....................|    0.7378 |     1.519 |     1.302 |     1.296 |
-#> |    F| Forward Diff. |    -15.15 |    0.2290 |    0.2476 |   -0.1455 |
-#> |.....................|   -0.7111 |    -1.138 |    0.8895 |     1.880 |
-#> |.....................|    -1.837 |    0.2029 |    0.3485 |   -0.6531 |
-#> |   22|     458.67841 |    0.9992 |    -1.651 |   -0.9027 |   -0.9245 |
-#> |.....................|   -0.8733 |   -0.5209 |   -0.7232 |    -1.036 |
-#> |.....................|    -1.001 |   -0.6164 |   -0.6125 |   -0.6771 |
-#> |    U|     458.67841 |     93.92 |    -6.051 |   -0.9815 |   -0.2291 |
-#> |.....................|     2.076 |     2.330 |     1.286 |    0.6333 |
-#> |.....................|    0.7647 |     1.488 |     1.374 |     1.343 |
-#> |    X|     458.67841 |     93.92 |  0.002355 |    0.2726 |    0.7952 |
-#> |.....................|     7.971 |     2.330 |     1.286 |    0.6333 |
-#> |.....................|    0.7647 |     1.488 |     1.374 |     1.343 |
-#> |   23|     458.25487 |     1.002 |    -1.469 |   -0.8998 |   -0.8789 |
-#> |.....................|   -0.8006 |   -0.5263 |   -0.7262 |   -0.9666 |
-#> |.....................|    -1.026 |   -0.5942 |   -0.6683 |   -0.7117 |
-#> |    U|     458.25487 |     94.17 |    -5.869 |   -0.9787 |   -0.1835 |
-#> |.....................|     2.148 |     2.325 |     1.285 |    0.6855 |
-#> |.....................|    0.7425 |     1.514 |     1.313 |     1.304 |
-#> |    X|     458.25487 |     94.17 |  0.002825 |    0.2732 |    0.8324 |
-#> |.....................|     8.572 |     2.325 |     1.285 |    0.6855 |
-#> |.....................|    0.7425 |     1.514 |     1.313 |     1.304 |
-#> |   24|     458.28425 |     1.002 |    -1.442 |   -0.8994 |   -0.8721 |
-#> |.....................|   -0.7899 |   -0.5271 |   -0.7267 |   -0.9564 |
-#> |.....................|    -1.030 |   -0.5910 |   -0.6765 |   -0.7168 |
-#> |    U|     458.28425 |     94.21 |    -5.842 |   -0.9783 |   -0.1768 |
-#> |.....................|     2.159 |     2.324 |     1.284 |    0.6932 |
-#> |.....................|    0.7392 |     1.518 |     1.304 |     1.298 |
-#> |    X|     458.28425 |     94.21 |  0.002902 |    0.2732 |    0.8380 |
-#> |.....................|     8.664 |     2.324 |     1.284 |    0.6932 |
-#> |.....................|    0.7392 |     1.518 |     1.304 |     1.298 |
-#> |   25|     458.13208 |    0.9983 |    -1.435 |   -0.8993 |   -0.8705 |
-#> |.....................|   -0.7874 |   -0.5276 |   -0.7266 |   -0.9533 |
-#> |.....................|    -1.031 |   -0.5901 |   -0.6785 |   -0.7183 |
-#> |    U|     458.13208 |     93.84 |    -5.835 |   -0.9781 |   -0.1751 |
-#> |.....................|     2.162 |     2.323 |     1.284 |    0.6955 |
-#> |.....................|    0.7380 |     1.519 |     1.302 |     1.296 |
-#> |    X|     458.13208 |     93.84 |  0.002922 |    0.2733 |    0.8394 |
-#> |.....................|     8.686 |     2.323 |     1.284 |    0.6955 |
-#> |.....................|    0.7380 |     1.519 |     1.302 |     1.296 |
-#> |    F| Forward Diff. |     13.75 |    0.2391 |    0.3431 |   -0.1129 |
-#> |.....................|   -0.6079 |    -1.684 |    0.2301 |     1.587 |
-#> |.....................|    0.9924 |   -0.4675 |    0.3927 |   -0.7567 |
-#> |   26|     458.12484 |    0.9973 |    -1.435 |   -0.8993 |   -0.8705 |
-#> |.....................|   -0.7874 |   -0.5275 |   -0.7266 |   -0.9535 |
-#> |.....................|    -1.031 |   -0.5900 |   -0.6785 |   -0.7182 |
-#> |    U|     458.12484 |     93.75 |    -5.835 |   -0.9782 |   -0.1751 |
-#> |.....................|     2.162 |     2.324 |     1.284 |    0.6954 |
-#> |.....................|    0.7379 |     1.519 |     1.302 |     1.297 |
-#> |    X|     458.12484 |     93.75 |  0.002922 |    0.2733 |    0.8394 |
-#> |.....................|     8.686 |     2.324 |     1.284 |    0.6954 |
-#> |.....................|    0.7379 |     1.519 |     1.302 |     1.297 |
-#> |    F| Forward Diff. |   -0.4576 |    0.2336 |    0.2904 |   -0.1274 |
-#> |.....................|   -0.6585 |    -1.014 |    0.9040 |     1.932 |
-#> |.....................|    -1.695 |    0.2950 |    0.3980 |   -0.7211 |
-#> |   27|     458.12349 |    0.9975 |    -1.436 |   -0.8994 |   -0.8704 |
-#> |.....................|   -0.7872 |   -0.5272 |   -0.7269 |   -0.9542 |
-#> |.....................|    -1.031 |   -0.5901 |   -0.6787 |   -0.7180 |
-#> |    U|     458.12349 |     93.76 |    -5.836 |   -0.9783 |   -0.1751 |
-#> |.....................|     2.162 |     2.324 |     1.284 |    0.6949 |
-#> |.....................|    0.7384 |     1.519 |     1.302 |     1.297 |
-#> |    X|     458.12349 |     93.76 |  0.002922 |    0.2732 |    0.8394 |
-#> |.....................|     8.688 |     2.324 |     1.284 |    0.6949 |
-#> |.....................|    0.7384 |     1.519 |     1.302 |     1.297 |
-#> |    F| Forward Diff. |     1.734 |    0.2328 |    0.2907 |   -0.1244 |
-#> |.....................|   -0.6480 |   -0.5259 |     1.203 |     2.086 |
-#> |.....................|    -1.687 |    0.2714 |    0.3976 |   -0.7167 |
-#> |   28|     458.12069 |    0.9972 |    -1.436 |   -0.8995 |   -0.8704 |
-#> |.....................|   -0.7868 |   -0.5270 |   -0.7278 |   -0.9557 |
-#> |.....................|    -1.030 |   -0.5902 |   -0.6785 |   -0.7174 |
-#> |    U|     458.12069 |     93.74 |    -5.836 |   -0.9784 |   -0.1750 |
-#> |.....................|     2.162 |     2.324 |     1.284 |    0.6937 |
-#> |.....................|    0.7392 |     1.519 |     1.302 |     1.297 |
-#> |    X|     458.12069 |     93.74 |  0.002921 |    0.2732 |    0.8394 |
-#> |.....................|     8.691 |     2.324 |     1.284 |    0.6937 |
-#> |.....................|    0.7392 |     1.519 |     1.302 |     1.297 |
-#> |    F| Forward Diff. |    -1.995 |    0.2265 |    0.2648 |   -0.1319 |
-#> |.....................|   -0.6577 |    -1.056 |    0.5532 |     1.629 |
-#> |.....................|   -0.4851 |    0.2582 |    0.3806 |   -0.6784 |
-#> |   29|     458.12793 |    0.9986 |    -1.436 |   -0.8997 |   -0.8703 |
-#> |.....................|   -0.7863 |   -0.5263 |   -0.7282 |   -0.9568 |
-#> |.....................|    -1.029 |   -0.5904 |   -0.6788 |   -0.7169 |
-#> |    U|     458.12793 |     93.87 |    -5.836 |   -0.9785 |   -0.1749 |
-#> |.....................|     2.163 |     2.325 |     1.283 |    0.6929 |
-#> |.....................|    0.7395 |     1.519 |     1.302 |     1.298 |
-#> |    X|     458.12793 |     93.87 |  0.002920 |    0.2732 |    0.8395 |
-#> |.....................|     8.695 |     2.325 |     1.283 |    0.6929 |
-#> |.....................|    0.7395 |     1.519 |     1.302 |     1.298 |
-#> |   30|     458.12002 |    0.9975 |    -1.436 |   -0.8996 |   -0.8704 |
-#> |.....................|   -0.7866 |   -0.5269 |   -0.7279 |   -0.9559 |
-#> |.....................|    -1.030 |   -0.5903 |   -0.6786 |   -0.7173 |
-#> |    U|     458.12002 |     93.77 |    -5.836 |   -0.9784 |   -0.1750 |
-#> |.....................|     2.162 |     2.324 |     1.284 |    0.6935 |
-#> |.....................|    0.7392 |     1.519 |     1.302 |     1.298 |
-#> |    X|     458.12002 |     93.77 |  0.002921 |    0.2732 |    0.8395 |
-#> |.....................|     8.692 |     2.324 |     1.284 |    0.6935 |
-#> |.....................|    0.7392 |     1.519 |     1.302 |     1.298 |
-#> |    F| Forward Diff. |     2.647 |    0.2293 |    0.2815 |   -0.1267 |
-#> |.....................|   -0.6372 |   -0.9129 |    0.8290 |     1.823 |
-#> |.....................|    -1.624 |    0.2659 |    0.4184 |   -0.6478 |
-#> |   31|     458.11922 |    0.9973 |    -1.436 |   -0.8996 |   -0.8704 |
-#> |.....................|   -0.7866 |   -0.5268 |   -0.7280 |   -0.9563 |
-#> |.....................|    -1.029 |   -0.5903 |   -0.6786 |   -0.7171 |
-#> |    U|     458.11922 |     93.74 |    -5.836 |   -0.9784 |   -0.1750 |
-#> |.....................|     2.163 |     2.324 |     1.284 |    0.6933 |
-#> |.....................|    0.7394 |     1.519 |     1.302 |     1.298 |
-#> |    X|     458.11922 |     93.74 |  0.002920 |    0.2732 |    0.8395 |
-#> |.....................|     8.693 |     2.324 |     1.284 |    0.6933 |
-#> |.....................|    0.7394 |     1.519 |     1.302 |     1.298 |
-#> |    F| Forward Diff. |   -0.8024 |    0.2274 |    0.2665 |   -0.1307 |
-#> |.....................|   -0.6475 |    -1.019 |    0.5594 |     1.618 |
-#> |.....................|    -1.681 |    0.3232 |    0.3907 |   -0.6658 |
-#> |   32|     458.11869 |    0.9974 |    -1.436 |   -0.8996 |   -0.8703 |
-#> |.....................|   -0.7864 |   -0.5266 |   -0.7281 |   -0.9565 |
-#> |.....................|    -1.029 |   -0.5904 |   -0.6787 |   -0.7170 |
-#> |    U|     458.11869 |     93.76 |    -5.836 |   -0.9785 |   -0.1750 |
-#> |.....................|     2.163 |     2.324 |     1.283 |    0.6931 |
-#> |.....................|    0.7397 |     1.519 |     1.302 |     1.298 |
-#> |    X|     458.11869 |     93.76 |  0.002920 |    0.2732 |    0.8395 |
-#> |.....................|     8.694 |     2.324 |     1.283 |    0.6931 |
-#> |.....................|    0.7397 |     1.519 |     1.302 |     1.298 |
-#> |    F| Forward Diff. |     1.112 |    0.2271 |    0.2694 |   -0.1286 |
-#> |.....................|   -0.6401 |    -1.529 |    0.3516 |     1.832 |
-#> |.....................|   -0.3653 |    0.2635 |    0.3774 |   -0.6589 |
-#> |   33|     458.11797 |    0.9972 |    -1.436 |   -0.8997 |   -0.8703 |
-#> |.....................|   -0.7863 |   -0.5263 |   -0.7282 |   -0.9569 |
-#> |.....................|    -1.029 |   -0.5904 |   -0.6788 |   -0.7169 |
-#> |    U|     458.11797 |     93.74 |    -5.836 |   -0.9785 |   -0.1749 |
-#> |.....................|     2.163 |     2.325 |     1.283 |    0.6928 |
-#> |.....................|    0.7397 |     1.519 |     1.302 |     1.298 |
-#> |    X|     458.11797 |     93.74 |  0.002920 |    0.2732 |    0.8395 |
-#> |.....................|     8.695 |     2.325 |     1.283 |    0.6928 |
-#> |.....................|    0.7397 |     1.519 |     1.302 |     1.298 |
-#> |    F| Forward Diff. |    -1.528 |    0.2260 |    0.2581 |   -0.1311 |
-#> |.....................|   -0.6478 |    -1.074 |    0.7096 |     1.705 |
-#> |.....................|    -1.609 |    0.2690 |    0.3809 |   -0.6419 |
-#> |   34|     458.11744 |    0.9975 |    -1.436 |   -0.8997 |   -0.8703 |
-#> |.....................|   -0.7862 |   -0.5262 |   -0.7283 |   -0.9571 |
-#> |.....................|    -1.029 |   -0.5904 |   -0.6788 |   -0.7168 |
-#> |    U|     458.11744 |     93.76 |    -5.836 |   -0.9786 |   -0.1749 |
-#> |.....................|     2.163 |     2.325 |     1.283 |    0.6926 |
-#> |.....................|    0.7399 |     1.519 |     1.302 |     1.298 |
-#> |    X|     458.11744 |     93.76 |  0.002920 |    0.2732 |    0.8395 |
-#> |.....................|     8.696 |     2.325 |     1.283 |    0.6926 |
-#> |.....................|    0.7399 |     1.519 |     1.302 |     1.298 |
-#> |    F| Forward Diff. |     1.737 |    0.2262 |    0.2659 |   -0.1276 |
-#> |.....................|   -0.6346 |   -0.9458 |    0.5100 |     1.567 |
-#> |.....................|    -1.640 |    0.3111 |    0.3526 |   -0.6225 |
-#> |   35|     458.11714 |    0.9972 |    -1.436 |   -0.8998 |   -0.8703 |
-#> |.....................|   -0.7861 |   -0.5260 |   -0.7284 |   -0.9574 |
-#> |.....................|    -1.029 |   -0.5905 |   -0.6789 |   -0.7167 |
-#> |    U|     458.11714 |     93.74 |    -5.836 |   -0.9786 |   -0.1749 |
-#> |.....................|     2.163 |     2.325 |     1.283 |    0.6924 |
-#> |.....................|    0.7402 |     1.519 |     1.302 |     1.298 |
-#> |    X|     458.11714 |     93.74 |  0.002920 |    0.2732 |    0.8395 |
-#> |.....................|     8.697 |     2.325 |     1.283 |    0.6924 |
-#> |.....................|    0.7402 |     1.519 |     1.302 |     1.298 |
-#> |    F| Forward Diff. |    -1.976 |    0.2241 |    0.2491 |   -0.1309 |
-#> |.....................|   -0.6467 |   -0.8649 |    0.8521 |     1.757 |
-#> |.....................|    -1.585 |    0.2641 |    0.3618 |   -0.6092 |
-#> |   36|     458.11663 |    0.9975 |    -1.436 |   -0.8998 |   -0.8703 |
-#> |.....................|   -0.7860 |   -0.5259 |   -0.7285 |   -0.9576 |
-#> |.....................|    -1.028 |   -0.5905 |   -0.6789 |   -0.7166 |
-#> |    U|     458.11663 |     93.76 |    -5.836 |   -0.9787 |   -0.1749 |
-#> |.....................|     2.163 |     2.325 |     1.283 |    0.6923 |
-#> |.....................|    0.7404 |     1.518 |     1.301 |     1.298 |
-#> |    X|     458.11663 |     93.76 |  0.002920 |    0.2732 |    0.8396 |
-#> |.....................|     8.698 |     2.325 |     1.283 |    0.6923 |
-#> |.....................|    0.7404 |     1.518 |     1.301 |     1.298 |
-#> |    F| Forward Diff. |     2.001 |    0.2249 |    0.2609 |   -0.1271 |
-#> |.....................|   -0.6310 |   -0.8317 |    0.8110 |     1.745 |
-#> |.....................|   -0.3162 |    0.2564 |    0.3586 |   -0.6097 |
-#> |   37|     458.11610 |    0.9971 |    -1.436 |   -0.8999 |   -0.8702 |
-#> |.....................|   -0.7859 |   -0.5258 |   -0.7286 |   -0.9579 |
-#> |.....................|    -1.028 |   -0.5906 |   -0.6790 |   -0.7165 |
-#> |    U|      458.1161 |     93.73 |    -5.836 |   -0.9787 |   -0.1749 |
-#> |.....................|     2.163 |     2.325 |     1.283 |    0.6920 |
-#> |.....................|    0.7404 |     1.518 |     1.301 |     1.298 |
-#> |    X|      458.1161 |     93.73 |  0.002920 |    0.2732 |    0.8396 |
-#> |.....................|     8.699 |     2.325 |     1.283 |    0.6920 |
-#> |.....................|    0.7404 |     1.518 |     1.301 |     1.298 |
-#> |    F| Forward Diff. |    -2.471 |    0.2228 |    0.2417 |   -0.1310 |
-#> |.....................|   -0.6447 |    -1.605 |  0.009434 |     1.531 |
-#> |.....................|    -1.615 |    0.2909 |    0.3664 |   -0.6093 |
-#> |   38|     458.11531 |    0.9974 |    -1.436 |   -0.8999 |   -0.8702 |
-#> |.....................|   -0.7859 |   -0.5256 |   -0.7287 |   -0.9582 |
-#> |.....................|    -1.028 |   -0.5905 |   -0.6791 |   -0.7164 |
-#> |    U|     458.11531 |     93.76 |    -5.836 |   -0.9788 |   -0.1749 |
-#> |.....................|     2.163 |     2.326 |     1.283 |    0.6918 |
-#> |.....................|    0.7405 |     1.518 |     1.301 |     1.299 |
-#> |    X|     458.11531 |     93.76 |  0.002919 |    0.2731 |    0.8396 |
-#> |.....................|     8.699 |     2.326 |     1.283 |    0.6918 |
-#> |.....................|    0.7405 |     1.518 |     1.301 |     1.299 |
-#> |    F| Forward Diff. |     1.540 |    0.2236 |    0.2522 |   -0.1268 |
-#> |.....................|   -0.6308 |   -0.9638 |    0.7239 |     1.714 |
-#> |.....................|    -1.540 |    0.2567 |    0.3599 |   -0.5942 |
-#> |   39|     458.11496 |    0.9972 |    -1.436 |   -0.8999 |   -0.8702 |
-#> |.....................|   -0.7858 |   -0.5254 |   -0.7288 |   -0.9585 |
-#> |.....................|    -1.028 |   -0.5906 |   -0.6791 |   -0.7163 |
-#> |    U|     458.11496 |     93.74 |    -5.836 |   -0.9788 |   -0.1748 |
-#> |.....................|     2.163 |     2.326 |     1.283 |    0.6916 |
-#> |.....................|    0.7408 |     1.518 |     1.301 |     1.299 |
-#> |    X|     458.11496 |     93.74 |  0.002919 |    0.2731 |    0.8396 |
-#> |.....................|     8.700 |     2.326 |     1.283 |    0.6916 |
-#> |.....................|    0.7408 |     1.518 |     1.301 |     1.299 |
-#> |    F| Forward Diff. |    -1.772 |    0.2217 |    0.2376 |   -0.1305 |
-#> |.....................|   -0.6412 |    -1.736 |    0.1210 |     1.307 |
-#> |.....................|    -1.540 |    0.2780 |    0.3483 |   -0.5916 |
-#> |   40|     458.11458 |    0.9975 |    -1.436 |   -0.9000 |   -0.8702 |
-#> |.....................|   -0.7857 |   -0.5252 |   -0.7289 |   -0.9587 |
-#> |.....................|    -1.028 |   -0.5906 |   -0.6792 |   -0.7163 |
-#> |    U|     458.11458 |     93.76 |    -5.836 |   -0.9788 |   -0.1748 |
-#> |.....................|     2.163 |     2.326 |     1.283 |    0.6915 |
-#> |.....................|    0.7410 |     1.518 |     1.301 |     1.299 |
-#> |    X|     458.11458 |     93.76 |  0.002919 |    0.2731 |    0.8396 |
-#> |.....................|     8.701 |     2.326 |     1.283 |    0.6915 |
-#> |.....................|    0.7410 |     1.518 |     1.301 |     1.299 |
-#> |    F| Forward Diff. |     1.896 |    0.2223 |    0.2476 |   -0.1262 |
-#> |.....................|   -0.6268 |   -0.4531 |    0.7600 |     1.698 |
-#> |.....................|    -1.483 |    0.2984 |    0.3374 |   -0.6006 |
-#> |   41|     458.11430 |    0.9972 |    -1.436 |   -0.9000 |   -0.8702 |
-#> |.....................|   -0.7856 |   -0.5251 |   -0.7290 |   -0.9589 |
-#> |.....................|    -1.027 |   -0.5907 |   -0.6792 |   -0.7162 |
-#> |    U|      458.1143 |     93.73 |    -5.836 |   -0.9789 |   -0.1748 |
-#> |.....................|     2.164 |     2.326 |     1.283 |    0.6913 |
-#> |.....................|    0.7412 |     1.518 |     1.301 |     1.299 |
-#> |    X|      458.1143 |     93.73 |  0.002919 |    0.2731 |    0.8396 |
-#> |.....................|     8.702 |     2.326 |     1.283 |    0.6913 |
-#> |.....................|    0.7412 |     1.518 |     1.301 |     1.299 |
-#> |    F| Forward Diff. |    -2.121 |    0.2201 |    0.2306 |   -0.1307 |
-#> |.....................|   -0.6392 |   -0.8820 |    0.4853 |     1.475 |
-#> |.....................|    -1.568 |    0.2856 |    0.3442 |   -0.5942 |
-#> |   42|     458.11392 |    0.9975 |    -1.437 |   -0.9001 |   -0.8702 |
-#> |.....................|   -0.7855 |   -0.5250 |   -0.7290 |   -0.9592 |
-#> |.....................|    -1.027 |   -0.5907 |   -0.6793 |   -0.7161 |
-#> |    U|     458.11392 |     93.76 |    -5.837 |   -0.9789 |   -0.1748 |
-#> |.....................|     2.164 |     2.326 |     1.283 |    0.6911 |
-#> |.....................|    0.7414 |     1.518 |     1.301 |     1.299 |
-#> |    X|     458.11392 |     93.76 |  0.002919 |    0.2731 |    0.8396 |
-#> |.....................|     8.702 |     2.326 |     1.283 |    0.6911 |
-#> |.....................|    0.7414 |     1.518 |     1.301 |     1.299 |
-#> |    F| Forward Diff. |     2.218 |    0.2203 |    0.2415 |   -0.1269 |
-#> |.....................|   -0.6242 |    -1.700 |   -0.1298 |     1.090 |
-#> |.....................|     1.097 |   -0.4639 |    0.3406 |   -0.5940 |
-#> |   43|     458.11292 |    0.9972 |    -1.437 |   -0.9001 |   -0.8702 |
-#> |.....................|   -0.7854 |   -0.5247 |   -0.7291 |   -0.9594 |
-#> |.....................|    -1.027 |   -0.5906 |   -0.6794 |   -0.7160 |
-#> |    U|     458.11292 |     93.74 |    -5.837 |   -0.9790 |   -0.1748 |
-#> |.....................|     2.164 |     2.326 |     1.283 |    0.6909 |
-#> |.....................|    0.7412 |     1.518 |     1.301 |     1.299 |
-#> |    X|     458.11292 |     93.74 |  0.002919 |    0.2731 |    0.8396 |
-#> |.....................|     8.703 |     2.326 |     1.283 |    0.6909 |
-#> |.....................|    0.7412 |     1.518 |     1.301 |     1.299 |
-#> |    F| Forward Diff. |    -1.114 |    0.2202 |    0.2288 |   -0.1307 |
-#> |.....................|   -0.6328 |   -0.7727 |    0.7964 |     1.664 |
-#> |.....................|   -0.2569 |    0.2827 |    0.3132 |   -0.5835 |
-#> |   44|     458.11219 |    0.9975 |    -1.437 |   -0.9002 |   -0.8701 |
-#> |.....................|   -0.7853 |   -0.5246 |   -0.7293 |   -0.9597 |
-#> |.....................|    -1.027 |   -0.5907 |   -0.6795 |   -0.7158 |
-#> |    U|     458.11219 |     93.76 |    -5.837 |   -0.9790 |   -0.1748 |
-#> |.....................|     2.164 |     2.327 |     1.283 |    0.6907 |
-#> |.....................|    0.7413 |     1.518 |     1.301 |     1.299 |
-#> |    X|     458.11219 |     93.76 |  0.002919 |    0.2731 |    0.8397 |
-#> |.....................|     8.704 |     2.327 |     1.283 |    0.6907 |
-#> |.....................|    0.7413 |     1.518 |     1.301 |     1.299 |
-#> |    F| Forward Diff. |     1.924 |    0.2207 |    0.2357 |   -0.1254 |
-#> |.....................|   -0.6202 |   -0.4451 |    0.8288 |     1.643 |
-#> |.....................|    -1.561 |    0.2786 |    0.3167 |   -0.5797 |
-#> |   45|     458.11161 |    0.9972 |    -1.437 |   -0.9002 |   -0.8701 |
-#> |.....................|   -0.7852 |   -0.5246 |   -0.7295 |   -0.9601 |
-#> |.....................|    -1.027 |   -0.5907 |   -0.6795 |   -0.7157 |
-#> |    U|     458.11161 |     93.74 |    -5.837 |   -0.9791 |   -0.1747 |
-#> |.....................|     2.164 |     2.327 |     1.283 |    0.6904 |
-#> |.....................|    0.7414 |     1.518 |     1.301 |     1.299 |
-#> |    X|     458.11161 |     93.74 |  0.002918 |    0.2731 |    0.8397 |
-#> |.....................|     8.705 |     2.327 |     1.283 |    0.6904 |
-#> |.....................|    0.7414 |     1.518 |     1.301 |     1.299 |
-#> |    F| Forward Diff. |    -1.221 |    0.2188 |    0.2217 |   -0.1291 |
-#> |.....................|   -0.6301 |    -1.629 |    0.1332 |     1.223 |
-#> |.....................|    -1.491 |    0.2969 |    0.3215 |   -0.5516 |
-#> |   46|     458.11130 |    0.9974 |    -1.437 |   -0.9003 |   -0.8701 |
-#> |.....................|   -0.7851 |   -0.5243 |   -0.7295 |   -0.9603 |
-#> |.....................|    -1.027 |   -0.5907 |   -0.6796 |   -0.7156 |
-#> |    U|      458.1113 |     93.76 |    -5.837 |   -0.9791 |   -0.1747 |
-#> |.....................|     2.164 |     2.327 |     1.283 |    0.6902 |
-#> |.....................|    0.7416 |     1.518 |     1.301 |     1.299 |
-#> |    X|      458.1113 |     93.76 |  0.002918 |    0.2731 |    0.8397 |
-#> |.....................|     8.706 |     2.327 |     1.283 |    0.6902 |
-#> |.....................|    0.7416 |     1.518 |     1.301 |     1.299 |
-#> |    F| Forward Diff. |     1.605 |    0.2188 |    0.2279 |   -0.1262 |
-#> |.....................|   -0.6191 |    -1.596 |    0.1216 |     1.254 |
-#> |.....................|     1.158 |   -0.4084 |    0.3005 |   -0.5648 |
-#> |   47|     458.11059 |    0.9972 |    -1.437 |   -0.9003 |   -0.8701 |
-#> |.....................|   -0.7850 |   -0.5240 |   -0.7295 |   -0.9605 |
-#> |.....................|    -1.027 |   -0.5906 |   -0.6796 |   -0.7155 |
-#> |    U|     458.11059 |     93.73 |    -5.837 |   -0.9791 |   -0.1747 |
-#> |.....................|     2.164 |     2.327 |     1.283 |    0.6901 |
-#> |.....................|    0.7415 |     1.518 |     1.301 |     1.300 |
-#> |    X|     458.11059 |     93.73 |  0.002918 |    0.2731 |    0.8397 |
-#> |.....................|     8.707 |     2.327 |     1.283 |    0.6901 |
-#> |.....................|    0.7415 |     1.518 |     1.301 |     1.300 |
-#> |    F| Forward Diff. |    -2.022 |    0.2179 |    0.2140 |   -0.1317 |
-#> |.....................|   -0.6294 |   -0.4112 |    0.8588 |     1.629 |
-#> |.....................|    -1.524 |    0.3410 |    0.3226 |   -0.5400 |
-#> |   48|     458.10995 |    0.9975 |    -1.437 |   -0.9003 |   -0.8701 |
-#> |.....................|   -0.7849 |   -0.5239 |   -0.7297 |   -0.9608 |
-#> |.....................|    -1.027 |   -0.5906 |   -0.6797 |   -0.7154 |
-#> |    U|     458.10995 |     93.76 |    -5.837 |   -0.9792 |   -0.1747 |
-#> |.....................|     2.164 |     2.327 |     1.283 |    0.6899 |
-#> |.....................|    0.7416 |     1.518 |     1.301 |     1.300 |
-#> |    X|     458.10995 |     93.76 |  0.002918 |    0.2731 |    0.8397 |
-#> |.....................|     8.708 |     2.327 |     1.283 |    0.6899 |
-#> |.....................|    0.7416 |     1.518 |     1.301 |     1.300 |
-#> |    F| Forward Diff. |     1.872 |    0.2188 |    0.2245 |   -0.1278 |
-#> |.....................|   -0.6141 |    -1.055 |    0.5121 |     1.433 |
-#> |.....................|    -1.504 |    0.3641 |    0.3235 |   -0.5302 |
-#> |   49|     458.10978 |    0.9972 |    -1.437 |   -0.9004 |   -0.8700 |
-#> |.....................|   -0.7848 |   -0.5238 |   -0.7297 |   -0.9610 |
-#> |.....................|    -1.027 |   -0.5907 |   -0.6797 |   -0.7153 |
-#> |    U|     458.10978 |     93.73 |    -5.837 |   -0.9792 |   -0.1747 |
-#> |.....................|     2.164 |     2.327 |     1.282 |    0.6897 |
-#> |.....................|    0.7418 |     1.518 |     1.301 |     1.300 |
-#> |    X|     458.10978 |     93.73 |  0.002918 |    0.2730 |    0.8397 |
-#> |.....................|     8.709 |     2.327 |     1.282 |    0.6897 |
-#> |.....................|    0.7418 |     1.518 |     1.301 |     1.300 |
-#> |    C| Central Diff. |    -2.410 |    0.2142 |    0.1743 |   -0.1457 |
-#> |.....................|   -0.6441 |   -0.7806 |    0.7426 |     1.188 |
-#> |.....................|  -0.06181 |   -0.3659 |    0.5158 |   -0.5913 |
-#> |   50|     458.10914 |    0.9975 |    -1.437 |   -0.9004 |   -0.8700 |
-#> |.....................|   -0.7847 |   -0.5236 |   -0.7299 |   -0.9612 |
-#> |.....................|    -1.027 |   -0.5906 |   -0.6798 |   -0.7152 |
-#> |    U|     458.10914 |     93.77 |    -5.837 |   -0.9792 |   -0.1747 |
-#> |.....................|     2.164 |     2.327 |     1.282 |    0.6895 |
-#> |.....................|    0.7418 |     1.518 |     1.300 |     1.300 |
-#> |    X|     458.10914 |     93.77 |  0.002918 |    0.2730 |    0.8397 |
-#> |.....................|     8.709 |     2.327 |     1.282 |    0.6895 |
-#> |.....................|    0.7418 |     1.518 |     1.300 |     1.300 |
-#> |    F| Forward Diff. |     2.690 |    0.2171 |    0.2203 |   -0.1291 |
-#> |.....................|   -0.6099 |   -0.7940 |    0.4528 |     1.377 |
-#> |.....................|    -1.452 |    0.2831 |    0.2911 |   -0.5300 |
-#> |   51|     458.10832 |    0.9972 |    -1.437 |   -0.9004 |   -0.8700 |
-#> |.....................|   -0.7846 |   -0.5235 |   -0.7300 |   -0.9615 |
-#> |.....................|    -1.027 |   -0.5905 |   -0.6799 |   -0.7151 |
-#> |    U|     458.10832 |     93.74 |    -5.837 |   -0.9793 |   -0.1747 |
-#> |.....................|     2.164 |     2.328 |     1.282 |    0.6893 |
-#> |.....................|    0.7418 |     1.518 |     1.300 |     1.300 |
-#> |    X|     458.10832 |     93.74 |  0.002918 |    0.2730 |    0.8397 |
-#> |.....................|     8.710 |     2.328 |     1.282 |    0.6893 |
-#> |.....................|    0.7418 |     1.518 |     1.300 |     1.300 |
-#> |    F| Forward Diff. |    -1.386 |    0.2164 |    0.2066 |   -0.1317 |
-#> |.....................|   -0.6210 |   -0.6390 |    0.8493 |     1.598 |
-#> |.....................|    -1.491 |    0.2964 |    0.2278 |   -0.4988 |
-#> |   52|     458.10801 |    0.9974 |    -1.437 |   -0.9005 |   -0.8700 |
-#> |.....................|   -0.7845 |   -0.5234 |   -0.7302 |   -0.9618 |
-#> |.....................|    -1.026 |   -0.5906 |   -0.6800 |   -0.7150 |
-#> |    U|     458.10801 |     93.76 |    -5.837 |   -0.9793 |   -0.1746 |
-#> |.....................|     2.165 |     2.328 |     1.282 |    0.6891 |
-#> |.....................|    0.7421 |     1.518 |     1.300 |     1.300 |
-#> |    X|     458.10801 |     93.76 |  0.002918 |    0.2730 |    0.8398 |
-#> |.....................|     8.711 |     2.328 |     1.282 |    0.6891 |
-#> |.....................|    0.7421 |     1.518 |     1.300 |     1.300 |
-#> |    F| Forward Diff. |     1.854 |    0.2167 |    0.2150 |   -0.1282 |
-#> |.....................|   -0.6083 |   -0.7461 |    0.7029 |     1.539 |
-#> |.....................|   -0.1981 |    0.2733 |    0.2717 |   -0.5257 |
-#> |   53|     458.10765 |    0.9971 |    -1.437 |   -0.9005 |   -0.8700 |
-#> |.....................|   -0.7844 |   -0.5232 |   -0.7303 |   -0.9621 |
-#> |.....................|    -1.026 |   -0.5906 |   -0.6800 |   -0.7149 |
-#> |    U|     458.10765 |     93.73 |    -5.837 |   -0.9794 |   -0.1746 |
-#> |.....................|     2.165 |     2.328 |     1.282 |    0.6889 |
-#> |.....................|    0.7421 |     1.518 |     1.300 |     1.300 |
-#> |    X|     458.10765 |     93.73 |  0.002917 |    0.2730 |    0.8398 |
-#> |.....................|     8.712 |     2.328 |     1.282 |    0.6889 |
-#> |.....................|    0.7421 |     1.518 |     1.300 |     1.300 |
-#> |    F| Forward Diff. |    -2.678 |    0.2148 |    0.1964 |   -0.1329 |
-#> |.....................|   -0.6222 |   -0.7140 |    0.5004 |     1.353 |
-#> |.....................|   -0.2647 |    0.3470 |    0.3026 |   -0.5041 |
-#> |   54|     458.10677 |    0.9974 |    -1.437 |   -0.9006 |   -0.8700 |
-#> |.....................|   -0.7843 |   -0.5231 |   -0.7305 |   -0.9624 |
-#> |.....................|    -1.026 |   -0.5907 |   -0.6801 |   -0.7148 |
-#> |    U|     458.10677 |     93.76 |    -5.837 |   -0.9794 |   -0.1746 |
-#> |.....................|     2.165 |     2.328 |     1.282 |    0.6887 |
-#> |.....................|    0.7421 |     1.518 |     1.300 |     1.300 |
-#> |    X|     458.10677 |     93.76 |  0.002917 |    0.2730 |    0.8398 |
-#> |.....................|     8.713 |     2.328 |     1.282 |    0.6887 |
-#> |.....................|    0.7421 |     1.518 |     1.300 |     1.300 |
-#> |    F| Forward Diff. |     1.911 |    0.2164 |    0.2105 |   -0.1281 |
-#> |.....................|   -0.6034 |   -0.7920 |    0.6471 |     1.488 |
-#> |.....................|   -0.2445 |    0.2110 |    0.2380 |   -0.4469 |
-#> |   55|     458.10609 |    0.9972 |    -1.437 |   -0.9006 |   -0.8700 |
-#> |.....................|   -0.7842 |   -0.5230 |   -0.7306 |   -0.9627 |
-#> |.....................|    -1.026 |   -0.5907 |   -0.6801 |   -0.7147 |
-#> |    U|     458.10609 |     93.74 |    -5.837 |   -0.9794 |   -0.1746 |
-#> |.....................|     2.165 |     2.328 |     1.282 |    0.6884 |
-#> |.....................|    0.7421 |     1.518 |     1.300 |     1.300 |
-#> |    X|     458.10609 |     93.74 |  0.002917 |    0.2730 |    0.8398 |
-#> |.....................|     8.714 |     2.328 |     1.282 |    0.6884 |
-#> |.....................|    0.7421 |     1.518 |     1.300 |     1.300 |
-#> |    F| Forward Diff. |    -1.589 |    0.2148 |    0.1951 |   -0.1322 |
-#> |.....................|   -0.6145 |   -0.8575 |    0.5942 |     1.427 |
-#> |.....................|    -1.492 |    0.2699 |    0.1872 |   -0.4796 |
-#> |   56|     458.10567 |    0.9974 |    -1.437 |   -0.9006 |   -0.8699 |
-#> |.....................|   -0.7841 |   -0.5228 |   -0.7308 |   -0.9630 |
-#> |.....................|    -1.026 |   -0.5907 |   -0.6801 |   -0.7146 |
-#> |    U|     458.10567 |     93.76 |    -5.837 |   -0.9795 |   -0.1746 |
-#> |.....................|     2.165 |     2.328 |     1.282 |    0.6882 |
-#> |.....................|    0.7422 |     1.518 |     1.300 |     1.301 |
-#> |    X|     458.10567 |     93.76 |  0.002917 |    0.2730 |    0.8398 |
-#> |.....................|     8.715 |     2.328 |     1.282 |    0.6882 |
-#> |.....................|    0.7422 |     1.518 |     1.300 |     1.301 |
-#> |    F| Forward Diff. |     1.760 |    0.2153 |    0.2043 |   -0.1283 |
-#> |.....................|   -0.6005 |   -0.7529 |    0.6292 |     1.454 |
-#> |.....................|   -0.2107 |    0.2534 |    0.2280 |   -0.4318 |
-#> |   57|     458.10540 |    0.9971 |    -1.437 |   -0.9007 |   -0.8699 |
-#> |.....................|   -0.7840 |   -0.5227 |   -0.7309 |   -0.9633 |
-#> |.....................|    -1.026 |   -0.5907 |   -0.6801 |   -0.7146 |
-#> |    U|      458.1054 |     93.73 |    -5.837 |   -0.9795 |   -0.1745 |
-#> |.....................|     2.165 |     2.328 |     1.282 |    0.6880 |
-#> |.....................|    0.7423 |     1.518 |     1.300 |     1.301 |
-#> |    X|      458.1054 |     93.73 |  0.002917 |    0.2730 |    0.8398 |
-#> |.....................|     8.716 |     2.328 |     1.282 |    0.6880 |
-#> |.....................|    0.7423 |     1.518 |     1.300 |     1.301 |
-#> |    F| Forward Diff. |    -2.789 |    0.2130 |    0.1850 |   -0.1339 |
-#> |.....................|   -0.6160 |   -0.6903 |    0.7130 |     1.481 |
-#> |.....................|   -0.1975 |    0.2824 |    0.2646 |   -0.4868 |
-#> |   58|     458.10444 |    0.9974 |    -1.437 |   -0.9007 |   -0.8699 |
-#> |.....................|   -0.7839 |   -0.5226 |   -0.7311 |   -0.9636 |
-#> |.....................|    -1.026 |   -0.5907 |   -0.6801 |   -0.7145 |
-#> |    U|     458.10444 |     93.76 |    -5.837 |   -0.9796 |   -0.1745 |
-#> |.....................|     2.165 |     2.329 |     1.282 |    0.6878 |
-#> |.....................|    0.7423 |     1.518 |     1.300 |     1.301 |
-#> |    X|     458.10444 |     93.76 |  0.002916 |    0.2730 |    0.8398 |
-#> |.....................|     8.717 |     2.329 |     1.282 |    0.6878 |
-#> |.....................|    0.7423 |     1.518 |     1.300 |     1.301 |
-#> |    F| Forward Diff. |     1.285 |    0.2143 |    0.1972 |   -0.1290 |
-#> |.....................|   -0.5987 |   -0.7355 |    0.6064 |     1.421 |
-#> |.....................|    -1.460 |    0.2526 |    0.2188 |   -0.4206 |
-#> |   59|     458.10435 |    0.9972 |    -1.437 |   -0.9008 |   -0.8699 |
-#> |.....................|   -0.7838 |   -0.5224 |   -0.7312 |   -0.9638 |
-#> |.....................|    -1.026 |   -0.5908 |   -0.6802 |   -0.7144 |
-#> |    U|     458.10435 |     93.73 |    -5.837 |   -0.9796 |   -0.1745 |
-#> |.....................|     2.165 |     2.329 |     1.282 |    0.6876 |
-#> |.....................|    0.7425 |     1.518 |     1.300 |     1.301 |
-#> |    X|     458.10435 |     93.73 |  0.002916 |    0.2730 |    0.8399 |
-#> |.....................|     8.718 |     2.329 |     1.282 |    0.6876 |
-#> |.....................|    0.7425 |     1.518 |     1.300 |     1.301 |
-#> |    C| Central Diff. |    -2.184 |    0.2097 |    0.1486 |   -0.1446 |
-#> |.....................|   -0.6255 |   -0.7028 |    0.6444 |     1.495 |
-#> |.....................|    -1.416 |    0.3010 |    0.4942 |   -0.5303 |
-#> |   60|     458.10393 |    0.9975 |    -1.438 |   -0.9008 |   -0.8699 |
-#> |.....................|   -0.7837 |   -0.5223 |   -0.7313 |   -0.9641 |
-#> |.....................|    -1.026 |   -0.5908 |   -0.6802 |   -0.7143 |
-#> |    U|     458.10393 |     93.76 |    -5.838 |   -0.9796 |   -0.1745 |
-#> |.....................|     2.165 |     2.329 |     1.282 |    0.6873 |
-#> |.....................|    0.7426 |     1.518 |     1.300 |     1.301 |
-#> |    X|     458.10393 |     93.76 |  0.002916 |    0.2730 |    0.8399 |
-#> |.....................|     8.718 |     2.329 |     1.282 |    0.6873 |
-#> |.....................|    0.7426 |     1.518 |     1.300 |     1.301 |
-#> |    F| Forward Diff. |     2.045 |    0.2119 |    0.1940 |   -0.1305 |
-#> |.....................|   -0.5955 |   -0.7252 |    0.6285 |     1.413 |
-#> |.....................|   -0.2070 |    0.2194 |    0.2208 |   -0.3980 |
-#> |   61|     458.10364 |    0.9971 |    -1.438 |   -0.9008 |   -0.8699 |
-#> |.....................|   -0.7836 |   -0.5222 |   -0.7314 |   -0.9644 |
-#> |.....................|    -1.026 |   -0.5908 |   -0.6803 |   -0.7142 |
-#> |    U|     458.10364 |     93.73 |    -5.838 |   -0.9796 |   -0.1745 |
-#> |.....................|     2.166 |     2.329 |     1.281 |    0.6871 |
-#> |.....................|    0.7427 |     1.518 |     1.300 |     1.301 |
-#> |    X|     458.10364 |     93.73 |  0.002916 |    0.2730 |    0.8399 |
-#> |.....................|     8.719 |     2.329 |     1.281 |    0.6871 |
-#> |.....................|    0.7427 |     1.518 |     1.300 |     1.301 |
-#> |    F| Forward Diff. |    -2.727 |    0.2108 |    0.1771 |   -0.1339 |
-#> |.....................|   -0.6094 |   -0.7304 |    0.6317 |     1.376 |
-#> |.....................|    -1.443 |    0.2644 |    0.2580 |   -0.4629 |
-#> |   62|     458.10286 |    0.9974 |    -1.438 |   -0.9008 |   -0.8699 |
-#> |.....................|   -0.7835 |   -0.5221 |   -0.7316 |   -0.9647 |
-#> |.....................|    -1.026 |   -0.5908 |   -0.6803 |   -0.7141 |
-#> |    U|     458.10286 |     93.75 |    -5.838 |   -0.9796 |   -0.1745 |
-#> |.....................|     2.166 |     2.329 |     1.281 |    0.6869 |
-#> |.....................|    0.7427 |     1.518 |     1.300 |     1.301 |
-#> |    X|     458.10286 |     93.75 |  0.002915 |    0.2730 |    0.8399 |
-#> |.....................|     8.720 |     2.329 |     1.281 |    0.6869 |
-#> |.....................|    0.7427 |     1.518 |     1.300 |     1.301 |
-#> |    F| Forward Diff. |     1.225 |    0.2118 |    0.1898 |   -0.1294 |
-#> |.....................|   -0.5932 |   -0.6493 |    0.6517 |     1.411 |
-#> |.....................|   -0.1402 |    0.3233 |    0.2428 |   -0.3732 |
-#> |   63|     458.10253 |    0.9971 |    -1.438 |   -0.9009 |   -0.8698 |
-#> |.....................|   -0.7834 |   -0.5219 |   -0.7318 |   -0.9650 |
-#> |.....................|    -1.026 |   -0.5909 |   -0.6803 |   -0.7141 |
-#> |    U|     458.10253 |     93.73 |    -5.838 |   -0.9797 |   -0.1745 |
-#> |.....................|     2.166 |     2.329 |     1.281 |    0.6867 |
-#> |.....................|    0.7428 |     1.518 |     1.300 |     1.301 |
-#> |    X|     458.10253 |     93.73 |  0.002915 |    0.2730 |    0.8399 |
-#> |.....................|     8.721 |     2.329 |     1.281 |    0.6867 |
-#> |.....................|    0.7428 |     1.518 |     1.300 |     1.301 |
-#> |    F| Forward Diff. |    -2.449 |    0.2099 |    0.1736 |   -0.1338 |
-#> |.....................|   -0.6049 |   -0.7015 |    0.6330 |     1.384 |
-#> |.....................|   -0.1863 |    0.2615 |    0.2563 |   -0.4532 |
-#> |   64|     458.10167 |    0.9974 |    -1.438 |   -0.9009 |   -0.8698 |
-#> |.....................|   -0.7832 |   -0.5218 |   -0.7320 |   -0.9653 |
-#> |.....................|    -1.026 |   -0.5909 |   -0.6804 |   -0.7140 |
-#> |    U|     458.10167 |     93.76 |    -5.838 |   -0.9797 |   -0.1744 |
-#> |.....................|     2.166 |     2.329 |     1.281 |    0.6864 |
-#> |.....................|    0.7427 |     1.518 |     1.300 |     1.301 |
-#> |    X|     458.10167 |     93.76 |  0.002915 |    0.2729 |    0.8399 |
-#> |.....................|     8.722 |     2.329 |     1.281 |    0.6864 |
-#> |.....................|    0.7427 |     1.518 |     1.300 |     1.301 |
-#> |    F| Forward Diff. |     1.422 |    0.2110 |    0.1849 |   -0.1293 |
-#> |.....................|   -0.5889 |   -0.5964 |    0.6731 |     1.405 |
-#> |.....................|   -0.1535 |    0.3114 |    0.2496 |   -0.4521 |
-#> |   65|     458.10133 |    0.9971 |    -1.438 |   -0.9009 |   -0.8698 |
-#> |.....................|   -0.7831 |   -0.5217 |   -0.7321 |   -0.9657 |
-#> |.....................|    -1.026 |   -0.5909 |   -0.6804 |   -0.7139 |
-#> |    U|     458.10133 |     93.73 |    -5.838 |   -0.9798 |   -0.1744 |
-#> |.....................|     2.166 |     2.329 |     1.281 |    0.6862 |
-#> |.....................|    0.7428 |     1.518 |     1.300 |     1.301 |
-#> |    X|     458.10133 |     93.73 |  0.002915 |    0.2729 |    0.8400 |
-#> |.....................|     8.723 |     2.329 |     1.281 |    0.6862 |
-#> |.....................|    0.7428 |     1.518 |     1.300 |     1.301 |
-#> |    F| Forward Diff. |    -2.461 |    0.2094 |    0.1688 |   -0.1332 |
-#> |.....................|   -0.6003 |   -0.7109 |    0.5914 |     1.349 |
-#> |.....................|    -1.404 |    0.2951 |    0.2552 |   -0.4331 |
-#> |   66|     458.10059 |    0.9974 |    -1.438 |   -0.9009 |   -0.8698 |
-#> |.....................|   -0.7830 |   -0.5215 |   -0.7323 |   -0.9660 |
-#> |.....................|    -1.026 |   -0.5909 |   -0.6804 |   -0.7138 |
-#> |    U|     458.10059 |     93.75 |    -5.838 |   -0.9798 |   -0.1744 |
-#> |.....................|     2.166 |     2.330 |     1.281 |    0.6860 |
-#> |.....................|    0.7428 |     1.518 |     1.300 |     1.302 |
-#> |    X|     458.10059 |     93.75 |  0.002915 |    0.2729 |    0.8400 |
-#> |.....................|     8.724 |     2.330 |     1.281 |    0.6860 |
-#> |.....................|    0.7428 |     1.518 |     1.300 |     1.302 |
-#> |    F| Forward Diff. |     1.228 |    0.2101 |    0.1802 |   -0.1294 |
-#> |.....................|   -0.5857 |   -0.2287 |    0.9339 |     1.558 |
-#> |.....................|    -1.376 |    0.3488 |    0.2665 |   -0.4324 |
-#> |   67|     458.10050 |    0.9972 |    -1.438 |   -0.9010 |   -0.8697 |
-#> |.....................|   -0.7829 |   -0.5215 |   -0.7325 |   -0.9663 |
-#> |.....................|    -1.025 |   -0.5910 |   -0.6804 |   -0.7137 |
-#> |    U|      458.1005 |     93.73 |    -5.838 |   -0.9798 |   -0.1744 |
-#> |.....................|     2.166 |     2.330 |     1.281 |    0.6857 |
-#> |.....................|    0.7430 |     1.518 |     1.300 |     1.302 |
-#> |    X|      458.1005 |     93.73 |  0.002915 |    0.2729 |    0.8400 |
-#> |.....................|     8.725 |     2.330 |     1.281 |    0.6857 |
-#> |.....................|    0.7430 |     1.518 |     1.300 |     1.302 |
-#> |    C| Central Diff. |    -2.045 |    0.2058 |    0.1327 |   -0.1461 |
-#> |.....................|   -0.6105 |   -0.6040 |    0.6130 |    0.9518 |
-#> |.....................|   0.01902 |    0.3702 |    0.4676 |   -0.4886 |
-#> |   68|     458.10013 |    0.9974 |    -1.438 |   -0.9010 |   -0.8697 |
-#> |.....................|   -0.7829 |   -0.5214 |   -0.7325 |   -0.9664 |
-#> |.....................|    -1.025 |   -0.5910 |   -0.6805 |   -0.7136 |
-#> |    U|     458.10013 |     93.75 |    -5.838 |   -0.9798 |   -0.1744 |
-#> |.....................|     2.166 |     2.330 |     1.281 |    0.6857 |
-#> |.....................|    0.7430 |     1.518 |     1.300 |     1.302 |
-#> |    X|     458.10013 |     93.75 |  0.002914 |    0.2729 |    0.8400 |
-#> |.....................|     8.725 |     2.330 |     1.281 |    0.6857 |
-#> |.....................|    0.7430 |     1.518 |     1.300 |     1.302 |
-#> |    F| Forward Diff. |    0.8557 |    0.2088 |    0.1747 |   -0.1300 |
-#> |.....................|   -0.5847 |   -0.2393 |    0.9114 |     1.536 |
-#> |.....................|    -1.367 |    0.3016 |    0.2557 |   -0.4123 |
-#> |   69|     458.10002 |    0.9973 |    -1.438 |   -0.9010 |   -0.8697 |
-#> |.....................|   -0.7828 |   -0.5214 |   -0.7326 |   -0.9665 |
-#> |.....................|    -1.025 |   -0.5911 |   -0.6805 |   -0.7136 |
-#> |    U|     458.10002 |     93.74 |    -5.838 |   -0.9798 |   -0.1744 |
-#> |.....................|     2.166 |     2.330 |     1.281 |    0.6856 |
-#> |.....................|    0.7432 |     1.518 |     1.300 |     1.302 |
-#> |    X|     458.10002 |     93.74 |  0.002914 |    0.2729 |    0.8400 |
-#> |.....................|     8.726 |     2.330 |     1.281 |    0.6856 |
-#> |.....................|    0.7432 |     1.518 |     1.300 |     1.302 |
-#> |    C| Central Diff. |   -0.5131 |    0.2058 |    0.1358 |   -0.1441 |
-#> |.....................|   -0.6029 |   -0.6262 |    0.5998 |     1.158 |
-#> |.....................|    -1.373 |    0.3470 |    0.4566 |   -0.4872 |
-#> |   70|     458.09992 |    0.9973 |    -1.438 |   -0.9010 |   -0.8697 |
-#> |.....................|   -0.7827 |   -0.5214 |   -0.7327 |   -0.9666 |
-#> |.....................|    -1.025 |   -0.5911 |   -0.6806 |   -0.7135 |
-#> |    U|     458.09992 |     93.75 |    -5.838 |   -0.9799 |   -0.1743 |
-#> |.....................|     2.166 |     2.330 |     1.281 |    0.6855 |
-#> |.....................|    0.7433 |     1.518 |     1.300 |     1.302 |
-#> |    X|     458.09992 |     93.75 |  0.002914 |    0.2729 |    0.8400 |
-#> |.....................|     8.726 |     2.330 |     1.281 |    0.6855 |
-#> |.....................|    0.7433 |     1.518 |     1.300 |     1.302 |
-#> |    C| Central Diff. |    0.2584 |    0.2056 |    0.1371 |   -0.1438 |
-#> |.....................|   -0.5991 |   -0.6198 |    0.6082 |    0.9676 |
-#> |.....................|     1.295 |    0.3221 |    0.4533 |   -0.4750 |
-#> |   71|     458.09944 |    0.9973 |    -1.438 |   -0.9010 |   -0.8697 |
-#> |.....................|   -0.7827 |   -0.5213 |   -0.7328 |   -0.9668 |
-#> |.....................|    -1.025 |   -0.5911 |   -0.6806 |   -0.7135 |
-#> |    U|     458.09944 |     93.75 |    -5.838 |   -0.9799 |   -0.1743 |
-#> |.....................|     2.166 |     2.330 |     1.281 |    0.6854 |
-#> |.....................|    0.7431 |     1.518 |     1.300 |     1.302 |
-#> |    X|     458.09944 |     93.75 |  0.002914 |    0.2729 |    0.8400 |
-#> |.....................|     8.727 |     2.330 |     1.281 |    0.6854 |
-#> |.....................|    0.7431 |     1.518 |     1.300 |     1.302 |
-#> |   72|     458.09825 |    0.9974 |    -1.438 |   -0.9011 |   -0.8697 |
-#> |.....................|   -0.7824 |   -0.5210 |   -0.7332 |   -0.9672 |
-#> |.....................|    -1.025 |   -0.5911 |   -0.6808 |   -0.7131 |
-#> |    U|     458.09825 |     93.76 |    -5.838 |   -0.9799 |   -0.1743 |
-#> |.....................|     2.167 |     2.330 |     1.280 |    0.6851 |
-#> |.....................|    0.7430 |     1.518 |     1.299 |     1.302 |
-#> |    X|     458.09825 |     93.76 |  0.002914 |    0.2729 |    0.8401 |
-#> |.....................|     8.729 |     2.330 |     1.280 |    0.6851 |
-#> |.....................|    0.7430 |     1.518 |     1.299 |     1.302 |
-#> |   73|     458.09793 |    0.9981 |    -1.438 |   -0.9013 |   -0.8695 |
-#> |.....................|   -0.7815 |   -0.5202 |   -0.7349 |   -0.9686 |
-#> |.....................|    -1.026 |   -0.5909 |   -0.6812 |   -0.7117 |
-#> |    U|     458.09793 |     93.82 |    -5.838 |   -0.9801 |   -0.1741 |
-#> |.....................|     2.168 |     2.331 |     1.279 |    0.6840 |
-#> |.....................|    0.7428 |     1.518 |     1.299 |     1.304 |
-#> |    X|     458.09793 |     93.82 |  0.002913 |    0.2729 |    0.8402 |
-#> |.....................|     8.737 |     2.331 |     1.279 |    0.6840 |
-#> |.....................|    0.7428 |     1.518 |     1.299 |     1.304 |
-#> |    F| Forward Diff. |     10.76 |    0.2116 |    0.1923 |   -0.1162 |
-#> |.....................|   -0.5255 |   -0.5796 |    0.3777 |     1.210 |
-#> |.....................|    -1.409 |    0.2855 |    0.1875 |   -0.3085 |
-#> |   74|     458.08987 |    0.9971 |    -1.438 |   -0.9013 |   -0.8695 |
-#> |.....................|   -0.7808 |   -0.5187 |   -0.7369 |   -0.9692 |
-#> |.....................|    -1.026 |   -0.5907 |   -0.6832 |   -0.7095 |
-#> |    U|     458.08987 |     93.72 |    -5.838 |   -0.9802 |   -0.1741 |
-#> |.....................|     2.168 |     2.332 |     1.278 |    0.6836 |
-#> |.....................|    0.7427 |     1.518 |     1.297 |     1.306 |
-#> |    X|     458.08987 |     93.72 |  0.002914 |    0.2729 |    0.8402 |
-#> |.....................|     8.743 |     2.332 |     1.278 |    0.6836 |
-#> |.....................|    0.7427 |     1.518 |     1.297 |     1.306 |
-#> |    F| Forward Diff. |    -2.512 |    0.2078 |    0.1434 |   -0.1372 |
-#> |.....................|   -0.5667 |   -0.8061 |    0.1467 |     1.033 |
-#> |.....................|     1.202 |   -0.4065 |   0.09417 |   -0.1935 |
-#> |   75|     458.08564 |    0.9973 |    -1.438 |   -0.9016 |   -0.8695 |
-#> |.....................|   -0.7801 |   -0.5170 |   -0.7384 |   -0.9704 |
-#> |.....................|    -1.026 |   -0.5898 |   -0.6859 |   -0.7082 |
-#> |    U|     458.08564 |     93.74 |    -5.838 |   -0.9804 |   -0.1741 |
-#> |.....................|     2.169 |     2.334 |     1.277 |    0.6827 |
-#> |.....................|    0.7424 |     1.519 |     1.294 |     1.308 |
-#> |    X|     458.08564 |     93.74 |  0.002914 |    0.2728 |    0.8402 |
-#> |.....................|     8.749 |     2.334 |     1.277 |    0.6827 |
-#> |.....................|    0.7424 |     1.519 |     1.294 |     1.308 |
-#> |   76|     458.08078 |    0.9972 |    -1.438 |   -0.9021 |   -0.8695 |
-#> |.....................|   -0.7788 |   -0.5136 |   -0.7416 |   -0.9727 |
-#> |.....................|    -1.027 |   -0.5879 |   -0.6916 |   -0.7053 |
-#> |    U|     458.08078 |     93.73 |    -5.838 |   -0.9809 |   -0.1742 |
-#> |.....................|     2.170 |     2.338 |     1.275 |    0.6809 |
-#> |.....................|    0.7420 |     1.522 |     1.288 |     1.311 |
-#> |    X|     458.08078 |     93.73 |  0.002915 |    0.2727 |    0.8402 |
-#> |.....................|     8.761 |     2.338 |     1.275 |    0.6809 |
-#> |.....................|    0.7420 |     1.522 |     1.288 |     1.311 |
-#> |    F| Forward Diff. |   -0.8456 |    0.2109 |    0.1052 |   -0.1453 |
-#> |.....................|   -0.5381 |   -0.2225 |   -0.1274 |    0.8336 |
-#> |.....................|   -0.2653 |    0.4698 |   -0.4321 |   0.07917 |
-#> |   77|     458.08109 |    0.9983 |    -1.445 |   -0.9066 |   -0.8702 |
-#> |.....................|   -0.7727 |   -0.5143 |   -0.7362 |   -0.9770 |
-#> |.....................|    -1.027 |   -0.5885 |   -0.6915 |   -0.7058 |
-#> |    U|     458.08109 |     93.84 |    -5.845 |   -0.9853 |   -0.1748 |
-#> |.....................|     2.176 |     2.337 |     1.279 |    0.6777 |
-#> |.....................|    0.7418 |     1.521 |     1.288 |     1.310 |
-#> |    X|     458.08109 |     93.84 |  0.002894 |    0.2718 |    0.8396 |
-#> |.....................|     8.815 |     2.337 |     1.279 |    0.6777 |
-#> |.....................|    0.7418 |     1.521 |     1.288 |     1.310 |
-#> |   78|     458.08775 |    0.9985 |    -1.441 |   -0.9040 |   -0.8696 |
-#> |.....................|   -0.7757 |   -0.5136 |   -0.7393 |   -0.9753 |
-#> |.....................|    -1.026 |   -0.5887 |   -0.6911 |   -0.7056 |
-#> |    U|     458.08775 |     93.86 |    -5.841 |   -0.9828 |   -0.1743 |
-#> |.....................|     2.173 |     2.338 |     1.277 |    0.6789 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08775 |     93.86 |  0.002906 |    0.2723 |    0.8401 |
-#> |.....................|     8.788 |     2.338 |     1.277 |    0.6789 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |   79|     458.08407 |    0.9980 |    -1.438 |   -0.9022 |   -0.8694 |
-#> |.....................|   -0.7783 |   -0.5133 |   -0.7415 |   -0.9736 |
-#> |.....................|    -1.026 |   -0.5884 |   -0.6912 |   -0.7054 |
-#> |    U|     458.08407 |     93.81 |    -5.838 |   -0.9810 |   -0.1740 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6802 |
-#> |.....................|    0.7422 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08407 |     93.81 |  0.002915 |    0.2727 |    0.8403 |
-#> |.....................|     8.766 |     2.338 |     1.275 |    0.6802 |
-#> |.....................|    0.7422 |     1.521 |     1.288 |     1.311 |
-#> |   80|     458.08069 |    0.9973 |    -1.438 |   -0.9021 |   -0.8695 |
-#> |.....................|   -0.7787 |   -0.5135 |   -0.7416 |   -0.9729 |
-#> |.....................|    -1.026 |   -0.5880 |   -0.6915 |   -0.7053 |
-#> |    U|     458.08069 |     93.75 |    -5.838 |   -0.9809 |   -0.1741 |
-#> |.....................|     2.170 |     2.338 |     1.275 |    0.6807 |
-#> |.....................|    0.7420 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08069 |     93.75 |  0.002915 |    0.2727 |    0.8402 |
-#> |.....................|     8.762 |     2.338 |     1.275 |    0.6807 |
-#> |.....................|    0.7420 |     1.521 |     1.288 |     1.311 |
-#> |    F| Forward Diff. |     1.424 |    0.2112 |    0.1114 |   -0.1426 |
-#> |.....................|   -0.5267 |   -0.3290 |  -0.02249 |    0.9218 |
-#> |.....................|    -1.516 |    0.4273 |   -0.4325 |   0.09748 |
-#> |   81|     458.08076 |    0.9972 |    -1.438 |   -0.9021 |   -0.8695 |
-#> |.....................|   -0.7786 |   -0.5134 |   -0.7416 |   -0.9730 |
-#> |.....................|    -1.026 |   -0.5880 |   -0.6914 |   -0.7055 |
-#> |    U|     458.08076 |     93.74 |    -5.838 |   -0.9810 |   -0.1741 |
-#> |.....................|     2.170 |     2.338 |     1.275 |    0.6807 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08076 |     93.74 |  0.002915 |    0.2727 |    0.8402 |
-#> |.....................|     8.763 |     2.338 |     1.275 |    0.6807 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |   82|     458.08078 |    0.9973 |    -1.438 |   -0.9021 |   -0.8695 |
-#> |.....................|   -0.7787 |   -0.5135 |   -0.7416 |   -0.9730 |
-#> |.....................|    -1.026 |   -0.5880 |   -0.6915 |   -0.7053 |
-#> |    U|     458.08078 |     93.74 |    -5.838 |   -0.9809 |   -0.1741 |
-#> |.....................|     2.170 |     2.338 |     1.275 |    0.6807 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08078 |     93.74 |  0.002915 |    0.2727 |    0.8402 |
-#> |.....................|     8.762 |     2.338 |     1.275 |    0.6807 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |   83|     458.08068 |    0.9973 |    -1.438 |   -0.9021 |   -0.8695 |
-#> |.....................|   -0.7787 |   -0.5135 |   -0.7416 |   -0.9729 |
-#> |.....................|    -1.026 |   -0.5880 |   -0.6915 |   -0.7053 |
-#> |    U|     458.08068 |     93.75 |    -5.838 |   -0.9809 |   -0.1741 |
-#> |.....................|     2.170 |     2.338 |     1.275 |    0.6807 |
-#> |.....................|    0.7420 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08068 |     93.75 |  0.002915 |    0.2727 |    0.8402 |
-#> |.....................|     8.762 |     2.338 |     1.275 |    0.6807 |
-#> |.....................|    0.7420 |     1.521 |     1.288 |     1.311 |
-#> |    C| Central Diff. |    0.7458 |    0.2086 |   0.07146 |   -0.1568 |
-#> |.....................|   -0.5453 |   -0.1723 |    0.1066 |    0.6006 |
-#> |.....................|  -0.05957 |    0.1717 |   -0.3314 |   0.06442 |
-#> |   84|     458.08065 |    0.9973 |    -1.438 |   -0.9021 |   -0.8695 |
-#> |.....................|   -0.7787 |   -0.5135 |   -0.7416 |   -0.9729 |
-#> |.....................|    -1.026 |   -0.5880 |   -0.6915 |   -0.7053 |
-#> |    U|     458.08065 |     93.74 |    -5.838 |   -0.9809 |   -0.1741 |
-#> |.....................|     2.170 |     2.338 |     1.275 |    0.6807 |
-#> |.....................|    0.7420 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08065 |     93.74 |  0.002915 |    0.2727 |    0.8402 |
-#> |.....................|     8.762 |     2.338 |     1.275 |    0.6807 |
-#> |.....................|    0.7420 |     1.521 |     1.288 |     1.311 |
-#> |    C| Central Diff. |    0.5271 |    0.2085 |   0.07055 |   -0.1570 |
-#> |.....................|   -0.5454 |   -0.3138 |   0.09492 |    0.7765 |
-#> |.....................|     1.192 |    0.4934 |   -0.3382 |    0.1071 |
-#> |   85|     458.08062 |    0.9973 |    -1.438 |   -0.9021 |   -0.8695 |
-#> |.....................|   -0.7786 |   -0.5135 |   -0.7416 |   -0.9730 |
-#> |.....................|    -1.026 |   -0.5880 |   -0.6915 |   -0.7054 |
-#> |    U|     458.08062 |     93.74 |    -5.838 |   -0.9809 |   -0.1741 |
-#> |.....................|     2.170 |     2.338 |     1.275 |    0.6807 |
-#> |.....................|    0.7420 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08062 |     93.74 |  0.002915 |    0.2727 |    0.8402 |
-#> |.....................|     8.762 |     2.338 |     1.275 |    0.6807 |
-#> |.....................|    0.7420 |     1.521 |     1.288 |     1.311 |
-#> |    C| Central Diff. |    0.1077 |    0.2083 |   0.06880 |   -0.1572 |
-#> |.....................|   -0.5469 |   -0.1727 |    0.1219 |    0.9565 |
-#> |.....................|    -1.457 |    0.5128 |   -0.3399 |    0.1022 |
-#> |   86|     458.08061 |    0.9972 |    -1.438 |   -0.9021 |   -0.8695 |
-#> |.....................|   -0.7786 |   -0.5135 |   -0.7416 |   -0.9730 |
-#> |.....................|    -1.026 |   -0.5881 |   -0.6914 |   -0.7054 |
-#> |    U|     458.08061 |     93.74 |    -5.838 |   -0.9809 |   -0.1741 |
-#> |.....................|     2.170 |     2.338 |     1.275 |    0.6807 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08061 |     93.74 |  0.002915 |    0.2727 |    0.8402 |
-#> |.....................|     8.763 |     2.338 |     1.275 |    0.6807 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |    C| Central Diff. |   -0.6930 |    0.2078 |   0.06712 |   -0.1577 |
-#> |.....................|   -0.5484 |   -0.1767 |    0.1148 |    0.9863 |
-#> |.....................|   -0.2038 |    0.5855 |   -0.3296 |    0.1002 |
-#> |   87|     458.08058 |    0.9972 |    -1.438 |   -0.9021 |   -0.8695 |
-#> |.....................|   -0.7786 |   -0.5135 |   -0.7416 |   -0.9731 |
-#> |.....................|    -1.026 |   -0.5881 |   -0.6914 |   -0.7054 |
-#> |    U|     458.08058 |     93.74 |    -5.838 |   -0.9809 |   -0.1741 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6806 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08058 |     93.74 |  0.002915 |    0.2727 |    0.8402 |
-#> |.....................|     8.763 |     2.338 |     1.275 |    0.6806 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |    C| Central Diff. |   -0.3701 |    0.2079 |   0.06808 |   -0.1573 |
-#> |.....................|   -0.5470 |   -0.1729 |  0.005725 |    0.9526 |
-#> |.....................|    -1.465 |    0.5101 |   -0.1466 |  -0.02770 |
-#> |   88|     458.08052 |    0.9973 |    -1.438 |   -0.9021 |   -0.8695 |
-#> |.....................|   -0.7785 |   -0.5135 |   -0.7416 |   -0.9731 |
-#> |.....................|    -1.026 |   -0.5881 |   -0.6914 |   -0.7053 |
-#> |    U|     458.08052 |     93.74 |    -5.838 |   -0.9809 |   -0.1741 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6806 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08052 |     93.74 |  0.002915 |    0.2727 |    0.8402 |
-#> |.....................|     8.763 |     2.338 |     1.275 |    0.6806 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |    C| Central Diff. |    0.2062 |    0.2080 |   0.06837 |   -0.1566 |
-#> |.....................|   -0.5439 |   -0.1704 |   0.09858 |    0.5928 |
-#> |.....................|  -0.05984 |    0.5131 |   -0.3447 |   0.06046 |
-#> |   89|     458.08047 |    0.9972 |    -1.438 |   -0.9021 |   -0.8694 |
-#> |.....................|   -0.7785 |   -0.5134 |   -0.7416 |   -0.9732 |
-#> |.....................|    -1.026 |   -0.5882 |   -0.6914 |   -0.7054 |
-#> |    U|     458.08047 |     93.74 |    -5.838 |   -0.9809 |   -0.1741 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6805 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08047 |     93.74 |  0.002915 |    0.2727 |    0.8402 |
-#> |.....................|     8.764 |     2.338 |     1.275 |    0.6805 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |    C| Central Diff. |  -0.06148 |    0.2077 |   0.06828 |   -0.1566 |
-#> |.....................|   -0.5434 |   -0.1748 |    0.1045 |    0.7316 |
-#> |.....................|   -0.7607 |    0.4924 |   -0.3350 |    0.1046 |
-#> |   90|     458.08041 |    0.9972 |    -1.438 |   -0.9021 |   -0.8694 |
-#> |.....................|   -0.7784 |   -0.5134 |   -0.7417 |   -0.9733 |
-#> |.....................|    -1.026 |   -0.5883 |   -0.6913 |   -0.7054 |
-#> |    U|     458.08041 |     93.74 |    -5.838 |   -0.9810 |   -0.1740 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6804 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08041 |     93.74 |  0.002915 |    0.2727 |    0.8403 |
-#> |.....................|     8.765 |     2.338 |     1.275 |    0.6804 |
-#> |.....................|    0.7421 |     1.521 |     1.288 |     1.311 |
-#> |    C| Central Diff. |   -0.5076 |    0.2073 |   0.06528 |   -0.1564 |
-#> |.....................|   -0.5454 |   -0.1802 |    0.1061 |    0.9740 |
-#> |.....................|   -0.1992 |    0.5430 |   -0.2714 |    0.1031 |
-#> |   91|     458.08026 |    0.9972 |    -1.438 |   -0.9022 |   -0.8694 |
-#> |.....................|   -0.7782 |   -0.5133 |   -0.7417 |   -0.9736 |
-#> |.....................|    -1.026 |   -0.5884 |   -0.6912 |   -0.7055 |
-#> |    U|     458.08026 |     93.74 |    -5.838 |   -0.9810 |   -0.1740 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6802 |
-#> |.....................|    0.7422 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08026 |     93.74 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.766 |     2.338 |     1.275 |    0.6802 |
-#> |.....................|    0.7422 |     1.521 |     1.288 |     1.311 |
-#> |    C| Central Diff. |   -0.3779 |    0.2092 |   0.07455 |   -0.1547 |
-#> |.....................|   -0.5349 |    0.4172 |   -0.5362 |    0.7903 |
-#> |.....................|    -1.451 |    0.5182 |   -0.2163 |   -0.4361 |
-#> |   92|     458.08039 |    0.9975 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7778 |   -0.5133 |   -0.7416 |   -0.9742 |
-#> |.....................|    -1.026 |   -0.5887 |   -0.6910 |   -0.7056 |
-#> |    U|     458.08039 |     93.76 |    -5.838 |   -0.9811 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6798 |
-#> |.....................|    0.7424 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08039 |     93.76 |  0.002914 |    0.2727 |    0.8404 |
-#> |.....................|     8.769 |     2.338 |     1.275 |    0.6798 |
-#> |.....................|    0.7424 |     1.521 |     1.288 |     1.311 |
-#> |   93|     458.08025 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08025 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08025 |     93.75 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    C| Central Diff. |     1.019 |    0.2066 |   0.06601 |   -0.1530 |
-#> |.....................|   -0.5270 |   -0.1637 |    0.1163 |    0.9184 |
-#> |.....................|    -1.439 |    0.4715 |   -0.2217 |   0.03756 |
-#> |   94|     458.08029 |    0.9972 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08029 |     93.74 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7424 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08029 |     93.74 |  0.002914 |    0.2727 |    0.8404 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7424 |     1.521 |     1.288 |     1.311 |
-#> |   95|     458.08025 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08025 |     93.74 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7424 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08025 |     93.74 |  0.002914 |    0.2727 |    0.8404 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7424 |     1.521 |     1.288 |     1.311 |
-#> |   96|     458.08029 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08029 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08029 |     93.75 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |   97|     458.08024 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08024 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08024 |     93.75 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    C| Central Diff. |    0.9275 |    0.2065 |   0.06562 |   -0.1530 |
-#> |.....................|   -0.5278 |   -0.1682 |    0.1168 |    0.9523 |
-#> |.....................|   -0.1838 |    0.4888 |   -0.3154 |   0.09539 |
-#> |   98|     458.08024 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08024 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08024 |     93.75 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    C| Central Diff. |    0.8715 |    0.2065 |   0.06540 |   -0.1531 |
-#> |.....................|   -0.5308 |  -0.07756 |    0.1164 |    0.5595 |
-#> |.....................|  -0.04465 |   -0.2577 |   -0.3240 |    0.1066 |
-#> |   99|     458.08023 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08023 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08023 |     93.75 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |  100|     458.08013 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08013 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08013 |     93.75 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    C| Central Diff. |    0.7255 |    0.2064 |   0.06482 |   -0.1531 |
-#> |.....................|   -0.5283 |   -0.1617 |    0.1081 |    0.9192 |
-#> |.....................|    -1.441 |    0.4906 |   -0.2900 |    0.1161 |
-#> |  101|     458.08017 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5885 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08017 |     93.74 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08017 |     93.74 |  0.002914 |    0.2727 |    0.8404 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |  102|     458.08021 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08021 |     93.74 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08021 |     93.74 |  0.002914 |    0.2727 |    0.8404 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |  103|     458.08029 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08029 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08029 |     93.75 |  0.002914 |    0.2727 |    0.8404 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |  104|     458.08032 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08032 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08032 |     93.75 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |  105|     458.08033 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08033 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08033 |     93.75 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |  106|     458.08032 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08032 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08032 |     93.75 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |  107|     458.08032 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08032 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08032 |     93.75 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |  108|     458.08032 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08032 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08032 |     93.75 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |  109|     458.08032 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08032 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08032 |     93.75 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |  110|     458.08032 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08032 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08032 |     93.75 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |  111|     458.08032 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08032 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08032 |     93.75 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |  112|     458.08032 |    0.9973 |    -1.438 |   -0.9022 |   -0.8693 |
-#> |.....................|   -0.7780 |   -0.5133 |   -0.7416 |   -0.9739 |
-#> |.....................|    -1.026 |   -0.5886 |   -0.6911 |   -0.7055 |
-#> |    U|     458.08032 |     93.75 |    -5.838 |   -0.9810 |   -0.1739 |
-#> |.....................|     2.171 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> |    X|     458.08032 |     93.75 |  0.002914 |    0.2727 |    0.8403 |
-#> |.....................|     8.768 |     2.338 |     1.275 |    0.6800 |
-#> |.....................|    0.7423 |     1.521 |     1.288 |     1.311 |
-#> calculating covariance matrix
-#> done
-#> Calculating residuals/tables
-#> done
-f_nlmixr_dfop_sfo_saem_obs <- nlmixr(f_mmkin_obs["DFOP-SFO", ], est = "saem")
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#>  
-#> → generate SAEM model
-#> ✔ done
-#> 1:    93.0952   -5.6337   -1.8988   -4.1294   -1.2035    0.1038    5.2152    1.6150    1.0450    2.6377    0.5035    0.5225   20.0768   11.4566
-#> 2:    93.1464   -5.6948   -1.8729   -4.2029   -1.1302    0.1295    5.5478    1.5342    0.9927    2.5059    0.4783    0.5147   11.2089    8.1577
-#> 3:    93.1719   -5.7029   -1.8810   -4.2024   -1.0686    0.1063    5.2764    1.5217    0.9431    2.3806    0.4544    0.5587    9.3753    5.7166
-#> 4:    92.8647   -5.8139   -1.8979   -4.1992   -1.0168    0.1122    5.4892    1.7893    0.8960    2.2615    0.4317    0.5307    9.4134    4.7166
-#> 5:    92.7759   -5.8627   -1.8873   -4.1402   -1.0347    0.1243    6.2028    2.1819    0.8795    2.1485    0.4101    0.5042    9.5964    4.7340
-#> 6:    92.8080   -5.8954   -1.9186   -4.1772   -0.9727    0.1311    5.8926    2.0728    0.8633    2.0410    0.3896    0.4790    8.7334    4.1957
-#> 7:    92.9042   -5.9034   -1.9603   -4.1854   -0.9717    0.1630    5.5980    2.2068    0.8672    1.9390    0.3701    0.4550    8.7213    3.3409
-#> 8:    92.9302   -5.8545   -1.9240   -4.2343   -0.9748    0.1686    5.3181    2.3934    0.8239    1.9533    0.3516    0.4323    7.6950    2.9174
-#> 9:    92.9518   -5.5561   -1.9734   -4.1856   -0.9322    0.2129    5.0522    2.2738    0.7830    2.0138    0.3340    0.4689    7.9230    2.1930
-#> 10:    93.0672   -5.5564   -1.9633   -4.1456   -0.9343    0.2049    4.7996    2.1601    0.7438    2.0517    0.3173    0.4771    8.0644    2.0682
-#> 11:    92.6849   -5.6187   -1.9773   -4.1793   -0.9342    0.2290    4.5596    2.0521    0.7123    2.0774    0.3015    0.5052    8.2355    1.9349
-#> 12:    92.6425   -5.6989   -2.0144   -4.1395   -0.9342    0.2669    4.3316    2.2634    0.7142    2.3008    0.2864    0.5728    7.5188    1.8028
-#> 13:    92.2996   -5.6700   -1.9885   -4.0443   -0.9202    0.2750    4.5787    2.1608    0.7019    2.7515    0.2721    0.6641    7.0744    1.8958
-#> 14:    92.2457   -5.5825   -2.0314   -3.9788   -0.9142    0.2908    6.3744    2.0527    0.7018    3.2703    0.2585    0.6387    6.9499    1.8421
-#> 15:    92.1741   -5.5333   -2.0318   -3.9664   -0.9059    0.2894    6.0557    1.9501    0.7179    3.2869    0.2455    0.6068    7.0951    1.6824
-#> 16:    92.5772   -5.4982   -2.0352   -3.9471   -0.9063    0.2930    5.7529    1.8526    0.7244    3.6994    0.2333    0.5764    7.2138    1.7042
-#> 17:    92.7024   -5.4902   -2.0438   -4.0347   -0.9079    0.2959    5.4652    1.7600    0.7393    3.5144    0.2216    0.5765    7.0258    1.6793
-#> 18:    92.0240   -5.5539   -2.0520   -3.9601   -0.9079    0.2884    6.5142    1.9232    0.7320    3.9052    0.2157    0.5521    7.2568    1.6151
-#> 19:    92.6532   -5.6325   -2.0456   -3.9091   -0.9179    0.3047    6.5743    2.3363    0.7405    4.5825    0.2049    0.5425    7.6201    1.6565
-#> 20:    92.3488   -5.6617   -2.0554   -3.9501   -0.9216    0.3056    6.7080    2.7562    0.7218    4.7569    0.2083    0.5432    7.3481    1.8059
-#> 21:    92.5679   -5.7469   -2.0614   -4.0829   -0.8890    0.3158    6.6510    3.1993    0.7136    4.5191    0.1978    0.5281    7.3723    1.7461
-#> 22:    92.4785   -5.9527   -2.0657   -4.0580   -0.8971    0.3084    6.3184    4.1791    0.7144    4.2931    0.1929    0.5157    7.1922    1.6984
-#> 23:    92.5594   -5.8590   -2.0723   -4.0580   -0.9020    0.2952    6.0025    3.9702    0.7335    4.0784    0.1833    0.5129    7.7560    1.6302
-#> 24:    92.6152   -5.9488   -2.0658   -4.1187   -0.9050    0.2997    5.7024    4.5381    0.7215    3.8745    0.1875    0.5129    7.6182    1.6362
-#> 25:    92.4658   -5.8715   -2.0791   -4.0949   -0.8922    0.3074    6.1428    4.3112    0.7353    3.6808    0.1896    0.5157    7.2703    1.5633
-#> 26:    92.2507   -5.9797   -2.0707   -4.0834   -0.8868    0.3266    6.4124    4.7125    0.7334    3.5368    0.1851    0.5217    7.3085    1.5828
-#> 27:    92.7055   -5.9792   -2.0779   -4.2066   -0.8887    0.2993    6.0918    4.8624    0.7659    3.7456    0.1841    0.4956    7.3534    1.5240
-#> 28:    92.3971   -6.0253   -2.0648   -4.1406   -0.9042    0.2897    5.7872    4.7690    0.7449    3.5583    0.1823    0.4709    7.2479    1.5008
-#> 29:    92.4045   -5.9045   -2.0730   -4.1407   -0.8969    0.3103    5.6683    4.5306    0.7349    3.3816    0.1849    0.5054    7.1719    1.6004
-#> 30:    92.1714   -5.8598   -2.0645   -4.0913   -0.8964    0.2743    5.3849    4.3040    0.7538    3.3509    0.1757    0.4801    7.3739    1.5736
-#> 31:    91.9134   -5.7867   -2.0367   -4.0563   -0.8957    0.2280    5.1156    4.0888    0.7299    3.3452    0.1749    0.4673    6.5991    1.5909
-#> 32:    92.3743   -5.9967   -2.0255   -4.0668   -0.9025    0.2247    4.8599    4.6666    0.7256    3.3271    0.1714    0.5008    6.4693    1.5458
-#> 33:    92.5239   -5.9301   -2.0387   -4.0365   -0.9033    0.2558    4.6169    4.4333    0.7492    3.6109    0.1688    0.5424    6.7730    1.5771
-#> 34:    92.6892   -6.1135   -2.0587   -4.0280   -0.8993    0.2430    4.3860    6.0227    0.7798    3.5725    0.1672    0.5153    6.8110    1.5417
-#> 35:    92.7276   -6.0815   -2.0629   -4.0833   -0.8943    0.2375    4.6811    5.7216    0.8010    3.3939    0.1715    0.4895    6.6812    1.5478
-#> 36:    92.7316   -6.0691   -2.0882   -4.0626   -0.9030    0.2405    4.4614    5.4355    0.8355    3.2242    0.1789    0.4650    6.8443    1.4806
-#> 37:    92.6685   -5.7905   -2.0666   -4.0663   -0.8998    0.2784    5.1916    5.1637    0.7937    3.0641    0.1823    0.4418    6.5421    1.6284
-#> 38:    93.0325   -5.6829   -2.0674   -4.0772   -0.9167    0.2499    4.9320    4.9055    0.7768    3.1213    0.1887    0.4290    6.8220    1.5224
-#> 39:    93.0378   -5.5554   -2.0743   -4.0772   -0.9189    0.2361    4.6854    4.6603    0.7822    3.1213    0.1813    0.4242    7.1137    1.5021
-#> 40:    93.3297   -5.6270   -2.0591   -4.1200   -0.9167    0.2035    4.4511    4.4272    0.8128    2.9653    0.1829    0.4030    7.3894    1.5064
-#> 41:    93.3408   -5.5437   -2.0344   -4.1042   -0.9078    0.1744    4.2286    4.2059    0.8228    2.8170    0.1881    0.3829    7.2734    1.5519
-#> 42:    93.1691   -5.4436   -2.0551   -4.1048   -0.8984    0.1732    4.0172    3.9956    0.7816    2.6762    0.1853    0.3637    6.9712    1.5332
-#> 43:    93.2443   -5.5247   -2.0722   -4.0980   -0.8992    0.1756    3.8163    3.7958    0.7781    2.7200    0.1956    0.3455    6.7012    1.5344
-#> 44:    92.9509   -5.5020   -2.0495   -4.0961   -0.8964    0.1777    3.6255    3.6060    0.7555    2.8172    0.1994    0.3283    6.2180    1.6137
-#> 45:    92.8898   -5.4913   -2.0462   -4.1079   -0.9003    0.1701    4.1177    3.4257    0.7491    2.8491    0.1989    0.3372    6.2876    1.6205
-#> 46:    92.6044   -5.6429   -2.0499   -4.1079   -0.9069    0.1999    4.2103    3.2544    0.7657    2.8491    0.1921    0.3532    6.2261    1.6435
-#> 47:    92.7740   -5.6128   -2.0804   -4.1186   -0.8976    0.1864    5.2188    3.0917    0.7381    2.9036    0.2030    0.3391    6.6803    1.6177
-#> 48:    92.4691   -5.6645   -2.0600   -4.1288   -0.8796    0.1913    6.2045    2.9371    0.7774    2.9223    0.1966    0.3396    6.7169    1.6215
-#> 49:    92.4128   -5.7079   -2.0802   -4.1166   -0.8798    0.1741    5.8943    3.1446    0.7854    2.8715    0.1935    0.3369    6.9151    1.4834
-#> 50:    91.8883   -5.7713   -2.0932   -4.0899   -0.8886    0.1758    5.5996    3.5478    0.8033    2.8192    0.2014    0.3201    7.0775    1.4635
-#> 51:    92.1187   -5.7306   -2.0903   -4.0878   -0.8923    0.2024    5.3196    3.6534    0.7823    2.7891    0.1969    0.3140    6.9879    1.5430
-#> 52:    92.3209   -5.7897   -2.0903   -4.1622   -0.9072    0.2261    5.3781    3.4707    0.8001    3.0801    0.2063    0.3088    6.7047    1.4499
-#> 53:    92.4318   -5.6954   -2.0950   -4.1866   -0.9082    0.2131    7.1200    3.2972    0.7711    3.3398    0.2034    0.3186    6.6152    1.5123
-#> 54:    92.5380   -5.6975   -2.0782   -4.2394   -0.8976    0.2118    6.7640    3.1323    0.7744    3.5385    0.2175    0.3296    6.4402    1.5403
-#> 55:    92.7213   -5.6663   -2.0427   -4.3288   -0.9028    0.2032    8.1796    2.9757    0.7748    4.4495    0.2142    0.3316    6.4111    1.5369
-#> 56:    92.7219   -5.6865   -2.0557   -4.3434   -0.9084    0.2021    7.7706    2.8269    0.7989    4.6691    0.2174    0.3433    6.4256    1.4639
-#> 57:    92.8932   -5.5736   -2.0497   -4.3955   -0.9216    0.1694    7.3821    2.6856    0.8205    4.9791    0.2142    0.3500    6.5378    1.5406
-#> 58:    92.9219   -5.5789   -2.0547   -4.3094   -0.9183    0.1838    7.0130    2.5513    0.7958    4.7302    0.2193    0.3495    6.2662    1.4940
-#> 59:    93.0432   -5.6201   -2.0395   -4.2527   -0.9199    0.2302    6.6623    2.4237    0.8241    4.4937    0.2241    0.3321    5.8693    1.6176
-#> 60:    92.9724   -5.5971   -2.0537   -4.3509   -0.9219    0.2118    7.5905    2.3026    0.8418    4.4546    0.2177    0.3155    5.5960    1.5040
-#> 61:    93.1235   -5.6332   -2.0671   -4.3572   -0.9219    0.1917    7.2521    2.3037    0.8527    4.5707    0.2230    0.2997    5.8136    1.4516
-#> 62:    93.5431   -5.6373   -2.0371   -4.3384   -0.9276    0.1997    8.5187    2.3895    0.8575    4.4378    0.2258    0.3041    5.5746    1.4572
-#> 63:    93.5009   -5.5634   -2.0224   -4.3560   -0.9339    0.2167    8.0927    2.2700    0.8462    4.4449    0.2266    0.3162    5.4922    1.5233
-#> 64:    93.7369   -5.6032   -2.0362   -4.2323   -0.9355    0.2159    9.6684    2.1949    0.8514    4.2227    0.2300    0.3318    5.7597    1.4866
-#> 65:    93.5021   -5.5769   -2.0311   -4.3204   -0.9375    0.1927    9.5537    2.0852    0.8559    4.6151    0.2208    0.3550    5.6975    1.5031
-#> 66:    93.4211   -5.7184   -2.0384   -4.3041   -0.9228    0.2121    9.0760    2.6390    0.8430    4.3843    0.2098    0.3755    5.8990    1.5133
-#> 67:    93.3435   -5.6579   -2.0456   -4.2222   -0.9183    0.1825    8.6222    2.5071    0.8719    4.1651    0.2152    0.3567    5.9004    1.4874
-#> 68:    93.3914   -5.6554   -2.0420   -4.1618   -0.9303    0.1714    8.1911    2.3817    0.8856    3.9569    0.2272    0.3388    6.1793    1.4917
-#> 69:    93.5112   -5.6834   -2.0349   -4.1591   -0.9331    0.1759    8.9900    2.5191    0.9184    3.7590    0.2236    0.3219    6.1618    1.4697
-#> 70:    93.4289   -5.6576   -2.0273   -4.1763   -0.9399    0.1738    8.5405    2.4302    0.8725    3.5711    0.2149    0.3288    6.5324    1.5410
-#> 71:    93.2936   -5.6699   -2.0256   -4.1405   -0.9370    0.1922    8.1134    2.3831    0.8289    3.3925    0.2080    0.3548    5.9794    1.5904
-#> 72:    92.9152   -5.6742   -2.0382   -4.1523   -0.9411    0.1991    7.7078    2.4322    0.7875    3.2916    0.2007    0.3456    6.0999    1.6022
-#> 73:    92.8129   -5.8099   -2.0372   -4.1735   -0.9377    0.1605    8.2752    2.8931    0.7737    3.4015    0.2057    0.3283    6.0140    1.5472
-#> 74:    92.7806   -5.7269   -2.0315   -4.1877   -0.9399    0.1675    8.4688    2.7484    0.7773    3.4620    0.2174    0.3249    5.8495    1.5779
-#> 75:    92.9128   -5.8680   -2.0304   -4.1459   -0.9387    0.1567    8.0454    3.2365    0.7681    3.2935    0.2198    0.3187    5.8539    1.5815
-#> 76:    92.8931   -5.8483   -2.0253   -4.1815   -0.9387    0.1540    9.6800    3.0747    0.8007    3.5838    0.2198    0.3291    5.9005    1.5053
-#> 77:    92.7474   -5.7995   -2.0202   -4.1904   -0.9333    0.1724   10.0488    2.9210    0.7841    3.7255    0.2148    0.3465    5.9418    1.5569
-#> 78:    92.8150   -5.9608   -2.0025   -4.1583   -0.9511    0.1566    9.5464    3.5249    0.7858    3.6988    0.2246    0.3292    5.7737    1.5904
-#> 79:    92.6663   -6.0485   -2.0245   -4.1437   -0.9446    0.1786    9.0690    4.1252    0.7803    3.6526    0.2155    0.3335    5.9109    1.5521
-#> 80:    92.5932   -6.1001   -2.0304   -4.1969   -0.9409    0.1424    8.6156    4.6478    0.8007    4.0379    0.2114    0.3168    6.1732    1.5544
-#> 81:    92.6789   -6.3510   -2.0062   -4.2272   -0.9541    0.1360    8.3363    5.9861    0.7719    3.8800    0.2202    0.3010    5.6841    1.6317
-#> 82:    92.9996   -6.5680   -2.0048   -4.1609   -0.9578    0.1367   10.6901    7.4391    0.7962    3.6860    0.2092    0.2859    5.7335    1.6391
-#> 83:    93.1087   -6.5298   -1.9757   -4.1694   -0.9596    0.1323   10.5524    7.4660    0.8237    3.8009    0.2134    0.2716    5.9664    1.6316
-#> 84:    93.1929   -6.5844   -2.0191   -4.2021   -0.9616    0.1384   10.0248    7.7313    0.8230    3.6109    0.2110    0.2580    5.7854    1.5609
-#> 85:    92.9161   -6.4934   -2.0281   -4.2008   -0.9600    0.1107    9.5236    7.4269    0.8448    3.5630    0.2110    0.2451    5.6111    1.5333
-#> 86:    92.9816   -6.5397   -2.0234   -4.1830   -0.9694    0.1111    9.1945    7.4382    0.8481    3.3849    0.2166    0.2329    5.8375    1.5263
-#> 87:    93.0930   -6.5749   -2.0168   -4.1986   -0.9816    0.0926    8.7348    8.4431    0.8646    3.3032    0.2155    0.2212    5.7542    1.5736
-#> 88:    93.0765   -6.4914   -2.0274   -4.2274   -0.9870    0.1148    8.4666    8.0209    0.8666    3.5292    0.2048    0.2102    5.8988    1.5329
-#> 89:    92.8699   -6.6431   -2.0199   -4.2175   -0.9463    0.1011    8.4648    7.7973    0.8908    3.3980    0.1945    0.2102    5.6876    1.5177
-#> 90:    92.8225   -6.6932   -2.0211   -4.2175   -0.9505    0.0887   10.1862    8.7787    0.8730    3.3980    0.1877    0.1997    5.9135    1.4821
-#> 91:    92.7874   -6.7007   -2.0420   -4.2936   -0.9468    0.0927   11.2275    8.3397    0.8600    3.9490    0.1885    0.2147    6.1108    1.4315
-#> 92:    93.2320   -6.8088   -2.0341   -4.2817   -0.9582    0.1270   12.4029    9.6204    0.8503    3.7516    0.1950    0.2070    5.9434    1.5251
-#> 93:    93.8996   -6.5471   -2.0440   -4.2123   -0.9543    0.1140   11.7828    9.1394    0.8493    3.5640    0.1988    0.2017    6.1302    1.5568
-#> 94:    93.4416   -6.4623   -2.0448   -4.2188   -0.9595    0.1174   12.1277    8.6824    0.8568    3.3858    0.1975    0.1938    5.9173    1.5204
-#> 95:    93.2953   -6.1521   -2.0477   -4.2216   -0.9551    0.1152   11.5213    8.2483    0.8356    3.2165    0.1979    0.1855    5.8298    1.5357
-#> 96:    92.9577   -6.0477   -2.0579   -4.2534   -0.9465    0.1284   10.9452    7.8359    0.8202    3.3357    0.1937    0.1917    5.8590    1.5738
-#> 97:    92.8703   -6.1037   -2.0745   -4.1960   -0.9405    0.1417   10.4858    7.4441    0.8488    3.1690    0.1969    0.2016    5.7948    1.4759
-#> 98:    92.9728   -6.3534   -2.0868   -4.2155   -0.9444    0.1069    9.9615    7.1788    0.8736    3.1913    0.1998    0.2114    5.6533    1.4322
-#> 99:    93.4116   -6.1712   -2.0837   -4.2280   -0.9473    0.1197    9.4634    6.8198    0.8959    3.1806    0.1899    0.2167    5.9149    1.3768
-#> 100:    93.2598   -6.1345   -2.0645   -4.2237   -0.9575    0.1099    8.9903    6.4788    0.9204    3.2429    0.1903    0.2058    5.7085    1.4133
-#> 101:    93.3082   -6.1574   -2.0474   -4.2315   -0.9619    0.1161    9.0819    6.1549    0.8744    3.2049    0.1891    0.2278    5.6493    1.4894
-#> 102:    93.5741   -6.2923   -2.0484   -4.2853   -0.9665    0.1325   10.4108    5.8522    0.8804    3.5370    0.2024    0.2324    5.6995    1.4594
-#> 103:    92.9199   -6.1797   -2.0522   -4.2940   -0.9568    0.1289    9.8903    5.5596    0.8722    3.6682    0.1975    0.2398    5.5536    1.4510
-#> 104:    93.1139   -6.1630   -2.0546   -4.2912   -0.9613    0.1115    9.3958    5.2816    0.8648    3.6673    0.2010    0.2278    5.5768    1.4812
-#> 105:    93.4085   -6.0359   -2.0450   -4.2889   -0.9591    0.1258    8.9260    5.0175    0.8412    3.7286    0.1917    0.2171    5.6780    1.5203
-#> 106:    93.3103   -6.1029   -2.0425   -4.2948   -0.9579    0.0934    8.4797    4.7667    0.8539    3.6947    0.1947    0.2234    5.7210    1.4760
-#> 107:    93.6389   -5.9750   -2.0309   -4.2630   -0.9660    0.1110    8.0557    4.5283    0.8470    3.5100    0.2044    0.2299    5.6280    1.5525
-#> 108:    93.8641   -5.8551   -2.0360   -4.2311   -0.9629    0.0900    7.6529    4.3019    0.8567    3.3345    0.2014    0.2302    5.7841    1.5978
-#> 109:    93.6274   -6.0268   -2.0445   -4.3047   -0.9488    0.0979    7.2703    4.7807    0.8565    3.7665    0.1929    0.2271    5.7941    1.5580
-#> 110:    93.6320   -5.8321   -2.0413   -4.2855   -0.9477    0.1143    6.9068    4.5417    0.8412    3.6165    0.1901    0.2199    5.8169    1.5477
-#> 111:    93.6245   -5.8256   -2.0157   -4.2797   -0.9612    0.0940    6.5774    4.3146    0.8460    3.5782    0.1837    0.2182    5.6157    1.6424
-#> 112:    93.8512   -5.9045   -2.0116   -4.2409   -0.9708    0.0883    6.2486    4.0989    0.8658    3.5059    0.1761    0.2073    5.8852    1.6073
-#> 113:    93.7080   -5.9935   -2.0306   -4.1884   -0.9690    0.0740    5.9361    4.0088    0.9072    3.3400    0.1957    0.2169    6.3792    1.4770
-#> 114:    93.8574   -5.9185   -2.0233   -4.2030   -0.9588    0.1137    5.6393    3.8084    0.9322    3.2878    0.1939    0.2098    5.8891    1.5325
-#> 115:    93.7414   -5.8789   -2.0183   -4.2256   -0.9701    0.1105    5.6148    3.6180    0.9222    3.5507    0.1921    0.1993    5.6441    1.5458
-#> 116:    93.4104   -5.9704   -2.0428   -4.2091   -0.9807    0.1099    5.3341    4.1157    0.9363    3.4004    0.1968    0.2134    5.7764    1.4617
-#> 117:    93.5239   -5.9057   -2.0518   -4.2494   -0.9812    0.1127    6.8839    3.9099    0.9151    3.6604    0.1921    0.2095    5.4753    1.4249
-#> 118:    93.7599   -5.9418   -2.0482   -4.2272   -0.9822    0.1094    6.8133    3.7144    0.9198    3.5160    0.1971    0.2039    5.6467    1.4116
-#> 119:    93.6617   -6.0020   -2.0483   -4.2146   -0.9816    0.1003    6.4727    3.8251    0.9103    3.4716    0.1950    0.2109    5.8513    1.4268
-#> 120:    93.5436   -5.9804   -2.0458   -4.1906   -0.9819    0.1065    6.1490    3.6756    0.9088    3.2980    0.1989    0.2123    5.8268    1.4689
-#> 121:    93.4880   -5.9047   -2.0452   -4.1957   -0.9640    0.1349    5.8416    3.4918    0.8824    3.2437    0.1889    0.2017    5.7152    1.4382
-#> 122:    93.7406   -5.9844   -2.0596   -4.2328   -0.9558    0.1563    5.5495    3.7606    0.8489    3.3043    0.1795    0.2015    5.5095    1.5112
-#> 123:    93.6728   -6.0394   -2.0372   -4.2812   -0.9592    0.1507    5.2720    4.2004    0.8341    3.5274    0.1817    0.2008    5.6936    1.6011
-#> 124:    93.9591   -6.0483   -2.0280   -4.2613   -0.9594    0.1463    5.3846    4.1913    0.8351    3.4341    0.1870    0.2193    5.5694    1.5684
-#> 125:    94.0201   -5.9102   -2.0507   -4.2686   -0.9697    0.1455    5.1154    3.9818    0.8512    3.3475    0.1859    0.2165    5.6224    1.5643
-#> 126:    93.8825   -5.8970   -2.0543   -4.2569   -0.9663    0.1493    4.9144    3.7827    0.8907    3.3030    0.1876    0.2180    5.7351    1.4722
-#> 127:    93.9893   -5.8955   -2.0624   -4.2430   -0.9802    0.1476    7.2413    3.5935    0.8915    3.2740    0.1851    0.2110    5.7614    1.4305
-#> 128:    94.1849   -5.9123   -2.0624   -4.2385   -0.9786    0.1523    7.9575    3.4139    0.9094    3.2656    0.1807    0.2198    5.7366    1.4264
-#> 129:    94.0812   -6.0044   -2.0696   -4.3056   -0.9770    0.1693    8.7809    3.7526    0.9111    3.6172    0.1859    0.2255    5.8064    1.4718
-#> 130:    93.6046   -6.1387   -2.0718   -4.3056   -0.9821    0.1477    8.3419    4.3029    0.9177    3.6172    0.1867    0.2143    5.8893    1.4447
-#> 131:    93.5216   -6.1347   -2.0740   -4.3114   -0.9766    0.1288    8.2937    4.3407    0.9250    3.5298    0.1881    0.2293    5.8054    1.4219
-#> 132:    93.6142   -6.2789   -2.0786   -4.3297   -0.9716    0.1288    8.3731    5.1225    0.9236    3.6683    0.1929    0.2295    5.8064    1.4194
-#> 133:    93.4410   -5.9177   -2.0916   -4.3557   -0.9798    0.1066    7.9544    4.8663    0.9537    3.7076    0.1937    0.2279    5.9844    1.4297
-#> 134:    93.4716   -5.9152   -2.0838   -4.3611   -0.9818    0.1332    7.5567    4.6230    0.9161    3.7833    0.2017    0.2308    6.0611    1.5717
-#> 135:    93.3787   -6.0381   -2.0728   -4.2627   -0.9719    0.1051    7.2396    4.3919    0.8970    3.5941    0.1916    0.2193    5.8837    1.6057
-#> 136:    93.4339   -5.9876   -2.0801   -4.3002   -0.9690    0.1214    6.8776    4.1723    0.8888    3.4144    0.2002    0.2227    6.0141    1.5231
-#> 137:    93.7639   -6.0411   -2.0803   -4.2799   -0.9646    0.1484    6.5337    3.9765    0.8969    3.2437    0.1995    0.2115    5.9404    1.6402
-#> 138:    93.6414   -6.0122   -2.0714   -4.2666   -0.9755    0.1506    7.4057    3.7962    0.9242    3.1524    0.1934    0.2010    6.0666    1.5001
-#> 139:    93.7743   -5.7966   -2.0613   -4.2289   -0.9722    0.1383    7.9358    3.6064    0.9015    2.9948    0.1946    0.2029    5.9655    1.5250
-#> 140:    93.1082   -5.7994   -2.0388   -4.2289   -0.9659    0.1382    8.0282    3.4261    0.9053    2.9079    0.1909    0.2138    5.9183    1.5191
-#> 141:    93.2122   -6.0181   -2.0396   -4.2398   -0.9587    0.1016    8.9769    3.9426    0.9028    2.9136    0.1941    0.2195    6.1560    1.4902
-#> 142:    93.4684   -6.1438   -2.0273   -4.2541   -0.9508    0.0848    8.5281    4.8727    0.9056    2.9875    0.1901    0.2233    6.2546    1.4695
-#> 143:    93.0059   -6.0964   -2.0145   -4.2760   -0.9563    0.0826    8.1017    4.6291    0.9312    3.1063    0.1850    0.2138    6.5768    1.4391
-#> 144:    93.0612   -6.1127   -1.9951   -4.2589   -0.9539    0.0904    7.6966    4.6160    0.9623    3.1681    0.1824    0.2032    6.1506    1.4497
-#> 145:    93.5170   -6.1066   -1.9951   -4.3574   -0.9478    0.1040    7.3118    4.6263    0.9639    3.6914    0.1986    0.2292    5.9389    1.4867
-#> 146:    93.4915   -6.3235   -2.0006   -4.3866   -0.9579    0.1202    6.9462    6.0529    0.9514    3.9899    0.1887    0.2335    5.9265    1.4978
-#> 147:    93.8963   -6.1119   -2.0055   -4.3446   -0.9682    0.1242    7.1711    5.7503    0.9315    3.7904    0.1923    0.2332    5.9346    1.5021
-#> 148:    93.6758   -5.9705   -2.0137   -4.2906   -0.9614    0.1125    6.8125    5.4628    0.9506    3.6009    0.1913    0.2371    6.2579    1.4384
-#> 149:    93.6499   -6.0049   -2.0246   -4.2730   -0.9776    0.0996    6.4719    5.1896    0.9736    3.4209    0.1817    0.2252    6.3224    1.3878
-#> 150:    94.0242   -5.9760   -2.0176   -4.2182   -0.9773    0.1032    6.1483    4.9301    0.9944    3.2498    0.1807    0.2290    6.5662    1.3618
-#> 151:    93.9234   -5.8772   -2.0132   -4.2362   -0.9651    0.1058    7.2453    4.6836    0.9824    3.4860    0.1806    0.2175    6.2575    1.4370
-#> 152:    94.2513   -5.9391   -2.0814   -4.2278   -0.9753    0.1221    4.9753    3.4013    0.9808    3.3265    0.1836    0.1897    6.6966    1.3457
-#> 153:    93.9434   -6.1294   -2.0570   -4.2447   -0.9761    0.1527    5.0454    4.3115    0.9494    3.3663    0.1684    0.1680    5.9106    1.4777
-#> 154:    93.8141   -6.2749   -2.0366   -4.2383   -0.9835    0.1440    5.5466    5.3351    0.9320    3.3337    0.1731    0.1913    5.8842    1.4325
-#> 155:    94.1987   -6.1029   -2.0252   -4.2520   -0.9780    0.1132    7.1508    4.2713    0.9457    3.3428    0.1727    0.1691    6.1632    1.4658
-#> 156:    94.0626   -6.2640   -2.0263   -4.2461   -0.9854    0.1346    5.6296    5.1645    0.9423    3.3987    0.1697    0.1778    5.9631    1.4483
-#> 157:    93.9319   -6.1392   -2.0388   -4.2294   -0.9921    0.1265    5.6768    4.7366    0.9210    3.3673    0.1733    0.1789    5.9114    1.4976
-#> 158:    93.9123   -6.1970   -2.0165   -4.2241   -0.9924    0.1540    7.2552    4.7537    0.9369    3.2727    0.1805    0.1923    5.9324    1.5351
-#> 159:    93.9704   -6.4018   -2.0455   -4.2127   -0.9919    0.1413    7.7561    6.0732    0.9802    3.3376    0.1806    0.2260    6.4511    1.4227
-#> 160:    94.1967   -6.2985   -2.0412   -4.2264   -0.9795    0.1206    8.3836    6.1319    0.9689    3.4685    0.1792    0.2150    6.5116    1.4706
-#> 161:    94.3500   -6.1427   -2.0189   -4.2242   -1.0022    0.0837    8.0282    4.5505    0.9524    3.3269    0.1859    0.1816    6.0642    1.4746
-#> 162:    94.2711   -5.9578   -2.0215   -4.2078   -1.0110    0.0946    7.8634    3.3072    0.9559    3.2374    0.1876    0.1791    6.0798    1.4903
-#> 163:    93.9824   -5.8794   -2.0409   -4.2367   -0.9970    0.1150    9.3872    3.0498    0.9830    3.3179    0.1880    0.1828    5.8091    1.4852
-#> 164:    94.2013   -5.8651   -2.0122   -4.2257   -0.9906    0.1267    7.1953    3.0510    0.9697    3.2713    0.1871    0.1832    5.8741    1.5313
-#> 165:    94.1804   -5.7868   -2.0200   -4.2053   -0.9812    0.1219    6.7375    2.4769    0.9688    3.2706    0.1910    0.1859    5.7890    1.5188
-#> 166:    93.9790   -5.8156   -2.0311   -4.2438   -0.9784    0.1247    5.7617    2.6907    0.9533    3.5342    0.1953    0.1872    5.8816    1.5243
-#> 167:    93.2524   -5.8603   -2.0497   -4.2594   -0.9787    0.1265    4.7086    2.9121    0.9117    3.4696    0.1943    0.1832    5.9672    1.4567
-#> 168:    93.2924   -6.0371   -2.0528   -4.2607   -0.9727    0.1201    5.5273    4.0286    0.9177    3.4501    0.1918    0.1908    5.7790    1.4701
-#> 169:    93.4838   -6.1497   -2.0389   -4.2716   -0.9639    0.1127    5.4524    4.2700    0.9544    3.4329    0.1940    0.1871    5.7795    1.4575
-#> 170:    93.3951   -6.2298   -2.0438   -4.4133   -0.9939    0.1088    6.1460    4.6552    0.9645    4.5240    0.1978    0.2091    5.7549    1.5233
-#> 171:    93.4113   -6.1187   -2.0536   -4.4019   -0.9771    0.0899    6.8123    4.0073    0.9531    4.4290    0.1878    0.1970    5.9067    1.4857
-#> 172:    93.1140   -5.9515   -2.0530   -4.3250   -0.9723    0.1094    5.1247    3.4502    0.9572    3.8504    0.1954    0.1944    5.8583    1.4867
-#> 173:    92.9782   -6.0415   -2.0633   -4.2887   -0.9608    0.1081    4.1020    3.8967    0.9478    3.7222    0.1890    0.1812    5.9473    1.4583
-#> 174:    92.9661   -5.9295   -2.0457   -4.2907   -0.9626    0.0991    5.7954    3.3581    0.9785    3.7311    0.1867    0.2026    5.8087    1.4797
-#> 175:    93.2577   -5.8895   -2.0281   -4.2845   -0.9560    0.0829    7.3434    3.1501    0.9975    3.6334    0.1920    0.2151    5.4717    1.4832
-#> 176:    93.1210   -5.9567   -2.0370   -4.2848   -0.9488    0.0787    6.8946    3.4999    0.9983    3.6159    0.1922    0.2233    5.8426    1.4096
-#> 177:    92.5456   -6.1797   -2.0319   -4.2684   -0.9401    0.0873    6.9744    5.2939    0.9928    3.4880    0.1989    0.2213    5.9613    1.4367
-#> 178:    92.6854   -6.1483   -2.0278   -4.2705   -0.9504    0.0630    5.0582    5.0622    0.9953    3.4915    0.1930    0.2238    5.9775    1.4263
-#> 179:    93.1323   -6.1739   -2.0353   -4.2590   -0.9455    0.0584    4.9914    4.7898    0.9817    3.4163    0.1899    0.2124    5.9579    1.4242
-#> 180:    93.0611   -6.2228   -2.0441   -4.2977   -0.9387    0.0320    4.0323    5.5685    0.9890    3.7202    0.1940    0.2335    6.2224    1.4194
-#> 181:    92.7741   -6.1462   -2.0477   -4.3335   -0.9454    0.1011    3.7007    5.1590    0.9807    3.8469    0.1939    0.2463    5.9703    1.4343
-#> 182:    93.0775   -6.0640   -2.0496   -4.3171   -0.9444    0.0897    5.0266    4.5597    0.9792    3.7741    0.1931    0.2186    5.6727    1.4858
-#> 183:    93.2566   -6.1757   -2.0368   -4.2888   -0.9560    0.0809    5.8284    5.2504    0.9636    3.7078    0.1939    0.2262    5.5170    1.4560
-#> 184:    93.0357   -6.1158   -2.0217   -4.3111   -0.9453    0.0901    6.7209    5.4048    0.9503    3.8949    0.1967    0.2209    5.3578    1.4704
-#> 185:    93.0173   -6.1998   -2.0371   -4.3713   -0.9451    0.0752    6.1040    5.8272    0.9333    4.4038    0.1951    0.2238    5.5896    1.4202
-#> 186:    93.2835   -6.1217   -2.0383   -4.3308   -0.9574    0.1110    6.0519    4.7669    0.9400    4.0265    0.1972    0.2274    5.4560    1.4602
-#> 187:    93.5312   -6.3356   -2.0253   -4.3418   -0.9583    0.1166    6.7561    5.8784    0.9346    4.0264    0.2038    0.2281    5.5024    1.4994
-#> 188:    93.6460   -5.8426   -2.0237   -4.4519   -0.9594    0.1283    6.3492    3.4189    0.9091    4.9358    0.2086    0.2348    5.4301    1.5893
-#> 189:    93.8538   -6.0183   -2.0178   -4.3911   -0.9797    0.1262    8.7939    3.7358    0.9008    4.4894    0.2125    0.2199    5.6613    1.5073
-#> 190:    93.1543   -6.1364   -2.0451   -4.4389   -0.9708    0.1584    9.9803    4.2747    0.8922    4.8507    0.2084    0.2607    5.9136    1.4572
-#> 191:    93.4334   -6.1466   -2.0389   -4.4661   -0.9678    0.1565    7.8390    4.4393    0.9022    4.7857    0.2105    0.2634    5.7161    1.5325
-#> 192:    93.3623   -6.0940   -2.0240   -4.4569   -0.9673    0.1420    8.0856    4.3185    0.8895    4.4721    0.2113    0.2350    5.5282    1.5221
-#> 193:    93.1990   -5.9864   -2.0301   -4.4538   -0.9563    0.1515    8.4425    3.7598    0.8814    4.4376    0.2013    0.2257    5.4205    1.4820
-#> 194:    93.3165   -6.0045   -2.0353   -4.4314   -0.9525    0.1486    8.2370    3.6742    0.8947    4.4594    0.1960    0.2248    5.4579    1.4767
-#> 195:    93.1288   -6.1006   -2.0551   -4.5184   -0.9503    0.1583    9.6259    4.2294    0.9040    5.1981    0.1950    0.1962    5.5602    1.4254
-#> 196:    93.1943   -5.9871   -2.0607   -4.4728   -0.9446    0.1482    9.3401    3.5579    0.8925    4.7901    0.1892    0.1879    5.7296    1.4172
-#> 197:    93.5803   -5.9131   -2.0522   -4.3675   -0.9476    0.1571    7.2599    3.4241    0.8857    3.8551    0.1886    0.1793    5.4832    1.6006
-#> 198:    93.5703   -5.9980   -2.0550   -4.3578   -0.9519    0.1491    7.0416    3.8805    0.8563    3.7930    0.1882    0.1896    5.4355    1.5402
-#> 199:    93.2909   -5.8288   -2.0532   -4.3605   -0.9518    0.1692    8.3926    3.0173    0.8566    3.8610    0.1902    0.2033    5.5735    1.5647
-#> 200:    93.4049   -5.7474   -2.0447   -4.3548   -0.9517    0.1812    7.4977    2.8256    0.8520    3.8236    0.1897    0.2060    5.5092    1.5699
-#> 201:    93.3386   -5.8209   -2.0398   -4.4174   -0.9597    0.1738    6.3555    3.0871    0.8431    4.3211    0.1853    0.2062    5.5460    1.5925
-#> 202:    93.3397   -5.8313   -2.0387   -4.4364   -0.9580    0.1669    6.0946    3.1018    0.8460    4.5093    0.1821    0.2068    5.6622    1.5740
-#> 203:    93.3071   -5.8276   -2.0384   -4.4758   -0.9571    0.1639    5.7815    3.0575    0.8608    4.9441    0.1826    0.2052    5.6855    1.5570
-#> 204:    93.3138   -5.8477   -2.0368   -4.4714   -0.9541    0.1658    5.7526    3.1322    0.8704    4.9129    0.1816    0.2057    5.6642    1.5606
-#> 205:    93.3066   -5.8537   -2.0395   -4.4842   -0.9521    0.1642    5.6045    3.1633    0.8748    5.0053    0.1805    0.2036    5.6633    1.5550
-#> 206:    93.3042   -5.8790   -2.0453   -4.4977   -0.9501    0.1633    5.7219    3.3320    0.8807    5.1121    0.1793    0.1999    5.6888    1.5413
-#> 207:    93.3281   -5.9005   -2.0504   -4.5109   -0.9480    0.1629    5.8004    3.4696    0.8865    5.2248    0.1789    0.1961    5.7206    1.5357
-#> 208:    93.3437   -5.8972   -2.0569   -4.5200   -0.9452    0.1641    5.7523    3.4604    0.8875    5.2848    0.1787    0.1933    5.7450    1.5288
-#> 209:    93.3265   -5.8864   -2.0628   -4.5092   -0.9440    0.1639    5.5355    3.4138    0.8882    5.1586    0.1791    0.1916    5.7744    1.5283
-#> 210:    93.3087   -5.8812   -2.0671   -4.5004   -0.9426    0.1677    5.3488    3.3975    0.8895    5.0589    0.1798    0.1924    5.7781    1.5307
-#> 211:    93.2807   -5.8760   -2.0703   -4.5009   -0.9413    0.1709    5.2654    3.3770    0.8894    5.0377    0.1805    0.1927    5.7808    1.5282
-#> 212:    93.2815   -5.8637   -2.0711   -4.4955   -0.9409    0.1708    5.3028    3.3250    0.8914    4.9702    0.1819    0.1941    5.7827    1.5274
-#> 213:    93.2828   -5.8481   -2.0709   -4.4895   -0.9396    0.1702    5.3840    3.2614    0.8913    4.9108    0.1826    0.1953    5.7744    1.5301
-#> 214:    93.2645   -5.8422   -2.0704   -4.4882   -0.9384    0.1710    5.3939    3.2358    0.8931    4.8944    0.1828    0.1955    5.7797    1.5351
-#> 215:    93.2591   -5.8519   -2.0709   -4.4858   -0.9380    0.1713    5.5142    3.2959    0.8953    4.8587    0.1822    0.1960    5.7853    1.5369
-#> 216:    93.2595   -5.8523   -2.0715   -4.4827   -0.9376    0.1723    5.5563    3.3077    0.8964    4.8306    0.1817    0.1973    5.7975    1.5396
-#> 217:    93.2503   -5.8512   -2.0732   -4.4737   -0.9373    0.1734    5.5036    3.3182    0.8959    4.7582    0.1817    0.1992    5.7940    1.5365
-#> 218:    93.2345   -5.8463   -2.0749   -4.4639   -0.9372    0.1747    5.5046    3.2959    0.8959    4.6771    0.1817    0.2008    5.7889    1.5340
-#> 219:    93.2264   -5.8439   -2.0757   -4.4549   -0.9364    0.1759    5.4970    3.2802    0.8966    4.6015    0.1819    0.2027    5.7804    1.5321
-#> 220:    93.2259   -5.8464   -2.0758   -4.4493   -0.9363    0.1771    5.4793    3.2944    0.8950    4.5498    0.1823    0.2049    5.7745    1.5344
-#> 221:    93.2243   -5.8505   -2.0768   -4.4443   -0.9367    0.1785    5.5360    3.3132    0.8924    4.5028    0.1829    0.2068    5.7556    1.5329
-#> 222:    93.2385   -5.8603   -2.0776   -4.4371   -0.9376    0.1800    5.5401    3.3878    0.8903    4.4416    0.1834    0.2096    5.7522    1.5317
-#> 223:    93.2339   -5.8634   -2.0780   -4.4309   -0.9377    0.1803    5.5522    3.4132    0.8882    4.3844    0.1838    0.2118    5.7457    1.5323
-#> 224:    93.2379   -5.8686   -2.0778   -4.4262   -0.9374    0.1803    5.5469    3.4421    0.8848    4.3375    0.1842    0.2137    5.7429    1.5323
-#> 225:    93.2329   -5.8654   -2.0784   -4.4222   -0.9373    0.1811    5.5553    3.4255    0.8843    4.2952    0.1848    0.2160    5.7452    1.5295
-#> 226:    93.2330   -5.8621   -2.0789   -4.4182   -0.9366    0.1816    5.5838    3.4123    0.8838    4.2565    0.1858    0.2176    5.7453    1.5284
-#> 227:    93.2309   -5.8549   -2.0794   -4.4153   -0.9365    0.1823    5.6720    3.3787    0.8827    4.2227    0.1866    0.2181    5.7339    1.5287
-#> 228:    93.2248   -5.8556   -2.0794   -4.4116   -0.9372    0.1832    5.7344    3.3780    0.8830    4.1863    0.1873    0.2200    5.7232    1.5308
-#> 229:    93.2215   -5.8615   -2.0798   -4.4081   -0.9373    0.1844    5.8478    3.4087    0.8821    4.1558    0.1878    0.2217    5.7174    1.5283
-#> 230:    93.2122   -5.8646   -2.0807   -4.4053   -0.9372    0.1858    5.8987    3.4233    0.8800    4.1288    0.1881    0.2233    5.7073    1.5272
-#> 231:    93.2080   -5.8665   -2.0816   -4.4025   -0.9372    0.1872    5.9544    3.4381    0.8782    4.1008    0.1883    0.2250    5.7006    1.5283
-#> 232:    93.1921   -5.8677   -2.0829   -4.3997   -0.9370    0.1887    5.9768    3.4440    0.8770    4.0748    0.1883    0.2268    5.7012    1.5261
-#> 233:    93.1794   -5.8674   -2.0840   -4.3972   -0.9363    0.1892    6.0074    3.4397    0.8757    4.0495    0.1884    0.2281    5.6997    1.5235
-#> 234:    93.1623   -5.8677   -2.0853   -4.3959   -0.9358    0.1898    5.9759    3.4442    0.8750    4.0330    0.1887    0.2295    5.7000    1.5223
-#> 235:    93.1499   -5.8709   -2.0862   -4.3918   -0.9356    0.1900    5.9951    3.4709    0.8747    4.0020    0.1891    0.2309    5.7002    1.5219
-#> 236:    93.1408   -5.8764   -2.0875   -4.3879   -0.9349    0.1898    6.0359    3.5027    0.8752    3.9720    0.1895    0.2321    5.7098    1.5196
-#> 237:    93.1307   -5.8766   -2.0887   -4.3843   -0.9344    0.1896    6.0589    3.5108    0.8755    3.9437    0.1900    0.2330    5.7176    1.5174
-#> 238:    93.1233   -5.8767   -2.0889   -4.3806   -0.9341    0.1891    6.0959    3.5158    0.8745    3.9173    0.1907    0.2339    5.7198    1.5169
-#> 239:    93.1245   -5.8810   -2.0889   -4.3775   -0.9337    0.1885    6.1196    3.5614    0.8746    3.8935    0.1915    0.2349    5.7177    1.5172
-#> 240:    93.1180   -5.8836   -2.0893   -4.3745   -0.9332    0.1883    6.1647    3.6004    0.8741    3.8709    0.1921    0.2360    5.7150    1.5192
-#> 241:    93.1096   -5.8838   -2.0898   -4.3714   -0.9327    0.1883    6.2283    3.6196    0.8743    3.8487    0.1927    0.2366    5.7177    1.5202
-#> 242:    93.1058   -5.8804   -2.0912   -4.3684   -0.9320    0.1888    6.2553    3.6018    0.8723    3.8274    0.1933    0.2378    5.7265    1.5198
-#> 243:    93.0953   -5.8762   -2.0924   -4.3668   -0.9315    0.1892    6.2692    3.5785    0.8705    3.8130    0.1940    0.2391    5.7353    1.5205
-#> 244:    93.0840   -5.8758   -2.0928   -4.3658   -0.9310    0.1889    6.2702    3.5746    0.8695    3.8007    0.1947    0.2401    5.7382    1.5205
-#> 245:    93.0720   -5.8795   -2.0933   -4.3647   -0.9306    0.1895    6.3022    3.5971    0.8685    3.7886    0.1953    0.2407    5.7367    1.5192
-#> 246:    93.0626   -5.8798   -2.0933   -4.3637   -0.9301    0.1898    6.2987    3.5992    0.8680    3.7781    0.1957    0.2410    5.7331    1.5184
-#> 247:    93.0526   -5.8805   -2.0934   -4.3610   -0.9298    0.1903    6.3067    3.6060    0.8682    3.7618    0.1963    0.2414    5.7329    1.5189
-#> 248:    93.0481   -5.8780   -2.0933   -4.3583   -0.9296    0.1911    6.3135    3.6007    0.8683    3.7460    0.1967    0.2420    5.7344    1.5191
-#> 249:    93.0483   -5.8762   -2.0933   -4.3558   -0.9294    0.1913    6.3095    3.5961    0.8685    3.7298    0.1970    0.2422    5.7414    1.5179
-#> 250:    93.0520   -5.8768   -2.0931   -4.3538   -0.9292    0.1912    6.2900    3.6003    0.8692    3.7176    0.1973    0.2424    5.7547    1.5148
-#> 251:    93.0430   -5.8769   -2.0930   -4.3516   -0.9291    0.1905    6.2815    3.6041    0.8704    3.7045    0.1975    0.2427    5.7653    1.5123
-#> 252:    93.0300   -5.8743   -2.0928   -4.3490   -0.9291    0.1901    6.2896    3.5885    0.8716    3.6919    0.1978    0.2428    5.7797    1.5106
-#> 253:    93.0217   -5.8740   -2.0926   -4.3468   -0.9289    0.1898    6.3238    3.5875    0.8731    3.6817    0.1981    0.2429    5.7885    1.5102
-#> 254:    93.0147   -5.8729   -2.0924   -4.3439   -0.9289    0.1892    6.3418    3.5857    0.8732    3.6683    0.1980    0.2426    5.7912    1.5102
-#> 255:    93.0144   -5.8743   -2.0922   -4.3407   -0.9290    0.1885    6.3755    3.5933    0.8735    3.6580    0.1979    0.2420    5.7932    1.5086
-#> 256:    93.0136   -5.8778   -2.0919   -4.3376   -0.9290    0.1876    6.3932    3.6240    0.8741    3.6481    0.1980    0.2418    5.7969    1.5066
-#> 257:    93.0116   -5.8792   -2.0917   -4.3345   -0.9291    0.1862    6.4096    3.6459    0.8744    3.6385    0.1980    0.2414    5.7990    1.5065
-#> 258:    93.0084   -5.8812   -2.0913   -4.3319   -0.9290    0.1842    6.4231    3.6686    0.8753    3.6281    0.1980    0.2414    5.8024    1.5050
-#> 259:    93.0090   -5.8866   -2.0909   -4.3293   -0.9287    0.1825    6.4361    3.7063    0.8762    3.6181    0.1981    0.2413    5.8106    1.5030
-#> 260:    93.0067   -5.8911   -2.0902   -4.3265   -0.9283    0.1811    6.4128    3.7384    0.8765    3.6076    0.1981    0.2412    5.8102    1.5026
-#> 261:    93.0060   -5.8933   -2.0894   -4.3237   -0.9284    0.1799    6.4253    3.7604    0.8765    3.5968    0.1981    0.2410    5.8080    1.5026
-#> 262:    93.0051   -5.8934   -2.0884   -4.3208   -0.9285    0.1789    6.4008    3.7597    0.8762    3.5855    0.1981    0.2412    5.8046    1.5020
-#> 263:    93.0019   -5.8945   -2.0875   -4.3182   -0.9287    0.1781    6.3788    3.7644    0.8758    3.5756    0.1982    0.2411    5.8048    1.5023
-#> 264:    93.0021   -5.8959   -2.0870   -4.3158   -0.9293    0.1773    6.3614    3.7682    0.8749    3.5667    0.1983    0.2410    5.8017    1.5021
-#> 265:    93.0053   -5.8989   -2.0866   -4.3130   -0.9296    0.1766    6.3506    3.7814    0.8739    3.5567    0.1982    0.2409    5.7995    1.5018
-#> 266:    93.0061   -5.8992   -2.0864   -4.3104   -0.9300    0.1757    6.3307    3.7730    0.8733    3.5471    0.1982    0.2408    5.7994    1.5012
-#> 267:    93.0098   -5.9009   -2.0861   -4.3077   -0.9302    0.1749    6.3326    3.7738    0.8730    3.5388    0.1983    0.2407    5.7964    1.5004
-#> 268:    93.0144   -5.9000   -2.0853   -4.3054   -0.9304    0.1740    6.3487    3.7623    0.8729    3.5290    0.1985    0.2405    5.7897    1.5014
-#> 269:    93.0146   -5.8984   -2.0847   -4.3032   -0.9306    0.1731    6.3716    3.7485    0.8735    3.5197    0.1985    0.2402    5.7867    1.5016
-#> 270:    93.0159   -5.8950   -2.0842   -4.3013   -0.9307    0.1722    6.3630    3.7266    0.8743    3.5098    0.1986    0.2400    5.7837    1.5016
-#> 271:    93.0161   -5.8925   -2.0837   -4.2995   -0.9309    0.1715    6.3539    3.7068    0.8744    3.5001    0.1986    0.2400    5.7843    1.5020
-#> 272:    93.0195   -5.8919   -2.0837   -4.2977   -0.9314    0.1710    6.3430    3.6964    0.8744    3.4922    0.1985    0.2400    5.7859    1.5031
-#> 273:    93.0184   -5.8923   -2.0837   -4.2961   -0.9318    0.1705    6.3531    3.6914    0.8743    3.4854    0.1984    0.2402    5.7880    1.5030
-#> 274:    93.0178   -5.8927   -2.0834   -4.2951   -0.9320    0.1701    6.3818    3.6865    0.8749    3.4824    0.1984    0.2403    5.7928    1.5020
-#> 275:    93.0204   -5.8937   -2.0833   -4.2942   -0.9324    0.1700    6.3961    3.6842    0.8754    3.4790    0.1984    0.2402    5.7949    1.5011
-#> 276:    93.0228   -5.8958   -2.0833   -4.2932   -0.9327    0.1699    6.3965    3.6870    0.8760    3.4752    0.1984    0.2402    5.7934    1.5002
-#> 277:    93.0251   -5.9000   -2.0833   -4.2921   -0.9329    0.1695    6.4076    3.7032    0.8766    3.4712    0.1985    0.2400    5.7979    1.4989
-#> 278:    93.0297   -5.9021   -2.0833   -4.2912   -0.9331    0.1690    6.4279    3.7073    0.8771    3.4671    0.1986    0.2399    5.7978    1.4981
-#> 279:    93.0273   -5.9021   -2.0832   -4.2902   -0.9332    0.1684    6.4349    3.7003    0.8779    3.4622    0.1988    0.2400    5.7993    1.4972
-#> 280:    93.0236   -5.9030   -2.0831   -4.2892   -0.9334    0.1674    6.4776    3.6986    0.8787    3.4576    0.1990    0.2401    5.8026    1.4963
-#> 281:    93.0172   -5.9037   -2.0829   -4.2881   -0.9337    0.1665    6.4942    3.6984    0.8797    3.4536    0.1992    0.2402    5.8056    1.4955
-#> 282:    93.0147   -5.9055   -2.0827   -4.2872   -0.9339    0.1656    6.4861    3.7031    0.8810    3.4492    0.1992    0.2403    5.8107    1.4954
-#> 283:    93.0138   -5.9053   -2.0824   -4.2865   -0.9341    0.1646    6.4962    3.6967    0.8822    3.4451    0.1993    0.2406    5.8142    1.4959
-#> 284:    93.0132   -5.9067   -2.0821   -4.2864   -0.9343    0.1636    6.5021    3.7013    0.8838    3.4437    0.1993    0.2406    5.8146    1.4955
-#> 285:    93.0138   -5.9081   -2.0819   -4.2859   -0.9343    0.1628    6.5037    3.7043    0.8851    3.4406    0.1994    0.2406    5.8146    1.4945
-#> 286:    93.0119   -5.9086   -2.0815   -4.2858   -0.9342    0.1620    6.5068    3.7037    0.8864    3.4395    0.1994    0.2404    5.8133    1.4936
-#> 287:    93.0122   -5.9089   -2.0813   -4.2860   -0.9342    0.1614    6.5202    3.7044    0.8872    3.4399    0.1997    0.2401    5.8096    1.4929
-#> 288:    93.0104   -5.9083   -2.0812   -4.2858   -0.9342    0.1609    6.5237    3.6997    0.8876    3.4376    0.1999    0.2398    5.8041    1.4924
-#> 289:    93.0076   -5.9066   -2.0812   -4.2854   -0.9342    0.1604    6.5121    3.6893    0.8881    3.4342    0.1999    0.2394    5.8021    1.4922
-#> 290:    93.0064   -5.9052   -2.0813   -4.2851   -0.9343    0.1602    6.5106    3.6772    0.8886    3.4309    0.2000    0.2389    5.7988    1.4915
-#> 291:    93.0071   -5.9031   -2.0813   -4.2849   -0.9345    0.1601    6.5031    3.6628    0.8891    3.4284    0.2000    0.2384    5.7959    1.4908
-#> 292:    93.0114   -5.9023   -2.0809   -4.2841   -0.9346    0.1594    6.4930    3.6538    0.8894    3.4237    0.2001    0.2383    5.7923    1.4902
-#> 293:    93.0148   -5.9032   -2.0807   -4.2834   -0.9348    0.1589    6.4836    3.6542    0.8898    3.4206    0.2002    0.2380    5.7893    1.4893
-#> 294:    93.0161   -5.9026   -2.0806   -4.2826   -0.9349    0.1582    6.4719    3.6469    0.8901    3.4176    0.2005    0.2375    5.7898    1.4886
-#> 295:    93.0212   -5.9008   -2.0806   -4.2817   -0.9350    0.1576    6.4649    3.6372    0.8904    3.4145    0.2007    0.2370    5.7885    1.4890
-#> 296:    93.0270   -5.8989   -2.0805   -4.2809   -0.9351    0.1569    6.4835    3.6279    0.8911    3.4124    0.2010    0.2366    5.7886    1.4884
-#> 297:    93.0291   -5.8969   -2.0803   -4.2800   -0.9352    0.1560    6.5014    3.6177    0.8915    3.4094    0.2012    0.2364    5.7873    1.4880
-#> 298:    93.0332   -5.8963   -2.0801   -4.2790   -0.9352    0.1551    6.5168    3.6111    0.8919    3.4065    0.2014    0.2361    5.7855    1.4875
-#> 299:    93.0339   -5.8961   -2.0799   -4.2782   -0.9352    0.1542    6.5288    3.6081    0.8927    3.4038    0.2015    0.2358    5.7844    1.4869
-#> 300:    93.0335   -5.8971   -2.0797   -4.2772   -0.9351    0.1533    6.5409    3.6097    0.8937    3.4009    0.2017    0.2356    5.7844    1.4859
-#> 301:    93.0320   -5.8979   -2.0796   -4.2762   -0.9350    0.1522    6.5553    3.6126    0.8945    3.3977    0.2020    0.2354    5.7898    1.4847
-#> 302:    93.0321   -5.8997   -2.0795   -4.2751   -0.9351    0.1513    6.5737    3.6195    0.8956    3.3943    0.2023    0.2351    5.7917    1.4835
-#> 303:    93.0328   -5.8984   -2.0792   -4.2739   -0.9351    0.1504    6.5888    3.6111    0.8964    3.3912    0.2025    0.2350    5.7915    1.4825
-#> 304:    93.0357   -5.8969   -2.0790   -4.2728   -0.9350    0.1494    6.5907    3.6018    0.8975    3.3882    0.2026    0.2348    5.7929    1.4813
-#> 305:    93.0351   -5.8953   -2.0786   -4.2718   -0.9349    0.1484    6.5764    3.5916    0.8986    3.3858    0.2027    0.2345    5.7937    1.4816
-#> 306:    93.0352   -5.8950   -2.0784   -4.2707   -0.9350    0.1475    6.5727    3.5890    0.8999    3.3835    0.2028    0.2341    5.7981    1.4810
-#> 307:    93.0354   -5.8947   -2.0784   -4.2699   -0.9351    0.1466    6.5759    3.5853    0.9010    3.3820    0.2030    0.2339    5.8028    1.4799
-#> 308:    93.0336   -5.8938   -2.0783   -4.2690   -0.9351    0.1459    6.5855    3.5776    0.9022    3.3809    0.2031    0.2333    5.8014    1.4788
-#> 309:    93.0311   -5.8931   -2.0780   -4.2683   -0.9351    0.1452    6.5799    3.5717    0.9038    3.3805    0.2033    0.2328    5.8048    1.4779
-#> 310:    93.0303   -5.8915   -2.0778   -4.2675   -0.9352    0.1447    6.5716    3.5609    0.9046    3.3797    0.2033    0.2323    5.8060    1.4774
-#> 311:    93.0275   -5.8915   -2.0776   -4.2668   -0.9352    0.1441    6.5679    3.5581    0.9052    3.3788    0.2034    0.2319    5.8056    1.4770
-#> 312:    93.0258   -5.8920   -2.0775   -4.2659   -0.9352    0.1435    6.5573    3.5571    0.9058    3.3775    0.2033    0.2314    5.8053    1.4766
-#> 313:    93.0234   -5.8928   -2.0773   -4.2649   -0.9353    0.1431    6.5510    3.5573    0.9065    3.3761    0.2033    0.2309    5.8046    1.4757
-#> 314:    93.0237   -5.8937   -2.0771   -4.2639   -0.9355    0.1425    6.5488    3.5578    0.9074    3.3747    0.2033    0.2303    5.8029    1.4751
-#> 315:    93.0237   -5.8940   -2.0769   -4.2629   -0.9357    0.1420    6.5480    3.5565    0.9081    3.3730    0.2034    0.2299    5.8010    1.4746
-#> 316:    93.0218   -5.8936   -2.0767   -4.2617   -0.9358    0.1413    6.5424    3.5517    0.9087    3.3705    0.2034    0.2296    5.7992    1.4741
-#> 317:    93.0218   -5.8932   -2.0766   -4.2606   -0.9359    0.1406    6.5576    3.5474    0.9091    3.3679    0.2034    0.2292    5.7965    1.4736
-#> 318:    93.0215   -5.8927   -2.0765   -4.2597   -0.9361    0.1402    6.5884    3.5420    0.9096    3.3661    0.2034    0.2288    5.7960    1.4727
-#> 319:    93.0201   -5.8938   -2.0764   -4.2588   -0.9361    0.1397    6.6095    3.5439    0.9101    3.3642    0.2034    0.2283    5.7943    1.4719
-#> 320:    93.0188   -5.8926   -2.0763   -4.2579   -0.9361    0.1392    6.6170    3.5368    0.9103    3.3622    0.2034    0.2282    5.7930    1.4711
-#> 321:    93.0155   -5.8908   -2.0762   -4.2569   -0.9361    0.1385    6.6328    3.5268    0.9105    3.3598    0.2033    0.2282    5.7921    1.4702
-#> 322:    93.0133   -5.8894   -2.0760   -4.2561   -0.9360    0.1378    6.6415    3.5192    0.9110    3.3580    0.2032    0.2282    5.7903    1.4698
-#> 323:    93.0089   -5.8888   -2.0759   -4.2555   -0.9360    0.1372    6.6480    3.5131    0.9107    3.3563    0.2031    0.2285    5.7915    1.4691
-#> 324:    93.0038   -5.8881   -2.0758   -4.2547   -0.9359    0.1364    6.6639    3.5076    0.9106    3.3547    0.2029    0.2287    5.7912    1.4687
-#> 325:    93.0011   -5.8871   -2.0756   -4.2540   -0.9359    0.1361    6.6587    3.5005    0.9102    3.3531    0.2028    0.2289    5.7896    1.4686
-#> 326:    93.0033   -5.8874   -2.0755   -4.2535   -0.9360    0.1360    6.6621    3.4995    0.9098    3.3510    0.2026    0.2294    5.7883    1.4686
-#> 327:    93.0039   -5.8885   -2.0754   -4.2532   -0.9361    0.1359    6.6589    3.5051    0.9093    3.3497    0.2025    0.2297    5.7869    1.4687
-#> 328:    93.0061   -5.8896   -2.0753   -4.2529   -0.9362    0.1355    6.6671    3.5132    0.9088    3.3484    0.2024    0.2299    5.7854    1.4687
-#> 329:    93.0077   -5.8915   -2.0755   -4.2525   -0.9363    0.1352    6.6719    3.5255    0.9085    3.3464    0.2024    0.2301    5.7850    1.4682
-#> 330:    93.0061   -5.8942   -2.0757   -4.2518   -0.9365    0.1351    6.6696    3.5399    0.9083    3.3438    0.2023    0.2302    5.7840    1.4680
-#> 331:    93.0032   -5.8953   -2.0759   -4.2513   -0.9366    0.1348    6.6554    3.5433    0.9080    3.3411    0.2022    0.2302    5.7839    1.4677
-#> 332:    93.0013   -5.8956   -2.0761   -4.2507   -0.9367    0.1347    6.6298    3.5423    0.9079    3.3385    0.2021    0.2302    5.7851    1.4672
-#> 333:    93.0026   -5.8950   -2.0764   -4.2502   -0.9368    0.1346    6.6207    3.5365    0.9078    3.3357    0.2021    0.2303    5.7849    1.4667
-#> 334:    93.0019   -5.8933   -2.0767   -4.2497   -0.9369    0.1348    6.6145    3.5259    0.9077    3.3330    0.2021    0.2302    5.7856    1.4662
-#> 335:    93.0038   -5.8930   -2.0768   -4.2492   -0.9370    0.1348    6.6200    3.5227    0.9078    3.3307    0.2020    0.2303    5.7845    1.4654
-#> 336:    93.0038   -5.8923   -2.0765   -4.2488   -0.9371    0.1348    6.6316    3.5180    0.9081    3.3291    0.2019    0.2304    5.7837    1.4654
-#> 337:    93.0074   -5.8927   -2.0764   -4.2485   -0.9373    0.1349    6.6509    3.5187    0.9083    3.3275    0.2018    0.2304    5.7808    1.4655
-#> 338:    93.0117   -5.8950   -2.0761   -4.2483   -0.9377    0.1349    6.6559    3.5291    0.9087    3.3263    0.2018    0.2303    5.7770    1.4657
-#> 339:    93.0172   -5.8960   -2.0759   -4.2482   -0.9380    0.1349    6.6610    3.5304    0.9090    3.3260    0.2017    0.2302    5.7744    1.4657
-#> 340:    93.0179   -5.8977   -2.0757   -4.2481   -0.9383    0.1349    6.6583    3.5340    0.9093    3.3263    0.2017    0.2301    5.7749    1.4650
-#> 341:    93.0201   -5.8986   -2.0755   -4.2484   -0.9386    0.1348    6.6603    3.5337    0.9092    3.3283    0.2018    0.2300    5.7738    1.4650
-#> 342:    93.0245   -5.8990   -2.0752   -4.2484   -0.9389    0.1348    6.6680    3.5324    0.9093    3.3297    0.2018    0.2300    5.7727    1.4649
-#> 343:    93.0302   -5.9006   -2.0751   -4.2484   -0.9391    0.1347    6.6715    3.5367    0.9093    3.3313    0.2017    0.2300    5.7729    1.4645
-#> 344:    93.0340   -5.9026   -2.0749   -4.2484   -0.9394    0.1346    6.6793    3.5438    0.9093    3.3326    0.2017    0.2301    5.7709    1.4646
-#> 345:    93.0372   -5.9049   -2.0746   -4.2484   -0.9397    0.1347    6.6874    3.5515    0.9090    3.3340    0.2017    0.2301    5.7688    1.4648
-#> 346:    93.0372   -5.9063   -2.0743   -4.2483   -0.9399    0.1348    6.6963    3.5592    0.9090    3.3348    0.2018    0.2299    5.7680    1.4656
-#> 347:    93.0383   -5.9075   -2.0742   -4.2481   -0.9402    0.1350    6.7101    3.5658    0.9093    3.3353    0.2018    0.2299    5.7672    1.4649
-#> 348:    93.0412   -5.9084   -2.0742   -4.2479   -0.9405    0.1351    6.7183    3.5707    0.9095    3.3356    0.2019    0.2297    5.7657    1.4645
-#> 349:    93.0436   -5.9097   -2.0742   -4.2477   -0.9407    0.1351    6.7143    3.5783    0.9098    3.3359    0.2019    0.2295    5.7646    1.4643
-#> 350:    93.0476   -5.9105   -2.0742   -4.2474   -0.9409    0.1351    6.7239    3.5808    0.9100    3.3354    0.2019    0.2294    5.7628    1.4639
-#> 351:    93.0506   -5.9113   -2.0741   -4.2473   -0.9411    0.1352    6.7270    3.5825    0.9103    3.3356    0.2019    0.2292    5.7604    1.4637
-#> 352:    93.0529   -5.9127   -2.0740   -4.2471   -0.9413    0.1353    6.7312    3.5886    0.9107    3.3358    0.2019    0.2290    5.7594    1.4634
-#> 353:    93.0580   -5.9139   -2.0739   -4.2470   -0.9415    0.1354    6.7315    3.5922    0.9111    3.3357    0.2019    0.2288    5.7571    1.4636
-#> 354:    93.0639   -5.9129   -2.0738   -4.2468   -0.9417    0.1354    6.7390    3.5876    0.9112    3.3356    0.2018    0.2286    5.7541    1.4642
-#> 355:    93.0671   -5.9131   -2.0737   -4.2467   -0.9417    0.1353    6.7348    3.5906    0.9113    3.3354    0.2017    0.2284    5.7520    1.4648
-#> 356:    93.0682   -5.9134   -2.0737   -4.2465   -0.9418    0.1352    6.7329    3.5962    0.9113    3.3353    0.2017    0.2283    5.7505    1.4649
-#> 357:    93.0698   -5.9128   -2.0738   -4.2471   -0.9418    0.1354    6.7397    3.5933    0.9115    3.3388    0.2016    0.2280    5.7512    1.4651
-#> 358:    93.0709   -5.9129   -2.0740   -4.2475   -0.9419    0.1355    6.7379    3.5915    0.9119    3.3416    0.2016    0.2278    5.7526    1.4644
-#> 359:    93.0718   -5.9128   -2.0742   -4.2478   -0.9419    0.1358    6.7428    3.5886    0.9123    3.3432    0.2015    0.2275    5.7516    1.4641
-#> 360:    93.0693   -5.9136   -2.0743   -4.2481   -0.9419    0.1360    6.7385    3.5930    0.9125    3.3443    0.2015    0.2272    5.7511    1.4636
-#> 361:    93.0674   -5.9148   -2.0744   -4.2484   -0.9419    0.1361    6.7230    3.6002    0.9127    3.3458    0.2015    0.2270    5.7514    1.4634
-#> 362:    93.0660   -5.9168   -2.0745   -4.2486   -0.9420    0.1361    6.7313    3.6117    0.9130    3.3473    0.2014    0.2270    5.7506    1.4636
-#> 363:    93.0635   -5.9196   -2.0746   -4.2490   -0.9421    0.1360    6.7388    3.6275    0.9132    3.3500    0.2014    0.2269    5.7493    1.4636
-#> 364:    93.0631   -5.9210   -2.0747   -4.2497   -0.9421    0.1361    6.7383    3.6323    0.9135    3.3548    0.2015    0.2268    5.7483    1.4634
-#> 365:    93.0635   -5.9219   -2.0747   -4.2504   -0.9421    0.1361    6.7402    3.6341    0.9137    3.3590    0.2015    0.2268    5.7461    1.4635
-#> 366:    93.0640   -5.9232   -2.0746   -4.2511   -0.9422    0.1362    6.7477    3.6409    0.9142    3.3624    0.2015    0.2267    5.7451    1.4641
-#> 367:    93.0616   -5.9247   -2.0746   -4.2518   -0.9422    0.1364    6.7557    3.6473    0.9148    3.3653    0.2015    0.2269    5.7472    1.4640
-#> 368:    93.0601   -5.9247   -2.0746   -4.2522   -0.9422    0.1366    6.7632    3.6452    0.9150    3.3678    0.2015    0.2270    5.7482    1.4639
-#> 369:    93.0583   -5.9240   -2.0748   -4.2527   -0.9423    0.1369    6.7737    3.6395    0.9148    3.3695    0.2015    0.2273    5.7499    1.4636
-#> 370:    93.0591   -5.9236   -2.0752   -4.2532   -0.9423    0.1373    6.7721    3.6352    0.9145    3.3718    0.2015    0.2276    5.7513    1.4636
-#> 371:    93.0607   -5.9235   -2.0755   -4.2540   -0.9424    0.1378    6.7682    3.6330    0.9143    3.3754    0.2015    0.2280    5.7535    1.4635
-#> 372:    93.0615   -5.9229   -2.0759   -4.2549   -0.9424    0.1382    6.7640    3.6288    0.9142    3.3795    0.2014    0.2284    5.7553    1.4633
-#> 373:    93.0612   -5.9237   -2.0763   -4.2557   -0.9424    0.1385    6.7641    3.6327    0.9140    3.3832    0.2012    0.2288    5.7570    1.4629
-#> 374:    93.0611   -5.9240   -2.0766   -4.2565   -0.9424    0.1389    6.7701    3.6341    0.9137    3.3872    0.2011    0.2293    5.7599    1.4625
-#> 375:    93.0615   -5.9247   -2.0770   -4.2573   -0.9424    0.1393    6.7729    3.6362    0.9134    3.3912    0.2009    0.2296    5.7629    1.4620
-#> 376:    93.0621   -5.9248   -2.0772   -4.2578   -0.9425    0.1397    6.7732    3.6371    0.9132    3.3931    0.2008    0.2298    5.7654    1.4613
-#> 377:    93.0622   -5.9255   -2.0774   -4.2582   -0.9426    0.1401    6.7681    3.6389    0.9130    3.3953    0.2007    0.2300    5.7678    1.4607
-#> 378:    93.0609   -5.9256   -2.0775   -4.2585   -0.9426    0.1402    6.7705    3.6381    0.9128    3.3972    0.2006    0.2301    5.7673    1.4602
-#> 379:    93.0590   -5.9262   -2.0776   -4.2589   -0.9426    0.1404    6.7777    3.6382    0.9127    3.3991    0.2005    0.2303    5.7668    1.4599
-#> 380:    93.0607   -5.9258   -2.0777   -4.2595   -0.9427    0.1407    6.7836    3.6350    0.9127    3.4031    0.2004    0.2305    5.7665    1.4598
-#> 381:    93.0617   -5.9251   -2.0777   -4.2596   -0.9427    0.1410    6.7880    3.6294    0.9125    3.4030    0.2003    0.2307    5.7651    1.4601
-#> 382:    93.0631   -5.9252   -2.0777   -4.2599   -0.9428    0.1413    6.7912    3.6278    0.9123    3.4038    0.2002    0.2310    5.7649    1.4606
-#> 383:    93.0621   -5.9253   -2.0778   -4.2602   -0.9429    0.1415    6.7834    3.6279    0.9119    3.4053    0.2000    0.2312    5.7657    1.4607
-#> 384:    93.0614   -5.9254   -2.0779   -4.2604   -0.9430    0.1416    6.7853    3.6280    0.9115    3.4066    0.1999    0.2313    5.7662    1.4608
-#> 385:    93.0613   -5.9259   -2.0780   -4.2605   -0.9430    0.1418    6.7757    3.6301    0.9112    3.4066    0.1997    0.2315    5.7678    1.4609
-#> 386:    93.0614   -5.9264   -2.0780   -4.2607   -0.9431    0.1418    6.7610    3.6331    0.9110    3.4073    0.1995    0.2317    5.7696    1.4612
-#> 387:    93.0631   -5.9276   -2.0780   -4.2610   -0.9432    0.1420    6.7595    3.6397    0.9108    3.4085    0.1993    0.2318    5.7716    1.4612
-#> 388:    93.0650   -5.9282   -2.0779   -4.2613   -0.9433    0.1421    6.7552    3.6445    0.9106    3.4092    0.1992    0.2318    5.7731    1.4612
-#> 389:    93.0644   -5.9286   -2.0779   -4.2616   -0.9434    0.1422    6.7488    3.6471    0.9104    3.4098    0.1991    0.2317    5.7724    1.4614
-#> 390:    93.0653   -5.9297   -2.0778   -4.2619   -0.9435    0.1423    6.7412    3.6524    0.9101    3.4103    0.1990    0.2317    5.7722    1.4615
-#> 391:    93.0647   -5.9297   -2.0778   -4.2623   -0.9435    0.1425    6.7508    3.6524    0.9101    3.4115    0.1989    0.2317    5.7729    1.4621
-#> 392:    93.0637   -5.9293   -2.0778   -4.2624   -0.9436    0.1427    6.7572    3.6498    0.9102    3.4109    0.1988    0.2317    5.7727    1.4623
-#> 393:    93.0657   -5.9294   -2.0778   -4.2632   -0.9436    0.1429    6.7607    3.6496    0.9104    3.4148    0.1987    0.2318    5.7719    1.4621
-#> 394:    93.0689   -5.9293   -2.0779   -4.2635   -0.9438    0.1431    6.7635    3.6489    0.9108    3.4141    0.1987    0.2318    5.7724    1.4623
-#> 395:    93.0705   -5.9295   -2.0780   -4.2640   -0.9438    0.1433    6.7753    3.6500    0.9110    3.4145    0.1986    0.2319    5.7724    1.4622
-#> 396:    93.0704   -5.9296   -2.0780   -4.2648   -0.9438    0.1435    6.7793    3.6511    0.9112    3.4175    0.1985    0.2319    5.7720    1.4618
-#> 397:    93.0715   -5.9302   -2.0781   -4.2656   -0.9438    0.1437    6.7782    3.6530    0.9114    3.4206    0.1985    0.2320    5.7706    1.4617
-#> 398:    93.0719   -5.9297   -2.0781   -4.2666   -0.9438    0.1439    6.7774    3.6510    0.9120    3.4258    0.1984    0.2319    5.7709    1.4616
-#> 399:    93.0720   -5.9296   -2.0781   -4.2678   -0.9438    0.1441    6.7819    3.6526    0.9126    3.4317    0.1984    0.2319    5.7717    1.4615
-#> 400:    93.0730   -5.9296   -2.0783   -4.2691   -0.9438    0.1443    6.7786    3.6538    0.9129    3.4389    0.1983    0.2319    5.7716    1.4614
-#> 401:    93.0728   -5.9292   -2.0783   -4.2706   -0.9437    0.1445    6.7731    3.6521    0.9133    3.4478    0.1982    0.2319    5.7701    1.4615
-#> 402:    93.0732   -5.9289   -2.0784   -4.2718   -0.9438    0.1447    6.7698    3.6517    0.9137    3.4542    0.1981    0.2319    5.7689    1.4618
-#> 403:    93.0732   -5.9301   -2.0785   -4.2730   -0.9438    0.1450    6.7640    3.6576    0.9142    3.4593    0.1980    0.2320    5.7693    1.4615
-#> 404:    93.0710   -5.9316   -2.0787   -4.2740   -0.9439    0.1453    6.7544    3.6647    0.9147    3.4644    0.1979    0.2320    5.7708    1.4611
-#> 405:    93.0687   -5.9322   -2.0788   -4.2750   -0.9440    0.1454    6.7547    3.6663    0.9153    3.4693    0.1978    0.2322    5.7714    1.4608
-#> 406:    93.0673   -5.9337   -2.0789   -4.2760   -0.9440    0.1456    6.7563    3.6726    0.9163    3.4742    0.1977    0.2324    5.7718    1.4603
-#> 407:    93.0653   -5.9345   -2.0791   -4.2769   -0.9440    0.1456    6.7601    3.6756    0.9169    3.4786    0.1976    0.2327    5.7732    1.4598
-#> 408:    93.0640   -5.9357   -2.0793   -4.2779   -0.9440    0.1455    6.7547    3.6821    0.9177    3.4838    0.1974    0.2329    5.7751    1.4592
-#> 409:    93.0646   -5.9371   -2.0795   -4.2784   -0.9440    0.1456    6.7486    3.6915    0.9184    3.4863    0.1973    0.2330    5.7766    1.4588
-#> 410:    93.0639   -5.9391   -2.0797   -4.2791   -0.9441    0.1457    6.7523    3.7048    0.9192    3.4889    0.1972    0.2329    5.7770    1.4582
-#> 411:    93.0628   -5.9401   -2.0799   -4.2799   -0.9442    0.1457    6.7529    3.7113    0.9199    3.4929    0.1972    0.2329    5.7761    1.4580
-#> 412:    93.0620   -5.9402   -2.0801   -4.2808   -0.9443    0.1458    6.7502    3.7099    0.9207    3.4972    0.1971    0.2328    5.7767    1.4577
-#> 413:    93.0628   -5.9403   -2.0804   -4.2816   -0.9443    0.1461    6.7466    3.7091    0.9214    3.5007    0.1970    0.2326    5.7771    1.4572
-#> 414:    93.0627   -5.9405   -2.0807   -4.2825   -0.9443    0.1463    6.7480    3.7089    0.9221    3.5048    0.1969    0.2325    5.7774    1.4567
-#> 415:    93.0614   -5.9402   -2.0810   -4.2836   -0.9443    0.1465    6.7474    3.7066    0.9226    3.5098    0.1969    0.2323    5.7780    1.4564
-#> 416:    93.0610   -5.9408   -2.0813   -4.2848   -0.9443    0.1469    6.7544    3.7116    0.9229    3.5157    0.1968    0.2321    5.7786    1.4559
-#> 417:    93.0601   -5.9413   -2.0815   -4.2860   -0.9443    0.1471    6.7592    3.7158    0.9234    3.5206    0.1967    0.2319    5.7793    1.4556
-#> 418:    93.0606   -5.9424   -2.0817   -4.2868   -0.9444    0.1473    6.7589    3.7214    0.9238    3.5237    0.1966    0.2318    5.7787    1.4553
-#> 419:    93.0605   -5.9433   -2.0818   -4.2877   -0.9444    0.1476    6.7641    3.7253    0.9242    3.5274    0.1965    0.2316    5.7780    1.4552
-#> 420:    93.0623   -5.9427   -2.0819   -4.2886   -0.9445    0.1478    6.7593    3.7216    0.9246    3.5310    0.1965    0.2314    5.7772    1.4551
-#> 421:    93.0630   -5.9418   -2.0819   -4.2895   -0.9445    0.1480    6.7489    3.7166    0.9250    3.5337    0.1964    0.2312    5.7764    1.4552
-#> 422:    93.0626   -5.9410   -2.0820   -4.2900   -0.9445    0.1482    6.7452    3.7124    0.9253    3.5350    0.1963    0.2311    5.7758    1.4549
-#> 423:    93.0629   -5.9407   -2.0822   -4.2906   -0.9446    0.1484    6.7409    3.7095    0.9256    3.5360    0.1963    0.2309    5.7753    1.4546
-#> 424:    93.0637   -5.9404   -2.0821   -4.2912   -0.9446    0.1485    6.7387    3.7073    0.9258    3.5370    0.1962    0.2308    5.7733    1.4546
-#> 425:    93.0625   -5.9402   -2.0821   -4.2917   -0.9447    0.1486    6.7330    3.7061    0.9258    3.5381    0.1961    0.2306    5.7722    1.4548
-#> 426:    93.0624   -5.9399   -2.0820   -4.2921   -0.9447    0.1487    6.7256    3.7034    0.9259    3.5387    0.1961    0.2304    5.7719    1.4545
-#> 427:    93.0606   -5.9397   -2.0821   -4.2925   -0.9447    0.1488    6.7139    3.7010    0.9257    3.5394    0.1961    0.2301    5.7730    1.4545
-#> 428:    93.0601   -5.9394   -2.0822   -4.2929   -0.9447    0.1489    6.7062    3.6984    0.9256    3.5405    0.1961    0.2298    5.7723    1.4543
-#> 429:    93.0615   -5.9391   -2.0821   -4.2933   -0.9447    0.1490    6.7040    3.6956    0.9254    3.5412    0.1960    0.2297    5.7714    1.4544
-#> 430:    93.0654   -5.9389   -2.0820   -4.2934   -0.9448    0.1491    6.7016    3.6934    0.9253    3.5412    0.1960    0.2295    5.7710    1.4546
-#> 431:    93.0674   -5.9392   -2.0819   -4.2936   -0.9449    0.1491    6.6946    3.6935    0.9252    3.5414    0.1960    0.2294    5.7699    1.4547
-#> 432:    93.0683   -5.9401   -2.0818   -4.2938   -0.9450    0.1491    6.6895    3.6960    0.9250    3.5417    0.1961    0.2292    5.7687    1.4549
-#> 433:    93.0693   -5.9411   -2.0815   -4.2942   -0.9451    0.1491    6.6826    3.7003    0.9254    3.5433    0.1961    0.2291    5.7679    1.4549
-#> 434:    93.0720   -5.9410   -2.0813   -4.2945   -0.9452    0.1491    6.6842    3.6998    0.9258    3.5440    0.1960    0.2290    5.7662    1.4548
-#> 435:    93.0735   -5.9417   -2.0811   -4.2947   -0.9453    0.1490    6.6907    3.7029    0.9261    3.5446    0.1960    0.2290    5.7651    1.4548
-#> 436:    93.0752   -5.9430   -2.0809   -4.2949   -0.9454    0.1489    6.6939    3.7083    0.9266    3.5459    0.1959    0.2290    5.7638    1.4547
-#> 437:    93.0774   -5.9442   -2.0807   -4.2952   -0.9455    0.1487    6.7016    3.7147    0.9270    3.5474    0.1960    0.2290    5.7624    1.4550
-#> 438:    93.0795   -5.9453   -2.0805   -4.2954   -0.9456    0.1485    6.7089    3.7212    0.9275    3.5491    0.1959    0.2291    5.7614    1.4551
-#> 439:    93.0816   -5.9467   -2.0802   -4.2956   -0.9457    0.1484    6.7230    3.7291    0.9281    3.5503    0.1959    0.2293    5.7616    1.4551
-#> 440:    93.0834   -5.9475   -2.0800   -4.2957   -0.9458    0.1480    6.7306    3.7340    0.9287    3.5512    0.1960    0.2295    5.7631    1.4551
-#> 441:    93.0855   -5.9480   -2.0797   -4.2961   -0.9459    0.1478    6.7436    3.7373    0.9292    3.5534    0.1960    0.2299    5.7642    1.4553
-#> 442:    93.0885   -5.9488   -2.0793   -4.2963   -0.9460    0.1474    6.7533    3.7419    0.9297    3.5546    0.1960    0.2304    5.7630    1.4554
-#> 443:    93.0907   -5.9497   -2.0789   -4.2967   -0.9461    0.1471    6.7641    3.7469    0.9304    3.5570    0.1960    0.2308    5.7616    1.4554
-#> 444:    93.0905   -5.9504   -2.0785   -4.2972   -0.9462    0.1467    6.7570    3.7486    0.9312    3.5601    0.1960    0.2311    5.7604    1.4553
-#> 445:    93.0903   -5.9515   -2.0782   -4.2977   -0.9462    0.1462    6.7547    3.7543    0.9319    3.5635    0.1960    0.2314    5.7595    1.4550
-#> 446:    93.0902   -5.9530   -2.0778   -4.2982   -0.9462    0.1459    6.7562    3.7615    0.9325    3.5664    0.1960    0.2316    5.7580    1.4548
-#> 447:    93.0905   -5.9541   -2.0775   -4.2990   -0.9463    0.1455    6.7639    3.7668    0.9333    3.5719    0.1960    0.2318    5.7574    1.4543
-#> 448:    93.0912   -5.9555   -2.0772   -4.2999   -0.9463    0.1452    6.7671    3.7736    0.9340    3.5783    0.1960    0.2322    5.7572    1.4540
-#> 449:    93.0918   -5.9570   -2.0769   -4.3004   -0.9464    0.1448    6.7824    3.7802    0.9345    3.5809    0.1960    0.2326    5.7561    1.4537
-#> 450:    93.0901   -5.9579   -2.0766   -4.3011   -0.9464    0.1444    6.7866    3.7829    0.9351    3.5853    0.1959    0.2329    5.7551    1.4536
-#> 451:    93.0899   -5.9594   -2.0763   -4.3016   -0.9465    0.1439    6.7875    3.7896    0.9356    3.5888    0.1959    0.2332    5.7550    1.4537
-#> 452:    93.0902   -5.9603   -2.0759   -4.3023   -0.9465    0.1435    6.7953    3.7926    0.9363    3.5927    0.1958    0.2335    5.7537    1.4538
-#> 453:    93.0906   -5.9615   -2.0755   -4.3026   -0.9465    0.1430    6.7996    3.7982    0.9372    3.5950    0.1958    0.2338    5.7531    1.4539
-#> 454:    93.0909   -5.9614   -2.0751   -4.3029   -0.9465    0.1425    6.8016    3.7969    0.9381    3.5976    0.1958    0.2340    5.7532    1.4540
-#> 455:    93.0909   -5.9610   -2.0749   -4.3035   -0.9464    0.1420    6.8022    3.7940    0.9391    3.6022    0.1957    0.2342    5.7532    1.4539
-#> 456:    93.0916   -5.9600   -2.0746   -4.3045   -0.9463    0.1416    6.7942    3.7893    0.9398    3.6104    0.1957    0.2344    5.7540    1.4537
-#> 457:    93.0905   -5.9595   -2.0744   -4.3058   -0.9463    0.1411    6.7931    3.7866    0.9407    3.6210    0.1956    0.2345    5.7551    1.4534
-#> 458:    93.0905   -5.9597   -2.0742   -4.3071   -0.9462    0.1407    6.7877    3.7882    0.9416    3.6327    0.1955    0.2347    5.7566    1.4532
-#> 459:    93.0895   -5.9598   -2.0741   -4.3078   -0.9461    0.1402    6.7884    3.7889    0.9425    3.6383    0.1955    0.2349    5.7601    1.4527
-#> 460:    93.0871   -5.9602   -2.0741   -4.3086   -0.9460    0.1398    6.7889    3.7912    0.9434    3.6439    0.1954    0.2350    5.7619    1.4522
-#> 461:    93.0854   -5.9613   -2.0739   -4.3091   -0.9459    0.1393    6.7813    3.7973    0.9440    3.6481    0.1953    0.2351    5.7620    1.4520
-#> 462:    93.0838   -5.9623   -2.0737   -4.3093   -0.9458    0.1388    6.7791    3.8037    0.9445    3.6498    0.1953    0.2353    5.7616    1.4518
-#> 463:    93.0816   -5.9629   -2.0734   -4.3095   -0.9457    0.1384    6.7733    3.8070    0.9451    3.6508    0.1952    0.2355    5.7626    1.4519
-#> 464:    93.0792   -5.9631   -2.0731   -4.3095   -0.9457    0.1379    6.7697    3.8081    0.9460    3.6507    0.1951    0.2358    5.7638    1.4518
-#> 465:    93.0775   -5.9633   -2.0728   -4.3095   -0.9456    0.1374    6.7717    3.8095    0.9466    3.6506    0.1950    0.2361    5.7647    1.4519
-#> 466:    93.0774   -5.9640   -2.0725   -4.3097   -0.9455    0.1368    6.7686    3.8141    0.9473    3.6516    0.1949    0.2363    5.7662    1.4516
-#> 467:    93.0773   -5.9646   -2.0722   -4.3100   -0.9454    0.1364    6.7668    3.8172    0.9480    3.6535    0.1948    0.2366    5.7671    1.4516
-#> 468:    93.0777   -5.9653   -2.0719   -4.3106   -0.9453    0.1358    6.7648    3.8226    0.9487    3.6566    0.1947    0.2371    5.7681    1.4514
-#> 469:    93.0778   -5.9657   -2.0717   -4.3112   -0.9453    0.1353    6.7617    3.8253    0.9495    3.6588    0.1947    0.2375    5.7686    1.4510
-#> 470:    93.0769   -5.9663   -2.0715   -4.3117   -0.9452    0.1347    6.7650    3.8278    0.9503    3.6613    0.1947    0.2379    5.7688    1.4506
-#> 471:    93.0749   -5.9664   -2.0714   -4.3123   -0.9451    0.1342    6.7708    3.8280    0.9510    3.6643    0.1947    0.2383    5.7699    1.4505
-#> 472:    93.0721   -5.9668   -2.0713   -4.3127   -0.9450    0.1337    6.7756    3.8284    0.9517    3.6665    0.1947    0.2386    5.7710    1.4501
-#> 473:    93.0696   -5.9670   -2.0713   -4.3133   -0.9449    0.1333    6.7784    3.8280    0.9522    3.6698    0.1947    0.2388    5.7716    1.4498
-#> 474:    93.0674   -5.9673   -2.0714   -4.3138   -0.9448    0.1329    6.7761    3.8281    0.9527    3.6731    0.1947    0.2390    5.7729    1.4496
-#> 475:    93.0655   -5.9679   -2.0714   -4.3143   -0.9447    0.1324    6.7779    3.8302    0.9531    3.6762    0.1947    0.2391    5.7743    1.4493
-#> 476:    93.0643   -5.9682   -2.0713   -4.3144   -0.9447    0.1321    6.7776    3.8314    0.9536    3.6768    0.1946    0.2391    5.7762    1.4492
-#> 477:    93.0631   -5.9684   -2.0714   -4.3146   -0.9446    0.1317    6.7725    3.8326    0.9540    3.6787    0.1945    0.2392    5.7768    1.4492
-#> 478:    93.0630   -5.9693   -2.0715   -4.3148   -0.9447    0.1314    6.7626    3.8365    0.9543    3.6788    0.1944    0.2395    5.7785    1.4492
-#> 479:    93.0634   -5.9710   -2.0714   -4.3148   -0.9447    0.1310    6.7499    3.8462    0.9547    3.6778    0.1943    0.2399    5.7798    1.4490
-#> 480:    93.0651   -5.9732   -2.0715   -4.3147   -0.9447    0.1307    6.7463    3.8616    0.9548    3.6770    0.1943    0.2403    5.7810    1.4488
-#> 481:    93.0664   -5.9747   -2.0715   -4.3149   -0.9447    0.1304    6.7442    3.8722    0.9550    3.6780    0.1941    0.2409    5.7811    1.4487
-#> 482:    93.0647   -5.9762   -2.0714   -4.3151   -0.9447    0.1300    6.7389    3.8834    0.9554    3.6784    0.1941    0.2414    5.7816    1.4484
-#> 483:    93.0628   -5.9778   -2.0714   -4.3153   -0.9447    0.1295    6.7352    3.8943    0.9557    3.6783    0.1940    0.2419    5.7820    1.4483
-#> 484:    93.0614   -5.9787   -2.0715   -4.3153   -0.9447    0.1291    6.7314    3.8999    0.9559    3.6774    0.1939    0.2424    5.7819    1.4481
-#> 485:    93.0593   -5.9789   -2.0715   -4.3153   -0.9447    0.1288    6.7293    3.9007    0.9561    3.6765    0.1938    0.2430    5.7815    1.4480
-#> 486:    93.0575   -5.9793   -2.0716   -4.3152   -0.9447    0.1284    6.7331    3.9021    0.9563    3.6753    0.1938    0.2434    5.7806    1.4480
-#> 487:    93.0555   -5.9796   -2.0716   -4.3152   -0.9447    0.1281    6.7342    3.9036    0.9566    3.6741    0.1937    0.2439    5.7805    1.4479
-#> 488:    93.0545   -5.9795   -2.0716   -4.3152   -0.9447    0.1277    6.7365    3.9024    0.9569    3.6729    0.1937    0.2444    5.7795    1.4480
-#> 489:    93.0550   -5.9800   -2.0716   -4.3152   -0.9447    0.1274    6.7336    3.9046    0.9571    3.6719    0.1937    0.2448    5.7778    1.4481
-#> 490:    93.0571   -5.9793   -2.0715   -4.3152   -0.9447    0.1272    6.7331    3.9009    0.9573    3.6704    0.1936    0.2450    5.7767    1.4484
-#> 491:    93.0584   -5.9787   -2.0714   -4.3151   -0.9447    0.1270    6.7280    3.8980    0.9575    3.6688    0.1936    0.2452    5.7764    1.4487
-#> 492:    93.0589   -5.9786   -2.0714   -4.3150   -0.9447    0.1267    6.7264    3.8971    0.9578    3.6675    0.1936    0.2455    5.7759    1.4489
-#> 493:    93.0593   -5.9790   -2.0711   -4.3149   -0.9447    0.1265    6.7273    3.8982    0.9584    3.6660    0.1935    0.2456    5.7759    1.4490
-#> 494:    93.0594   -5.9805   -2.0710   -4.3149   -0.9448    0.1263    6.7291    3.9066    0.9590    3.6650    0.1935    0.2457    5.7758    1.4489
-#> 495:    93.0596   -5.9816   -2.0709   -4.3148   -0.9448    0.1261    6.7281    3.9123    0.9593    3.6639    0.1936    0.2459    5.7745    1.4490
-#> 496:    93.0590   -5.9829   -2.0707   -4.3148   -0.9448    0.1259    6.7319    3.9227    0.9597    3.6628    0.1936    0.2461    5.7740    1.4491
-#> 497:    93.0580   -5.9842   -2.0706   -4.3148   -0.9448    0.1257    6.7388    3.9326    0.9600    3.6623    0.1936    0.2463    5.7732    1.4492
-#> 498:    93.0578   -5.9848   -2.0705   -4.3148   -0.9448    0.1255    6.7447    3.9368    0.9605    3.6618    0.1936    0.2464    5.7726    1.4494
-#> 499:    93.0568   -5.9843   -2.0704   -4.3147   -0.9447    0.1253    6.7475    3.9341    0.9609    3.6612    0.1937    0.2467    5.7718    1.4495
-#> 500:    93.0563   -5.9831   -2.0703   -4.3147   -0.9447    0.1251    6.7500    3.9292    0.9614    3.6607    0.1937    0.2469    5.7712    1.4496
-#> Calculating covariance matrix
-#> 
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> Needed Covariates:
-#> [1] "CMT"
-#> Calculating residuals/tables
-#> done
-f_nlmixr_dfop_sfo_focei_obs <- nlmixr(f_mmkin_obs["DFOP-SFO", ], est = "focei")
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → calculate jacobian
-#> 
-#> → calculate sensitivities
-#> 
-#> → calculate ∂(f)/∂(η)
-#> 
-#> → calculate ∂(R²)/∂(η)
-#> 
-#> → finding duplicate expressions in inner model...
-#> 
-#> → optimizing duplicate expressions in inner model...
-#> 
-#> → finding duplicate expressions in EBE model...
-#> 
-#> → optimizing duplicate expressions in EBE model...
-#> 
-#> → compiling inner model...
-#>  
-#> ✔ done
-#> → finding duplicate expressions in FD model...
-#> 
-#> → optimizing duplicate expressions in FD model...
-#> 
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> → compiling events FD model...
-#>  
-#> ✔ done
-#> Needed Covariates:
-#> [1] "CMT"
-#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> |    #| Objective Fun |  parent_0 |  log_k_A1 |f_parent_qlogis |    log_k1 |
-#> |.....................|    log_k2 |  g_qlogis |sigma_parent |  sigma_A1 |
-#> |.....................|        o1 |        o2 |        o3 |        o4 |
-#> |.....................|        o5 |        o6 |...........|...........|
-#> |    1|     488.98943 |     1.000 |    -1.000 |   -0.9115 |   -0.9329 |
-#> |.....................|   -0.9817 |   -0.8883 |   -0.8515 |   -0.8698 |
-#> |.....................|   -0.8775 |   -0.8743 |   -0.8683 |   -0.8723 |
-#> |.....................|   -0.8746 |   -0.8685 |...........|...........|
-#> |    U|     488.98943 |     93.00 |    -5.300 |   -0.9500 |    -2.000 |
-#> |.....................|    -4.400 |    0.1900 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    X|     488.98943 |     93.00 |  0.004992 |    0.2789 |    0.1353 |
-#> |.....................|   0.01228 |    0.5474 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    G|    Gill Diff. |    -27.68 |     2.403 |   -0.1248 |   -0.3242 |
-#> |.....................|   -0.3705 |   0.07384 |    -31.92 |    -15.13 |
-#> |.....................|     14.74 |     13.03 |    -12.01 |    -2.072 |
-#> |.....................|     5.553 |    -10.09 |...........|...........|
-#> |    2|     1205.4696 |     1.534 |    -1.046 |   -0.9091 |   -0.9266 |
-#> |.....................|   -0.9745 |   -0.8897 |   -0.2358 |   -0.5780 |
-#> |.....................|    -1.162 |    -1.126 |   -0.6367 |   -0.8323 |
-#> |.....................|   -0.9817 |   -0.6738 |...........|...........|
-#> |    U|     1205.4696 |     142.6 |    -5.346 |   -0.9477 |    -1.994 |
-#> |.....................|    -4.393 |    0.1897 |     2.616 |     1.260 |
-#> |.....................|    0.5160 |    0.6557 |     1.444 |     1.015 |
-#> |.....................|    0.7709 |     1.387 |...........|...........|
-#> |    X|     1205.4696 |     142.6 |  0.004766 |    0.2793 |    0.1362 |
-#> |.....................|   0.01237 |    0.5473 |     2.616 |     1.260 |
-#> |.....................|    0.5160 |    0.6557 |     1.444 |     1.015 |
-#> |.....................|    0.7709 |     1.387 |...........|...........|
-#> |    3|     510.70816 |     1.053 |    -1.005 |   -0.9113 |   -0.9322 |
-#> |.....................|   -0.9810 |   -0.8884 |   -0.7899 |   -0.8406 |
-#> |.....................|   -0.9059 |   -0.8995 |   -0.8452 |   -0.8683 |
-#> |.....................|   -0.8853 |   -0.8491 |...........|...........|
-#> |    U|     510.70816 |     97.96 |    -5.305 |   -0.9498 |    -1.999 |
-#> |.....................|    -4.399 |    0.1900 |     2.062 |     1.116 |
-#> |.....................|    0.7005 |    0.8538 |     1.199 |    0.9804 |
-#> |.....................|    0.8541 |     1.184 |...........|...........|
-#> |    X|     510.70816 |     97.96 |  0.004969 |    0.2789 |    0.1354 |
-#> |.....................|   0.01229 |    0.5474 |     2.062 |     1.116 |
-#> |.....................|    0.7005 |    0.8538 |     1.199 |    0.9804 |
-#> |.....................|    0.8541 |     1.184 |...........|...........|
-#> |    4|     494.11470 |     1.005 |    -1.000 |   -0.9115 |   -0.9328 |
-#> |.....................|   -0.9816 |   -0.8883 |   -0.8453 |   -0.8669 |
-#> |.....................|   -0.8803 |   -0.8769 |   -0.8660 |   -0.8719 |
-#> |.....................|   -0.8757 |   -0.8666 |...........|...........|
-#> |    U|      494.1147 |     93.50 |    -5.300 |   -0.9500 |    -2.000 |
-#> |.....................|    -4.400 |    0.1900 |     2.006 |     1.102 |
-#> |.....................|    0.7190 |    0.8736 |     1.175 |    0.9768 |
-#> |.....................|    0.8624 |     1.163 |...........|...........|
-#> |    X|      494.1147 |     93.50 |  0.004989 |    0.2789 |    0.1353 |
-#> |.....................|   0.01228 |    0.5474 |     2.006 |     1.102 |
-#> |.....................|    0.7190 |    0.8736 |     1.175 |    0.9768 |
-#> |.....................|    0.8624 |     1.163 |...........|...........|
-#> |    5|     494.35784 |     1.001 |    -1.000 |   -0.9115 |   -0.9329 |
-#> |.....................|   -0.9817 |   -0.8883 |   -0.8509 |   -0.8695 |
-#> |.....................|   -0.8778 |   -0.8746 |   -0.8681 |   -0.8723 |
-#> |.....................|   -0.8747 |   -0.8683 |...........|...........|
-#> |    U|     494.35784 |     93.05 |    -5.300 |   -0.9500 |    -2.000 |
-#> |.....................|    -4.400 |    0.1900 |     2.001 |     1.100 |
-#> |.....................|    0.7208 |    0.8755 |     1.172 |    0.9765 |
-#> |.....................|    0.8632 |     1.161 |...........|...........|
-#> |    X|     494.35784 |     93.05 |  0.004991 |    0.2789 |    0.1353 |
-#> |.....................|   0.01228 |    0.5474 |     2.001 |     1.100 |
-#> |.....................|    0.7208 |    0.8755 |     1.172 |    0.9765 |
-#> |.....................|    0.8632 |     1.161 |...........|...........|
-#> |    6|     494.40319 |     1.000 |    -1.000 |   -0.9115 |   -0.9329 |
-#> |.....................|   -0.9817 |   -0.8883 |   -0.8514 |   -0.8698 |
-#> |.....................|   -0.8775 |   -0.8744 |   -0.8683 |   -0.8723 |
-#> |.....................|   -0.8746 |   -0.8685 |...........|...........|
-#> |    U|     494.40319 |     93.00 |    -5.300 |   -0.9500 |    -2.000 |
-#> |.....................|    -4.400 |    0.1900 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8757 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    X|     494.40319 |     93.00 |  0.004992 |    0.2789 |    0.1353 |
-#> |.....................|   0.01228 |    0.5474 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8757 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    7|     494.40793 |     1.000 |    -1.000 |   -0.9115 |   -0.9329 |
-#> |.....................|   -0.9817 |   -0.8883 |   -0.8515 |   -0.8698 |
-#> |.....................|   -0.8775 |   -0.8744 |   -0.8683 |   -0.8723 |
-#> |.....................|   -0.8746 |   -0.8685 |...........|...........|
-#> |    U|     494.40793 |     93.00 |    -5.300 |   -0.9500 |    -2.000 |
-#> |.....................|    -4.400 |    0.1900 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    X|     494.40793 |     93.00 |  0.004992 |    0.2789 |    0.1353 |
-#> |.....................|   0.01228 |    0.5474 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    8|     494.40830 |     1.000 |    -1.000 |   -0.9115 |   -0.9329 |
-#> |.....................|   -0.9817 |   -0.8883 |   -0.8515 |   -0.8698 |
-#> |.....................|   -0.8775 |   -0.8743 |   -0.8683 |   -0.8723 |
-#> |.....................|   -0.8746 |   -0.8685 |...........|...........|
-#> |    U|      494.4083 |     93.00 |    -5.300 |   -0.9500 |    -2.000 |
-#> |.....................|    -4.400 |    0.1900 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    X|      494.4083 |     93.00 |  0.004992 |    0.2789 |    0.1353 |
-#> |.....................|   0.01228 |    0.5474 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    9|     494.40832 |     1.000 |    -1.000 |   -0.9115 |   -0.9329 |
-#> |.....................|   -0.9817 |   -0.8883 |   -0.8515 |   -0.8698 |
-#> |.....................|   -0.8775 |   -0.8743 |   -0.8683 |   -0.8723 |
-#> |.....................|   -0.8746 |   -0.8685 |...........|...........|
-#> |    U|     494.40832 |     93.00 |    -5.300 |   -0.9500 |    -2.000 |
-#> |.....................|    -4.400 |    0.1900 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    X|     494.40832 |     93.00 |  0.004992 |    0.2789 |    0.1353 |
-#> |.....................|   0.01228 |    0.5474 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |   10|     494.40832 |     1.000 |    -1.000 |   -0.9115 |   -0.9329 |
-#> |.....................|   -0.9817 |   -0.8883 |   -0.8515 |   -0.8698 |
-#> |.....................|   -0.8775 |   -0.8743 |   -0.8683 |   -0.8723 |
-#> |.....................|   -0.8746 |   -0.8685 |...........|...........|
-#> |    U|     494.40832 |     93.00 |    -5.300 |   -0.9500 |    -2.000 |
-#> |.....................|    -4.400 |    0.1900 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    X|     494.40832 |     93.00 |  0.004992 |    0.2789 |    0.1353 |
-#> |.....................|   0.01228 |    0.5474 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |   11|     494.40832 |     1.000 |    -1.000 |   -0.9115 |   -0.9329 |
-#> |.....................|   -0.9817 |   -0.8883 |   -0.8515 |   -0.8698 |
-#> |.....................|   -0.8775 |   -0.8743 |   -0.8683 |   -0.8723 |
-#> |.....................|   -0.8746 |   -0.8685 |...........|...........|
-#> |    U|     494.40832 |     93.00 |    -5.300 |   -0.9500 |    -2.000 |
-#> |.....................|    -4.400 |    0.1900 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    X|     494.40832 |     93.00 |  0.004992 |    0.2789 |    0.1353 |
-#> |.....................|   0.01228 |    0.5474 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |   12|     494.40832 |     1.000 |    -1.000 |   -0.9115 |   -0.9329 |
-#> |.....................|   -0.9817 |   -0.8883 |   -0.8515 |   -0.8698 |
-#> |.....................|   -0.8775 |   -0.8743 |   -0.8683 |   -0.8723 |
-#> |.....................|   -0.8746 |   -0.8685 |...........|...........|
-#> |    U|     494.40832 |     93.00 |    -5.300 |   -0.9500 |    -2.000 |
-#> |.....................|    -4.400 |    0.1900 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    X|     494.40832 |     93.00 |  0.004992 |    0.2789 |    0.1353 |
-#> |.....................|   0.01228 |    0.5474 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |   13|     494.40832 |     1.000 |    -1.000 |   -0.9115 |   -0.9329 |
-#> |.....................|   -0.9817 |   -0.8883 |   -0.8515 |   -0.8698 |
-#> |.....................|   -0.8775 |   -0.8743 |   -0.8683 |   -0.8723 |
-#> |.....................|   -0.8746 |   -0.8685 |...........|...........|
-#> |    U|     494.40832 |     93.00 |    -5.300 |   -0.9500 |    -2.000 |
-#> |.....................|    -4.400 |    0.1900 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    X|     494.40832 |     93.00 |  0.004992 |    0.2789 |    0.1353 |
-#> |.....................|   0.01228 |    0.5474 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |   14|     494.40832 |     1.000 |    -1.000 |   -0.9115 |   -0.9329 |
-#> |.....................|   -0.9817 |   -0.8883 |   -0.8515 |   -0.8698 |
-#> |.....................|   -0.8775 |   -0.8743 |   -0.8683 |   -0.8723 |
-#> |.....................|   -0.8746 |   -0.8685 |...........|...........|
-#> |    U|     494.40832 |     93.00 |    -5.300 |   -0.9500 |    -2.000 |
-#> |.....................|    -4.400 |    0.1900 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    X|     494.40832 |     93.00 |  0.004992 |    0.2789 |    0.1353 |
-#> |.....................|   0.01228 |    0.5474 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |   15|     494.40832 |     1.000 |    -1.000 |   -0.9115 |   -0.9329 |
-#> |.....................|   -0.9817 |   -0.8883 |   -0.8515 |   -0.8698 |
-#> |.....................|   -0.8775 |   -0.8743 |   -0.8683 |   -0.8723 |
-#> |.....................|   -0.8746 |   -0.8685 |...........|...........|
-#> |    U|     494.40832 |     93.00 |    -5.300 |   -0.9500 |    -2.000 |
-#> |.....................|    -4.400 |    0.1900 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    X|     494.40832 |     93.00 |  0.004992 |    0.2789 |    0.1353 |
-#> |.....................|   0.01228 |    0.5474 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |   16|     494.40832 |     1.000 |    -1.000 |   -0.9115 |   -0.9329 |
-#> |.....................|   -0.9817 |   -0.8883 |   -0.8515 |   -0.8698 |
-#> |.....................|   -0.8775 |   -0.8743 |   -0.8683 |   -0.8723 |
-#> |.....................|   -0.8746 |   -0.8685 |...........|...........|
-#> |    U|     494.40832 |     93.00 |    -5.300 |   -0.9500 |    -2.000 |
-#> |.....................|    -4.400 |    0.1900 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    X|     494.40832 |     93.00 |  0.004992 |    0.2789 |    0.1353 |
-#> |.....................|   0.01228 |    0.5474 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |   17|     494.40832 |     1.000 |    -1.000 |   -0.9115 |   -0.9329 |
-#> |.....................|   -0.9817 |   -0.8883 |   -0.8515 |   -0.8698 |
-#> |.....................|   -0.8775 |   -0.8743 |   -0.8683 |   -0.8723 |
-#> |.....................|   -0.8746 |   -0.8685 |...........|...........|
-#> |    U|     494.40832 |     93.00 |    -5.300 |   -0.9500 |    -2.000 |
-#> |.....................|    -4.400 |    0.1900 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> |    X|     494.40832 |     93.00 |  0.004992 |    0.2789 |    0.1353 |
-#> |.....................|   0.01228 |    0.5474 |     2.000 |     1.100 |
-#> |.....................|    0.7210 |    0.8758 |     1.172 |    0.9765 |
-#> |.....................|    0.8633 |     1.161 |...........|...........|
-#> calculating covariance matrix
-#> done
-#> Calculating residuals/tables
-#> done
-
-# Identical two-component error for all variables is only possible with
-# est = 'focei' in nlmixr
-f_nlmixr_fomc_sfo_focei_tc <- nlmixr(f_mmkin_tc["FOMC-SFO", ], est = "focei")
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → calculate jacobian
-#> 
-#> → calculate sensitivities
-#> 
-#> → calculate ∂(f)/∂(η)
-#> 
-#> → calculate ∂(R²)/∂(η)
-#> 
-#> → finding duplicate expressions in inner model...
-#> 
-#> → optimizing duplicate expressions in inner model...
-#> 
-#> → finding duplicate expressions in EBE model...
-#> 
-#> → optimizing duplicate expressions in EBE model...
-#> 
-#> → compiling inner model...
-#>  
-#> ✔ done
-#> → finding duplicate expressions in FD model...
-#> 
-#> → optimizing duplicate expressions in FD model...
-#> 
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> → compiling events FD model...
-#>  
-#> ✔ done
-#> Needed Covariates:
-#> [1] "CMT"
-#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> |    #| Objective Fun |  parent_0 |  log_k_A1 |f_parent_qlogis | log_alpha |
-#> |.....................|  log_beta | sigma_low |  rsd_high |        o1 |
-#> |.....................|        o2 |        o3 |        o4 |        o5 |
-#> |    1|     500.20030 |     1.000 |    -1.000 |   -0.9113 |   -0.8944 |
-#> |.....................|   -0.8454 |   -0.8678 |   -0.8916 |   -0.8767 |
-#> |.....................|   -0.8743 |   -0.8675 |   -0.8704 |   -0.8704 |
-#> |    U|      500.2003 |     93.00 |    -5.300 |   -0.9400 |   -0.1100 |
-#> |.....................|     2.300 |     1.200 |   0.03000 |    0.7598 |
-#> |.....................|    0.8758 |     1.214 |     1.068 |     1.071 |
-#> |    X|      500.2003 |     93.00 |  0.004992 |    0.2809 |    0.8958 |
-#> |.....................|     9.974 |     1.200 |   0.03000 |    0.7598 |
-#> |.....................|    0.8758 |     1.214 |     1.068 |     1.071 |
-#> |    G|    Gill Diff. |     48.88 |     2.383 |    0.1231 |    0.1986 |
-#> |.....................|    0.1571 |    -64.31 |    -21.89 |    0.6250 |
-#> |.....................|     11.41 |    -12.48 |    -9.903 |    -10.91 |
-#> |    2|     2909.4393 |    0.4361 |    -1.027 |   -0.9127 |   -0.8967 |
-#> |.....................|   -0.8472 |   -0.1258 |   -0.6390 |   -0.8839 |
-#> |.....................|    -1.006 |   -0.7235 |   -0.7562 |   -0.7445 |
-#> |    U|     2909.4393 |     40.56 |    -5.327 |   -0.9413 |   -0.1123 |
-#> |.....................|     2.298 |     1.645 |   0.03379 |    0.7544 |
-#> |.....................|    0.7605 |     1.389 |     1.189 |     1.206 |
-#> |    X|     2909.4393 |     40.56 |  0.004856 |    0.2806 |    0.8938 |
-#> |.....................|     9.956 |     1.645 |   0.03379 |    0.7544 |
-#> |.....................|    0.7605 |     1.389 |     1.189 |     1.206 |
-#> |    3|     515.24373 |    0.9436 |    -1.003 |   -0.9114 |   -0.8946 |
-#> |.....................|   -0.8456 |   -0.7936 |   -0.8663 |   -0.8774 |
-#> |.....................|   -0.8875 |   -0.8531 |   -0.8590 |   -0.8578 |
-#> |    U|     515.24373 |     87.76 |    -5.303 |   -0.9401 |   -0.1102 |
-#> |.....................|     2.300 |     1.245 |   0.03038 |    0.7593 |
-#> |.....................|    0.8642 |     1.232 |     1.080 |     1.084 |
-#> |    X|     515.24373 |     87.76 |  0.004978 |    0.2809 |    0.8956 |
-#> |.....................|     9.972 |     1.245 |   0.03038 |    0.7593 |
-#> |.....................|    0.8642 |     1.232 |     1.080 |     1.084 |
-#> |    4|     499.40695 |    0.9897 |    -1.001 |   -0.9113 |   -0.8944 |
-#> |.....................|   -0.8454 |   -0.8542 |   -0.8869 |   -0.8768 |
-#> |.....................|   -0.8768 |   -0.8648 |   -0.8684 |   -0.8681 |
-#> |    U|     499.40695 |     92.04 |    -5.301 |   -0.9400 |   -0.1100 |
-#> |.....................|     2.300 |     1.208 |   0.03007 |    0.7597 |
-#> |.....................|    0.8737 |     1.217 |     1.070 |     1.073 |
-#> |    X|     499.40695 |     92.04 |  0.004989 |    0.2809 |    0.8958 |
-#> |.....................|     9.974 |     1.208 |   0.03007 |    0.7597 |
-#> |.....................|    0.8737 |     1.217 |     1.070 |     1.073 |
-#> |    F| Forward Diff. |    -99.71 |     2.245 |   -0.1707 |    0.1202 |
-#> |.....................|   -0.1546 |    -61.69 |    -22.54 |     1.475 |
-#> |.....................|     7.677 |    -11.72 |    -9.584 |    -10.53 |
-#> |    5|     498.17135 |     1.001 |    -1.001 |   -0.9113 |   -0.8945 |
-#> |.....................|   -0.8454 |   -0.8410 |   -0.8822 |   -0.8771 |
-#> |.....................|   -0.8786 |   -0.8623 |   -0.8663 |   -0.8658 |
-#> |    U|     498.17135 |     93.06 |    -5.301 |   -0.9400 |   -0.1101 |
-#> |.....................|     2.300 |     1.216 |   0.03014 |    0.7595 |
-#> |.....................|    0.8720 |     1.221 |     1.072 |     1.076 |
-#> |    X|     498.17135 |     93.06 |  0.004987 |    0.2809 |    0.8958 |
-#> |.....................|     9.974 |     1.216 |   0.03014 |    0.7595 |
-#> |.....................|    0.8720 |     1.221 |     1.072 |     1.076 |
-#> |    F| Forward Diff. |     55.25 |     2.349 |    0.1359 |    0.2180 |
-#> |.....................|    0.1993 |    -60.48 |    -20.28 |     1.106 |
-#> |.....................|     9.662 |    -11.74 |    -9.501 |    -10.55 |
-#> |    6|     497.33758 |    0.9906 |    -1.002 |   -0.9113 |   -0.8945 |
-#> |.....................|   -0.8454 |   -0.8273 |   -0.8776 |   -0.8773 |
-#> |.....................|   -0.8808 |   -0.8596 |   -0.8642 |   -0.8634 |
-#> |    U|     497.33758 |     92.12 |    -5.302 |   -0.9400 |   -0.1101 |
-#> |.....................|     2.300 |     1.224 |   0.03021 |    0.7594 |
-#> |.....................|    0.8701 |     1.224 |     1.074 |     1.078 |
-#> |    X|     497.33758 |     92.12 |  0.004984 |    0.2809 |    0.8957 |
-#> |.....................|     9.974 |     1.224 |   0.03021 |    0.7594 |
-#> |.....................|    0.8701 |     1.224 |     1.074 |     1.078 |
-#> |    F| Forward Diff. |    -88.13 |     2.220 |   -0.1371 |    0.1382 |
-#> |.....................|   -0.1101 |    -57.44 |    -20.90 |     1.111 |
-#> |.....................|     7.358 |    -11.52 |    -9.371 |    -10.34 |
-#> |    7|     496.20963 |     1.001 |    -1.002 |   -0.9113 |   -0.8946 |
-#> |.....................|   -0.8454 |   -0.8137 |   -0.8728 |   -0.8776 |
-#> |.....................|   -0.8827 |   -0.8569 |   -0.8620 |   -0.8610 |
-#> |    U|     496.20963 |     93.07 |    -5.302 |   -0.9400 |   -0.1102 |
-#> |.....................|     2.300 |     1.232 |   0.03028 |    0.7592 |
-#> |.....................|    0.8684 |     1.227 |     1.077 |     1.081 |
-#> |    X|     496.20963 |     93.07 |  0.004981 |    0.2809 |    0.8957 |
-#> |.....................|     9.974 |     1.232 |   0.03028 |    0.7592 |
-#> |.....................|    0.8684 |     1.227 |     1.077 |     1.081 |
-#> |    F| Forward Diff. |     55.31 |     2.316 |    0.1573 |    0.2363 |
-#> |.....................|    0.2327 |    -56.27 |    -18.79 |    0.9054 |
-#> |.....................|     9.277 |    -11.53 |    -9.283 |    -10.35 |
-#> |    8|     495.35926 |    0.9914 |    -1.003 |   -0.9113 |   -0.8946 |
-#> |.....................|   -0.8455 |   -0.7996 |   -0.8680 |   -0.8778 |
-#> |.....................|   -0.8850 |   -0.8541 |   -0.8597 |   -0.8584 |
-#> |    U|     495.35926 |     92.20 |    -5.303 |   -0.9401 |   -0.1102 |
-#> |.....................|     2.300 |     1.241 |   0.03035 |    0.7590 |
-#> |.....................|    0.8664 |     1.231 |     1.079 |     1.084 |
-#> |    X|     495.35926 |     92.20 |  0.004979 |    0.2809 |    0.8956 |
-#> |.....................|     9.973 |     1.241 |   0.03035 |    0.7590 |
-#> |.....................|    0.8664 |     1.231 |     1.079 |     1.084 |
-#> |    F| Forward Diff. |    -77.78 |     2.194 |   -0.1077 |    0.1552 |
-#> |.....................|  -0.06714 |    -52.97 |    -19.27 |    0.8916 |
-#> |.....................|     7.037 |    -11.29 |    -9.130 |    -10.15 |
-#> |    9|     494.33654 |     1.001 |    -1.003 |   -0.9113 |   -0.8947 |
-#> |.....................|   -0.8455 |   -0.7857 |   -0.8631 |   -0.8780 |
-#> |.....................|   -0.8870 |   -0.8511 |   -0.8573 |   -0.8558 |
-#> |    U|     494.33654 |     93.09 |    -5.303 |   -0.9400 |   -0.1103 |
-#> |.....................|     2.300 |     1.249 |   0.03043 |    0.7588 |
-#> |.....................|    0.8647 |     1.234 |     1.082 |     1.087 |
-#> |    X|     494.33654 |     93.09 |  0.004976 |    0.2809 |    0.8956 |
-#> |.....................|     9.973 |     1.249 |   0.03043 |    0.7588 |
-#> |.....................|    0.8647 |     1.234 |     1.082 |     1.087 |
-#> |    F| Forward Diff. |     55.95 |     2.282 |    0.1850 |    0.2507 |
-#> |.....................|    0.2656 |    -51.81 |    -17.28 |    0.8212 |
-#> |.....................|     7.543 |    -11.27 |    -9.029 |    -10.13 |
-#> |   10|     493.47922 |    0.9922 |    -1.004 |   -0.9114 |   -0.8947 |
-#> |.....................|   -0.8455 |   -0.7714 |   -0.8582 |   -0.8782 |
-#> |.....................|   -0.8891 |   -0.8480 |   -0.8548 |   -0.8530 |
-#> |    U|     493.47922 |     92.28 |    -5.304 |   -0.9401 |   -0.1103 |
-#> |.....................|     2.300 |     1.258 |   0.03050 |    0.7587 |
-#> |.....................|    0.8629 |     1.238 |     1.084 |     1.090 |
-#> |    X|     493.47922 |     92.28 |  0.004973 |    0.2809 |    0.8955 |
-#> |.....................|     9.973 |     1.258 |   0.03050 |    0.7587 |
-#> |.....................|    0.8629 |     1.238 |     1.084 |     1.090 |
-#> |    F| Forward Diff. |    -67.18 |     2.173 |  -0.07166 |    0.1818 |
-#> |.....................|  -0.01313 |    -49.19 |    -17.69 |    0.7047 |
-#> |.....................|     8.114 |    -11.03 |    -8.882 |    -9.923 |
-#> |   11|     492.53845 |     1.001 |    -1.004 |   -0.9114 |   -0.8948 |
-#> |.....................|   -0.8456 |   -0.7572 |   -0.8532 |   -0.8784 |
-#> |.....................|   -0.8914 |   -0.8448 |   -0.8522 |   -0.8501 |
-#> |    U|     492.53845 |     93.09 |    -5.304 |   -0.9401 |   -0.1104 |
-#> |.....................|     2.300 |     1.266 |   0.03057 |    0.7585 |
-#> |.....................|    0.8608 |     1.242 |     1.087 |     1.093 |
-#> |    X|     492.53845 |     93.09 |  0.004969 |    0.2809 |    0.8955 |
-#> |.....................|     9.972 |     1.266 |   0.03057 |    0.7585 |
-#> |.....................|    0.8608 |     1.242 |     1.087 |     1.093 |
-#> |    F| Forward Diff. |     53.38 |     2.243 |    0.1941 |    0.2566 |
-#> |.....................|    0.2879 |    -47.96 |    -15.83 |    0.7595 |
-#> |.....................|     8.537 |    -10.98 |    -8.771 |    -9.890 |
-#> |   12|     491.72645 |    0.9926 |    -1.005 |   -0.9114 |   -0.8949 |
-#> |.....................|   -0.8456 |   -0.7429 |   -0.8484 |   -0.8786 |
-#> |.....................|   -0.8941 |   -0.8415 |   -0.8496 |   -0.8471 |
-#> |    U|     491.72645 |     92.31 |    -5.305 |   -0.9401 |   -0.1105 |
-#> |.....................|     2.300 |     1.275 |   0.03065 |    0.7584 |
-#> |.....................|    0.8584 |     1.246 |     1.090 |     1.096 |
-#> |    X|     491.72645 |     92.31 |  0.004966 |    0.2809 |    0.8954 |
-#> |.....................|     9.972 |     1.275 |   0.03065 |    0.7584 |
-#> |.....................|    0.8584 |     1.246 |     1.090 |     1.096 |
-#> |    F| Forward Diff. |    -63.56 |     2.131 |  -0.05387 |    0.1833 |
-#> |.....................| 0.0009134 |    -45.55 |    -16.30 |    0.3872 |
-#> |.....................|     9.447 |    -10.76 |    -8.612 |    -9.684 |
-#> |   13|     490.83850 |     1.001 |    -1.006 |   -0.9114 |   -0.8949 |
-#> |.....................|   -0.8457 |   -0.7286 |   -0.8435 |   -0.8787 |
-#> |.....................|   -0.8974 |   -0.8380 |   -0.8468 |   -0.8440 |
-#> |    U|      490.8385 |     93.07 |    -5.306 |   -0.9401 |   -0.1105 |
-#> |.....................|     2.300 |     1.283 |   0.03072 |    0.7583 |
-#> |.....................|    0.8556 |     1.250 |     1.093 |     1.099 |
-#> |    X|      490.8385 |     93.07 |  0.004963 |    0.2809 |    0.8954 |
-#> |.....................|     9.971 |     1.283 |   0.03072 |    0.7583 |
-#> |.....................|    0.8556 |     1.250 |     1.093 |     1.099 |
-#> |    F| Forward Diff. |     49.01 |     2.198 |    0.2057 |    0.2666 |
-#> |.....................|    0.3102 |    -44.06 |    -14.52 |    0.5614 |
-#> |.....................|     8.039 |    -10.72 |    -8.482 |    -9.628 |
-#> |   14|     490.09324 |    0.9928 |    -1.007 |   -0.9115 |   -0.8950 |
-#> |.....................|   -0.8458 |   -0.7143 |   -0.8387 |   -0.8788 |
-#> |.....................|   -0.9004 |   -0.8343 |   -0.8439 |   -0.8407 |
-#> |    U|     490.09324 |     92.33 |    -5.307 |   -0.9402 |   -0.1106 |
-#> |.....................|     2.300 |     1.292 |   0.03079 |    0.7582 |
-#> |.....................|    0.8529 |     1.254 |     1.096 |     1.103 |
-#> |    X|     490.09324 |     92.33 |  0.004959 |    0.2809 |    0.8953 |
-#> |.....................|     9.970 |     1.292 |   0.03079 |    0.7582 |
-#> |.....................|    0.8529 |     1.254 |     1.096 |     1.103 |
-#> |    F| Forward Diff. |    -62.13 |     2.095 |  -0.03472 |    0.1999 |
-#> |.....................|   0.03562 |    -41.55 |    -14.84 |    0.5236 |
-#> |.....................|     7.264 |    -10.46 |    -8.310 |    -9.412 |
-#> |   15|     489.25271 |     1.001 |    -1.007 |   -0.9115 |   -0.8951 |
-#> |.....................|   -0.8458 |   -0.7001 |   -0.8338 |   -0.8789 |
-#> |.....................|   -0.9032 |   -0.8304 |   -0.8408 |   -0.8372 |
-#> |    U|     489.25271 |     93.06 |    -5.307 |   -0.9402 |   -0.1107 |
-#> |.....................|     2.300 |     1.301 |   0.03087 |    0.7581 |
-#> |.....................|    0.8505 |     1.259 |     1.099 |     1.107 |
-#> |    X|     489.25271 |     93.06 |  0.004955 |    0.2809 |    0.8952 |
-#> |.....................|     9.970 |     1.301 |   0.03087 |    0.7581 |
-#> |.....................|    0.8505 |     1.259 |     1.099 |     1.107 |
-#> |    F| Forward Diff. |     44.98 |     2.155 |    0.2191 |    0.2769 |
-#> |.....................|    0.3339 |    -40.42 |    -13.24 |    0.4473 |
-#> |.....................|     7.595 |    -10.35 |    -8.165 |    -9.335 |
-#> |   16|     488.54089 |    0.9934 |    -1.008 |   -0.9116 |   -0.8952 |
-#> |.....................|   -0.8459 |   -0.6857 |   -0.8290 |   -0.8790 |
-#> |.....................|   -0.9061 |   -0.8262 |   -0.8376 |   -0.8335 |
-#> |    U|     488.54089 |     92.38 |    -5.308 |   -0.9403 |   -0.1108 |
-#> |.....................|     2.299 |     1.309 |   0.03094 |    0.7581 |
-#> |.....................|    0.8479 |     1.264 |     1.103 |     1.111 |
-#> |    X|     488.54089 |     92.38 |  0.004951 |    0.2808 |    0.8951 |
-#> |.....................|     9.968 |     1.309 |   0.03094 |    0.7581 |
-#> |.....................|    0.8479 |     1.264 |     1.103 |     1.111 |
-#> |    F| Forward Diff. |    -55.81 |     2.061 |  -0.02096 |    0.2050 |
-#> |.....................|   0.07367 |    -38.08 |    -13.50 |    0.4111 |
-#> |.....................|     6.904 |    -10.08 |    -7.981 |    -9.106 |
-#> |   17|     487.77387 |     1.001 |    -1.009 |   -0.9116 |   -0.8953 |
-#> |.....................|   -0.8461 |   -0.6716 |   -0.8243 |   -0.8791 |
-#> |.....................|   -0.9092 |   -0.8218 |   -0.8341 |   -0.8294 |
-#> |    U|     487.77387 |     93.07 |    -5.309 |   -0.9403 |   -0.1109 |
-#> |.....................|     2.299 |     1.318 |   0.03101 |    0.7580 |
-#> |.....................|    0.8453 |     1.270 |     1.106 |     1.115 |
-#> |    X|     487.77387 |     93.07 |  0.004946 |    0.2808 |    0.8950 |
-#> |.....................|     9.967 |     1.318 |   0.03101 |    0.7580 |
-#> |.....................|    0.8453 |     1.270 |     1.106 |     1.115 |
-#> |    F| Forward Diff. |     43.45 |     2.114 |    0.2402 |    0.2940 |
-#> |.....................|    0.3672 |    -36.87 |    -12.03 |    0.3081 |
-#> |.....................|     7.143 |    -10.02 |    -7.799 |    -9.000 |
-#> |   18|     487.09815 |    0.9939 |    -1.010 |   -0.9118 |   -0.8955 |
-#> |.....................|   -0.8463 |   -0.6575 |   -0.8197 |   -0.8791 |
-#> |.....................|   -0.9124 |   -0.8169 |   -0.8304 |   -0.8251 |
-#> |    U|     487.09815 |     92.43 |    -5.310 |   -0.9404 |   -0.1111 |
-#> |.....................|     2.299 |     1.326 |   0.03108 |    0.7580 |
-#> |.....................|    0.8425 |     1.276 |     1.110 |     1.120 |
-#> |    X|     487.09815 |     92.43 |  0.004941 |    0.2808 |    0.8948 |
-#> |.....................|     9.965 |     1.326 |   0.03108 |    0.7580 |
-#> |.....................|    0.8425 |     1.276 |     1.110 |     1.120 |
-#> |    F| Forward Diff. |    -50.03 |     2.024 |  0.005993 |    0.2193 |
-#> |.....................|    0.1119 |    -34.69 |    -12.26 |    0.2072 |
-#> |.....................|     6.453 |    -9.722 |    -7.597 |    -8.758 |
-#> |   19|     486.39882 |     1.001 |    -1.011 |   -0.9119 |   -0.8957 |
-#> |.....................|   -0.8465 |   -0.6438 |   -0.8151 |   -0.8789 |
-#> |.....................|   -0.9156 |   -0.8116 |   -0.8264 |   -0.8203 |
-#> |    U|     486.39882 |     93.07 |    -5.311 |   -0.9405 |   -0.1113 |
-#> |.....................|     2.299 |     1.334 |   0.03115 |    0.7582 |
-#> |.....................|    0.8396 |     1.282 |     1.114 |     1.125 |
-#> |    X|     486.39882 |     93.07 |  0.004935 |    0.2808 |    0.8947 |
-#> |.....................|     9.963 |     1.334 |   0.03115 |    0.7582 |
-#> |.....................|    0.8396 |     1.282 |     1.114 |     1.125 |
-#> |    F| Forward Diff. |     41.24 |     2.069 |    0.2581 |    0.3038 |
-#> |.....................|    0.3965 |    -33.71 |    -10.93 |    0.1523 |
-#> |.....................|     5.279 |    -9.597 |    -7.397 |    -8.617 |
-#> |   20|     485.77269 |    0.9943 |    -1.013 |   -0.9120 |   -0.8959 |
-#> |.....................|   -0.8467 |   -0.6301 |   -0.8107 |   -0.8786 |
-#> |.....................|   -0.9175 |   -0.8058 |   -0.8222 |   -0.8151 |
-#> |    U|     485.77269 |     92.47 |    -5.313 |   -0.9407 |   -0.1115 |
-#> |.....................|     2.299 |     1.343 |   0.03121 |    0.7584 |
-#> |.....................|    0.8380 |     1.289 |     1.119 |     1.130 |
-#> |    X|     485.77269 |     92.47 |  0.004928 |    0.2808 |    0.8945 |
-#> |.....................|     9.960 |     1.343 |   0.03121 |    0.7584 |
-#> |.....................|    0.8380 |     1.289 |     1.119 |     1.130 |
-#> |    F| Forward Diff. |    -45.38 |     1.992 |   0.03513 |    0.2356 |
-#> |.....................|    0.1513 |    -31.62 |    -11.12 |   0.08802 |
-#> |.....................|     6.113 |    -9.278 |    -7.167 |    -8.332 |
-#> |   21|     485.13787 |     1.001 |    -1.014 |   -0.9122 |   -0.8962 |
-#> |.....................|   -0.8471 |   -0.6169 |   -0.8065 |   -0.8780 |
-#> |.....................|   -0.9196 |   -0.7993 |   -0.8176 |   -0.8094 |
-#> |    U|     485.13787 |     93.06 |    -5.314 |   -0.9409 |   -0.1118 |
-#> |.....................|     2.298 |     1.351 |   0.03128 |    0.7588 |
-#> |.....................|    0.8361 |     1.297 |     1.124 |     1.136 |
-#> |    X|     485.13787 |     93.06 |  0.004921 |    0.2807 |    0.8942 |
-#> |.....................|     9.957 |     1.351 |   0.03128 |    0.7588 |
-#> |.....................|    0.8361 |     1.297 |     1.124 |     1.136 |
-#> |    F| Forward Diff. |     37.95 |     2.033 |    0.2726 |    0.3147 |
-#> |.....................|    0.4223 |    -30.68 |    -9.906 |   0.05100 |
-#> |.....................|     4.975 |    -9.039 |    -6.928 |    -8.144 |
-#> |   22|     484.56781 |    0.9947 |    -1.016 |   -0.9125 |   -0.8965 |
-#> |.....................|   -0.8476 |   -0.6040 |   -0.8026 |   -0.8774 |
-#> |.....................|   -0.9219 |   -0.7925 |   -0.8127 |   -0.8032 |
-#> |    U|     484.56781 |     92.51 |    -5.316 |   -0.9411 |   -0.1121 |
-#> |.....................|     2.298 |     1.358 |   0.03133 |    0.7593 |
-#> |.....................|    0.8341 |     1.305 |     1.129 |     1.143 |
-#> |    X|     484.56781 |     92.51 |  0.004912 |    0.2807 |    0.8939 |
-#> |.....................|     9.952 |     1.358 |   0.03133 |    0.7593 |
-#> |.....................|    0.8341 |     1.305 |     1.129 |     1.143 |
-#> |    F| Forward Diff. |    -42.28 |     1.959 |   0.05438 |    0.2483 |
-#> |.....................|    0.1829 |    -28.95 |    -10.12 |  -0.04344 |
-#> |.....................|     4.379 |    -8.677 |    -6.653 |    -7.817 |
-#> |   23|     484.00832 |     1.000 |    -1.018 |   -0.9128 |   -0.8970 |
-#> |.....................|   -0.8481 |   -0.5915 |   -0.7988 |   -0.8764 |
-#> |.....................|   -0.9214 |   -0.7852 |   -0.8076 |   -0.7966 |
-#> |    U|     484.00832 |     93.05 |    -5.318 |   -0.9414 |   -0.1125 |
-#> |.....................|     2.297 |     1.366 |   0.03139 |    0.7601 |
-#> |.....................|    0.8346 |     1.314 |     1.135 |     1.150 |
-#> |    X|     484.00832 |     93.05 |  0.004901 |    0.2806 |    0.8936 |
-#> |.....................|     9.947 |     1.366 |   0.03139 |    0.7601 |
-#> |.....................|    0.8346 |     1.314 |     1.135 |     1.150 |
-#> |    F| Forward Diff. |     34.54 |     2.001 |    0.2786 |    0.3182 |
-#> |.....................|    0.4381 |    -28.02 |    -9.026 |  -0.09975 |
-#> |.....................|     6.146 |    -8.496 |    -6.417 |    -7.602 |
-#> |   24|     483.48726 |    0.9952 |    -1.021 |   -0.9132 |   -0.8975 |
-#> |.....................|   -0.8489 |   -0.5798 |   -0.7955 |   -0.8750 |
-#> |.....................|   -0.9256 |   -0.7775 |   -0.8025 |   -0.7898 |
-#> |    U|     483.48726 |     92.55 |    -5.321 |   -0.9418 |   -0.1131 |
-#> |.....................|     2.296 |     1.373 |   0.03144 |    0.7611 |
-#> |.....................|    0.8309 |     1.323 |     1.140 |     1.157 |
-#> |    X|     483.48726 |     92.55 |  0.004889 |    0.2805 |    0.8931 |
-#> |.....................|     9.939 |     1.373 |   0.03144 |    0.7611 |
-#> |.....................|    0.8309 |     1.323 |     1.140 |     1.157 |
-#> |    F| Forward Diff. |    -37.52 |     1.926 |   0.07054 |    0.2526 |
-#> |.....................|    0.2102 |    -26.43 |    -9.184 |   -0.1123 |
-#> |.....................|     5.591 |    -8.057 |    -6.119 |    -7.239 |
-#> |   25|     482.99669 |     1.001 |    -1.023 |   -0.9136 |   -0.8980 |
-#> |.....................|   -0.8497 |   -0.5700 |   -0.7928 |   -0.8735 |
-#> |.....................|   -0.9342 |   -0.7702 |   -0.7978 |   -0.7834 |
-#> |    U|     482.99669 |     93.05 |    -5.323 |   -0.9422 |   -0.1136 |
-#> |.....................|     2.296 |     1.379 |   0.03148 |    0.7623 |
-#> |.....................|    0.8234 |     1.332 |     1.145 |     1.164 |
-#> |    X|     482.99669 |     93.05 |  0.004876 |    0.2805 |    0.8926 |
-#> |.....................|     9.932 |     1.379 |   0.03148 |    0.7623 |
-#> |.....................|    0.8234 |     1.332 |     1.145 |     1.164 |
-#> |    F| Forward Diff. |     33.56 |     1.934 |    0.3091 |    0.3219 |
-#> |.....................|    0.4700 |    -25.85 |    -8.255 |  -0.09267 |
-#> |.....................|     5.467 |    -7.833 |    -5.883 |    -7.031 |
-#> |   26|     482.53338 |    0.9957 |    -1.027 |   -0.9143 |   -0.8987 |
-#> |.....................|   -0.8507 |   -0.5600 |   -0.7904 |   -0.8719 |
-#> |.....................|   -0.9423 |   -0.7626 |   -0.7931 |   -0.7767 |
-#> |    U|     482.53338 |     92.60 |    -5.327 |   -0.9428 |   -0.1143 |
-#> |.....................|     2.295 |     1.385 |   0.03152 |    0.7635 |
-#> |.....................|    0.8163 |     1.342 |     1.150 |     1.171 |
-#> |    X|     482.53338 |     92.60 |  0.004861 |    0.2803 |    0.8920 |
-#> |.....................|     9.921 |     1.385 |   0.03152 |    0.7635 |
-#> |.....................|    0.8163 |     1.342 |     1.150 |     1.171 |
-#> |    F| Forward Diff. |    -33.71 |     1.852 |    0.1405 |    0.2615 |
-#> |.....................|    0.2476 |    -24.53 |    -8.462 |   -0.2274 |
-#> |.....................|     4.657 |    -7.455 |    -5.599 |    -6.689 |
-#> |   27|     482.07760 |     1.001 |    -1.030 |   -0.9154 |   -0.8996 |
-#> |.....................|   -0.8522 |   -0.5495 |   -0.7881 |   -0.8694 |
-#> |.....................|   -0.9481 |   -0.7546 |   -0.7885 |   -0.7696 |
-#> |    U|      482.0776 |     93.06 |    -5.330 |   -0.9439 |   -0.1152 |
-#> |.....................|     2.293 |     1.391 |   0.03155 |    0.7654 |
-#> |.....................|    0.8112 |     1.351 |     1.155 |     1.179 |
-#> |    X|      482.0776 |     93.06 |  0.004842 |    0.2801 |    0.8912 |
-#> |.....................|     9.906 |     1.391 |   0.03155 |    0.7654 |
-#> |.....................|    0.8112 |     1.351 |     1.155 |     1.179 |
-#> |    F| Forward Diff. |     31.51 |     1.862 |    0.3171 |    0.3253 |
-#> |.....................|    0.4890 |    -23.74 |    -7.570 |   -0.1627 |
-#> |.....................|     4.673 |    -7.176 |    -5.365 |    -6.441 |
-#> |   28|     481.65018 |    0.9960 |    -1.035 |   -0.9168 |   -0.9007 |
-#> |.....................|   -0.8541 |   -0.5386 |   -0.7859 |   -0.8662 |
-#> |.....................|   -0.9515 |   -0.7465 |   -0.7840 |   -0.7624 |
-#> |    U|     481.65018 |     92.63 |    -5.335 |   -0.9452 |   -0.1163 |
-#> |.....................|     2.291 |     1.398 |   0.03158 |    0.7678 |
-#> |.....................|    0.8082 |     1.361 |     1.160 |     1.187 |
-#> |    X|     481.65018 |     92.63 |  0.004820 |    0.2799 |    0.8902 |
-#> |.....................|     9.887 |     1.398 |   0.03158 |    0.7678 |
-#> |.....................|    0.8082 |     1.361 |     1.160 |     1.187 |
-#> |    F| Forward Diff. |    -31.18 |     1.794 |    0.1244 |    0.2518 |
-#> |.....................|    0.2479 |    -22.54 |    -7.736 |   -0.2537 |
-#> |.....................|     4.155 |    -6.794 |    -5.094 |    -6.088 |
-#> |   29|     481.23911 |     1.000 |    -1.041 |   -0.9182 |   -0.9020 |
-#> |.....................|   -0.8564 |   -0.5274 |   -0.7840 |   -0.8624 |
-#> |.....................|   -0.9539 |   -0.7386 |   -0.7800 |   -0.7556 |
-#> |    U|     481.23911 |     93.04 |    -5.341 |   -0.9465 |   -0.1176 |
-#> |.....................|     2.289 |     1.404 |   0.03161 |    0.7707 |
-#> |.....................|    0.8061 |     1.371 |     1.164 |     1.194 |
-#> |    X|     481.23911 |     93.04 |  0.004792 |    0.2796 |    0.8890 |
-#> |.....................|     9.865 |     1.404 |   0.03161 |    0.7707 |
-#> |.....................|    0.8061 |     1.371 |     1.164 |     1.194 |
-#> |   30|     480.84332 |     1.001 |    -1.048 |   -0.9201 |   -0.9037 |
-#> |.....................|   -0.8593 |   -0.5164 |   -0.7829 |   -0.8573 |
-#> |.....................|   -0.9562 |   -0.7293 |   -0.7754 |   -0.7475 |
-#> |    U|     480.84332 |     93.06 |    -5.348 |   -0.9483 |   -0.1193 |
-#> |.....................|     2.286 |     1.411 |   0.03163 |    0.7746 |
-#> |.....................|    0.8041 |     1.382 |     1.169 |     1.203 |
-#> |    X|     480.84332 |     93.06 |  0.004757 |    0.2792 |    0.8875 |
-#> |.....................|     9.836 |     1.411 |   0.03163 |    0.7746 |
-#> |.....................|    0.8041 |     1.382 |     1.169 |     1.203 |
-#> |   31|     479.47395 |     1.001 |    -1.077 |   -0.9274 |   -0.9105 |
-#> |.....................|   -0.8708 |   -0.4737 |   -0.7785 |   -0.8375 |
-#> |.....................|   -0.9655 |   -0.6927 |   -0.7575 |   -0.7158 |
-#> |    U|     479.47395 |     93.12 |    -5.377 |   -0.9551 |   -0.1261 |
-#> |.....................|     2.275 |     1.436 |   0.03170 |    0.7896 |
-#> |.....................|    0.7959 |     1.426 |     1.188 |     1.237 |
-#> |    X|     479.47395 |     93.12 |  0.004620 |    0.2779 |    0.8816 |
-#> |.....................|     9.723 |     1.436 |   0.03170 |    0.7896 |
-#> |.....................|    0.7959 |     1.426 |     1.188 |     1.237 |
-#> |   32|     477.01144 |     1.003 |    -1.162 |   -0.9485 |   -0.9300 |
-#> |.....................|   -0.9044 |   -0.3493 |   -0.7656 |   -0.7799 |
-#> |.....................|   -0.9925 |   -0.5865 |   -0.7057 |   -0.6237 |
-#> |    U|     477.01144 |     93.31 |    -5.462 |   -0.9750 |   -0.1456 |
-#> |.....................|     2.241 |     1.511 |   0.03189 |    0.8334 |
-#> |.....................|    0.7723 |     1.555 |     1.243 |     1.335 |
-#> |    X|     477.01144 |     93.31 |  0.004245 |    0.2739 |    0.8645 |
-#> |.....................|     9.403 |     1.511 |   0.03189 |    0.8334 |
-#> |.....................|    0.7723 |     1.555 |     1.243 |     1.335 |
-#> |    F| Forward Diff. |     48.38 |     1.353 |   -0.3553 |  -0.05530 |
-#> |.....................| -0.006768 |    -8.661 |    -2.325 |   -0.1540 |
-#> |.....................|     2.503 |   -0.2811 |   -0.6438 |   -0.5229 |
-#> |   33|     477.99463 |     1.002 |    -1.284 |   -0.8933 |   -0.9162 |
-#> |.....................|   -0.8846 |   -0.1951 |   -0.7385 |   -0.7367 |
-#> |.....................|    -1.093 |   -0.7697 |   -0.8046 |   -0.7596 |
-#> |    U|     477.99463 |     93.20 |    -5.584 |   -0.9231 |   -0.1318 |
-#> |.....................|     2.261 |     1.604 |   0.03230 |    0.8662 |
-#> |.....................|    0.6840 |     1.333 |     1.138 |     1.190 |
-#> |    X|     477.99463 |     93.20 |  0.003757 |    0.2843 |    0.8766 |
-#> |.....................|     9.591 |     1.604 |   0.03230 |    0.8662 |
-#> |.....................|    0.6840 |     1.333 |     1.138 |     1.190 |
-#> |   34|     476.67952 |     1.000 |    -1.201 |   -0.9310 |   -0.9256 |
-#> |.....................|   -0.8981 |   -0.3000 |   -0.7569 |   -0.7662 |
-#> |.....................|    -1.025 |   -0.6445 |   -0.7370 |   -0.6668 |
-#> |    U|     476.67952 |     93.04 |    -5.501 |   -0.9585 |   -0.1412 |
-#> |.....................|     2.247 |     1.541 |   0.03202 |    0.8438 |
-#> |.....................|    0.7442 |     1.485 |     1.210 |     1.289 |
-#> |    X|     476.67952 |     93.04 |  0.004084 |    0.2772 |    0.8683 |
-#> |.....................|     9.462 |     1.541 |   0.03202 |    0.8438 |
-#> |.....................|    0.7442 |     1.485 |     1.210 |     1.289 |
-#> |    F| Forward Diff. |     3.308 |     1.138 |    0.3206 |  0.007327 |
-#> |.....................| -0.005220 |    -6.420 |    -1.952 |   -0.8085 |
-#> |.....................|   -0.4295 |    -3.531 |    -2.349 |    -2.485 |
-#> |   35|     477.00015 |    0.9939 |    -1.268 |   -0.9234 |   -0.9152 |
-#> |.....................|   -0.8823 |   -0.2647 |   -0.7585 |   -0.7168 |
-#> |.....................|   -0.9725 |   -0.6365 |   -0.7310 |   -0.6853 |
-#> |    U|     477.00015 |     92.43 |    -5.568 |   -0.9514 |   -0.1308 |
-#> |.....................|     2.263 |     1.562 |   0.03200 |    0.8813 |
-#> |.....................|    0.7898 |     1.495 |     1.216 |     1.269 |
-#> |    X|     477.00015 |     92.43 |  0.003818 |    0.2786 |    0.8774 |
-#> |.....................|     9.613 |     1.562 |   0.03200 |    0.8813 |
-#> |.....................|    0.7898 |     1.495 |     1.216 |     1.269 |
-#> |   36|     476.87328 |    0.9941 |    -1.216 |   -0.9300 |   -0.9236 |
-#> |.....................|   -0.8950 |   -0.2832 |   -0.7542 |   -0.7554 |
-#> |.....................|    -1.014 |   -0.6375 |   -0.7322 |   -0.6666 |
-#> |    U|     476.87328 |     92.45 |    -5.516 |   -0.9576 |   -0.1392 |
-#> |.....................|     2.250 |     1.551 |   0.03206 |    0.8520 |
-#> |.....................|    0.7536 |     1.493 |     1.215 |     1.289 |
-#> |    X|     476.87328 |     92.45 |  0.004024 |    0.2774 |    0.8700 |
-#> |.....................|     9.491 |     1.551 |   0.03206 |    0.8520 |
-#> |.....................|    0.7536 |     1.493 |     1.215 |     1.289 |
-#> |   37|     476.68202 |    0.9977 |    -1.202 |   -0.9313 |   -0.9256 |
-#> |.....................|   -0.8981 |   -0.2947 |   -0.7553 |   -0.7655 |
-#> |.....................|    -1.024 |   -0.6416 |   -0.7351 |   -0.6648 |
-#> |    U|     476.68202 |     92.79 |    -5.502 |   -0.9588 |   -0.1412 |
-#> |.....................|     2.247 |     1.544 |   0.03204 |    0.8443 |
-#> |.....................|    0.7445 |     1.488 |     1.212 |     1.291 |
-#> |    X|     476.68202 |     92.79 |  0.004080 |    0.2771 |    0.8683 |
-#> |.....................|     9.462 |     1.544 |   0.03204 |    0.8443 |
-#> |.....................|    0.7445 |     1.488 |     1.212 |     1.291 |
-#> |   38|     476.66620 |    0.9991 |    -1.201 |   -0.9311 |   -0.9256 |
-#> |.....................|   -0.8981 |   -0.2974 |   -0.7561 |   -0.7659 |
-#> |.....................|    -1.024 |   -0.6431 |   -0.7361 |   -0.6658 |
-#> |    U|      476.6662 |     92.92 |    -5.501 |   -0.9587 |   -0.1412 |
-#> |.....................|     2.247 |     1.542 |   0.03203 |    0.8441 |
-#> |.....................|    0.7443 |     1.487 |     1.211 |     1.290 |
-#> |    X|      476.6662 |     92.92 |  0.004082 |    0.2771 |    0.8683 |
-#> |.....................|     9.462 |     1.542 |   0.03203 |    0.8441 |
-#> |.....................|    0.7443 |     1.487 |     1.211 |     1.290 |
-#> |    F| Forward Diff. |    -16.67 |     1.127 |    0.2138 |  -0.01630 |
-#> |.....................|   -0.1134 |    -4.869 |    -1.703 |  -0.03057 |
-#> |.....................|  -0.03000 |    -2.848 |    -2.302 |    -2.432 |
-#> |   39|     476.65034 |     1.001 |    -1.204 |   -0.9308 |   -0.9253 |
-#> |.....................|   -0.8974 |   -0.2967 |   -0.7561 |   -0.7660 |
-#> |.....................|    -1.024 |   -0.6432 |   -0.7350 |   -0.6655 |
-#> |    U|     476.65034 |     93.06 |    -5.504 |   -0.9584 |   -0.1409 |
-#> |.....................|     2.248 |     1.543 |   0.03203 |    0.8440 |
-#> |.....................|    0.7448 |     1.487 |     1.212 |     1.290 |
-#> |    X|     476.65034 |     93.06 |  0.004070 |    0.2772 |    0.8686 |
-#> |.....................|     9.468 |     1.543 |   0.03203 |    0.8440 |
-#> |.....................|    0.7448 |     1.487 |     1.212 |     1.290 |
-#> |    F| Forward Diff. |     7.111 |     1.131 |    0.3498 |   0.02199 |
-#> |.....................|   0.03596 |    -6.336 |    -1.893 |   -0.8646 |
-#> |.....................|   -0.4089 |    -3.511 |    -2.253 |    -2.437 |
-#> |   40|     476.63921 |    0.9998 |    -1.207 |   -0.9306 |   -0.9249 |
-#> |.....................|   -0.8968 |   -0.2957 |   -0.7561 |   -0.7661 |
-#> |.....................|    -1.024 |   -0.6430 |   -0.7338 |   -0.6650 |
-#> |    U|     476.63921 |     92.98 |    -5.507 |   -0.9581 |   -0.1405 |
-#> |.....................|     2.249 |     1.543 |   0.03203 |    0.8439 |
-#> |.....................|    0.7451 |     1.487 |     1.213 |     1.291 |
-#> |    X|     476.63921 |     92.98 |  0.004058 |    0.2773 |    0.8689 |
-#> |.....................|     9.474 |     1.543 |   0.03203 |    0.8439 |
-#> |.....................|    0.7451 |     1.487 |     1.213 |     1.291 |
-#> |    F| Forward Diff. |    -6.837 |     1.116 |    0.2875 |   0.01149 |
-#> |.....................|  -0.02542 |    -4.741 |    -1.572 |   0.01643 |
-#> |.....................|    -1.427 |    -2.805 |    -2.162 |    -2.393 |
-#> |   41|     476.63321 |     1.001 |    -1.209 |   -0.9304 |   -0.9247 |
-#> |.....................|   -0.8965 |   -0.2943 |   -0.7557 |   -0.7669 |
-#> |.....................|    -1.022 |   -0.6432 |   -0.7330 |   -0.6644 |
-#> |    U|     476.63321 |     93.07 |    -5.509 |   -0.9580 |   -0.1403 |
-#> |.....................|     2.249 |     1.544 |   0.03204 |    0.8433 |
-#> |.....................|    0.7468 |     1.487 |     1.214 |     1.292 |
-#> |    X|     476.63321 |     93.07 |  0.004050 |    0.2773 |    0.8691 |
-#> |.....................|     9.477 |     1.544 |   0.03204 |    0.8433 |
-#> |.....................|    0.7468 |     1.487 |     1.214 |     1.292 |
-#> |    F| Forward Diff. |     8.780 |     1.119 |    0.3715 |   0.03544 |
-#> |.....................|   0.06786 |    -4.773 |    -1.470 |  -0.02124 |
-#> |.....................|    -1.265 |    -2.850 |    -2.132 |    -2.390 |
-#> |   42|     476.62737 |    0.9998 |    -1.211 |   -0.9303 |   -0.9246 |
-#> |.....................|   -0.8963 |   -0.2932 |   -0.7554 |   -0.7683 |
-#> |.....................|    -1.020 |   -0.6436 |   -0.7322 |   -0.6637 |
-#> |    U|     476.62737 |     92.98 |    -5.511 |   -0.9578 |   -0.1402 |
-#> |.....................|     2.249 |     1.545 |   0.03204 |    0.8422 |
-#> |.....................|    0.7485 |     1.486 |     1.215 |     1.292 |
-#> |    X|     476.62737 |     92.98 |  0.004043 |    0.2773 |    0.8692 |
-#> |.....................|     9.479 |     1.545 |   0.03204 |    0.8422 |
-#> |.....................|    0.7485 |     1.486 |     1.215 |     1.292 |
-#> |    F| Forward Diff. |    -5.468 |     1.108 |    0.2964 |   0.01787 |
-#> |.....................|  -0.01029 |    -4.584 |    -1.512 |  -0.04750 |
-#> |.....................|    -1.233 |    -2.839 |    -2.097 |    -2.338 |
-#> |   43|     476.62183 |     1.001 |    -1.213 |   -0.9301 |   -0.9245 |
-#> |.....................|   -0.8960 |   -0.2918 |   -0.7549 |   -0.7696 |
-#> |.....................|    -1.018 |   -0.6438 |   -0.7313 |   -0.6628 |
-#> |    U|     476.62183 |     93.07 |    -5.513 |   -0.9577 |   -0.1401 |
-#> |.....................|     2.249 |     1.546 |   0.03205 |    0.8412 |
-#> |.....................|    0.7501 |     1.486 |     1.216 |     1.293 |
-#> |    X|     476.62183 |     93.07 |  0.004035 |    0.2773 |    0.8693 |
-#> |.....................|     9.481 |     1.546 |   0.03205 |    0.8412 |
-#> |.....................|    0.7501 |     1.486 |     1.216 |     1.293 |
-#> |    F| Forward Diff. |     8.726 |     1.111 |    0.3721 |   0.03969 |
-#> |.....................|   0.07339 |    -4.588 |    -1.391 |  -0.04583 |
-#> |.....................|    -1.059 |    -2.851 |    -2.052 |    -2.306 |
-#> |   44|     476.61645 |    0.9998 |    -1.215 |   -0.9300 |   -0.9243 |
-#> |.....................|   -0.8958 |   -0.2908 |   -0.7546 |   -0.7711 |
-#> |.....................|    -1.016 |   -0.6442 |   -0.7306 |   -0.6621 |
-#> |    U|     476.61645 |     92.98 |    -5.515 |   -0.9576 |   -0.1399 |
-#> |.....................|     2.250 |     1.546 |   0.03205 |    0.8401 |
-#> |.....................|    0.7517 |     1.485 |     1.217 |     1.294 |
-#> |    X|     476.61645 |     92.98 |  0.004027 |    0.2774 |    0.8694 |
-#> |.....................|     9.484 |     1.546 |   0.03205 |    0.8401 |
-#> |.....................|    0.7517 |     1.485 |     1.217 |     1.294 |
-#> |    F| Forward Diff. |    -5.224 |     1.099 |    0.2980 |   0.02349 |
-#> |.....................| -0.002638 |    -4.438 |    -1.447 |  -0.09166 |
-#> |.....................|    0.4490 |    -2.896 |    -2.021 |    -2.267 |
-#> |   45|     476.60491 |     1.001 |    -1.217 |   -0.9300 |   -0.9242 |
-#> |.....................|   -0.8956 |   -0.2899 |   -0.7543 |   -0.7729 |
-#> |.....................|    -1.016 |   -0.6437 |   -0.7294 |   -0.6608 |
-#> |    U|     476.60491 |     93.08 |    -5.517 |   -0.9576 |   -0.1398 |
-#> |.....................|     2.250 |     1.547 |   0.03206 |    0.8387 |
-#> |.....................|    0.7514 |     1.486 |     1.218 |     1.295 |
-#> |    X|     476.60491 |     93.08 |  0.004018 |    0.2774 |    0.8695 |
-#> |.....................|     9.485 |     1.547 |   0.03206 |    0.8387 |
-#> |.....................|    0.7514 |     1.486 |     1.218 |     1.295 |
-#> |    F| Forward Diff. |     9.891 |     1.101 |    0.3805 |   0.04781 |
-#> |.....................|   0.09121 |    -4.602 |    -1.355 |   -0.1211 |
-#> |.....................|   -0.9908 |    -2.875 |    -1.954 |    -2.212 |
-#> |   46|     476.59275 |    0.9999 |    -1.219 |   -0.9301 |   -0.9241 |
-#> |.....................|   -0.8954 |   -0.2896 |   -0.7542 |   -0.7748 |
-#> |.....................|    -1.017 |   -0.6434 |   -0.7284 |   -0.6597 |
-#> |    U|     476.59275 |     92.99 |    -5.519 |   -0.9576 |   -0.1397 |
-#> |.....................|     2.250 |     1.547 |   0.03206 |    0.8373 |
-#> |.....................|    0.7512 |     1.486 |     1.219 |     1.297 |
-#> |    X|     476.59275 |     92.99 |  0.004009 |    0.2774 |    0.8696 |
-#> |.....................|     9.487 |     1.547 |   0.03206 |    0.8373 |
-#> |.....................|    0.7512 |     1.486 |     1.219 |     1.297 |
-#> |    F| Forward Diff. |    -4.741 |     1.086 |    0.3018 |   0.02978 |
-#> |.....................|   0.01334 |    -4.300 |    -1.393 |  -0.08082 |
-#> |.....................|    0.4335 |    -2.821 |    -1.884 |    -2.156 |
-#> |   47|     476.58049 |     1.001 |    -1.222 |   -0.9302 |   -0.9241 |
-#> |.....................|   -0.8953 |   -0.2889 |   -0.7541 |   -0.7767 |
-#> |.....................|    -1.017 |   -0.6427 |   -0.7275 |   -0.6585 |
-#> |    U|     476.58049 |     93.06 |    -5.522 |   -0.9577 |   -0.1397 |
-#> |.....................|     2.250 |     1.547 |   0.03206 |    0.8359 |
-#> |.....................|    0.7507 |     1.487 |     1.220 |     1.298 |
-#> |    X|     476.58049 |     93.06 |  0.003999 |    0.2773 |    0.8697 |
-#> |.....................|     9.488 |     1.547 |   0.03206 |    0.8359 |
-#> |.....................|    0.7507 |     1.487 |     1.220 |     1.298 |
-#> |   48|     476.57085 |     1.001 |    -1.225 |   -0.9302 |   -0.9239 |
-#> |.....................|   -0.8951 |   -0.2891 |   -0.7542 |   -0.7796 |
-#> |.....................|    -1.018 |   -0.6424 |   -0.7265 |   -0.6573 |
-#> |    U|     476.57085 |     93.06 |    -5.525 |   -0.9578 |   -0.1395 |
-#> |.....................|     2.250 |     1.547 |   0.03206 |    0.8336 |
-#> |.....................|    0.7502 |     1.488 |     1.221 |     1.299 |
-#> |    X|     476.57085 |     93.06 |  0.003985 |    0.2773 |    0.8698 |
-#> |.....................|     9.490 |     1.547 |   0.03206 |    0.8336 |
-#> |.....................|    0.7502 |     1.488 |     1.221 |     1.299 |
-#> |   49|     476.52700 |     1.000 |    -1.243 |   -0.9306 |   -0.9233 |
-#> |.....................|   -0.8940 |   -0.2898 |   -0.7549 |   -0.7948 |
-#> |.....................|    -1.021 |   -0.6409 |   -0.7216 |   -0.6509 |
-#> |    U|       476.527 |     93.02 |    -5.543 |   -0.9582 |   -0.1389 |
-#> |.....................|     2.251 |     1.547 |   0.03205 |    0.8221 |
-#> |.....................|    0.7475 |     1.489 |     1.226 |     1.306 |
-#> |    X|       476.527 |     93.02 |  0.003915 |    0.2772 |    0.8703 |
-#> |.....................|     9.501 |     1.547 |   0.03205 |    0.8221 |
-#> |.....................|    0.7475 |     1.489 |     1.226 |     1.306 |
-#> |   50|     476.45166 |    0.9988 |    -1.314 |   -0.9321 |   -0.9209 |
-#> |.....................|   -0.8895 |   -0.2927 |   -0.7576 |   -0.8554 |
-#> |.....................|    -1.033 |   -0.6351 |   -0.7022 |   -0.6254 |
-#> |    U|     476.45166 |     92.89 |    -5.614 |   -0.9596 |   -0.1365 |
-#> |.....................|     2.256 |     1.545 |   0.03201 |    0.7760 |
-#> |.....................|    0.7365 |     1.496 |     1.247 |     1.333 |
-#> |    X|     476.45166 |     92.89 |  0.003648 |    0.2770 |    0.8724 |
-#> |.....................|     9.543 |     1.545 |   0.03201 |    0.7760 |
-#> |.....................|    0.7365 |     1.496 |     1.247 |     1.333 |
-#> |    F| Forward Diff. |    -21.31 |    0.8191 |    0.2022 |    0.1018 |
-#> |.....................|    0.1327 |    -4.505 |    -1.303 |    -1.202 |
-#> |.....................|    -2.080 |    -2.304 |   -0.3706 |   -0.4948 |
-#> |   51|     476.56836 |     1.004 |    -1.424 |   -0.9336 |   -0.9183 |
-#> |.....................|   -0.8856 |   -0.2810 |   -0.7637 |   -0.9206 |
-#> |.....................|    -1.004 |   -0.6303 |   -0.6962 |   -0.6148 |
-#> |    U|     476.56836 |     93.36 |    -5.724 |   -0.9609 |   -0.1338 |
-#> |.....................|     2.260 |     1.552 |   0.03192 |    0.7265 |
-#> |.....................|    0.7619 |     1.502 |     1.254 |     1.345 |
-#> |    X|     476.56836 |     93.36 |  0.003266 |    0.2767 |    0.8747 |
-#> |.....................|     9.581 |     1.552 |   0.03192 |    0.7265 |
-#> |.....................|    0.7619 |     1.502 |     1.254 |     1.345 |
-#> |   52|     476.44457 |     1.002 |    -1.351 |   -0.9326 |   -0.9200 |
-#> |.....................|   -0.8882 |   -0.2885 |   -0.7595 |   -0.8773 |
-#> |.....................|    -1.024 |   -0.6333 |   -0.7001 |   -0.6218 |
-#> |    U|     476.44457 |     93.15 |    -5.651 |   -0.9600 |   -0.1356 |
-#> |.....................|     2.257 |     1.548 |   0.03198 |    0.7594 |
-#> |.....................|    0.7451 |     1.499 |     1.249 |     1.337 |
-#> |    X|     476.44457 |     93.15 |  0.003514 |    0.2769 |    0.8732 |
-#> |.....................|     9.556 |     1.548 |   0.03198 |    0.7594 |
-#> |.....................|    0.7451 |     1.499 |     1.249 |     1.337 |
-#> |    F| Forward Diff. |     15.82 |    0.7276 |    0.3571 |    0.1746 |
-#> |.....................|    0.4004 |    -4.436 |   -0.9222 |    -1.572 |
-#> |.....................|    -1.287 |    -2.164 |   -0.2873 |   -0.3883 |
-#> |   53|     476.40417 |     1.000 |    -1.371 |   -0.9349 |   -0.9209 |
-#> |.....................|   -0.8904 |   -0.2869 |   -0.7634 |   -0.8782 |
-#> |.....................|    -1.024 |   -0.6262 |   -0.7046 |   -0.6250 |
-#> |    U|     476.40417 |     93.02 |    -5.671 |   -0.9622 |   -0.1365 |
-#> |.....................|     2.255 |     1.549 |   0.03192 |    0.7587 |
-#> |.....................|    0.7444 |     1.507 |     1.245 |     1.334 |
-#> |    X|     476.40417 |     93.02 |  0.003446 |    0.2764 |    0.8724 |
-#> |.....................|     9.535 |     1.549 |   0.03192 |    0.7587 |
-#> |.....................|    0.7444 |     1.507 |     1.245 |     1.334 |
-#> |   54|     476.37918 |     1.000 |    -1.391 |   -0.9372 |   -0.9218 |
-#> |.....................|   -0.8927 |   -0.2856 |   -0.7675 |   -0.8792 |
-#> |.....................|    -1.025 |   -0.6191 |   -0.7092 |   -0.6283 |
-#> |    U|     476.37918 |     93.03 |    -5.691 |   -0.9644 |   -0.1374 |
-#> |.....................|     2.253 |     1.549 |   0.03186 |    0.7580 |
-#> |.....................|    0.7434 |     1.516 |     1.240 |     1.330 |
-#> |    X|     476.37918 |     93.03 |  0.003376 |    0.2760 |    0.8716 |
-#> |.....................|     9.513 |     1.549 |   0.03186 |    0.7580 |
-#> |.....................|    0.7434 |     1.516 |     1.240 |     1.330 |
-#> |   55|     476.33357 |     1.001 |    -1.461 |   -0.9453 |   -0.9249 |
-#> |.....................|   -0.9004 |   -0.2814 |   -0.7818 |   -0.8827 |
-#> |.....................|    -1.029 |   -0.5944 |   -0.7253 |   -0.6399 |
-#> |    U|     476.33357 |     93.07 |    -5.761 |   -0.9719 |   -0.1405 |
-#> |.....................|     2.245 |     1.552 |   0.03165 |    0.7553 |
-#> |.....................|    0.7403 |     1.546 |     1.222 |     1.318 |
-#> |    X|     476.33357 |     93.07 |  0.003146 |    0.2745 |    0.8689 |
-#> |.....................|     9.440 |     1.552 |   0.03165 |    0.7553 |
-#> |.....................|    0.7403 |     1.546 |     1.222 |     1.318 |
-#> |    F| Forward Diff. |    -1.553 |    0.4475 |   -0.2195 |   0.07220 |
-#> |.....................|   0.05655 |    -4.350 |    -1.061 |    -1.750 |
-#> |.....................|    0.1436 |   -0.4527 |    -1.673 |    -1.245 |
-#> |   56|     476.20746 |     1.002 |    -1.571 |   -0.9452 |   -0.9313 |
-#> |.....................|   -0.9123 |   -0.2680 |   -0.8139 |   -0.8382 |
-#> |.....................|    -1.032 |   -0.6009 |   -0.7081 |   -0.6381 |
-#> |    U|     476.20746 |     93.20 |    -5.871 |   -0.9719 |   -0.1469 |
-#> |.....................|     2.233 |     1.560 |   0.03117 |    0.7891 |
-#> |.....................|    0.7373 |     1.538 |     1.241 |     1.320 |
-#> |    X|     476.20746 |     93.20 |  0.002821 |    0.2745 |    0.8634 |
-#> |.....................|     9.328 |     1.560 |   0.03117 |    0.7891 |
-#> |.....................|    0.7373 |     1.538 |     1.241 |     1.320 |
-#> |    F| Forward Diff. |     12.15 |    0.1791 |  -0.01894 | -0.004675 |
-#> |.....................|  -0.06593 |    -5.850 |    -1.512 |    -1.794 |
-#> |.....................|    -1.396 |    -1.647 |   -0.7085 |    -1.309 |
-#> |   57|     476.15444 |     1.000 |    -1.669 |   -0.9317 |   -0.9229 |
-#> |.....................|   -0.8889 |   -0.2480 |   -0.8424 |   -0.7961 |
-#> |.....................|    -1.030 |   -0.6117 |   -0.7275 |   -0.5959 |
-#> |    U|     476.15444 |     93.03 |    -5.969 |   -0.9591 |   -0.1385 |
-#> |.....................|     2.256 |     1.572 |   0.03074 |    0.8211 |
-#> |.....................|    0.7395 |     1.525 |     1.220 |     1.365 |
-#> |    X|     476.15444 |     93.03 |  0.002558 |    0.2771 |    0.8707 |
-#> |.....................|     9.549 |     1.572 |   0.03074 |    0.8211 |
-#> |.....................|    0.7395 |     1.525 |     1.220 |     1.365 |
-#> |    F| Forward Diff. |    -13.97 |  -0.09883 |    0.5245 |    0.1410 |
-#> |.....................|    0.5845 |    -3.407 |    -1.272 |   -0.2800 |
-#> |.....................|    0.9652 |    -1.487 |    -1.684 |    0.3572 |
-#> |   58|     476.18235 |     1.000 |    -1.690 |   -0.9781 |   -0.8961 |
-#> |.....................|   -0.8818 |   -0.1915 |   -0.8548 |   -0.7635 |
-#> |.....................|    -1.041 |   -0.6068 |   -0.6702 |   -0.6625 |
-#> |    U|     476.18235 |     93.04 |    -5.990 |    -1.003 |   -0.1117 |
-#> |.....................|     2.264 |     1.606 |   0.03055 |    0.8458 |
-#> |.....................|    0.7299 |     1.531 |     1.281 |     1.294 |
-#> |    X|     476.18235 |     93.04 |  0.002505 |    0.2684 |    0.8943 |
-#> |.....................|     9.617 |     1.606 |   0.03055 |    0.8458 |
-#> |.....................|    0.7299 |     1.531 |     1.281 |     1.294 |
-#> |   59|     476.08231 |     1.003 |    -1.678 |   -0.9530 |   -0.9107 |
-#> |.....................|   -0.8858 |   -0.2215 |   -0.8479 |   -0.7811 |
-#> |.....................|    -1.035 |   -0.6092 |   -0.7010 |   -0.6265 |
-#> |    U|     476.08231 |     93.25 |    -5.978 |   -0.9792 |   -0.1263 |
-#> |.....................|     2.260 |     1.588 |   0.03066 |    0.8325 |
-#> |.....................|    0.7350 |     1.528 |     1.248 |     1.332 |
-#> |    X|     476.08231 |     93.25 |  0.002533 |    0.2730 |    0.8814 |
-#> |.....................|     9.579 |     1.588 |   0.03066 |    0.8325 |
-#> |.....................|    0.7350 |     1.528 |     1.248 |     1.332 |
-#> |    F| Forward Diff. |     18.25 |  -0.08933 |   -0.2508 |    0.5157 |
-#> |.....................|    0.8830 |    -3.835 |    -1.133 |    -1.026 |
-#> |.....................|    -1.010 |    -2.153 |   -0.2439 |    -1.007 |
-#> |   60|     476.03808 |     1.001 |    -1.672 |   -0.9320 |   -0.9310 |
-#> |.....................|   -0.9291 |   -0.2079 |   -0.8419 |   -0.7733 |
-#> |.....................|    -1.039 |   -0.6026 |   -0.6913 |   -0.6380 |
-#> |    U|     476.03808 |     93.13 |    -5.972 |   -0.9594 |   -0.1466 |
-#> |.....................|     2.216 |     1.596 |   0.03074 |    0.8384 |
-#> |.....................|    0.7314 |     1.536 |     1.259 |     1.320 |
-#> |    X|     476.03808 |     93.13 |  0.002548 |    0.2770 |    0.8636 |
-#> |.....................|     9.173 |     1.596 |   0.03074 |    0.8384 |
-#> |.....................|    0.7314 |     1.536 |     1.259 |     1.320 |
-#> |    F| Forward Diff. |    -5.407 |  -0.06545 |    0.6727 |   0.05373 |
-#> |.....................|   -0.4541 |    -1.330 |   -0.5709 |   -0.1224 |
-#> |.....................|   -0.8702 |    -1.228 |    0.2640 |    -1.506 |
-#> |   61|     476.03300 |     1.003 |    -1.664 |   -0.9621 |   -0.9598 |
-#> |.....................|   -0.9520 |   -0.2020 |   -0.8337 |   -0.7650 |
-#> |.....................|    -1.042 |   -0.6106 |   -0.7076 |   -0.6154 |
-#> |    U|       476.033 |     93.29 |    -5.964 |   -0.9878 |   -0.1754 |
-#> |.....................|     2.193 |     1.599 |   0.03087 |    0.8447 |
-#> |.....................|    0.7289 |     1.526 |     1.241 |     1.344 |
-#> |    X|       476.033 |     93.29 |  0.002569 |    0.2714 |    0.8391 |
-#> |.....................|     8.966 |     1.599 |   0.03087 |    0.8447 |
-#> |.....................|    0.7289 |     1.526 |     1.241 |     1.344 |
-#> |    F| Forward Diff. |     15.25 | -0.008049 |   -0.5780 |   -0.5632 |
-#> |.....................|   -0.9601 |   -0.9870 |   -0.1614 |  -0.08306 |
-#> |.....................|    0.3446 |    -1.564 |   -0.5735 |   -0.5777 |
-#> |   62|     475.98457 |     1.001 |    -1.657 |   -0.9620 |   -0.9650 |
-#> |.....................|   -0.9284 |   -0.2016 |   -0.8312 |   -0.7567 |
-#> |.....................|    -1.045 |   -0.6004 |   -0.7091 |   -0.6133 |
-#> |    U|     475.98457 |     93.13 |    -5.957 |   -0.9877 |   -0.1806 |
-#> |.....................|     2.217 |     1.600 |   0.03091 |    0.8511 |
-#> |.....................|    0.7262 |     1.538 |     1.240 |     1.346 |
-#> |    X|     475.98457 |     93.13 |  0.002588 |    0.2714 |    0.8347 |
-#> |.....................|     9.180 |     1.600 |   0.03091 |    0.8511 |
-#> |.....................|    0.7262 |     1.538 |     1.240 |     1.346 |
-#> |   63|     475.96536 |     1.003 |    -1.649 |   -0.9620 |   -0.9705 |
-#> |.....................|   -0.9043 |   -0.2014 |   -0.8286 |   -0.7480 |
-#> |.....................|    -1.048 |   -0.5903 |   -0.7109 |   -0.6113 |
-#> |    U|     475.96536 |     93.24 |    -5.949 |   -0.9876 |   -0.1861 |
-#> |.....................|     2.241 |     1.600 |   0.03094 |    0.8576 |
-#> |.....................|    0.7235 |     1.551 |     1.238 |     1.349 |
-#> |    X|     475.96536 |     93.24 |  0.002608 |    0.2714 |    0.8302 |
-#> |.....................|     9.403 |     1.600 |   0.03094 |    0.8576 |
-#> |.....................|    0.7235 |     1.551 |     1.238 |     1.349 |
-#> |   64|     476.05821 |     1.003 |    -1.627 |   -0.9618 |   -0.9866 |
-#> |.....................|   -0.8332 |   -0.2007 |   -0.8211 |   -0.7226 |
-#> |.....................|    -1.057 |   -0.5602 |   -0.7159 |   -0.6052 |
-#> |    U|     476.05821 |     93.28 |    -5.927 |   -0.9874 |   -0.2022 |
-#> |.....................|     2.312 |     1.600 |   0.03106 |    0.8769 |
-#> |.....................|    0.7156 |     1.587 |     1.233 |     1.355 |
-#> |    X|     476.05821 |     93.28 |  0.002666 |    0.2714 |    0.8169 |
-#> |.....................|     10.10 |     1.600 |   0.03106 |    0.8769 |
-#> |.....................|    0.7156 |     1.587 |     1.233 |     1.355 |
-#> |    F| Forward Diff. |     11.90 |   0.05098 |   -0.6601 |   -0.8657 |
-#> |.....................|    0.4347 |   -0.9523 |   -0.3178 |   -0.1283 |
-#> |.....................|   -0.1024 |   -0.7800 |   -0.7284 |   -0.4981 |
-#> |   65|     476.00714 |     1.001 |    -1.643 |   -0.9512 |   -0.8390 |
-#> |.....................|   -0.8932 |   -0.2051 |   -0.7956 |   -0.7365 |
-#> |.....................|    -1.045 |   -0.5599 |   -0.7127 |   -0.5744 |
-#> |    U|     476.00714 |     93.11 |    -5.943 |   -0.9775 |  -0.05460 |
-#> |.....................|     2.252 |     1.598 |   0.03144 |    0.8663 |
-#> |.....................|    0.7264 |     1.588 |     1.236 |     1.388 |
-#> |    X|     476.00714 |     93.11 |  0.002624 |    0.2734 |    0.9469 |
-#> |.....................|     9.508 |     1.598 |   0.03144 |    0.8663 |
-#> |.....................|    0.7264 |     1.588 |     1.236 |     1.388 |
-#> |   66|     475.93814 |     1.000 |    -1.647 |   -0.9575 |   -0.9171 |
-#> |.....................|   -0.8999 |   -0.2027 |   -0.8152 |   -0.7434 |
-#> |.....................|    -1.047 |   -0.5779 |   -0.7115 |   -0.5963 |
-#> |    U|     475.93814 |     93.01 |    -5.947 |   -0.9834 |   -0.1327 |
-#> |.....................|     2.245 |     1.599 |   0.03115 |    0.8612 |
-#> |.....................|    0.7247 |     1.566 |     1.237 |     1.365 |
-#> |    X|     475.93814 |     93.01 |  0.002614 |    0.2722 |    0.8757 |
-#> |.....................|     9.445 |     1.599 |   0.03115 |    0.8612 |
-#> |.....................|    0.7247 |     1.566 |     1.237 |     1.365 |
-#> |    F| Forward Diff. |    -23.67 |   0.03897 |   -0.7058 |    0.2979 |
-#> |.....................|    0.2507 |   -0.5051 |   -0.4675 |  -0.05050 |
-#> |.....................|    -1.329 |   -0.1594 |   -0.7628 |    0.1885 |
-#> |   67|     475.98668 |     1.003 |    -1.653 |   -0.9119 |   -0.8938 |
-#> |.....................|   -0.8940 |   -0.2050 |   -0.7980 |   -0.7479 |
-#> |.....................|    -1.040 |   -0.5617 |   -0.7056 |   -0.5853 |
-#> |    U|     475.98668 |     93.26 |    -5.953 |   -0.9406 |   -0.1094 |
-#> |.....................|     2.251 |     1.598 |   0.03140 |    0.8577 |
-#> |.....................|    0.7310 |     1.586 |     1.243 |     1.376 |
-#> |    X|     475.98668 |     93.26 |  0.002598 |    0.2808 |    0.8964 |
-#> |.....................|     9.501 |     1.598 |   0.03140 |    0.8577 |
-#> |.....................|    0.7310 |     1.586 |     1.243 |     1.376 |
-#> |   68|     475.93401 |     1.003 |    -1.649 |   -0.9419 |   -0.9092 |
-#> |.....................|   -0.8979 |   -0.2035 |   -0.8093 |   -0.7449 |
-#> |.....................|    -1.044 |   -0.5723 |   -0.7094 |   -0.5925 |
-#> |    U|     475.93401 |     93.26 |    -5.949 |   -0.9687 |   -0.1248 |
-#> |.....................|     2.247 |     1.599 |   0.03123 |    0.8600 |
-#> |.....................|    0.7270 |     1.573 |     1.239 |     1.369 |
-#> |    X|     475.93401 |     93.26 |  0.002609 |    0.2751 |    0.8827 |
-#> |.....................|     9.464 |     1.599 |   0.03123 |    0.8600 |
-#> |.....................|    0.7270 |     1.573 |     1.239 |     1.369 |
-#> |    F| Forward Diff. |     21.62 |   0.03755 |    0.3553 |    0.5344 |
-#> |.....................|    0.5780 |   -0.8226 |   -0.2181 |   -0.2167 |
-#> |.....................|    -1.049 |  0.002537 |   -0.7279 |    0.2347 |
-#> |   69|     475.92580 |     1.001 |    -1.653 |   -0.9417 |   -0.9124 |
-#> |.....................|   -0.8966 |   -0.2037 |   -0.8058 |   -0.7501 |
-#> |.....................|    -1.041 |   -0.5739 |   -0.7048 |   -0.5926 |
-#> |    U|      475.9258 |     93.12 |    -5.953 |   -0.9686 |   -0.1280 |
-#> |.....................|     2.249 |     1.598 |   0.03129 |    0.8560 |
-#> |.....................|    0.7297 |     1.571 |     1.244 |     1.369 |
-#> |    X|      475.9258 |     93.12 |  0.002598 |    0.2752 |    0.8798 |
-#> |.....................|     9.476 |     1.598 |   0.03129 |    0.8560 |
-#> |.....................|    0.7297 |     1.571 |     1.244 |     1.369 |
-#> |    F| Forward Diff. |    -1.238 |  0.003180 |    0.2025 |    0.4289 |
-#> |.....................|    0.4493 |   -0.2935 |   -0.2270 |   -0.1209 |
-#> |.....................|    0.3327 |  -0.04065 |   -0.4864 |    0.2705 |
-#> |   70|     475.92421 |     1.002 |    -1.655 |   -0.9475 |   -0.9180 |
-#> |.....................|   -0.8971 |   -0.2051 |   -0.8017 |   -0.7499 |
-#> |.....................|    -1.041 |   -0.5760 |   -0.7024 |   -0.5951 |
-#> |    U|     475.92421 |     93.14 |    -5.955 |   -0.9740 |   -0.1336 |
-#> |.....................|     2.248 |     1.598 |   0.03135 |    0.8562 |
-#> |.....................|    0.7299 |     1.568 |     1.247 |     1.366 |
-#> |    X|     475.92421 |     93.14 |  0.002593 |    0.2741 |    0.8749 |
-#> |.....................|     9.472 |     1.598 |   0.03135 |    0.8562 |
-#> |.....................|    0.7299 |     1.568 |     1.247 |     1.366 |
-#> |    F| Forward Diff. |     1.572 | 0.0005078 |  -0.07939 |    0.3039 |
-#> |.....................|    0.4520 |   -0.5123 |   -0.2298 |   -0.1955 |
-#> |.....................|    0.3506 |   -0.1759 |   -0.3471 |    0.1717 |
-#> |   71|     475.91356 |     1.001 |    -1.654 |   -0.9476 |   -0.9223 |
-#> |.....................|   -0.8992 |   -0.2071 |   -0.7965 |   -0.7440 |
-#> |.....................|    -1.043 |   -0.5749 |   -0.7035 |   -0.5974 |
-#> |    U|     475.91356 |     93.12 |    -5.954 |   -0.9741 |   -0.1379 |
-#> |.....................|     2.246 |     1.596 |   0.03143 |    0.8607 |
-#> |.....................|    0.7278 |     1.569 |     1.246 |     1.363 |
-#> |    X|     475.91356 |     93.12 |  0.002596 |    0.2741 |    0.8712 |
-#> |.....................|     9.452 |     1.596 |   0.03143 |    0.8607 |
-#> |.....................|    0.7278 |     1.569 |     1.246 |     1.363 |
-#> |   72|     475.89054 |     1.001 |    -1.650 |   -0.9479 |   -0.9349 |
-#> |.....................|   -0.9054 |   -0.2136 |   -0.7808 |   -0.7261 |
-#> |.....................|    -1.051 |   -0.5716 |   -0.7071 |   -0.6043 |
-#> |    U|     475.89054 |     93.11 |    -5.950 |   -0.9744 |   -0.1505 |
-#> |.....................|     2.240 |     1.592 |   0.03166 |    0.8742 |
-#> |.....................|    0.7214 |     1.574 |     1.242 |     1.356 |
-#> |    X|     475.89054 |     93.11 |  0.002606 |    0.2740 |    0.8602 |
-#> |.....................|     9.393 |     1.592 |   0.03166 |    0.8742 |
-#> |.....................|    0.7214 |     1.574 |     1.242 |     1.356 |
-#> |    F| Forward Diff. |    -3.467 |   0.05330 |   -0.1133 |   -0.1045 |
-#> |.....................|    0.1362 |   -0.3304 |   -0.2172 |   0.04726 |
-#> |.....................|    -1.416 |   0.08323 |   -0.4566 |   -0.2851 |
-#> |   73|     476.06529 |     1.002 |    -1.688 |   -0.8959 |   -0.9784 |
-#> |.....................|   -0.9076 |   -0.2354 |   -0.6823 |   -0.7302 |
-#> |.....................|    -1.035 |   -0.5603 |   -0.6700 |   -0.6079 |
-#> |    U|     476.06529 |     93.20 |    -5.988 |   -0.9255 |   -0.1940 |
-#> |.....................|     2.238 |     1.579 |   0.03314 |    0.8712 |
-#> |.....................|    0.7347 |     1.587 |     1.281 |     1.352 |
-#> |    X|     476.06529 |     93.20 |  0.002510 |    0.2838 |    0.8236 |
-#> |.....................|     9.372 |     1.579 |   0.03314 |    0.8712 |
-#> |.....................|    0.7347 |     1.587 |     1.281 |     1.352 |
-#> |   74|     475.89054 |     1.001 |    -1.650 |   -0.9479 |   -0.9349 |
-#> |.....................|   -0.9054 |   -0.2136 |   -0.7808 |   -0.7261 |
-#> |.....................|    -1.051 |   -0.5716 |   -0.7071 |   -0.6043 |
-#> |    U|     475.89054 |     93.11 |    -5.950 |   -0.9744 |   -0.1505 |
-#> |.....................|     2.240 |     1.592 |   0.03166 |    0.8742 |
-#> |.....................|    0.7214 |     1.574 |     1.242 |     1.356 |
-#> |    X|     475.89054 |     93.11 |  0.002606 |    0.2740 |    0.8602 |
-#> |.....................|     9.393 |     1.592 |   0.03166 |    0.8742 |
-#> |.....................|    0.7214 |     1.574 |     1.242 |     1.356 |
-#> calculating covariance matrix
-#> done
-#> Calculating residuals/tables
-#> done
-f_nlmixr_dfop_sfo_focei_tc <- nlmixr(f_mmkin_tc["DFOP-SFO", ], est = "focei")
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → calculate jacobian
-#> 
-#> → calculate sensitivities
-#> 
-#> → calculate ∂(f)/∂(η)
-#> 
-#> → calculate ∂(R²)/∂(η)
-#> 
-#> → finding duplicate expressions in inner model...
-#> 
-#> → optimizing duplicate expressions in inner model...
-#> 
-#> → finding duplicate expressions in EBE model...
-#> 
-#> → optimizing duplicate expressions in EBE model...
-#> 
-#> → compiling inner model...
-#>  
-#> ✔ done
-#> → finding duplicate expressions in FD model...
-#> 
-#> → optimizing duplicate expressions in FD model...
-#> 
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> → compiling events FD model...
-#>  
-#> ✔ done
-#> Needed Covariates:
-#> [1] "CMT"
-#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> |    #| Objective Fun |  parent_0 |  log_k_A1 |f_parent_qlogis |    log_k1 |
-#> |.....................|    log_k2 |  g_qlogis | sigma_low |  rsd_high |
-#> |.....................|        o1 |        o2 |        o3 |        o4 |
-#> |.....................|        o5 |        o6 |...........|...........|
-#> |    1|     495.48573 |     1.000 |    -1.000 |   -0.9104 |   -0.9376 |
-#> |.....................|   -0.9875 |   -0.8823 |   -0.8746 |   -0.8907 |
-#> |.....................|   -0.8767 |   -0.8731 |   -0.8673 |   -0.8720 |
-#> |.....................|   -0.8739 |   -0.8666 |...........|...........|
-#> |    U|     495.48573 |     91.00 |    -5.200 |   -0.8900 |    -2.200 |
-#> |.....................|    -4.600 |    0.4600 |    0.8300 |   0.05800 |
-#> |.....................|    0.7311 |    0.9036 |     1.183 |    0.9554 |
-#> |.....................|    0.8633 |     1.214 |...........|...........|
-#> |    X|     495.48573 |     91.00 |  0.005517 |    0.2911 |    0.1108 |
-#> |.....................|   0.01005 |    0.6130 |    0.8300 |   0.05800 |
-#> |.....................|    0.7311 |    0.9036 |     1.183 |    0.9554 |
-#> |.....................|    0.8633 |     1.214 |...........|...........|
-#> |    G|    Gill Diff. |   -0.9650 |     2.223 |   -0.3153 |  -0.01817 |
-#> |.....................|   -0.3350 |    0.6789 |    -29.17 |    -19.58 |
-#> |.....................|    0.9642 |     9.851 |    -11.94 |    -1.319 |
-#> |.....................|     8.578 |    -12.45 |...........|...........|
-#> |    2|     487.27153 |     1.023 |    -1.054 |   -0.9028 |   -0.9372 |
-#> |.....................|   -0.9794 |   -0.8987 |   -0.1695 |   -0.4175 |
-#> |.....................|   -0.9000 |    -1.111 |   -0.5788 |   -0.8401 |
-#> |.....................|    -1.081 |   -0.5657 |...........|...........|
-#> |    U|     487.27153 |     93.12 |    -5.254 |   -0.8832 |    -2.200 |
-#> |.....................|    -4.592 |    0.4525 |     1.123 |   0.07172 |
-#> |.....................|    0.7141 |    0.6884 |     1.525 |    0.9859 |
-#> |.....................|    0.6843 |     1.580 |...........|...........|
-#> |    X|     487.27153 |     93.12 |  0.005228 |    0.2925 |    0.1109 |
-#> |.....................|   0.01013 |    0.6112 |     1.123 |   0.07172 |
-#> |.....................|    0.7141 |    0.6884 |     1.525 |    0.9859 |
-#> |.....................|    0.6843 |     1.580 |...........|...........|
-#> |    F| Forward Diff. |     131.2 |     1.375 |     2.844 |   -0.2311 |
-#> |.....................|    0.2724 |    0.4206 |     9.234 |     14.82 |
-#> |.....................|   -0.3432 |    -1.547 |    -2.137 |     2.699 |
-#> |.....................|    -4.845 |    -6.389 |...........|...........|
-#> |    3|     3806.3530 |    0.1967 |    -1.082 |   -0.9181 |   -0.9356 |
-#> |.....................|   -0.9782 |   -0.9073 |   0.02635 |   -0.3409 |
-#> |.....................|   -0.9062 |    -1.204 |   -0.4610 |   -0.8458 |
-#> |.....................|    -1.125 |   -0.4164 |...........|...........|
-#> |    U|      3806.353 |     17.90 |    -5.282 |   -0.8969 |    -2.198 |
-#> |.....................|    -4.591 |    0.4485 |     1.204 |   0.07394 |
-#> |.....................|    0.7095 |    0.6043 |     1.664 |    0.9805 |
-#> |.....................|    0.6463 |     1.761 |...........|...........|
-#> |    X|      3806.353 |     17.90 |  0.005083 |    0.2897 |    0.1110 |
-#> |.....................|   0.01015 |    0.6103 |     1.204 |   0.07394 |
-#> |.....................|    0.7095 |    0.6043 |     1.664 |    0.9805 |
-#> |.....................|    0.6463 |     1.761 |...........|...........|
-#> |    4|     498.29847 |    0.9363 |    -1.055 |   -0.9047 |   -0.9370 |
-#> |.....................|   -0.9796 |   -0.8990 |   -0.1756 |   -0.4273 |
-#> |.....................|   -0.8998 |    -1.110 |   -0.5773 |   -0.8419 |
-#> |.....................|    -1.078 |   -0.5615 |...........|...........|
-#> |    U|     498.29847 |     85.20 |    -5.255 |   -0.8849 |    -2.199 |
-#> |.....................|    -4.592 |    0.4523 |     1.120 |   0.07144 |
-#> |.....................|    0.7142 |    0.6894 |     1.526 |    0.9842 |
-#> |.....................|    0.6871 |     1.585 |...........|...........|
-#> |    X|     498.29847 |     85.20 |  0.005223 |    0.2922 |    0.1109 |
-#> |.....................|   0.01013 |    0.6112 |     1.120 |   0.07144 |
-#> |.....................|    0.7142 |    0.6894 |     1.526 |    0.9842 |
-#> |.....................|    0.6871 |     1.585 |...........|...........|
-#> |    5|     485.66266 |     1.001 |    -1.054 |   -0.9033 |   -0.9372 |
-#> |.....................|   -0.9795 |   -0.8988 |   -0.1711 |   -0.4200 |
-#> |.....................|   -0.8999 |    -1.111 |   -0.5784 |   -0.8406 |
-#> |.....................|    -1.080 |   -0.5646 |...........|...........|
-#> |    U|     485.66266 |     91.08 |    -5.254 |   -0.8836 |    -2.200 |
-#> |.....................|    -4.592 |    0.4524 |     1.122 |   0.07165 |
-#> |.....................|    0.7141 |    0.6887 |     1.525 |    0.9855 |
-#> |.....................|    0.6850 |     1.581 |...........|...........|
-#> |    X|     485.66266 |     91.08 |  0.005227 |    0.2924 |    0.1109 |
-#> |.....................|   0.01013 |    0.6112 |     1.122 |   0.07165 |
-#> |.....................|    0.7141 |    0.6887 |     1.525 |    0.9855 |
-#> |.....................|    0.6850 |     1.581 |...........|...........|
-#> |    F| Forward Diff. |     5.221 |     1.276 |    0.8286 |   0.07146 |
-#> |.....................|    0.3378 |    0.6177 |     8.950 |     14.42 |
-#> |.....................|    -2.232 |    -2.934 |    -2.090 |     2.822 |
-#> |.....................|    -4.031 |    -6.085 |...........|...........|
-#> |    6|     485.32609 |    0.9950 |    -1.055 |   -0.9042 |   -0.9372 |
-#> |.....................|   -0.9799 |   -0.8995 |   -0.1813 |   -0.4364 |
-#> |.....................|   -0.8974 |    -1.108 |   -0.5760 |   -0.8438 |
-#> |.....................|    -1.076 |   -0.5577 |...........|...........|
-#> |    U|     485.32609 |     90.54 |    -5.255 |   -0.8845 |    -2.200 |
-#> |.....................|    -4.592 |    0.4521 |     1.118 |   0.07117 |
-#> |.....................|    0.7160 |    0.6917 |     1.528 |    0.9824 |
-#> |.....................|    0.6890 |     1.589 |...........|...........|
-#> |    X|     485.32609 |     90.54 |  0.005219 |    0.2922 |    0.1108 |
-#> |.....................|   0.01013 |    0.6111 |     1.118 |   0.07117 |
-#> |.....................|    0.7160 |    0.6917 |     1.528 |    0.9824 |
-#> |.....................|    0.6890 |     1.589 |...........|...........|
-#> |    F| Forward Diff. |    -30.72 |     1.256 |    0.2407 |    0.1468 |
-#> |.....................|    0.3576 |    0.6982 |     8.550 |     13.79 |
-#> |.....................|    -2.152 |    -3.092 |    -1.869 |     2.672 |
-#> |.....................|    -3.399 |    -5.827 |...........|...........|
-#> |    7|     484.94767 |     1.003 |    -1.055 |   -0.9045 |   -0.9373 |
-#> |.....................|   -0.9801 |   -0.8996 |   -0.1956 |   -0.4497 |
-#> |.....................|   -0.8963 |    -1.103 |   -0.5795 |   -0.8455 |
-#> |.....................|    -1.071 |   -0.5595 |...........|...........|
-#> |    U|     484.94767 |     91.28 |    -5.255 |   -0.8848 |    -2.200 |
-#> |.....................|    -4.593 |    0.4521 |     1.112 |   0.07079 |
-#> |.....................|    0.7168 |    0.6961 |     1.524 |    0.9808 |
-#> |.....................|    0.6930 |     1.587 |...........|...........|
-#> |    X|     484.94767 |     91.28 |  0.005220 |    0.2922 |    0.1108 |
-#> |.....................|   0.01013 |    0.6111 |     1.112 |   0.07079 |
-#> |.....................|    0.7168 |    0.6961 |     1.524 |    0.9808 |
-#> |.....................|    0.6930 |     1.587 |...........|...........|
-#> |    F| Forward Diff. |     16.95 |     1.308 |    0.9181 |   0.03760 |
-#> |.....................|    0.3308 |    0.6549 |     8.124 |     13.74 |
-#> |.....................|    -1.975 |    -2.369 |    -2.107 |     2.437 |
-#> |.....................|    -3.334 |    -5.928 |...........|...........|
-#> |    8|     484.63747 |    0.9965 |    -1.055 |   -0.9051 |   -0.9373 |
-#> |.....................|   -0.9805 |   -0.8998 |   -0.2100 |   -0.4642 |
-#> |.....................|   -0.8952 |    -1.098 |   -0.5823 |   -0.8472 |
-#> |.....................|    -1.067 |   -0.5602 |...........|...........|
-#> |    U|     484.63747 |     90.68 |    -5.255 |   -0.8853 |    -2.200 |
-#> |.....................|    -4.593 |    0.4520 |     1.106 |   0.07037 |
-#> |.....................|    0.7176 |    0.7002 |     1.521 |    0.9792 |
-#> |.....................|    0.6968 |     1.586 |...........|...........|
-#> |    X|     484.63747 |     90.68 |  0.005220 |    0.2921 |    0.1108 |
-#> |.....................|   0.01012 |    0.6111 |     1.106 |   0.07037 |
-#> |.....................|    0.7176 |    0.7002 |     1.521 |    0.9792 |
-#> |.....................|    0.6968 |     1.586 |...........|...........|
-#> |    F| Forward Diff. |    -22.67 |     1.288 |    0.2773 |    0.1211 |
-#> |.....................|    0.3459 |    0.7203 |     8.028 |     13.24 |
-#> |.....................|    -1.967 |    -2.555 |    -2.117 |     2.333 |
-#> |.....................|    -2.789 |    -5.812 |...........|...........|
-#> |    9|     484.31288 |     1.003 |    -1.055 |   -0.9054 |   -0.9374 |
-#> |.....................|   -0.9808 |   -0.9000 |   -0.2248 |   -0.4783 |
-#> |.....................|   -0.8942 |    -1.094 |   -0.5856 |   -0.8486 |
-#> |.....................|    -1.063 |   -0.5617 |...........|...........|
-#> |    U|     484.31288 |     91.27 |    -5.255 |   -0.8855 |    -2.200 |
-#> |.....................|    -4.593 |    0.4519 |     1.100 |   0.06996 |
-#> |.....................|    0.7183 |    0.7043 |     1.517 |    0.9778 |
-#> |.....................|    0.7003 |     1.585 |...........|...........|
-#> |    X|     484.31288 |     91.27 |  0.005220 |    0.2920 |    0.1108 |
-#> |.....................|   0.01012 |    0.6111 |     1.100 |   0.06996 |
-#> |.....................|    0.7183 |    0.7043 |     1.517 |    0.9778 |
-#> |.....................|    0.7003 |     1.585 |...........|...........|
-#> |    F| Forward Diff. |     16.32 |     1.333 |    0.8110 |   0.03416 |
-#> |.....................|    0.3225 |    0.6774 |     7.502 |     12.95 |
-#> |.....................|    -1.990 |    -1.849 |    -2.190 |     2.193 |
-#> |.....................|    -2.714 |    -5.891 |...........|...........|
-#> |   10|     484.03445 |    0.9966 |    -1.055 |   -0.9058 |   -0.9374 |
-#> |.....................|   -0.9811 |   -0.9003 |   -0.2393 |   -0.4932 |
-#> |.....................|   -0.8929 |    -1.090 |   -0.5881 |   -0.8501 |
-#> |.....................|    -1.059 |   -0.5620 |...........|...........|
-#> |    U|     484.03445 |     90.69 |    -5.255 |   -0.8859 |    -2.200 |
-#> |.....................|    -4.594 |    0.4517 |     1.094 |   0.06953 |
-#> |.....................|    0.7192 |    0.7079 |     1.514 |    0.9764 |
-#> |.....................|    0.7034 |     1.584 |...........|...........|
-#> |    X|     484.03445 |     90.69 |  0.005219 |    0.2919 |    0.1108 |
-#> |.....................|   0.01012 |    0.6110 |     1.094 |   0.06953 |
-#> |.....................|    0.7192 |    0.7079 |     1.514 |    0.9764 |
-#> |.....................|    0.7034 |     1.584 |...........|...........|
-#> |    F| Forward Diff. |    -23.34 |     1.311 |    0.1997 |    0.1136 |
-#> |.....................|    0.3397 |    0.7422 |     7.043 |     12.17 |
-#> |.....................|    -1.843 |    -2.075 |    -2.300 |     2.141 |
-#> |.....................|    -2.235 |    -5.778 |...........|...........|
-#> |   11|     483.72794 |     1.003 |    -1.056 |   -0.9061 |   -0.9374 |
-#> |.....................|   -0.9815 |   -0.9008 |   -0.2540 |   -0.5081 |
-#> |.....................|   -0.8918 |    -1.086 |   -0.5906 |   -0.8514 |
-#> |.....................|    -1.056 |   -0.5623 |...........|...........|
-#> |    U|     483.72794 |     91.28 |    -5.256 |   -0.8861 |    -2.200 |
-#> |.....................|    -4.594 |    0.4515 |     1.088 |   0.06909 |
-#> |.....................|    0.7200 |    0.7113 |     1.511 |    0.9751 |
-#> |.....................|    0.7061 |     1.584 |...........|...........|
-#> |    X|     483.72794 |     91.28 |  0.005217 |    0.2919 |    0.1108 |
-#> |.....................|   0.01011 |    0.6110 |     1.088 |   0.06909 |
-#> |.....................|    0.7200 |    0.7113 |     1.511 |    0.9751 |
-#> |.....................|    0.7061 |     1.584 |...........|...........|
-#> |    F| Forward Diff. |     16.56 |     1.355 |    0.7367 |   0.03002 |
-#> |.....................|    0.3166 |    0.7021 |     6.528 |     11.89 |
-#> |.....................|    -1.880 |    -1.512 |    -2.404 |     1.917 |
-#> |.....................|    -2.215 |    -5.846 |...........|...........|
-#> |   12|     483.44272 |    0.9974 |    -1.057 |   -0.9064 |   -0.9375 |
-#> |.....................|   -0.9820 |   -0.9016 |   -0.2678 |   -0.5243 |
-#> |.....................|   -0.8904 |    -1.083 |   -0.5914 |   -0.8528 |
-#> |.....................|    -1.054 |   -0.5601 |...........|...........|
-#> |    U|     483.44272 |     90.76 |    -5.257 |   -0.8865 |    -2.200 |
-#> |.....................|    -4.594 |    0.4511 |     1.082 |   0.06862 |
-#> |.....................|    0.7211 |    0.7141 |     1.510 |    0.9738 |
-#> |.....................|    0.7081 |     1.587 |...........|...........|
-#> |    X|     483.44272 |     90.76 |  0.005212 |    0.2918 |    0.1108 |
-#> |.....................|   0.01011 |    0.6109 |     1.082 |   0.06862 |
-#> |.....................|    0.7211 |    0.7141 |     1.510 |    0.9738 |
-#> |.....................|    0.7081 |     1.587 |...........|...........|
-#> |    F| Forward Diff. |    -19.50 |     1.332 |    0.2061 |    0.1022 |
-#> |.....................|    0.3336 |    0.7519 |     5.944 |     11.09 |
-#> |.....................|    -1.878 |    -1.675 |    -2.404 |     1.054 |
-#> |.....................|    -1.833 |    -5.715 |...........|...........|
-#> |   13|     483.13758 |     1.003 |    -1.059 |   -0.9067 |   -0.9375 |
-#> |.....................|   -0.9826 |   -0.9029 |   -0.2791 |   -0.5415 |
-#> |.....................|   -0.8881 |    -1.081 |   -0.5896 |   -0.8508 |
-#> |.....................|    -1.053 |   -0.5541 |...........|...........|
-#> |    U|     483.13758 |     91.30 |    -5.259 |   -0.8867 |    -2.200 |
-#> |.....................|    -4.595 |    0.4505 |     1.077 |   0.06813 |
-#> |.....................|    0.7227 |    0.7157 |     1.512 |    0.9758 |
-#> |.....................|    0.7089 |     1.594 |...........|...........|
-#> |    X|     483.13758 |     91.30 |  0.005202 |    0.2918 |    0.1108 |
-#> |.....................|   0.01010 |    0.6108 |     1.077 |   0.06813 |
-#> |.....................|    0.7227 |    0.7157 |     1.512 |    0.9758 |
-#> |.....................|    0.7089 |     1.594 |...........|...........|
-#> |    F| Forward Diff. |     16.83 |     1.368 |    0.7006 |   0.02276 |
-#> |.....................|    0.3159 |    0.7144 |     5.487 |     10.74 |
-#> |.....................|    -1.773 |    -1.125 |    -2.251 |     1.956 |
-#> |.....................|    -1.882 |    -5.671 |...........|...........|
-#> |   14|     482.85180 |    0.9981 |    -1.062 |   -0.9072 |   -0.9376 |
-#> |.....................|   -0.9834 |   -0.9050 |   -0.2850 |   -0.5582 |
-#> |.....................|   -0.8853 |    -1.082 |   -0.5852 |   -0.8503 |
-#> |.....................|    -1.053 |   -0.5428 |...........|...........|
-#> |    U|      482.8518 |     90.83 |    -5.262 |   -0.8872 |    -2.200 |
-#> |.....................|    -4.596 |    0.4496 |     1.075 |   0.06764 |
-#> |.....................|    0.7248 |    0.7152 |     1.517 |    0.9762 |
-#> |.....................|    0.7084 |     1.607 |...........|...........|
-#> |    X|      482.8518 |     90.83 |  0.005184 |    0.2917 |    0.1108 |
-#> |.....................|   0.01009 |    0.6105 |     1.075 |   0.06764 |
-#> |.....................|    0.7248 |    0.7152 |     1.517 |    0.9762 |
-#> |.....................|    0.7084 |     1.607 |...........|...........|
-#> |    F| Forward Diff. |    -16.64 |     1.337 |    0.2421 |   0.09047 |
-#> |.....................|    0.3389 |    0.7643 |     5.051 |     10.06 |
-#> |.....................|    -1.787 |    -1.445 |    -2.047 |     2.073 |
-#> |.....................|    -1.627 |    -5.410 |...........|...........|
-#> |   15|     482.60290 |     1.003 |    -1.066 |   -0.9079 |   -0.9377 |
-#> |.....................|   -0.9844 |   -0.9075 |   -0.2858 |   -0.5723 |
-#> |.....................|   -0.8822 |    -1.083 |   -0.5806 |   -0.8571 |
-#> |.....................|    -1.055 |   -0.5294 |...........|...........|
-#> |    U|      482.6029 |     91.28 |    -5.266 |   -0.8878 |    -2.200 |
-#> |.....................|    -4.597 |    0.4484 |     1.074 |   0.06723 |
-#> |.....................|    0.7271 |    0.7136 |     1.523 |    0.9697 |
-#> |.....................|    0.7072 |     1.624 |...........|...........|
-#> |    X|      482.6029 |     91.28 |  0.005162 |    0.2916 |    0.1108 |
-#> |.....................|   0.01008 |    0.6103 |     1.074 |   0.06723 |
-#> |.....................|    0.7271 |    0.7136 |     1.523 |    0.9697 |
-#> |.....................|    0.7072 |     1.624 |...........|...........|
-#> |    F| Forward Diff. |     14.50 |     1.352 |    0.6742 |   0.02192 |
-#> |.....................|    0.3317 |    0.7297 |     4.803 |     9.894 |
-#> |.....................|    -1.694 |    -1.220 |    -2.031 |     1.506 |
-#> |.....................|    -1.722 |    -5.269 |...........|...........|
-#> |   16|     482.37953 |    0.9987 |    -1.071 |   -0.9090 |   -0.9377 |
-#> |.....................|   -0.9857 |   -0.9106 |   -0.2840 |   -0.5862 |
-#> |.....................|   -0.8787 |    -1.084 |   -0.5758 |   -0.8611 |
-#> |.....................|    -1.056 |   -0.5150 |...........|...........|
-#> |    U|     482.37953 |     90.88 |    -5.271 |   -0.8888 |    -2.200 |
-#> |.....................|    -4.598 |    0.4470 |     1.075 |   0.06683 |
-#> |.....................|    0.7296 |    0.7132 |     1.528 |    0.9659 |
-#> |.....................|    0.7058 |     1.641 |...........|...........|
-#> |    X|     482.37953 |     90.88 |  0.005137 |    0.2914 |    0.1108 |
-#> |.....................|   0.01007 |    0.6099 |     1.075 |   0.06683 |
-#> |.....................|    0.7296 |    0.7132 |     1.528 |    0.9659 |
-#> |.....................|    0.7058 |     1.641 |...........|...........|
-#> |   17|     482.17662 |    0.9986 |    -1.077 |   -0.9102 |   -0.9378 |
-#> |.....................|   -0.9871 |   -0.9141 |   -0.2800 |   -0.5994 |
-#> |.....................|   -0.8750 |    -1.085 |   -0.5707 |   -0.8654 |
-#> |.....................|    -1.059 |   -0.4996 |...........|...........|
-#> |    U|     482.17662 |     90.88 |    -5.277 |   -0.8898 |    -2.200 |
-#> |.....................|    -4.600 |    0.4454 |     1.077 |   0.06645 |
-#> |.....................|    0.7323 |    0.7123 |     1.534 |    0.9618 |
-#> |.....................|    0.7037 |     1.660 |...........|...........|
-#> |    X|     482.17662 |     90.88 |  0.005108 |    0.2911 |    0.1108 |
-#> |.....................|   0.01006 |    0.6095 |     1.077 |   0.06645 |
-#> |.....................|    0.7323 |    0.7123 |     1.534 |    0.9618 |
-#> |.....................|    0.7037 |     1.660 |...........|...........|
-#> |   18|     481.54428 |    0.9984 |    -1.097 |   -0.9142 |   -0.9379 |
-#> |.....................|   -0.9921 |   -0.9262 |   -0.2660 |   -0.6456 |
-#> |.....................|   -0.8623 |    -1.088 |   -0.5530 |   -0.8805 |
-#> |.....................|    -1.068 |   -0.4457 |...........|...........|
-#> |    U|     481.54428 |     90.86 |    -5.297 |   -0.8934 |    -2.200 |
-#> |.....................|    -4.605 |    0.4398 |     1.083 |   0.06511 |
-#> |.....................|    0.7417 |    0.7091 |     1.555 |    0.9473 |
-#> |.....................|    0.6961 |     1.725 |...........|...........|
-#> |    X|     481.54428 |     90.86 |  0.005009 |    0.2904 |    0.1108 |
-#> |.....................|   0.01001 |    0.6082 |     1.083 |   0.06511 |
-#> |.....................|    0.7417 |    0.7091 |     1.555 |    0.9473 |
-#> |.....................|    0.6961 |     1.725 |...........|...........|
-#> |   19|     480.42060 |    0.9980 |    -1.149 |   -0.9249 |   -0.9384 |
-#> |.....................|    -1.006 |   -0.9588 |   -0.2285 |   -0.7695 |
-#> |.....................|   -0.8280 |    -1.098 |   -0.5055 |   -0.9211 |
-#> |.....................|    -1.091 |   -0.3011 |...........|...........|
-#> |    U|      480.4206 |     90.81 |    -5.349 |   -0.9029 |    -2.201 |
-#> |.....................|    -4.618 |    0.4248 |     1.098 |   0.06151 |
-#> |.....................|    0.7667 |    0.7005 |     1.611 |    0.9085 |
-#> |.....................|    0.6759 |     1.901 |...........|...........|
-#> |    X|      480.4206 |     90.81 |  0.004753 |    0.2885 |    0.1107 |
-#> |.....................|  0.009872 |    0.6046 |     1.098 |   0.06151 |
-#> |.....................|    0.7667 |    0.7005 |     1.611 |    0.9085 |
-#> |.....................|    0.6759 |     1.901 |...........|...........|
-#> |    F| Forward Diff. |    -36.54 |     1.160 |   -0.4282 |   0.02550 |
-#> |.....................|    0.4248 |    0.7330 |     2.572 |     4.769 |
-#> |.....................|    -1.047 |    -1.982 |     1.244 |    -3.305 |
-#> |.....................|    -1.792 |    -2.494 |...........|...........|
-#> |   20|     480.52888 |     1.003 |    -1.232 |   -0.9300 |   -0.9345 |
-#> |.....................|    -1.037 |    -1.013 |   -0.2660 |   -0.9542 |
-#> |.....................|   -0.7770 |    -1.021 |   -0.6177 |   -0.7306 |
-#> |.....................|    -1.035 |   -0.1927 |...........|...........|
-#> |    U|     480.52888 |     91.28 |    -5.432 |   -0.9075 |    -2.197 |
-#> |.....................|    -4.649 |    0.3997 |     1.083 |   0.05616 |
-#> |.....................|    0.8040 |    0.7699 |     1.479 |     1.091 |
-#> |.....................|    0.7247 |     2.033 |...........|...........|
-#> |    X|     480.52888 |     91.28 |  0.004374 |    0.2875 |    0.1111 |
-#> |.....................|  0.009571 |    0.5986 |     1.083 |   0.05616 |
-#> |.....................|    0.8040 |    0.7699 |     1.479 |     1.091 |
-#> |.....................|    0.7247 |     2.033 |...........|...........|
-#> |   21|     479.69850 |     1.004 |    -1.189 |   -0.9273 |   -0.9365 |
-#> |.....................|    -1.020 |   -0.9850 |   -0.2467 |   -0.8583 |
-#> |.....................|   -0.8035 |    -1.061 |   -0.5593 |   -0.8297 |
-#> |.....................|    -1.064 |   -0.2490 |...........|...........|
-#> |    U|      479.6985 |     91.34 |    -5.389 |   -0.9050 |    -2.199 |
-#> |.....................|    -4.633 |    0.4128 |     1.091 |   0.05894 |
-#> |.....................|    0.7846 |    0.7338 |     1.548 |    0.9959 |
-#> |.....................|    0.6994 |     1.964 |...........|...........|
-#> |    X|      479.6985 |     91.34 |  0.004567 |    0.2880 |    0.1109 |
-#> |.....................|  0.009727 |    0.6018 |     1.091 |   0.05894 |
-#> |.....................|    0.7846 |    0.7338 |     1.548 |    0.9959 |
-#> |.....................|    0.6994 |     1.964 |...........|...........|
-#> |    F| Forward Diff. |     5.264 |     1.163 |  -0.05494 |  -0.06753 |
-#> |.....................|    0.3641 |    0.6248 |    0.1998 |     1.877 |
-#> |.....................|   -0.5696 |    0.3809 |    0.8989 |     3.758 |
-#> |.....................|    0.2123 |    -1.578 |...........|...........|
-#> |   22|     479.87893 |     1.001 |    -1.256 |   -0.9150 |   -0.9312 |
-#> |.....................|    -1.045 |    -1.024 |   -0.2268 |   -0.8946 |
-#> |.....................|   -0.7799 |    -1.052 |   -0.6825 |   -0.8629 |
-#> |.....................|    -1.056 |   -0.2060 |...........|...........|
-#> |    U|     479.87893 |     91.06 |    -5.456 |   -0.8941 |    -2.194 |
-#> |.....................|    -4.658 |    0.3949 |     1.099 |   0.05789 |
-#> |.....................|    0.8019 |    0.7416 |     1.402 |    0.9642 |
-#> |.....................|    0.7063 |     2.016 |...........|...........|
-#> |    X|     479.87893 |     91.06 |  0.004269 |    0.2903 |    0.1115 |
-#> |.....................|  0.009490 |    0.5975 |     1.099 |   0.05789 |
-#> |.....................|    0.8019 |    0.7416 |     1.402 |    0.9642 |
-#> |.....................|    0.7063 |     2.016 |...........|...........|
-#> |   23|     479.70356 |    0.9996 |    -1.214 |   -0.9229 |   -0.9346 |
-#> |.....................|    -1.029 |   -0.9992 |   -0.2397 |   -0.8723 |
-#> |.....................|   -0.7947 |    -1.058 |   -0.6038 |   -0.8437 |
-#> |.....................|    -1.061 |   -0.2328 |...........|...........|
-#> |    U|     479.70356 |     90.96 |    -5.414 |   -0.9011 |    -2.197 |
-#> |.....................|    -4.642 |    0.4062 |     1.093 |   0.05853 |
-#> |.....................|    0.7910 |    0.7364 |     1.495 |    0.9825 |
-#> |.....................|    0.7017 |     1.984 |...........|...........|
-#> |    X|     479.70356 |     90.96 |  0.004455 |    0.2888 |    0.1111 |
-#> |.....................|  0.009639 |    0.6002 |     1.093 |   0.05853 |
-#> |.....................|    0.7910 |    0.7364 |     1.495 |    0.9825 |
-#> |.....................|    0.7017 |     1.984 |...........|...........|
-#> |   24|     479.71523 |    0.9993 |    -1.201 |   -0.9253 |   -0.9356 |
-#> |.....................|    -1.025 |   -0.9918 |   -0.2436 |   -0.8656 |
-#> |.....................|   -0.7992 |    -1.060 |   -0.5801 |   -0.8379 |
-#> |.....................|    -1.063 |   -0.2408 |...........|...........|
-#> |    U|     479.71523 |     90.93 |    -5.401 |   -0.9032 |    -2.198 |
-#> |.....................|    -4.637 |    0.4096 |     1.092 |   0.05873 |
-#> |.....................|    0.7877 |    0.7349 |     1.523 |    0.9880 |
-#> |.....................|    0.7004 |     1.974 |...........|...........|
-#> |    X|     479.71523 |     90.93 |  0.004513 |    0.2884 |    0.1110 |
-#> |.....................|  0.009685 |    0.6010 |     1.092 |   0.05873 |
-#> |.....................|    0.7877 |    0.7349 |     1.523 |    0.9880 |
-#> |.....................|    0.7004 |     1.974 |...........|...........|
-#> |   25|     479.73471 |    0.9991 |    -1.194 |   -0.9266 |   -0.9362 |
-#> |.....................|    -1.022 |   -0.9877 |   -0.2457 |   -0.8619 |
-#> |.....................|   -0.8017 |    -1.061 |   -0.5670 |   -0.8347 |
-#> |.....................|    -1.064 |   -0.2453 |...........|...........|
-#> |    U|     479.73471 |     90.92 |    -5.394 |   -0.9044 |    -2.199 |
-#> |.....................|    -4.635 |    0.4115 |     1.091 |   0.05884 |
-#> |.....................|    0.7859 |    0.7340 |     1.539 |    0.9911 |
-#> |.....................|    0.6996 |     1.969 |...........|...........|
-#> |    X|     479.73471 |     90.92 |  0.004545 |    0.2881 |    0.1110 |
-#> |.....................|  0.009710 |    0.6015 |     1.091 |   0.05884 |
-#> |.....................|    0.7859 |    0.7340 |     1.539 |    0.9911 |
-#> |.....................|    0.6996 |     1.969 |...........|...........|
-#> |   26|     479.71271 |     1.001 |    -1.190 |   -0.9273 |   -0.9365 |
-#> |.....................|    -1.021 |   -0.9854 |   -0.2468 |   -0.8594 |
-#> |.....................|   -0.8032 |    -1.061 |   -0.5599 |   -0.8320 |
-#> |.....................|    -1.064 |   -0.2481 |...........|...........|
-#> |    U|     479.71271 |     91.05 |    -5.390 |   -0.9050 |    -2.199 |
-#> |.....................|    -4.633 |    0.4126 |     1.091 |   0.05891 |
-#> |.....................|    0.7849 |    0.7336 |     1.547 |    0.9937 |
-#> |.....................|    0.6993 |     1.965 |...........|...........|
-#> |    X|     479.71271 |     91.05 |  0.004564 |    0.2880 |    0.1109 |
-#> |.....................|  0.009725 |    0.6017 |     1.091 |   0.05891 |
-#> |.....................|    0.7849 |    0.7336 |     1.547 |    0.9937 |
-#> |.....................|    0.6993 |     1.965 |...........|...........|
-#> |   27|     479.69386 |     1.003 |    -1.189 |   -0.9273 |   -0.9365 |
-#> |.....................|    -1.020 |   -0.9851 |   -0.2467 |   -0.8587 |
-#> |.....................|   -0.8034 |    -1.061 |   -0.5595 |   -0.8305 |
-#> |.....................|    -1.064 |   -0.2487 |...........|...........|
-#> |    U|     479.69386 |     91.24 |    -5.389 |   -0.9050 |    -2.199 |
-#> |.....................|    -4.633 |    0.4127 |     1.091 |   0.05893 |
-#> |.....................|    0.7847 |    0.7338 |     1.548 |    0.9951 |
-#> |.....................|    0.6994 |     1.965 |...........|...........|
-#> |    X|     479.69386 |     91.24 |  0.004566 |    0.2880 |    0.1109 |
-#> |.....................|  0.009726 |    0.6017 |     1.091 |   0.05893 |
-#> |.....................|    0.7847 |    0.7338 |     1.548 |    0.9951 |
-#> |.....................|    0.6994 |     1.965 |...........|...........|
-#> |    F| Forward Diff. |    -3.722 |     1.155 |   -0.1645 |  -0.05121 |
-#> |.....................|    0.3669 |    0.6376 |   0.06785 |     1.772 |
-#> |.....................|   -0.5854 |    0.2936 |    0.9229 |     3.709 |
-#> |.....................|    0.2520 |    -1.579 |...........|...........|
-#> |   28|     479.68901 |     1.004 |    -1.189 |   -0.9273 |   -0.9365 |
-#> |.....................|    -1.021 |   -0.9853 |   -0.2467 |   -0.8591 |
-#> |.....................|   -0.8033 |    -1.061 |   -0.5597 |   -0.8314 |
-#> |.....................|    -1.064 |   -0.2483 |...........|...........|
-#> |    U|     479.68901 |     91.32 |    -5.389 |   -0.9050 |    -2.199 |
-#> |.....................|    -4.633 |    0.4126 |     1.091 |   0.05892 |
-#> |.....................|    0.7848 |    0.7337 |     1.547 |    0.9942 |
-#> |.....................|    0.6993 |     1.965 |...........|...........|
-#> |    X|     479.68901 |     91.32 |  0.004565 |    0.2880 |    0.1109 |
-#> |.....................|  0.009725 |    0.6017 |     1.091 |   0.05892 |
-#> |.....................|    0.7848 |    0.7337 |     1.547 |    0.9942 |
-#> |.....................|    0.6993 |     1.965 |...........|...........|
-#> |    F| Forward Diff. |     3.772 |     1.160 |  -0.07003 |  -0.06455 |
-#> |.....................|    0.3646 |    0.6238 |   0.08418 |     1.806 |
-#> |.....................|   -0.5672 |    0.3711 |    0.9250 |     3.651 |
-#> |.....................|    0.2161 |    -1.579 |...........|...........|
-#> |   29|     479.68474 |     1.003 |    -1.190 |   -0.9272 |   -0.9365 |
-#> |.....................|    -1.021 |   -0.9854 |   -0.2468 |   -0.8595 |
-#> |.....................|   -0.8031 |    -1.061 |   -0.5600 |   -0.8323 |
-#> |.....................|    -1.064 |   -0.2479 |...........|...........|
-#> |    U|     479.68474 |     91.24 |    -5.390 |   -0.9050 |    -2.199 |
-#> |.....................|    -4.633 |    0.4126 |     1.091 |   0.05890 |
-#> |.....................|    0.7849 |    0.7336 |     1.547 |    0.9934 |
-#> |.....................|    0.6993 |     1.966 |...........|...........|
-#> |    X|     479.68474 |     91.24 |  0.004563 |    0.2880 |    0.1109 |
-#> |.....................|  0.009724 |    0.6017 |     1.091 |   0.05890 |
-#> |.....................|    0.7849 |    0.7336 |     1.547 |    0.9934 |
-#> |.....................|    0.6993 |     1.966 |...........|...........|
-#> |    F| Forward Diff. |    -3.834 |     1.153 |   -0.1599 |  -0.05010 |
-#> |.....................|    0.3669 |    0.6355 |   0.09191 |     1.764 |
-#> |.....................|   -0.5796 |    0.2889 |     1.006 |     3.561 |
-#> |.....................|    0.2610 |    -1.565 |...........|...........|
-#> |   30|     479.68016 |     1.004 |    -1.190 |   -0.9272 |   -0.9365 |
-#> |.....................|    -1.021 |   -0.9856 |   -0.2468 |   -0.8600 |
-#> |.....................|   -0.8030 |    -1.061 |   -0.5602 |   -0.8332 |
-#> |.....................|    -1.064 |   -0.2475 |...........|...........|
-#> |    U|     479.68016 |     91.32 |    -5.390 |   -0.9050 |    -2.199 |
-#> |.....................|    -4.633 |    0.4125 |     1.091 |   0.05889 |
-#> |.....................|    0.7850 |    0.7336 |     1.547 |    0.9926 |
-#> |.....................|    0.6992 |     1.966 |...........|...........|
-#> |    X|     479.68016 |     91.32 |  0.004562 |    0.2880 |    0.1109 |
-#> |.....................|  0.009723 |    0.6017 |     1.091 |   0.05889 |
-#> |.....................|    0.7850 |    0.7336 |     1.547 |    0.9926 |
-#> |.....................|    0.6992 |     1.966 |...........|...........|
-#> |    F| Forward Diff. |     3.891 |     1.158 |  -0.06530 |  -0.06447 |
-#> |.....................|    0.3645 |    0.6207 |    0.1821 |     1.812 |
-#> |.....................|   -0.5486 |    0.3656 |     1.002 |     3.562 |
-#> |.....................|    0.2233 |    -1.574 |...........|...........|
-#> |   31|     479.67614 |     1.003 |    -1.190 |   -0.9272 |   -0.9365 |
-#> |.....................|    -1.021 |   -0.9857 |   -0.2468 |   -0.8604 |
-#> |.....................|   -0.8028 |    -1.061 |   -0.5604 |   -0.8341 |
-#> |.....................|    -1.064 |   -0.2472 |...........|...........|
-#> |    U|     479.67614 |     91.24 |    -5.390 |   -0.9049 |    -2.199 |
-#> |.....................|    -4.633 |    0.4124 |     1.091 |   0.05888 |
-#> |.....................|    0.7851 |    0.7335 |     1.546 |    0.9917 |
-#> |.....................|    0.6992 |     1.966 |...........|...........|
-#> |    X|     479.67614 |     91.24 |  0.004561 |    0.2880 |    0.1109 |
-#> |.....................|  0.009722 |    0.6017 |     1.091 |   0.05888 |
-#> |.....................|    0.7851 |    0.7335 |     1.546 |    0.9917 |
-#> |.....................|    0.6992 |     1.966 |...........|...........|
-#> |    F| Forward Diff. |    -3.915 |     1.151 |   -0.1574 |  -0.04977 |
-#> |.....................|    0.3672 |    0.6321 |   0.06058 |     1.705 |
-#> |.....................|   -0.5691 |    0.2601 |    0.8724 |     3.420 |
-#> |.....................|    0.2638 |    -1.562 |...........|...........|
-#> |   32|     479.67180 |     1.004 |    -1.191 |   -0.9271 |   -0.9364 |
-#> |.....................|    -1.021 |   -0.9859 |   -0.2469 |   -0.8608 |
-#> |.....................|   -0.8027 |    -1.061 |   -0.5607 |   -0.8349 |
-#> |.....................|    -1.064 |   -0.2468 |...........|...........|
-#> |    U|      479.6718 |     91.33 |    -5.391 |   -0.9049 |    -2.199 |
-#> |.....................|    -4.633 |    0.4124 |     1.091 |   0.05887 |
-#> |.....................|    0.7852 |    0.7334 |     1.546 |    0.9909 |
-#> |.....................|    0.6991 |     1.967 |...........|...........|
-#> |    X|      479.6718 |     91.33 |  0.004560 |    0.2880 |    0.1109 |
-#> |.....................|  0.009722 |    0.6017 |     1.091 |   0.05887 |
-#> |.....................|    0.7852 |    0.7334 |     1.546 |    0.9909 |
-#> |.....................|    0.6991 |     1.967 |...........|...........|
-#> |    F| Forward Diff. |     4.074 |     1.157 |  -0.05990 |  -0.06452 |
-#> |.....................|    0.3645 |    0.6170 |    0.1286 |     1.744 |
-#> |.....................|   -0.5576 |    0.3161 |    0.9007 |     3.345 |
-#> |.....................|    0.2216 |    -1.572 |...........|...........|
-#> |   33|     479.66809 |     1.003 |    -1.191 |   -0.9271 |   -0.9364 |
-#> |.....................|    -1.021 |   -0.9860 |   -0.2469 |   -0.8613 |
-#> |.....................|   -0.8026 |    -1.062 |   -0.5609 |   -0.8357 |
-#> |.....................|    -1.064 |   -0.2464 |...........|...........|
-#> |    U|     479.66809 |     91.23 |    -5.391 |   -0.9049 |    -2.199 |
-#> |.....................|    -4.634 |    0.4123 |     1.091 |   0.05885 |
-#> |.....................|    0.7853 |    0.7334 |     1.546 |    0.9901 |
-#> |.....................|    0.6991 |     1.967 |...........|...........|
-#> |    X|     479.66809 |     91.23 |  0.004558 |    0.2880 |    0.1109 |
-#> |.....................|  0.009721 |    0.6016 |     1.091 |   0.05885 |
-#> |.....................|    0.7853 |    0.7334 |     1.546 |    0.9901 |
-#> |.....................|    0.6991 |     1.967 |...........|...........|
-#> |    F| Forward Diff. |    -4.161 |     1.149 |   -0.1570 |  -0.04911 |
-#> |.....................|    0.3674 |    0.6293 |   0.04215 |     1.668 |
-#> |.....................|   -0.5621 |    0.2625 |    0.8940 |     3.313 |
-#> |.....................|    0.2611 |    -1.561 |...........|...........|
-#> |   34|     479.66397 |     1.004 |    -1.191 |   -0.9271 |   -0.9364 |
-#> |.....................|    -1.021 |   -0.9862 |   -0.2469 |   -0.8617 |
-#> |.....................|   -0.8024 |    -1.062 |   -0.5611 |   -0.8366 |
-#> |.....................|    -1.064 |   -0.2460 |...........|...........|
-#> |    U|     479.66397 |     91.33 |    -5.391 |   -0.9049 |    -2.199 |
-#> |.....................|    -4.634 |    0.4122 |     1.091 |   0.05884 |
-#> |.....................|    0.7854 |    0.7333 |     1.546 |    0.9893 |
-#> |.....................|    0.6990 |     1.968 |...........|...........|
-#> |    X|     479.66397 |     91.33 |  0.004557 |    0.2881 |    0.1109 |
-#> |.....................|  0.009720 |    0.6016 |     1.091 |   0.05884 |
-#> |.....................|    0.7854 |    0.7333 |     1.546 |    0.9893 |
-#> |.....................|    0.6990 |     1.968 |...........|...........|
-#> |    F| Forward Diff. |     4.197 |     1.155 |  -0.05534 |  -0.06448 |
-#> |.....................|    0.3644 |    0.6140 |    0.1526 |     1.765 |
-#> |.....................|   -0.5340 |    0.3555 |    0.9900 |     3.325 |
-#> |.....................|    0.2199 |    -1.571 |...........|...........|
-#> |   35|     479.66043 |     1.003 |    -1.191 |   -0.9271 |   -0.9364 |
-#> |.....................|    -1.021 |   -0.9863 |   -0.2469 |   -0.8621 |
-#> |.....................|   -0.8023 |    -1.062 |   -0.5613 |   -0.8374 |
-#> |.....................|    -1.064 |   -0.2456 |...........|...........|
-#> |    U|     479.66043 |     91.23 |    -5.391 |   -0.9048 |    -2.199 |
-#> |.....................|    -4.634 |    0.4122 |     1.090 |   0.05883 |
-#> |.....................|    0.7855 |    0.7332 |     1.545 |    0.9886 |
-#> |.....................|    0.6989 |     1.968 |...........|...........|
-#> |    X|     479.66043 |     91.23 |  0.004556 |    0.2881 |    0.1109 |
-#> |.....................|  0.009719 |    0.6016 |     1.090 |   0.05883 |
-#> |.....................|    0.7855 |    0.7332 |     1.545 |    0.9886 |
-#> |.....................|    0.6989 |     1.968 |...........|...........|
-#> |    F| Forward Diff. |    -4.161 |     1.147 |   -0.1538 |  -0.04891 |
-#> |.....................|    0.3674 |    0.6262 |   0.06581 |     1.677 |
-#> |.....................|   -0.5453 |    0.2828 |     1.029 |     3.251 |
-#> |.....................|    0.2683 |    -1.555 |...........|...........|
-#> |   36|     479.65652 |     1.004 |    -1.192 |   -0.9270 |   -0.9364 |
-#> |.....................|    -1.021 |   -0.9865 |   -0.2469 |   -0.8625 |
-#> |.....................|   -0.8022 |    -1.062 |   -0.5616 |   -0.8382 |
-#> |.....................|    -1.064 |   -0.2452 |...........|...........|
-#> |    U|     479.65652 |     91.33 |    -5.392 |   -0.9048 |    -2.199 |
-#> |.....................|    -4.634 |    0.4121 |     1.090 |   0.05882 |
-#> |.....................|    0.7856 |    0.7332 |     1.545 |    0.9878 |
-#> |.....................|    0.6989 |     1.969 |...........|...........|
-#> |    X|     479.65652 |     91.33 |  0.004554 |    0.2881 |    0.1109 |
-#> |.....................|  0.009718 |    0.6016 |     1.090 |   0.05882 |
-#> |.....................|    0.7856 |    0.7332 |     1.545 |    0.9878 |
-#> |.....................|    0.6989 |     1.969 |...........|...........|
-#> |    F| Forward Diff. |     4.221 |     1.153 |  -0.05203 |  -0.06424 |
-#> |.....................|    0.3643 |    0.6104 |   0.04854 |     1.680 |
-#> |.....................|   -0.5365 |    0.2999 |    0.7877 |     3.080 |
-#> |.....................|    0.2284 |    -1.566 |...........|...........|
-#> |   37|     479.65328 |     1.003 |    -1.192 |   -0.9270 |   -0.9364 |
-#> |.....................|    -1.021 |   -0.9866 |   -0.2470 |   -0.8629 |
-#> |.....................|   -0.8020 |    -1.062 |   -0.5618 |   -0.8389 |
-#> |.....................|    -1.064 |   -0.2448 |...........|...........|
-#> |    U|     479.65328 |     91.23 |    -5.392 |   -0.9048 |    -2.199 |
-#> |.....................|    -4.634 |    0.4120 |     1.090 |   0.05880 |
-#> |.....................|    0.7857 |    0.7331 |     1.545 |    0.9871 |
-#> |.....................|    0.6988 |     1.969 |...........|...........|
-#> |    X|     479.65328 |     91.23 |  0.004553 |    0.2881 |    0.1109 |
-#> |.....................|  0.009717 |    0.6016 |     1.090 |   0.05880 |
-#> |.....................|    0.7857 |    0.7331 |     1.545 |    0.9871 |
-#> |.....................|    0.6988 |     1.969 |...........|...........|
-#> |    F| Forward Diff. |    -4.438 |     1.145 |   -0.1538 |  -0.04822 |
-#> |.....................|    0.3675 |    0.6235 | 0.0004265 |     1.625 |
-#> |.....................|   -0.5487 |    0.2329 |    0.8499 |     3.058 |
-#> |.....................|    0.2658 |    -1.554 |...........|...........|
-#> |   38|     479.64923 |     1.004 |    -1.192 |   -0.9270 |   -0.9364 |
-#> |.....................|    -1.022 |   -0.9868 |   -0.2469 |   -0.8633 |
-#> |.....................|   -0.8019 |    -1.062 |   -0.5621 |   -0.8396 |
-#> |.....................|    -1.065 |   -0.2444 |...........|...........|
-#> |    U|     479.64923 |     91.32 |    -5.392 |   -0.9048 |    -2.199 |
-#> |.....................|    -4.634 |    0.4119 |     1.091 |   0.05879 |
-#> |.....................|    0.7858 |    0.7330 |     1.544 |    0.9864 |
-#> |.....................|    0.6988 |     1.970 |...........|...........|
-#> |    X|     479.64923 |     91.32 |  0.004551 |    0.2881 |    0.1109 |
-#> |.....................|  0.009716 |    0.6015 |     1.091 |   0.05879 |
-#> |.....................|    0.7858 |    0.7330 |     1.544 |    0.9864 |
-#> |.....................|    0.6988 |     1.970 |...........|...........|
-#> |    F| Forward Diff. |     3.878 |     1.150 |  -0.05277 |  -0.06333 |
-#> |.....................|    0.3643 |    0.6074 |   0.07271 |     1.651 |
-#> |.....................|   -0.5369 |    0.2992 |    0.8896 |     2.970 |
-#> |.....................|    0.2314 |    -1.562 |...........|...........|
-#> |   39|     479.64621 |     1.003 |    -1.193 |   -0.9270 |   -0.9363 |
-#> |.....................|    -1.022 |   -0.9870 |   -0.2469 |   -0.8638 |
-#> |.....................|   -0.8017 |    -1.062 |   -0.5623 |   -0.8404 |
-#> |.....................|    -1.065 |   -0.2440 |...........|...........|
-#> |    U|     479.64621 |     91.23 |    -5.393 |   -0.9047 |    -2.199 |
-#> |.....................|    -4.634 |    0.4119 |     1.091 |   0.05878 |
-#> |.....................|    0.7859 |    0.7330 |     1.544 |    0.9856 |
-#> |.....................|    0.6987 |     1.970 |...........|...........|
-#> |    X|     479.64621 |     91.23 |  0.004550 |    0.2881 |    0.1109 |
-#> |.....................|  0.009715 |    0.6015 |     1.091 |   0.05878 |
-#> |.....................|    0.7859 |    0.7330 |     1.544 |    0.9856 |
-#> |.....................|    0.6987 |     1.970 |...........|...........|
-#> |    F| Forward Diff. |    -4.471 |     1.143 |   -0.1506 |  -0.04802 |
-#> |.....................|    0.3674 |    0.6203 | -0.003354 |     1.603 |
-#> |.....................|   -0.5429 |    0.2243 |    0.9025 |     2.920 |
-#> |.....................|    0.2732 |    -1.548 |...........|...........|
-#> |   40|     479.64228 |     1.004 |    -1.193 |   -0.9269 |   -0.9363 |
-#> |.....................|    -1.022 |   -0.9872 |   -0.2468 |   -0.8642 |
-#> |.....................|   -0.8016 |    -1.062 |   -0.5627 |   -0.8411 |
-#> |.....................|    -1.065 |   -0.2435 |...........|...........|
-#> |    U|     479.64228 |     91.32 |    -5.393 |   -0.9047 |    -2.199 |
-#> |.....................|    -4.634 |    0.4118 |     1.091 |   0.05877 |
-#> |.....................|    0.7860 |    0.7329 |     1.544 |    0.9850 |
-#> |.....................|    0.6987 |     1.971 |...........|...........|
-#> |    X|     479.64228 |     91.32 |  0.004548 |    0.2881 |    0.1109 |
-#> |.....................|  0.009714 |    0.6015 |     1.091 |   0.05877 |
-#> |.....................|    0.7860 |    0.7329 |     1.544 |    0.9850 |
-#> |.....................|    0.6987 |     1.971 |...........|...........|
-#> |    F| Forward Diff. |     3.744 |     1.148 |  -0.05088 |  -0.06289 |
-#> |.....................|    0.3642 |    0.6037 |   0.03047 |     1.629 |
-#> |.....................|   -0.5287 |    0.2733 |    0.8334 |     2.850 |
-#> |.....................|    0.2290 |    -1.558 |...........|...........|
-#> |   41|     479.63935 |     1.003 |    -1.193 |   -0.9269 |   -0.9363 |
-#> |.....................|    -1.022 |   -0.9874 |   -0.2468 |   -0.8646 |
-#> |.....................|   -0.8014 |    -1.062 |   -0.5630 |   -0.8419 |
-#> |.....................|    -1.065 |   -0.2431 |...........|...........|
-#> |    U|     479.63935 |     91.23 |    -5.393 |   -0.9047 |    -2.199 |
-#> |.....................|    -4.634 |    0.4117 |     1.091 |   0.05876 |
-#> |.....................|    0.7861 |    0.7329 |     1.543 |    0.9843 |
-#> |.....................|    0.6986 |     1.971 |...........|...........|
-#> |    X|     479.63935 |     91.23 |  0.004547 |    0.2881 |    0.1110 |
-#> |.....................|  0.009713 |    0.6015 |     1.091 |   0.05876 |
-#> |.....................|    0.7861 |    0.7329 |     1.543 |    0.9843 |
-#> |.....................|    0.6986 |     1.971 |...........|...........|
-#> |    F| Forward Diff. |    -4.432 |     1.140 |   -0.1464 |  -0.04798 |
-#> |.....................|    0.3672 |    0.6157 |  -0.06295 |     1.547 |
-#> |.....................|   -0.5341 |    0.1919 |    0.7582 |     2.801 |
-#> |.....................|    0.2698 |    -1.544 |...........|...........|
-#> |   42|     479.63543 |     1.004 |    -1.194 |   -0.9268 |   -0.9363 |
-#> |.....................|    -1.022 |   -0.9876 |   -0.2467 |   -0.8650 |
-#> |.....................|   -0.8013 |    -1.062 |   -0.5633 |   -0.8425 |
-#> |.....................|    -1.065 |   -0.2426 |...........|...........|
-#> |    U|     479.63543 |     91.32 |    -5.394 |   -0.9046 |    -2.199 |
-#> |.....................|    -4.634 |    0.4116 |     1.091 |   0.05874 |
-#> |.....................|    0.7863 |    0.7328 |     1.543 |    0.9837 |
-#> |.....................|    0.6985 |     1.972 |...........|...........|
-#> |    X|     479.63543 |     91.32 |  0.004545 |    0.2881 |    0.1110 |
-#> |.....................|  0.009712 |    0.6015 |     1.091 |   0.05874 |
-#> |.....................|    0.7863 |    0.7328 |     1.543 |    0.9837 |
-#> |.....................|    0.6985 |     1.972 |...........|...........|
-#> |    F| Forward Diff. |     3.612 |     1.146 |  -0.04876 |  -0.06242 |
-#> |.....................|    0.3640 |    0.6002 |   0.04743 |     1.619 |
-#> |.....................|   -0.5199 |    0.2573 |    0.7734 |     2.739 |
-#> |.....................|    0.2298 |    -1.553 |...........|...........|
-#> |   43|     479.63248 |     1.003 |    -1.194 |   -0.9268 |   -0.9363 |
-#> |.....................|    -1.022 |   -0.9878 |   -0.2466 |   -0.8655 |
-#> |.....................|   -0.8011 |    -1.062 |   -0.5636 |   -0.8432 |
-#> |.....................|    -1.065 |   -0.2421 |...........|...........|
-#> |    U|     479.63248 |     91.23 |    -5.394 |   -0.9046 |    -2.199 |
-#> |.....................|    -4.635 |    0.4115 |     1.091 |   0.05873 |
-#> |.....................|    0.7864 |    0.7328 |     1.543 |    0.9830 |
-#> |.....................|    0.6985 |     1.973 |...........|...........|
-#> |    X|     479.63248 |     91.23 |  0.004543 |    0.2881 |    0.1110 |
-#> |.....................|  0.009710 |    0.6014 |     1.091 |   0.05873 |
-#> |.....................|    0.7864 |    0.7328 |     1.543 |    0.9830 |
-#> |.....................|    0.6985 |     1.973 |...........|...........|
-#> |    F| Forward Diff. |    -4.237 |     1.138 |   -0.1400 |  -0.04830 |
-#> |.....................|    0.3668 |    0.6108 |  -0.07665 |     1.521 |
-#> |.....................|   -0.5353 |    0.1893 |    0.7456 |     2.704 |
-#> |.....................|    0.2668 |    -1.543 |...........|...........|
-#> |   44|     479.62869 |     1.004 |    -1.195 |   -0.9268 |   -0.9362 |
-#> |.....................|    -1.022 |   -0.9880 |   -0.2464 |   -0.8659 |
-#> |.....................|   -0.8009 |    -1.062 |   -0.5639 |   -0.8438 |
-#> |.....................|    -1.065 |   -0.2415 |...........|...........|
-#> |    U|     479.62869 |     91.32 |    -5.395 |   -0.9046 |    -2.199 |
-#> |.....................|    -4.635 |    0.4114 |     1.091 |   0.05872 |
-#> |.....................|    0.7865 |    0.7327 |     1.542 |    0.9824 |
-#> |.....................|    0.6984 |     1.973 |...........|...........|
-#> |    X|     479.62869 |     91.32 |  0.004541 |    0.2881 |    0.1110 |
-#> |.....................|  0.009709 |    0.6014 |     1.091 |   0.05872 |
-#> |.....................|    0.7865 |    0.7327 |     1.542 |    0.9824 |
-#> |.....................|    0.6984 |     1.973 |...........|...........|
-#> |    F| Forward Diff. |     3.552 |     1.143 |  -0.04554 |  -0.06221 |
-#> |.....................|    0.3637 |    0.5952 |  -0.01323 |     1.563 |
-#> |.....................|   -0.3448 |    0.2470 |    0.7924 |     2.643 |
-#> |.....................|    0.2272 |    -1.550 |...........|...........|
-#> |   45|     479.62584 |     1.003 |    -1.195 |   -0.9268 |   -0.9362 |
-#> |.....................|    -1.022 |   -0.9883 |   -0.2463 |   -0.8663 |
-#> |.....................|   -0.8008 |    -1.062 |   -0.5642 |   -0.8446 |
-#> |.....................|    -1.065 |   -0.2410 |...........|...........|
-#> |    U|     479.62584 |     91.24 |    -5.395 |   -0.9046 |    -2.199 |
-#> |.....................|    -4.635 |    0.4113 |     1.091 |   0.05871 |
-#> |.....................|    0.7866 |    0.7326 |     1.542 |    0.9817 |
-#> |.....................|    0.6983 |     1.974 |...........|...........|
-#> |    X|     479.62584 |     91.24 |  0.004539 |    0.2881 |    0.1110 |
-#> |.....................|  0.009708 |    0.6014 |     1.091 |   0.05871 |
-#> |.....................|    0.7866 |    0.7326 |     1.542 |    0.9817 |
-#> |.....................|    0.6983 |     1.974 |...........|...........|
-#> |    F| Forward Diff. |    -4.148 |     1.135 |   -0.1348 |  -0.04846 |
-#> |.....................|    0.3664 |    0.6063 | -0.009834 |     1.510 |
-#> |.....................|   -0.5271 |    0.1803 |    0.7932 |     2.587 |
-#> |.....................|    0.2684 |    -1.536 |...........|...........|
-#> |   46|     479.62216 |     1.004 |    -1.195 |   -0.9267 |   -0.9362 |
-#> |.....................|    -1.023 |   -0.9885 |   -0.2462 |   -0.8667 |
-#> |.....................|   -0.8007 |    -1.062 |   -0.5646 |   -0.8451 |
-#> |.....................|    -1.065 |   -0.2404 |...........|...........|
-#> |    U|     479.62216 |     91.32 |    -5.395 |   -0.9045 |    -2.199 |
-#> |.....................|    -4.635 |    0.4112 |     1.091 |   0.05870 |
-#> |.....................|    0.7867 |    0.7326 |     1.541 |    0.9811 |
-#> |.....................|    0.6983 |     1.975 |...........|...........|
-#> |    X|     479.62216 |     91.32 |  0.004537 |    0.2881 |    0.1110 |
-#> |.....................|  0.009706 |    0.6014 |     1.091 |   0.05870 |
-#> |.....................|    0.7867 |    0.7326 |     1.541 |    0.9811 |
-#> |.....................|    0.6983 |     1.975 |...........|...........|
-#> |    F| Forward Diff. |     3.404 |     1.140 |  -0.04564 |  -0.06187 |
-#> |.....................|    0.3633 |    0.5903 |  -0.01970 |     1.541 |
-#> |.....................|   -0.5054 |    0.2303 |    0.6483 |     2.528 |
-#> |.....................|    0.2288 |    -1.542 |...........|...........|
-#> |   47|     479.61938 |     1.003 |    -1.196 |   -0.9267 |   -0.9362 |
-#> |.....................|    -1.023 |   -0.9887 |   -0.2461 |   -0.8672 |
-#> |.....................|   -0.8005 |    -1.062 |   -0.5649 |   -0.8458 |
-#> |.....................|    -1.065 |   -0.2398 |...........|...........|
-#> |    U|     479.61938 |     91.24 |    -5.396 |   -0.9045 |    -2.199 |
-#> |.....................|    -4.635 |    0.4111 |     1.091 |   0.05868 |
-#> |.....................|    0.7868 |    0.7325 |     1.541 |    0.9805 |
-#> |.....................|    0.6982 |     1.975 |...........|...........|
-#> |    X|     479.61938 |     91.24 |  0.004535 |    0.2881 |    0.1110 |
-#> |.....................|  0.009705 |    0.6013 |     1.091 |   0.05868 |
-#> |.....................|    0.7868 |    0.7325 |     1.541 |    0.9805 |
-#> |.....................|    0.6982 |     1.975 |...........|...........|
-#> |    F| Forward Diff. |    -4.197 |     1.132 |   -0.1312 |  -0.04839 |
-#> |.....................|    0.3660 |    0.6012 |   0.05916 |     1.560 |
-#> |.....................|   -0.4869 |    0.2015 |    0.8305 |     2.573 |
-#> |.....................|    0.2666 |    -1.531 |...........|...........|
-#> |   48|     479.61563 |     1.003 |    -1.196 |   -0.9266 |   -0.9361 |
-#> |.....................|    -1.023 |   -0.9890 |   -0.2459 |   -0.8676 |
-#> |.....................|   -0.8003 |    -1.062 |   -0.5653 |   -0.8464 |
-#> |.....................|    -1.065 |   -0.2392 |...........|...........|
-#> |    U|     479.61563 |     91.32 |    -5.396 |   -0.9044 |    -2.199 |
-#> |.....................|    -4.635 |    0.4109 |     1.091 |   0.05867 |
-#> |.....................|    0.7870 |    0.7325 |     1.541 |    0.9799 |
-#> |.....................|    0.6981 |     1.976 |...........|...........|
-#> |    X|     479.61563 |     91.32 |  0.004533 |    0.2881 |    0.1110 |
-#> |.....................|  0.009703 |    0.6013 |     1.091 |   0.05867 |
-#> |.....................|    0.7870 |    0.7325 |     1.541 |    0.9799 |
-#> |.....................|    0.6981 |     1.976 |...........|...........|
-#> |    F| Forward Diff. |     3.024 |     1.137 |  -0.04591 |  -0.06118 |
-#> |.....................|    0.3629 |    0.5856 |  0.004035 |     1.536 |
-#> |.....................|   -0.4978 |    0.2329 |    0.6617 |     2.436 |
-#> |.....................|    0.2318 |    -1.535 |...........|...........|
-#> |   49|     479.61337 |     1.003 |    -1.197 |   -0.9266 |   -0.9361 |
-#> |.....................|    -1.023 |   -0.9892 |   -0.2459 |   -0.8680 |
-#> |.....................|   -0.8001 |    -1.063 |   -0.5655 |   -0.8471 |
-#> |.....................|    -1.065 |   -0.2388 |...........|...........|
-#> |    U|     479.61337 |     91.23 |    -5.397 |   -0.9044 |    -2.198 |
-#> |.....................|    -4.635 |    0.4109 |     1.091 |   0.05866 |
-#> |.....................|    0.7871 |    0.7324 |     1.540 |    0.9792 |
-#> |.....................|    0.6980 |     1.977 |...........|...........|
-#> |    X|     479.61337 |     91.23 |  0.004531 |    0.2881 |    0.1110 |
-#> |.....................|  0.009702 |    0.6013 |     1.091 |   0.05866 |
-#> |.....................|    0.7871 |    0.7324 |     1.540 |    0.9792 |
-#> |.....................|    0.6980 |     1.977 |...........|...........|
-#> |    F| Forward Diff. |    -4.815 |     1.129 |   -0.1342 |  -0.04706 |
-#> |.....................|    0.3660 |    0.5971 |  -0.07697 |     1.438 |
-#> |.....................|   -0.5059 |    0.1462 |    0.6633 |     2.381 |
-#> |.....................|    0.2676 |    -1.522 |...........|...........|
-#> |   50|     479.60932 |     1.003 |    -1.197 |   -0.9266 |   -0.9361 |
-#> |.....................|    -1.023 |   -0.9894 |   -0.2456 |   -0.8684 |
-#> |.....................|   -0.8000 |    -1.063 |   -0.5659 |   -0.8476 |
-#> |.....................|    -1.066 |   -0.2381 |...........|...........|
-#> |    U|     479.60932 |     91.31 |    -5.397 |   -0.9044 |    -2.198 |
-#> |.....................|    -4.636 |    0.4107 |     1.091 |   0.05865 |
-#> |.....................|    0.7872 |    0.7324 |     1.540 |    0.9788 |
-#> |.....................|    0.6979 |     1.977 |...........|...........|
-#> |    X|     479.60932 |     91.31 |  0.004529 |    0.2882 |    0.1110 |
-#> |.....................|  0.009700 |    0.6013 |     1.091 |   0.05865 |
-#> |.....................|    0.7872 |    0.7324 |     1.540 |    0.9788 |
-#> |.....................|    0.6979 |     1.977 |...........|...........|
-#> |    F| Forward Diff. |     2.699 |     1.134 |  -0.04549 |  -0.06017 |
-#> |.....................|    0.3630 |    0.5814 |  -0.04512 |     1.484 |
-#> |.....................|   -0.4915 |    0.2556 |    0.7248 |     2.322 |
-#> |.....................|    0.2317 |    -1.529 |...........|...........|
-#> |   51|     479.60706 |     1.003 |    -1.198 |   -0.9265 |   -0.9361 |
-#> |.....................|    -1.023 |   -0.9896 |   -0.2455 |   -0.8689 |
-#> |.....................|   -0.7998 |    -1.063 |   -0.5661 |   -0.8484 |
-#> |.....................|    -1.066 |   -0.2376 |...........|...........|
-#> |    U|     479.60706 |     91.23 |    -5.398 |   -0.9044 |    -2.198 |
-#> |.....................|    -4.636 |    0.4106 |     1.091 |   0.05863 |
-#> |.....................|    0.7873 |    0.7323 |     1.540 |    0.9781 |
-#> |.....................|    0.6979 |     1.978 |...........|...........|
-#> |    X|     479.60706 |     91.23 |  0.004527 |    0.2882 |    0.1110 |
-#> |.....................|  0.009699 |    0.6012 |     1.091 |   0.05863 |
-#> |.....................|    0.7873 |    0.7323 |     1.540 |    0.9781 |
-#> |.....................|    0.6979 |     1.978 |...........|...........|
-#> |    F| Forward Diff. |    -4.618 |     1.127 |   -0.1276 |  -0.04760 |
-#> |.....................|    0.3656 |    0.5915 |  -0.08622 |     1.415 |
-#> |.....................|   -0.5531 |    0.1512 |    0.6569 |     2.298 |
-#> |.....................|    0.2620 |    -1.540 |...........|...........|
-#> |   52|     479.60314 |     1.003 |    -1.198 |   -0.9265 |   -0.9360 |
-#> |.....................|    -1.023 |   -0.9899 |   -0.2452 |   -0.8692 |
-#> |.....................|   -0.7996 |    -1.063 |   -0.5665 |   -0.8488 |
-#> |.....................|    -1.066 |   -0.2369 |...........|...........|
-#> |    U|     479.60314 |     91.31 |    -5.398 |   -0.9043 |    -2.198 |
-#> |.....................|    -4.636 |    0.4105 |     1.091 |   0.05862 |
-#> |.....................|    0.7875 |    0.7322 |     1.539 |    0.9776 |
-#> |.....................|    0.6978 |     1.979 |...........|...........|
-#> |    X|     479.60314 |     91.31 |  0.004525 |    0.2882 |    0.1110 |
-#> |.....................|  0.009698 |    0.6012 |     1.091 |   0.05862 |
-#> |.....................|    0.7875 |    0.7322 |     1.539 |    0.9776 |
-#> |.....................|    0.6978 |     1.979 |...........|...........|
-#> |    F| Forward Diff. |     2.641 |     1.131 |  -0.04213 |  -0.06002 |
-#> |.....................|    0.3627 |    0.5770 |  -0.05114 |     1.464 |
-#> |.....................|   -0.4913 |    0.1735 |    0.5980 |     2.238 |
-#> |.....................|    0.2116 |    -1.521 |...........|...........|
-#> |   53|     479.60093 |     1.003 |    -1.199 |   -0.9265 |   -0.9360 |
-#> |.....................|    -1.024 |   -0.9901 |   -0.2452 |   -0.8697 |
-#> |.....................|   -0.7994 |    -1.063 |   -0.5667 |   -0.8495 |
-#> |.....................|    -1.066 |   -0.2363 |...........|...........|
-#> |    U|     479.60093 |     91.23 |    -5.399 |   -0.9043 |    -2.198 |
-#> |.....................|    -4.636 |    0.4104 |     1.091 |   0.05861 |
-#> |.....................|    0.7876 |    0.7322 |     1.539 |    0.9769 |
-#> |.....................|    0.6977 |     1.980 |...........|...........|
-#> |    X|     479.60093 |     91.23 |  0.004523 |    0.2882 |    0.1110 |
-#> |.....................|  0.009696 |    0.6012 |     1.091 |   0.05861 |
-#> |.....................|    0.7876 |    0.7322 |     1.539 |    0.9769 |
-#> |.....................|    0.6977 |     1.980 |...........|...........|
-#> |    F| Forward Diff. |    -4.657 |     1.124 |   -0.1240 |  -0.04721 |
-#> |.....................|    0.3655 |    0.5872 |  -0.09119 |     1.382 |
-#> |.....................|   -0.4948 |    0.1646 |    0.6965 |     2.186 |
-#> |.....................|    0.2747 |    -1.512 |...........|...........|
-#> |   54|     479.59701 |     1.003 |    -1.199 |   -0.9264 |   -0.9360 |
-#> |.....................|    -1.024 |   -0.9904 |   -0.2448 |   -0.8700 |
-#> |.....................|   -0.7992 |    -1.063 |   -0.5670 |   -0.8499 |
-#> |.....................|    -1.066 |   -0.2356 |...........|...........|
-#> |    U|     479.59701 |     91.31 |    -5.399 |   -0.9043 |    -2.198 |
-#> |.....................|    -4.636 |    0.4103 |     1.091 |   0.05860 |
-#> |.....................|    0.7877 |    0.7321 |     1.539 |    0.9766 |
-#> |.....................|    0.6976 |     1.980 |...........|...........|
-#> |    X|     479.59701 |     91.31 |  0.004520 |    0.2882 |    0.1110 |
-#> |.....................|  0.009695 |    0.6012 |     1.091 |   0.05860 |
-#> |.....................|    0.7877 |    0.7321 |     1.539 |    0.9766 |
-#> |.....................|    0.6976 |     1.980 |...........|...........|
-#> |    F| Forward Diff. |     2.447 |     1.128 |  -0.03826 |  -0.05934 |
-#> |.....................|    0.3628 |    0.5721 |  -0.04376 |     1.440 |
-#> |.....................|   -0.4844 |    0.2233 |   -0.3355 |     1.410 |
-#> |.....................|   -0.3677 |    -1.539 |...........|...........|
-#> |   55|     479.59436 |     1.003 |    -1.200 |   -0.9264 |   -0.9360 |
-#> |.....................|    -1.024 |   -0.9907 |   -0.2446 |   -0.8705 |
-#> |.....................|   -0.7990 |    -1.063 |   -0.5669 |   -0.8504 |
-#> |.....................|    -1.066 |   -0.2349 |...........|...........|
-#> |    U|     479.59436 |     91.23 |    -5.400 |   -0.9042 |    -2.198 |
-#> |.....................|    -4.636 |    0.4102 |     1.091 |   0.05858 |
-#> |.....................|    0.7879 |    0.7320 |     1.539 |    0.9761 |
-#> |.....................|    0.6977 |     1.981 |...........|...........|
-#> |    X|     479.59436 |     91.23 |  0.004518 |    0.2882 |    0.1110 |
-#> |.....................|  0.009693 |    0.6011 |     1.091 |   0.05858 |
-#> |.....................|    0.7879 |    0.7320 |     1.539 |    0.9761 |
-#> |.....................|    0.6977 |     1.981 |...........|...........|
-#> |    F| Forward Diff. |    -4.478 |     1.121 |   -0.1165 |  -0.04761 |
-#> |.....................|    0.3651 |    0.5835 |  -0.09604 |     1.373 |
-#> |.....................|   -0.4943 |    0.1086 |   -0.4551 |     1.395 |
-#> |.....................|   -0.3088 |    -1.502 |...........|...........|
-#> |   56|     479.58979 |     1.003 |    -1.200 |   -0.9263 |   -0.9359 |
-#> |.....................|    -1.024 |   -0.9910 |   -0.2442 |   -0.8708 |
-#> |.....................|   -0.7988 |    -1.063 |   -0.5665 |   -0.8506 |
-#> |.....................|    -1.066 |   -0.2341 |...........|...........|
-#> |    U|     479.58979 |     91.30 |    -5.400 |   -0.9042 |    -2.198 |
-#> |.....................|    -4.637 |    0.4100 |     1.092 |   0.05858 |
-#> |.....................|    0.7880 |    0.7319 |     1.539 |    0.9759 |
-#> |.....................|    0.6978 |     1.982 |...........|...........|
-#> |    X|     479.58979 |     91.30 |  0.004516 |    0.2882 |    0.1110 |
-#> |.....................|  0.009691 |    0.6011 |     1.092 |   0.05858 |
-#> |.....................|    0.7880 |    0.7319 |     1.539 |    0.9759 |
-#> |.....................|    0.6978 |     1.982 |...........|...........|
-#> |    F| Forward Diff. |     1.813 |     1.125 |  -0.03904 |  -0.05862 |
-#> |.....................|    0.3624 |    0.5728 | -0.008587 |     1.448 |
-#> |.....................|   -0.2657 |    0.1639 |    0.6610 |     2.108 |
-#> |.....................|    0.2622 |    -1.501 |...........|...........|
-#> |   57|     479.58727 |     1.003 |    -1.201 |   -0.9263 |   -0.9359 |
-#> |.....................|    -1.024 |   -0.9912 |   -0.2441 |   -0.8713 |
-#> |.....................|   -0.7987 |    -1.063 |   -0.5668 |   -0.8514 |
-#> |.....................|    -1.066 |   -0.2335 |...........|...........|
-#> |    U|     479.58727 |     91.24 |    -5.401 |   -0.9042 |    -2.198 |
-#> |.....................|    -4.637 |    0.4099 |     1.092 |   0.05856 |
-#> |.....................|    0.7881 |    0.7318 |     1.539 |    0.9751 |
-#> |.....................|    0.6978 |     1.983 |...........|...........|
-#> |    X|     479.58727 |     91.24 |  0.004513 |    0.2882 |    0.1110 |
-#> |.....................|  0.009690 |    0.6011 |     1.092 |   0.05856 |
-#> |.....................|    0.7881 |    0.7318 |     1.539 |    0.9751 |
-#> |.....................|    0.6978 |     1.983 |...........|...........|
-#> |    F| Forward Diff. |    -3.987 |     1.119 |   -0.1055 |  -0.04878 |
-#> |.....................|    0.3644 |    0.5797 |  -0.03160 |     1.359 |
-#> |.....................|   -0.4809 |   0.09403 |   -0.4184 |     1.337 |
-#> |.....................|   -0.2770 |    -1.489 |...........|...........|
-#> |   58|     479.58366 |     1.004 |    -1.201 |   -0.9263 |   -0.9359 |
-#> |.....................|    -1.024 |   -0.9915 |   -0.2438 |   -0.8717 |
-#> |.....................|   -0.7986 |    -1.063 |   -0.5667 |   -0.8517 |
-#> |.....................|    -1.066 |   -0.2327 |...........|...........|
-#> |    U|     479.58366 |     91.32 |    -5.401 |   -0.9041 |    -2.198 |
-#> |.....................|    -4.637 |    0.4098 |     1.092 |   0.05855 |
-#> |.....................|    0.7882 |    0.7317 |     1.539 |    0.9749 |
-#> |.....................|    0.6978 |     1.984 |...........|...........|
-#> |    X|     479.58366 |     91.32 |  0.004511 |    0.2882 |    0.1110 |
-#> |.....................|  0.009688 |    0.6010 |     1.092 |   0.05855 |
-#> |.....................|    0.7882 |    0.7317 |     1.539 |    0.9749 |
-#> |.....................|    0.6978 |     1.984 |...........|...........|
-#> |    F| Forward Diff. |     3.434 |     1.122 |  -0.01954 |  -0.06326 |
-#> |.....................|    0.3597 |    0.5645 |  -0.03484 |     1.404 |
-#> |.....................|   -0.4782 |    0.1697 |  -0.05991 |     1.573 |
-#> |.....................|    0.2504 |    -1.489 |...........|...........|
-#> |   59|     479.57994 |     1.003 |    -1.202 |   -0.9262 |   -0.9358 |
-#> |.....................|    -1.025 |   -0.9918 |   -0.2433 |   -0.8720 |
-#> |.....................|   -0.7984 |    -1.063 |   -0.5664 |   -0.8520 |
-#> |.....................|    -1.066 |   -0.2319 |...........|...........|
-#> |    U|     479.57994 |     91.26 |    -5.402 |   -0.9041 |    -2.198 |
-#> |.....................|    -4.637 |    0.4096 |     1.092 |   0.05854 |
-#> |.....................|    0.7884 |    0.7316 |     1.539 |    0.9746 |
-#> |.....................|    0.6977 |     1.985 |...........|...........|
-#> |    X|     479.57994 |     91.26 |  0.004508 |    0.2882 |    0.1110 |
-#> |.....................|  0.009686 |    0.6010 |     1.092 |   0.05854 |
-#> |.....................|    0.7884 |    0.7316 |     1.539 |    0.9746 |
-#> |.....................|    0.6977 |     1.985 |...........|...........|
-#> |    F| Forward Diff. |    -2.328 |     1.117 |  -0.07952 |  -0.05137 |
-#> |.....................|    0.3636 |    0.5738 |   0.02815 |     1.418 |
-#> |.....................|   -0.4669 |    0.1345 |    0.7258 |     2.078 |
-#> |.....................|    0.2949 |    -1.476 |...........|...........|
-#> |   60|     479.57683 |     1.004 |    -1.202 |   -0.9262 |   -0.9358 |
-#> |.....................|    -1.025 |   -0.9921 |   -0.2431 |   -0.8724 |
-#> |.....................|   -0.7982 |    -1.064 |   -0.5667 |   -0.8526 |
-#> |.....................|    -1.066 |   -0.2311 |...........|...........|
-#> |    U|     479.57683 |     91.32 |    -5.402 |   -0.9041 |    -2.198 |
-#> |.....................|    -4.637 |    0.4095 |     1.092 |   0.05853 |
-#> |.....................|    0.7885 |    0.7315 |     1.539 |    0.9740 |
-#> |.....................|    0.6976 |     1.986 |...........|...........|
-#> |    X|     479.57683 |     91.32 |  0.004505 |    0.2882 |    0.1110 |
-#> |.....................|  0.009684 |    0.6010 |     1.092 |   0.05853 |
-#> |.....................|    0.7885 |    0.7315 |     1.539 |    0.9740 |
-#> |.....................|    0.6976 |     1.986 |...........|...........|
-#> |    F| Forward Diff. |     3.369 |     1.121 |  -0.01236 |  -0.06033 |
-#> |.....................|    0.3618 |    0.5608 | -0.009614 |     1.424 |
-#> |.....................|   -0.4677 |    0.1416 |    0.6194 |     1.932 |
-#> |.....................|    0.2634 |    -1.483 |...........|...........|
-#> |   61|     479.57433 |     1.003 |    -1.203 |   -0.9262 |   -0.9358 |
-#> |.....................|    -1.025 |   -0.9924 |   -0.2429 |   -0.8728 |
-#> |.....................|   -0.7980 |    -1.064 |   -0.5671 |   -0.8530 |
-#> |.....................|    -1.066 |   -0.2304 |...........|...........|
-#> |    U|     479.57433 |     91.25 |    -5.403 |   -0.9041 |    -2.198 |
-#> |.....................|    -4.637 |    0.4094 |     1.092 |   0.05852 |
-#> |.....................|    0.7886 |    0.7315 |     1.539 |    0.9736 |
-#> |.....................|    0.6975 |     1.987 |...........|...........|
-#> |    X|     479.57433 |     91.25 |  0.004503 |    0.2882 |    0.1110 |
-#> |.....................|  0.009683 |    0.6009 |     1.092 |   0.05852 |
-#> |.....................|    0.7886 |    0.7315 |     1.539 |    0.9736 |
-#> |.....................|    0.6975 |     1.987 |...........|...........|
-#> |    F| Forward Diff. |    -3.507 |     1.111 |  -0.09183 |  -0.05192 |
-#> |.....................|    0.3614 |    0.5665 |  -0.03887 |     1.349 |
-#> |.....................|   -0.4753 |   0.07826 |    0.5528 |     1.905 |
-#> |.....................|    0.2844 |    -1.468 |...........|...........|
-#> |   62|     479.57116 |     1.003 |    -1.204 |   -0.9262 |   -0.9357 |
-#> |.....................|    -1.025 |   -0.9927 |   -0.2425 |   -0.8732 |
-#> |.....................|   -0.7978 |    -1.064 |   -0.5674 |   -0.8534 |
-#> |.....................|    -1.066 |   -0.2297 |...........|...........|
-#> |    U|     479.57116 |     91.32 |    -5.404 |   -0.9040 |    -2.198 |
-#> |.....................|    -4.638 |    0.4092 |     1.092 |   0.05851 |
-#> |.....................|    0.7888 |    0.7315 |     1.538 |    0.9732 |
-#> |.....................|    0.6973 |     1.988 |...........|...........|
-#> |    X|     479.57116 |     91.32 |  0.004500 |    0.2882 |    0.1110 |
-#> |.....................|  0.009681 |    0.6009 |     1.092 |   0.05851 |
-#> |.....................|    0.7888 |    0.7315 |     1.538 |    0.9732 |
-#> |.....................|    0.6973 |     1.988 |...........|...........|
-#> |    F| Forward Diff. |     2.953 |     1.117 |  -0.01332 |  -0.05913 |
-#> |.....................|    0.3618 |    0.5550 |  -0.01942 |     1.377 |
-#> |.....................|   -0.4588 |    0.1396 |    0.5378 |     1.901 |
-#> |.....................|    0.2564 |    -1.475 |...........|...........|
-#> |   63|     479.56857 |     1.003 |    -1.204 |   -0.9261 |   -0.9357 |
-#> |.....................|    -1.025 |   -0.9930 |   -0.2422 |   -0.8735 |
-#> |.....................|   -0.7976 |    -1.064 |   -0.5677 |   -0.8539 |
-#> |.....................|    -1.066 |   -0.2289 |...........|...........|
-#> |    U|     479.56857 |     91.25 |    -5.404 |   -0.9040 |    -2.198 |
-#> |.....................|    -4.638 |    0.4091 |     1.092 |   0.05850 |
-#> |.....................|    0.7889 |    0.7314 |     1.538 |    0.9728 |
-#> |.....................|    0.6972 |     1.989 |...........|...........|
-#> |    X|     479.56857 |     91.25 |  0.004497 |    0.2882 |    0.1110 |
-#> |.....................|  0.009679 |    0.6009 |     1.092 |   0.05850 |
-#> |.....................|    0.7889 |    0.7314 |     1.538 |    0.9728 |
-#> |.....................|    0.6972 |     1.989 |...........|...........|
-#> |    F| Forward Diff. |    -3.279 |     1.109 |  -0.08378 |  -0.05051 |
-#> |.....................|    0.3625 |    0.5609 |  -0.06234 |     1.320 |
-#> |.....................|   -0.5093 |   0.06989 |    -1.266 |     1.852 |
-#> |.....................|    0.2753 |    -1.463 |...........|...........|
-#> |   64|     479.56430 |     1.003 |    -1.205 |   -0.9261 |   -0.9357 |
-#> |.....................|    -1.026 |   -0.9933 |   -0.2419 |   -0.8738 |
-#> |.....................|   -0.7974 |    -1.064 |   -0.5672 |   -0.8543 |
-#> |.....................|    -1.067 |   -0.2281 |...........|...........|
-#> |    U|      479.5643 |     91.31 |    -5.405 |   -0.9040 |    -2.198 |
-#> |.....................|    -4.638 |    0.4090 |     1.093 |   0.05849 |
-#> |.....................|    0.7891 |    0.7314 |     1.538 |    0.9724 |
-#> |.....................|    0.6971 |     1.990 |...........|...........|
-#> |    X|      479.5643 |     91.31 |  0.004495 |    0.2882 |    0.1110 |
-#> |.....................|  0.009677 |    0.6008 |     1.093 |   0.05849 |
-#> |.....................|    0.7891 |    0.7314 |     1.538 |    0.9724 |
-#> |.....................|    0.6971 |     1.990 |...........|...........|
-#> |    F| Forward Diff. |     2.181 |     1.113 |  -0.01711 |  -0.05862 |
-#> |.....................|    0.3610 |    0.5490 |  -0.06295 |     1.399 |
-#> |.....................|   -0.4495 |    0.1474 |    0.6781 |     1.913 |
-#> |.....................|    0.2455 |    -1.468 |...........|...........|
-#> |   65|     479.56239 |     1.003 |    -1.205 |   -0.9261 |   -0.9356 |
-#> |.....................|    -1.026 |   -0.9935 |   -0.2417 |   -0.8744 |
-#> |.....................|   -0.7972 |    -1.064 |   -0.5674 |   -0.8549 |
-#> |.....................|    -1.067 |   -0.2275 |...........|...........|
-#> |    U|     479.56239 |     91.24 |    -5.405 |   -0.9040 |    -2.198 |
-#> |.....................|    -4.638 |    0.4089 |     1.093 |   0.05847 |
-#> |.....................|    0.7892 |    0.7313 |     1.538 |    0.9718 |
-#> |.....................|    0.6970 |     1.990 |...........|...........|
-#> |    X|     479.56239 |     91.24 |  0.004493 |    0.2882 |    0.1110 |
-#> |.....................|  0.009675 |    0.6008 |     1.093 |   0.05847 |
-#> |.....................|    0.7892 |    0.7313 |     1.538 |    0.9718 |
-#> |.....................|    0.6970 |     1.990 |...........|...........|
-#> |    F| Forward Diff. |    -4.516 |     1.106 |  -0.09308 |  -0.04714 |
-#> |.....................|    0.3636 |    0.5580 |  -0.04406 |     1.488 |
-#> |.....................|   -0.4662 |   0.05187 |    0.6104 |     1.787 |
-#> |.....................|    0.2769 |    -1.453 |...........|...........|
-#> |   66|     479.55877 |     1.003 |    -1.206 |   -0.9261 |   -0.9356 |
-#> |.....................|    -1.026 |   -0.9938 |   -0.2414 |   -0.8747 |
-#> |.....................|   -0.7970 |    -1.064 |   -0.5678 |   -0.8553 |
-#> |.....................|    -1.067 |   -0.2268 |...........|...........|
-#> |    U|     479.55877 |     91.31 |    -5.406 |   -0.9039 |    -2.198 |
-#> |.....................|    -4.638 |    0.4087 |     1.093 |   0.05846 |
-#> |.....................|    0.7894 |    0.7313 |     1.538 |    0.9714 |
-#> |.....................|    0.6969 |     1.991 |...........|...........|
-#> |    X|     479.55877 |     91.31 |  0.004490 |    0.2882 |    0.1110 |
-#> |.....................|  0.009674 |    0.6008 |     1.093 |   0.05846 |
-#> |.....................|    0.7894 |    0.7313 |     1.538 |    0.9714 |
-#> |.....................|    0.6969 |     1.991 |...........|...........|
-#> |    F| Forward Diff. |     2.254 |     1.111 |  -0.01255 |  -0.05783 |
-#> |.....................|    0.3613 |    0.5437 |  -0.01079 |     1.366 |
-#> |.....................|   -0.4954 |    0.1048 |    0.5565 |     1.745 |
-#> |.....................|    0.2417 |    -1.458 |...........|...........|
-#> |   67|     479.55696 |     1.003 |    -1.206 |   -0.9261 |   -0.9356 |
-#> |.....................|    -1.026 |   -0.9940 |   -0.2413 |   -0.8753 |
-#> |.....................|   -0.7968 |    -1.064 |   -0.5681 |   -0.8559 |
-#> |.....................|    -1.067 |   -0.2262 |...........|...........|
-#> |    U|     479.55696 |     91.24 |    -5.406 |   -0.9039 |    -2.198 |
-#> |.....................|    -4.639 |    0.4086 |     1.093 |   0.05845 |
-#> |.....................|    0.7895 |    0.7312 |     1.537 |    0.9708 |
-#> |.....................|    0.6968 |     1.992 |...........|...........|
-#> |    X|     479.55696 |     91.24 |  0.004488 |    0.2882 |    0.1110 |
-#> |.....................|  0.009672 |    0.6008 |     1.093 |   0.05845 |
-#> |.....................|    0.7895 |    0.7312 |     1.537 |    0.9708 |
-#> |.....................|    0.6968 |     1.992 |...........|...........|
-#> |    F| Forward Diff. |    -4.420 |     1.104 |  -0.08938 |  -0.04652 |
-#> |.....................|    0.3638 |    0.5524 |  -0.03600 |     1.474 |
-#> |.....................|   -0.4537 |   0.08714 |    0.5943 |     1.686 |
-#> |.....................|    0.2777 |    -1.443 |...........|...........|
-#> |   68|     479.55331 |     1.003 |    -1.207 |   -0.9260 |   -0.9356 |
-#> |.....................|    -1.026 |   -0.9943 |   -0.2409 |   -0.8756 |
-#> |.....................|   -0.7966 |    -1.064 |   -0.5684 |   -0.8562 |
-#> |.....................|    -1.067 |   -0.2254 |...........|...........|
-#> |    U|     479.55331 |     91.31 |    -5.407 |   -0.9039 |    -2.198 |
-#> |.....................|    -4.639 |    0.4085 |     1.093 |   0.05844 |
-#> |.....................|    0.7897 |    0.7312 |     1.537 |    0.9706 |
-#> |.....................|    0.6966 |     1.993 |...........|...........|
-#> |    X|     479.55331 |     91.31 |  0.004485 |    0.2882 |    0.1110 |
-#> |.....................|  0.009670 |    0.6007 |     1.093 |   0.05844 |
-#> |.....................|    0.7897 |    0.7312 |     1.537 |    0.9706 |
-#> |.....................|    0.6966 |     1.993 |...........|...........|
-#> |    F| Forward Diff. |     1.940 |     1.107 |  -0.01326 |  -0.05734 |
-#> |.....................|    0.3610 |    0.5380 |  -0.03050 |     1.334 |
-#> |.....................|   -0.4419 |   0.09953 |    0.4758 |     1.660 |
-#> |.....................|    0.2363 |    -1.448 |...........|...........|
-#> |   69|     479.55178 |     1.003 |    -1.208 |   -0.9260 |   -0.9355 |
-#> |.....................|    -1.026 |   -0.9945 |   -0.2409 |   -0.8762 |
-#> |.....................|   -0.7964 |    -1.064 |   -0.5686 |   -0.8569 |
-#> |.....................|    -1.067 |   -0.2248 |...........|...........|
-#> |    U|     479.55178 |     91.23 |    -5.408 |   -0.9039 |    -2.198 |
-#> |.....................|    -4.639 |    0.4084 |     1.093 |   0.05842 |
-#> |.....................|    0.7898 |    0.7311 |     1.537 |    0.9699 |
-#> |.....................|    0.6965 |     1.994 |...........|...........|
-#> |    X|     479.55178 |     91.23 |  0.004483 |    0.2882 |    0.1110 |
-#> |.....................|  0.009668 |    0.6007 |     1.093 |   0.05842 |
-#> |.....................|    0.7898 |    0.7311 |     1.537 |    0.9699 |
-#> |.....................|    0.6965 |     1.994 |...........|...........|
-#> |    F| Forward Diff. |    -4.846 |     1.100 |  -0.09130 |  -0.04553 |
-#> |.....................|    0.3638 |    0.5474 |  -0.02936 |     1.430 |
-#> |.....................|   -0.4494 |   0.05105 |    0.6245 |     1.611 |
-#> |.....................|    0.2724 |    -1.435 |...........|...........|
-#> |   70|     479.54790 |     1.003 |    -1.208 |   -0.9260 |   -0.9355 |
-#> |.....................|    -1.027 |   -0.9948 |   -0.2405 |   -0.8765 |
-#> |.....................|   -0.7962 |    -1.064 |   -0.5690 |   -0.8571 |
-#> |.....................|    -1.067 |   -0.2240 |...........|...........|
-#> |    U|      479.5479 |     91.30 |    -5.408 |   -0.9039 |    -2.198 |
-#> |.....................|    -4.639 |    0.4083 |     1.093 |   0.05841 |
-#> |.....................|    0.7899 |    0.7311 |     1.536 |    0.9697 |
-#> |.....................|    0.6964 |     1.995 |...........|...........|
-#> |    X|      479.5479 |     91.30 |  0.004480 |    0.2883 |    0.1110 |
-#> |.....................|  0.009667 |    0.6007 |     1.093 |   0.05841 |
-#> |.....................|    0.7899 |    0.7311 |     1.536 |    0.9697 |
-#> |.....................|    0.6964 |     1.995 |...........|...........|
-#> |    F| Forward Diff. |     1.570 |     1.104 |  -0.01594 |  -0.05674 |
-#> |.....................|    0.3607 |    0.5327 |  -0.02577 |     1.253 |
-#> |.....................|   -0.4401 |   0.07544 |   -0.5163 |    0.8741 |
-#> |.....................|   -0.3456 |    -1.445 |...........|...........|
-#> |   71|     479.54587 |     1.003 |    -1.209 |   -0.9260 |   -0.9355 |
-#> |.....................|    -1.027 |   -0.9951 |   -0.2405 |   -0.8771 |
-#> |.....................|   -0.7960 |    -1.064 |   -0.5687 |   -0.8576 |
-#> |.....................|    -1.067 |   -0.2233 |...........|...........|
-#> |    U|     479.54587 |     91.23 |    -5.409 |   -0.9039 |    -2.198 |
-#> |.....................|    -4.639 |    0.4081 |     1.093 |   0.05839 |
-#> |.....................|    0.7901 |    0.7310 |     1.537 |    0.9693 |
-#> |.....................|    0.6965 |     1.995 |...........|...........|
-#> |    X|     479.54587 |     91.23 |  0.004478 |    0.2883 |    0.1110 |
-#> |.....................|  0.009665 |    0.6006 |     1.093 |   0.05839 |
-#> |.....................|    0.7901 |    0.7310 |     1.537 |    0.9693 |
-#> |.....................|    0.6965 |     1.995 |...........|...........|
-#> |    F| Forward Diff. |    -4.902 |     1.097 |  -0.08880 |  -0.04568 |
-#> |.....................|    0.3633 |    0.5436 |  -0.03820 |     1.421 |
-#> |.....................|   -0.4438 |   0.04451 |    0.5507 |     1.558 |
-#> |.....................|    0.2862 |    -1.423 |...........|...........|
-#> |   72|     479.54157 |     1.003 |    -1.209 |   -0.9260 |   -0.9354 |
-#> |.....................|    -1.027 |   -0.9954 |   -0.2399 |   -0.8773 |
-#> |.....................|   -0.7958 |    -1.064 |   -0.5687 |   -0.8577 |
-#> |.....................|    -1.067 |   -0.2225 |...........|...........|
-#> |    U|     479.54157 |     91.30 |    -5.409 |   -0.9038 |    -2.198 |
-#> |.....................|    -4.639 |    0.4080 |     1.093 |   0.05839 |
-#> |.....................|    0.7902 |    0.7309 |     1.537 |    0.9691 |
-#> |.....................|    0.6965 |     1.996 |...........|...........|
-#> |    X|     479.54157 |     91.30 |  0.004475 |    0.2883 |    0.1110 |
-#> |.....................|  0.009663 |    0.6006 |     1.093 |   0.05839 |
-#> |.....................|    0.7902 |    0.7309 |     1.537 |    0.9691 |
-#> |.....................|    0.6965 |     1.996 |...........|...........|
-#> |    F| Forward Diff. |     1.063 |     1.100 |  -0.01768 |  -0.05631 |
-#> |.....................|    0.3603 |    0.5311 |  -0.05904 |     1.468 |
-#> |.....................|   -0.4400 |   0.06384 |    0.5216 |     1.564 |
-#> |.....................|    0.2548 |    -1.433 |...........|...........|
-#> |   73|     479.53906 |     1.003 |    -1.210 |   -0.9259 |   -0.9354 |
-#> |.....................|    -1.027 |   -0.9956 |   -0.2399 |   -0.8780 |
-#> |.....................|   -0.7956 |    -1.064 |   -0.5689 |   -0.8584 |
-#> |.....................|    -1.067 |   -0.2218 |...........|...........|
-#> |    U|     479.53906 |     91.25 |    -5.410 |   -0.9038 |    -2.198 |
-#> |.....................|    -4.640 |    0.4079 |     1.093 |   0.05837 |
-#> |.....................|    0.7904 |    0.7309 |     1.536 |    0.9684 |
-#> |.....................|    0.6964 |     1.997 |...........|...........|
-#> |    X|     479.53906 |     91.25 |  0.004472 |    0.2883 |    0.1110 |
-#> |.....................|  0.009661 |    0.6006 |     1.093 |   0.05837 |
-#> |.....................|    0.7904 |    0.7309 |     1.536 |    0.9684 |
-#> |.....................|    0.6964 |     1.997 |...........|...........|
-#> |    F| Forward Diff. |    -3.131 |     1.095 |  -0.06506 |  -0.04908 |
-#> |.....................|    0.3620 |    0.5356 | -0.007514 |     1.441 |
-#> |.....................|   -0.4274 |   0.08578 |   -0.3543 |    0.8441 |
-#> |.....................|   -0.2944 |    -1.418 |...........|...........|
-#> |   74|     479.53616 |     1.004 |    -1.210 |   -0.9259 |   -0.9354 |
-#> |.....................|    -1.027 |   -0.9959 |   -0.2396 |   -0.8785 |
-#> |.....................|   -0.7954 |    -1.064 |   -0.5688 |   -0.8586 |
-#> |.....................|    -1.067 |   -0.2210 |...........|...........|
-#> |    U|     479.53616 |     91.33 |    -5.410 |   -0.9038 |    -2.198 |
-#> |.....................|    -4.640 |    0.4077 |     1.094 |   0.05835 |
-#> |.....................|    0.7905 |    0.7308 |     1.537 |    0.9682 |
-#> |.....................|    0.6965 |     1.998 |...........|...........|
-#> |    X|     479.53616 |     91.33 |  0.004470 |    0.2883 |    0.1111 |
-#> |.....................|  0.009659 |    0.6005 |     1.094 |   0.05835 |
-#> |.....................|    0.7905 |    0.7308 |     1.537 |    0.9682 |
-#> |.....................|    0.6965 |     1.998 |...........|...........|
-#> |    F| Forward Diff. |     3.979 |     1.099 |   0.01619 |  -0.06233 |
-#> |.....................|    0.3580 |    0.5217 |  -0.09749 |     1.245 |
-#> |.....................|   -0.4289 |    0.1115 |   -0.5282 |    0.7580 |
-#> |.....................|   -0.3266 |    -1.417 |...........|...........|
-#> |   75|     479.53242 |     1.003 |    -1.211 |   -0.9259 |   -0.9353 |
-#> |.....................|    -1.028 |   -0.9962 |   -0.2391 |   -0.8787 |
-#> |.....................|   -0.7953 |    -1.065 |   -0.5685 |   -0.8588 |
-#> |.....................|    -1.067 |   -0.2202 |...........|...........|
-#> |    U|     479.53242 |     91.27 |    -5.411 |   -0.9038 |    -2.198 |
-#> |.....................|    -4.640 |    0.4076 |     1.094 |   0.05835 |
-#> |.....................|    0.7906 |    0.7307 |     1.537 |    0.9681 |
-#> |.....................|    0.6966 |     1.999 |...........|...........|
-#> |    X|     479.53242 |     91.27 |  0.004467 |    0.2883 |    0.1111 |
-#> |.....................|  0.009657 |    0.6005 |     1.094 |   0.05835 |
-#> |.....................|    0.7906 |    0.7307 |     1.537 |    0.9681 |
-#> |.....................|    0.6966 |     1.999 |...........|...........|
-#> |    F| Forward Diff. |    -1.679 |     1.093 |  -0.04308 |  -0.05224 |
-#> |.....................|    0.3605 |    0.5318 | -0.002555 |     1.446 |
-#> |.....................|   -0.4215 |   0.05786 |    0.6079 |     1.538 |
-#> |.....................|    0.2997 |    -1.401 |...........|...........|
-#> |   76|     479.52958 |     1.004 |    -1.212 |   -0.9259 |   -0.9353 |
-#> |.....................|    -1.028 |   -0.9965 |   -0.2388 |   -0.8793 |
-#> |.....................|   -0.7951 |    -1.065 |   -0.5686 |   -0.8593 |
-#> |.....................|    -1.067 |   -0.2194 |...........|...........|
-#> |    U|     479.52958 |     91.33 |    -5.412 |   -0.9038 |    -2.198 |
-#> |.....................|    -4.640 |    0.4075 |     1.094 |   0.05833 |
-#> |.....................|    0.7908 |    0.7306 |     1.537 |    0.9676 |
-#> |.....................|    0.6965 |     2.000 |...........|...........|
-#> |    X|     479.52958 |     91.33 |  0.004464 |    0.2883 |    0.1111 |
-#> |.....................|  0.009655 |    0.6005 |     1.094 |   0.05833 |
-#> |.....................|    0.7908 |    0.7306 |     1.537 |    0.9676 |
-#> |.....................|    0.6965 |     2.000 |...........|...........|
-#> |    F| Forward Diff. |     3.139 |     1.094 |   0.01046 |  -0.06226 |
-#> |.....................|    0.3570 |    0.5194 |  -0.09592 |     1.421 |
-#> |.....................|   -0.4323 |   0.06052 |   -0.5454 |    0.7071 |
-#> |.....................|   -0.2962 |    -1.410 |...........|...........|
-#> |   77|     479.52646 |     1.003 |    -1.212 |   -0.9259 |   -0.9353 |
-#> |.....................|    -1.028 |   -0.9968 |   -0.2384 |   -0.8797 |
-#> |.....................|   -0.7949 |    -1.065 |   -0.5684 |   -0.8594 |
-#> |.....................|    -1.067 |   -0.2186 |...........|...........|
-#> |    U|     479.52646 |     91.26 |    -5.412 |   -0.9038 |    -2.198 |
-#> |.....................|    -4.640 |    0.4073 |     1.094 |   0.05832 |
-#> |.....................|    0.7909 |    0.7304 |     1.537 |    0.9675 |
-#> |.....................|    0.6966 |     2.001 |...........|...........|
-#> |    X|     479.52646 |     91.26 |  0.004461 |    0.2883 |    0.1111 |
-#> |.....................|  0.009653 |    0.6005 |     1.094 |   0.05832 |
-#> |.....................|    0.7909 |    0.7304 |     1.537 |    0.9675 |
-#> |.....................|    0.6966 |     2.001 |...........|...........|
-#> |    F| Forward Diff. |    -2.758 |     1.088 |  -0.05217 |  -0.05158 |
-#> |.....................|    0.3593 |    0.5291 |  -0.05980 |     1.185 |
-#> |.....................|   -0.4227 |    -2.218 |   -0.3659 |    0.8223 |
-#> |.....................|   -0.2423 |    -1.392 |...........|...........|
-#> |   78|     479.52294 |     1.003 |    -1.213 |   -0.9258 |   -0.9352 |
-#> |.....................|    -1.028 |   -0.9971 |   -0.2379 |   -0.8800 |
-#> |.....................|   -0.7947 |    -1.064 |   -0.5681 |   -0.8596 |
-#> |.....................|    -1.067 |   -0.2178 |...........|...........|
-#> |    U|     479.52294 |     91.30 |    -5.413 |   -0.9037 |    -2.198 |
-#> |.....................|    -4.641 |    0.4072 |     1.094 |   0.05831 |
-#> |.....................|    0.7910 |    0.7311 |     1.537 |    0.9673 |
-#> |.....................|    0.6967 |     2.002 |...........|...........|
-#> |    X|     479.52294 |     91.30 |  0.004458 |    0.2883 |    0.1111 |
-#> |.....................|  0.009652 |    0.6004 |     1.094 |   0.05831 |
-#> |.....................|    0.7910 |    0.7311 |     1.537 |    0.9673 |
-#> |.....................|    0.6967 |     2.002 |...........|...........|
-#> |    F| Forward Diff. |    0.7571 |     1.091 |  -0.01328 |  -0.05733 |
-#> |.....................|    0.3573 |    0.5211 |  0.006105 |     1.423 |
-#> |.....................|   -0.4119 |    0.1268 |    0.6771 |     1.465 |
-#> |.....................|    0.3146 |    -1.386 |...........|...........|
-#> |   79|     479.52041 |     1.003 |    -1.213 |   -0.9258 |   -0.9352 |
-#> |.....................|    -1.028 |   -0.9973 |   -0.2380 |   -0.8807 |
-#> |.....................|   -0.7945 |    -1.064 |   -0.5684 |   -0.8604 |
-#> |.....................|    -1.067 |   -0.2172 |...........|...........|
-#> |    U|     479.52041 |     91.27 |    -5.413 |   -0.9037 |    -2.198 |
-#> |.....................|    -4.641 |    0.4071 |     1.094 |   0.05829 |
-#> |.....................|    0.7912 |    0.7311 |     1.537 |    0.9666 |
-#> |.....................|    0.6965 |     2.003 |...........|...........|
-#> |    X|     479.52041 |     91.27 |  0.004456 |    0.2883 |    0.1111 |
-#> |.....................|  0.009650 |    0.6004 |     1.094 |   0.05829 |
-#> |.....................|    0.7912 |    0.7311 |     1.537 |    0.9666 |
-#> |.....................|    0.6965 |     2.003 |...........|...........|
-#> |    F| Forward Diff. |    -2.400 |     1.087 |  -0.04852 |  -0.05189 |
-#> |.....................|    0.3585 |    0.5236 |  -0.05100 |     1.183 |
-#> |.....................|   -0.4319 |   0.01564 |    0.3566 |     1.324 |
-#> |.....................|    0.3221 |    -1.379 |...........|...........|
-#> |   80|     479.51911 |     1.004 |    -1.214 |   -0.9258 |   -0.9352 |
-#> |.....................|    -1.029 |   -0.9976 |   -0.2379 |   -0.8812 |
-#> |.....................|   -0.7944 |    -1.064 |   -0.5686 |   -0.8609 |
-#> |.....................|    -1.067 |   -0.2166 |...........|...........|
-#> |    U|     479.51911 |     91.35 |    -5.414 |   -0.9037 |    -2.198 |
-#> |.....................|    -4.641 |    0.4070 |     1.094 |   0.05828 |
-#> |.....................|    0.7913 |    0.7310 |     1.537 |    0.9661 |
-#> |.....................|    0.6964 |     2.004 |...........|...........|
-#> |    X|     479.51911 |     91.35 |  0.004454 |    0.2883 |    0.1111 |
-#> |.....................|  0.009648 |    0.6004 |     1.094 |   0.05828 |
-#> |.....................|    0.7913 |    0.7310 |     1.537 |    0.9661 |
-#> |.....................|    0.6964 |     2.004 |...........|...........|
-#> |    F| Forward Diff. |     5.458 |     1.092 |   0.04306 |  -0.06507 |
-#> |.....................|    0.3552 |    0.5068 |  -0.06807 |     1.418 |
-#> |.....................|   -0.4090 |    0.1358 |   -0.5109 |    0.5676 |
-#> |.....................|   -0.2804 |    -1.390 |...........|...........|
-#> |   81|     479.51487 |     1.003 |    -1.215 |   -0.9258 |   -0.9352 |
-#> |.....................|    -1.029 |   -0.9978 |   -0.2377 |   -0.8817 |
-#> |.....................|   -0.7942 |    -1.064 |   -0.5685 |   -0.8612 |
-#> |.....................|    -1.067 |   -0.2158 |...........|...........|
-#> |    U|     479.51487 |     91.27 |    -5.415 |   -0.9037 |    -2.198 |
-#> |.....................|    -4.641 |    0.4069 |     1.094 |   0.05826 |
-#> |.....................|    0.7914 |    0.7307 |     1.537 |    0.9658 |
-#> |.....................|    0.6963 |     2.005 |...........|...........|
-#> |    X|     479.51487 |     91.27 |  0.004451 |    0.2883 |    0.1111 |
-#> |.....................|  0.009647 |    0.6003 |     1.094 |   0.05826 |
-#> |.....................|    0.7914 |    0.7307 |     1.537 |    0.9658 |
-#> |.....................|    0.6963 |     2.005 |...........|...........|
-#> |    F| Forward Diff. |    -1.582 |     1.084 |  -0.03533 |  -0.05340 |
-#> |.....................|    0.3581 |    0.5175 |  -0.06480 |     1.157 |
-#> |.....................|   -0.4224 |   0.03489 |   -0.5536 |    0.6041 |
-#> |.....................|   -0.2386 |    -1.371 |...........|...........|
-#> |   82|     479.51208 |     1.004 |    -1.215 |   -0.9258 |   -0.9351 |
-#> |.....................|    -1.029 |   -0.9981 |   -0.2375 |   -0.8823 |
-#> |.....................|   -0.7939 |    -1.065 |   -0.5682 |   -0.8615 |
-#> |.....................|    -1.067 |   -0.2150 |...........|...........|
-#> |    U|     479.51208 |     91.34 |    -5.415 |   -0.9037 |    -2.197 |
-#> |.....................|    -4.641 |    0.4067 |     1.094 |   0.05824 |
-#> |.....................|    0.7916 |    0.7306 |     1.537 |    0.9655 |
-#> |.....................|    0.6964 |     2.006 |...........|...........|
-#> |    X|     479.51208 |     91.34 |  0.004449 |    0.2883 |    0.1111 |
-#> |.....................|  0.009645 |    0.6003 |     1.094 |   0.05824 |
-#> |.....................|    0.7916 |    0.7306 |     1.537 |    0.9655 |
-#> |.....................|    0.6964 |     2.006 |...........|...........|
-#> |    F| Forward Diff. |     3.943 |     1.087 |   0.02817 |  -0.06279 |
-#> |.....................|    0.3555 |    0.5065 |  -0.06060 |     1.305 |
-#> |.....................|   -0.4115 |   0.06912 |    0.4865 |     1.240 |
-#> |.....................|    0.2990 |    -1.371 |...........|...........|
-#> |   83|     479.50842 |     1.003 |    -1.216 |   -0.9258 |   -0.9351 |
-#> |.....................|    -1.029 |   -0.9984 |   -0.2372 |   -0.8827 |
-#> |.....................|   -0.7937 |    -1.065 |   -0.5683 |   -0.8618 |
-#> |.....................|    -1.067 |   -0.2141 |...........|...........|
-#> |    U|     479.50842 |     91.29 |    -5.416 |   -0.9037 |    -2.197 |
-#> |.....................|    -4.642 |    0.4066 |     1.095 |   0.05823 |
-#> |.....................|    0.7918 |    0.7302 |     1.537 |    0.9652 |
-#> |.....................|    0.6962 |     2.007 |...........|...........|
-#> |    X|     479.50842 |     91.29 |  0.004446 |    0.2883 |    0.1111 |
-#> |.....................|  0.009643 |    0.6003 |     1.095 |   0.05823 |
-#> |.....................|    0.7918 |    0.7302 |     1.537 |    0.9652 |
-#> |.....................|    0.6962 |     2.007 |...........|...........|
-#> |    F| Forward Diff. |   -0.7463 |     1.081 |  -0.02105 |  -0.05532 |
-#> |.....................|    0.3572 |    0.5118 |  -0.07839 |     1.134 |
-#> |.....................|   -0.4206 |   0.01709 |   -0.5616 |    0.5218 |
-#> |.....................|   -0.2429 |    -1.361 |...........|...........|
-#> |   84|     479.50515 |     1.004 |    -1.216 |   -0.9258 |   -0.9351 |
-#> |.....................|    -1.029 |   -0.9987 |   -0.2372 |   -0.8834 |
-#> |.....................|   -0.7935 |    -1.065 |   -0.5680 |   -0.8621 |
-#> |.....................|    -1.067 |   -0.2133 |...........|...........|
-#> |    U|     479.50515 |     91.33 |    -5.416 |   -0.9037 |    -2.197 |
-#> |.....................|    -4.642 |    0.4065 |     1.095 |   0.05821 |
-#> |.....................|    0.7919 |    0.7302 |     1.537 |    0.9649 |
-#> |.....................|    0.6964 |     2.008 |...........|...........|
-#> |    X|     479.50515 |     91.33 |  0.004443 |    0.2883 |    0.1111 |
-#> |.....................|  0.009641 |    0.6002 |     1.095 |   0.05821 |
-#> |.....................|    0.7919 |    0.7302 |     1.537 |    0.9649 |
-#> |.....................|    0.6964 |     2.008 |...........|...........|
-#> |   85|     479.49887 |     1.004 |    -1.219 |   -0.9257 |   -0.9350 |
-#> |.....................|    -1.030 |   -0.9997 |   -0.2363 |   -0.8851 |
-#> |.....................|   -0.7928 |    -1.066 |   -0.5675 |   -0.8630 |
-#> |.....................|    -1.067 |   -0.2104 |...........|...........|
-#> |    U|     479.49887 |     91.39 |    -5.419 |   -0.9037 |    -2.197 |
-#> |.....................|    -4.642 |    0.4060 |     1.095 |   0.05816 |
-#> |.....................|    0.7925 |    0.7293 |     1.538 |    0.9641 |
-#> |.....................|    0.6963 |     2.011 |...........|...........|
-#> |    X|     479.49887 |     91.39 |  0.004434 |    0.2883 |    0.1111 |
-#> |.....................|  0.009634 |    0.6001 |     1.095 |   0.05816 |
-#> |.....................|    0.7925 |    0.7293 |     1.538 |    0.9641 |
-#> |.....................|    0.6963 |     2.011 |...........|...........|
-#> |    F| Forward Diff. |     8.922 |     1.081 |    0.1004 |  -0.07252 |
-#> |.....................|    0.3520 |    0.4871 |    0.2543 |     1.578 |
-#> |.....................|   -0.3854 |   0.03465 |   -0.5794 |    0.4083 |
-#> |.....................|   -0.2550 |    -1.344 |...........|...........|
-#> |   86|     479.48147 |     1.003 |    -1.221 |   -0.9257 |   -0.9348 |
-#> |.....................|    -1.031 |    -1.001 |   -0.2344 |   -0.8861 |
-#> |.....................|   -0.7921 |    -1.067 |   -0.5658 |   -0.8636 |
-#> |.....................|    -1.067 |   -0.2068 |...........|...........|
-#> |    U|     479.48147 |     91.29 |    -5.421 |   -0.9036 |    -2.197 |
-#> |.....................|    -4.643 |    0.4054 |     1.096 |   0.05813 |
-#> |.....................|    0.7930 |    0.7283 |     1.540 |    0.9635 |
-#> |.....................|    0.6963 |     2.016 |...........|...........|
-#> |    X|     479.48147 |     91.29 |  0.004421 |    0.2883 |    0.1111 |
-#> |.....................|  0.009626 |    0.6000 |     1.096 |   0.05813 |
-#> |.....................|    0.7930 |    0.7283 |     1.540 |    0.9635 |
-#> |.....................|    0.6963 |     2.016 |...........|...........|
-#> |   87|     479.46291 |     1.003 |    -1.226 |   -0.9256 |   -0.9345 |
-#> |.....................|    -1.032 |    -1.003 |   -0.2312 |   -0.8874 |
-#> |.....................|   -0.7910 |    -1.069 |   -0.5631 |   -0.8644 |
-#> |.....................|    -1.067 |   -0.2012 |...........|...........|
-#> |    U|     479.46291 |     91.29 |    -5.426 |   -0.9035 |    -2.197 |
-#> |.....................|    -4.645 |    0.4045 |     1.097 |   0.05809 |
-#> |.....................|    0.7937 |    0.7267 |     1.543 |    0.9627 |
-#> |.....................|    0.6964 |     2.022 |...........|...........|
-#> |    X|     479.46291 |     91.29 |  0.004402 |    0.2883 |    0.1111 |
-#> |.....................|  0.009612 |    0.5998 |     1.097 |   0.05809 |
-#> |.....................|    0.7937 |    0.7267 |     1.543 |    0.9627 |
-#> |.....................|    0.6964 |     2.022 |...........|...........|
-#> |   88|     479.38653 |     1.003 |    -1.248 |   -0.9250 |   -0.9332 |
-#> |.....................|    -1.039 |    -1.013 |   -0.2154 |   -0.8940 |
-#> |.....................|   -0.7859 |    -1.078 |   -0.5497 |   -0.8687 |
-#> |.....................|    -1.067 |   -0.1734 |...........|...........|
-#> |    U|     479.38653 |     91.26 |    -5.448 |   -0.9030 |    -2.196 |
-#> |.....................|    -4.652 |    0.4000 |     1.104 |   0.05790 |
-#> |.....................|    0.7975 |    0.7188 |     1.559 |    0.9587 |
-#> |.....................|    0.6966 |     2.056 |...........|...........|
-#> |    X|     479.38653 |     91.26 |  0.004306 |    0.2884 |    0.1113 |
-#> |.....................|  0.009547 |    0.5987 |     1.104 |   0.05790 |
-#> |.....................|    0.7975 |    0.7188 |     1.559 |    0.9587 |
-#> |.....................|    0.6966 |     2.056 |...........|...........|
-#> |   89|     479.33405 |     1.002 |    -1.333 |   -0.9226 |   -0.9281 |
-#> |.....................|    -1.066 |    -1.051 |   -0.1533 |   -0.9198 |
-#> |.....................|   -0.7659 |    -1.112 |   -0.4971 |   -0.8853 |
-#> |.....................|    -1.066 |  -0.06439 |...........|...........|
-#> |    U|     479.33405 |     91.15 |    -5.533 |   -0.9008 |    -2.190 |
-#> |.....................|    -4.678 |    0.3823 |     1.129 |   0.05715 |
-#> |.....................|    0.8121 |    0.6876 |     1.621 |    0.9427 |
-#> |.....................|    0.6975 |     2.188 |...........|...........|
-#> |    X|     479.33405 |     91.15 |  0.003953 |    0.2889 |    0.1119 |
-#> |.....................|  0.009294 |    0.5944 |     1.129 |   0.05715 |
-#> |.....................|    0.8121 |    0.6876 |     1.621 |    0.9427 |
-#> |.....................|    0.6975 |     2.188 |...........|...........|
-#> |    F| Forward Diff. |    -22.35 |    0.8049 |    0.3265 |  -0.06456 |
-#> |.....................|    0.3038 |    0.2091 |     1.763 |     1.473 |
-#> |.....................|   -0.5535 |    -2.463 |     1.244 |   -0.6274 |
-#> |.....................|     1.702 |   -0.2760 |...........|...........|
-#> |   90|     479.70817 |     1.005 |    -1.492 |   -0.9504 |   -0.9122 |
-#> |.....................|    -1.121 |    -1.106 |   -0.1774 |   -0.9510 |
-#> |.....................|   -0.7305 |    -1.145 |   -0.4385 |   -0.8800 |
-#> |.....................|    -1.177 |  -0.01012 |...........|...........|
-#> |    U|     479.70817 |     91.47 |    -5.692 |   -0.9256 |    -2.175 |
-#> |.....................|    -4.734 |    0.3572 |     1.119 |   0.05625 |
-#> |.....................|    0.8380 |    0.6579 |     1.691 |    0.9478 |
-#> |.....................|    0.6020 |     2.254 |...........|...........|
-#> |    X|     479.70817 |     91.47 |  0.003371 |    0.2838 |    0.1137 |
-#> |.....................|  0.008794 |    0.5884 |     1.119 |   0.05625 |
-#> |.....................|    0.8380 |    0.6579 |     1.691 |    0.9478 |
-#> |.....................|    0.6020 |     2.254 |...........|...........|
-#> |   91|     479.27063 |     1.005 |    -1.375 |   -0.9298 |   -0.9240 |
-#> |.....................|    -1.080 |    -1.065 |   -0.1597 |   -0.9281 |
-#> |.....................|   -0.7567 |    -1.120 |   -0.4820 |   -0.8839 |
-#> |.....................|    -1.095 |  -0.05030 |...........|...........|
-#> |    U|     479.27063 |     91.42 |    -5.575 |   -0.9073 |    -2.186 |
-#> |.....................|    -4.693 |    0.3758 |     1.127 |   0.05692 |
-#> |.....................|    0.8189 |    0.6801 |     1.639 |    0.9441 |
-#> |.....................|    0.6726 |     2.206 |...........|...........|
-#> |    X|     479.27063 |     91.42 |  0.003793 |    0.2876 |    0.1123 |
-#> |.....................|  0.009162 |    0.5929 |     1.127 |   0.05692 |
-#> |.....................|    0.8189 |    0.6801 |     1.639 |    0.9441 |
-#> |.....................|    0.6726 |     2.206 |...........|...........|
-#> |    F| Forward Diff. |     2.862 |    0.7516 |    0.3576 |  -0.07893 |
-#> |.....................|    0.2806 |   -0.4298 |     1.369 |     1.213 |
-#> |.....................|   -0.5227 |    -2.562 |     2.801 |    -1.010 |
-#> |.....................|    -1.234 |   -0.5388 |...........|...........|
-#> |   92|     479.18239 |     1.005 |    -1.423 |   -0.9401 |   -0.9189 |
-#> |.....................|    -1.098 |    -1.064 |   -0.1729 |   -0.9195 |
-#> |.....................|   -0.7414 |    -1.117 |   -0.4967 |   -0.8806 |
-#> |.....................|    -1.083 |  -0.04375 |...........|...........|
-#> |    U|     479.18239 |     91.43 |    -5.623 |   -0.9165 |    -2.181 |
-#> |.....................|    -4.710 |    0.3764 |     1.121 |   0.05716 |
-#> |.....................|    0.8300 |    0.6834 |     1.622 |    0.9472 |
-#> |.....................|    0.6830 |     2.213 |...........|...........|
-#> |    X|     479.18239 |     91.43 |  0.003613 |    0.2857 |    0.1129 |
-#> |.....................|  0.009001 |    0.5930 |     1.121 |   0.05716 |
-#> |.....................|    0.8300 |    0.6834 |     1.622 |    0.9472 |
-#> |.....................|    0.6830 |     2.213 |...........|...........|
-#> |    F| Forward Diff. |     2.797 |    0.6564 |   -0.1913 |  -0.04289 |
-#> |.....................|    0.2359 |   -0.3012 |     1.209 |     1.124 |
-#> |.....................|   -0.4349 |    -2.322 |     2.160 |   -0.7215 |
-#> |.....................|   -0.1578 |   -0.4171 |...........|...........|
-#> |   93|     479.53483 |    0.9938 |    -1.508 |   -0.8927 |   -0.9141 |
-#> |.....................|    -1.127 |    -1.054 |   -0.1802 |   -0.9016 |
-#> |.....................|   -0.7110 |    -1.089 |   -0.5260 |   -0.8567 |
-#> |.....................|    -1.093 |  -0.01567 |...........|...........|
-#> |    U|     479.53483 |     90.44 |    -5.708 |   -0.8742 |    -2.177 |
-#> |.....................|    -4.740 |    0.3812 |     1.118 |   0.05768 |
-#> |.....................|    0.8523 |    0.7081 |     1.587 |    0.9700 |
-#> |.....................|    0.6741 |     2.248 |...........|...........|
-#> |    X|     479.53483 |     90.44 |  0.003320 |    0.2944 |    0.1134 |
-#> |.....................|  0.008741 |    0.5942 |     1.118 |   0.05768 |
-#> |.....................|    0.8523 |    0.7081 |     1.587 |    0.9700 |
-#> |.....................|    0.6741 |     2.248 |...........|...........|
-#> |   94|     479.57437 |    0.9943 |    -1.436 |   -0.9336 |   -0.9181 |
-#> |.....................|    -1.102 |    -1.062 |   -0.1777 |   -0.9209 |
-#> |.....................|   -0.7362 |    -1.106 |   -0.5073 |   -0.8753 |
-#> |.....................|    -1.084 |  -0.03890 |...........|...........|
-#> |    U|     479.57437 |     90.49 |    -5.636 |   -0.9106 |    -2.181 |
-#> |.....................|    -4.715 |    0.3775 |     1.119 |   0.05712 |
-#> |.....................|    0.8338 |    0.6933 |     1.609 |    0.9523 |
-#> |.....................|    0.6824 |     2.219 |...........|...........|
-#> |    X|     479.57437 |     90.49 |  0.003567 |    0.2869 |    0.1130 |
-#> |.....................|  0.008961 |    0.5933 |     1.119 |   0.05712 |
-#> |.....................|    0.8338 |    0.6933 |     1.609 |    0.9523 |
-#> |.....................|    0.6824 |     2.219 |...........|...........|
-#> |   95|     479.18328 |     1.003 |    -1.424 |   -0.9400 |   -0.9189 |
-#> |.....................|    -1.098 |    -1.064 |   -0.1736 |   -0.9201 |
-#> |.....................|   -0.7412 |    -1.115 |   -0.4980 |   -0.8802 |
-#> |.....................|    -1.083 |  -0.04351 |...........|...........|
-#> |    U|     479.18328 |     91.28 |    -5.624 |   -0.9164 |    -2.181 |
-#> |.....................|    -4.711 |    0.3765 |     1.121 |   0.05715 |
-#> |.....................|    0.8302 |    0.6847 |     1.620 |    0.9476 |
-#> |.....................|    0.6831 |     2.214 |...........|...........|
-#> |    X|     479.18328 |     91.28 |  0.003612 |    0.2857 |    0.1129 |
-#> |.....................|  0.009000 |    0.5930 |     1.121 |   0.05715 |
-#> |.....................|    0.8302 |    0.6847 |     1.620 |    0.9476 |
-#> |.....................|    0.6831 |     2.214 |...........|...........|
-#> |   96|     479.17990 |     1.004 |    -1.423 |   -0.9401 |   -0.9189 |
-#> |.....................|    -1.098 |    -1.064 |   -0.1732 |   -0.9198 |
-#> |.....................|   -0.7413 |    -1.116 |   -0.4973 |   -0.8805 |
-#> |.....................|    -1.083 |  -0.04364 |...........|...........|
-#> |    U|      479.1799 |     91.36 |    -5.623 |   -0.9164 |    -2.181 |
-#> |.....................|    -4.710 |    0.3764 |     1.121 |   0.05716 |
-#> |.....................|    0.8301 |    0.6840 |     1.621 |    0.9474 |
-#> |.....................|    0.6831 |     2.214 |...........|...........|
-#> |    X|      479.1799 |     91.36 |  0.003612 |    0.2857 |    0.1129 |
-#> |.....................|  0.009001 |    0.5930 |     1.121 |   0.05716 |
-#> |.....................|    0.8301 |    0.6840 |     1.621 |    0.9474 |
-#> |.....................|    0.6831 |     2.214 |...........|...........|
-#> |    F| Forward Diff. |    -3.933 |    0.6514 |   -0.2757 |  -0.03244 |
-#> |.....................|    0.2382 |   -0.2823 |     1.183 |     1.090 |
-#> |.....................|   -0.4397 |    -2.345 |     2.145 |   -0.7620 |
-#> |.....................|   -0.1240 |   -0.3947 |...........|...........|
-#> |   97|     479.17667 |     1.005 |    -1.424 |   -0.9399 |   -0.9189 |
-#> |.....................|    -1.098 |    -1.064 |   -0.1735 |   -0.9200 |
-#> |.....................|   -0.7411 |    -1.116 |   -0.4978 |   -0.8802 |
-#> |.....................|    -1.083 |  -0.04350 |...........|...........|
-#> |    U|     479.17667 |     91.44 |    -5.624 |   -0.9162 |    -2.181 |
-#> |.....................|    -4.711 |    0.3765 |     1.121 |   0.05715 |
-#> |.....................|    0.8302 |    0.6845 |     1.621 |    0.9476 |
-#> |.....................|    0.6831 |     2.214 |...........|...........|
-#> |    X|     479.17667 |     91.44 |  0.003611 |    0.2857 |    0.1129 |
-#> |.....................|  0.009000 |    0.5930 |     1.121 |   0.05715 |
-#> |.....................|    0.8302 |    0.6845 |     1.621 |    0.9476 |
-#> |.....................|    0.6831 |     2.214 |...........|...........|
-#> |    F| Forward Diff. |     3.521 |    0.6547 |   -0.1751 |  -0.04313 |
-#> |.....................|    0.2353 |   -0.2995 |     1.118 |     1.121 |
-#> |.....................|   -0.4506 |    -2.323 |     2.084 |   -0.7259 |
-#> |.....................|   -0.1653 |   -0.4503 |...........|...........|
-#> |   98|     479.17418 |     1.004 |    -1.424 |   -0.9398 |   -0.9188 |
-#> |.....................|    -1.098 |    -1.064 |   -0.1738 |   -0.9202 |
-#> |.....................|   -0.7410 |    -1.115 |   -0.4983 |   -0.8800 |
-#> |.....................|    -1.083 |  -0.04335 |...........|...........|
-#> |    U|     479.17418 |     91.36 |    -5.624 |   -0.9161 |    -2.181 |
-#> |.....................|    -4.711 |    0.3765 |     1.121 |   0.05714 |
-#> |.....................|    0.8303 |    0.6850 |     1.620 |    0.9478 |
-#> |.....................|    0.6831 |     2.214 |...........|...........|
-#> |    X|     479.17418 |     91.36 |  0.003610 |    0.2857 |    0.1129 |
-#> |.....................|  0.008999 |    0.5930 |     1.121 |   0.05714 |
-#> |.....................|    0.8303 |    0.6850 |     1.620 |    0.9478 |
-#> |.....................|    0.6831 |     2.214 |...........|...........|
-#> |    F| Forward Diff. |    -3.859 |    0.6491 |   -0.2708 |  -0.03145 |
-#> |.....................|    0.2380 |   -0.2786 |     1.113 |     1.074 |
-#> |.....................|   -0.4387 |    -2.285 |     2.045 |   -0.7498 |
-#> |.....................|   -0.1354 |   -0.4011 |...........|...........|
-#> |   99|     479.17107 |     1.005 |    -1.424 |   -0.9396 |   -0.9188 |
-#> |.....................|    -1.098 |    -1.064 |   -0.1740 |   -0.9204 |
-#> |.....................|   -0.7408 |    -1.114 |   -0.4988 |   -0.8798 |
-#> |.....................|    -1.083 |  -0.04320 |...........|...........|
-#> |    U|     479.17107 |     91.44 |    -5.624 |   -0.9160 |    -2.181 |
-#> |.....................|    -4.711 |    0.3766 |     1.121 |   0.05714 |
-#> |.....................|    0.8305 |    0.6855 |     1.619 |    0.9480 |
-#> |.....................|    0.6831 |     2.214 |...........|...........|
-#> |    X|     479.17107 |     91.44 |  0.003609 |    0.2858 |    0.1129 |
-#> |.....................|  0.008997 |    0.5930 |     1.121 |   0.05714 |
-#> |.....................|    0.8305 |    0.6855 |     1.619 |    0.9480 |
-#> |.....................|    0.6831 |     2.214 |...........|...........|
-#> |    F| Forward Diff. |     3.569 |    0.6522 |   -0.1642 |  -0.04243 |
-#> |.....................|    0.2349 |   -0.2958 |     1.101 |     1.106 |
-#> |.....................|   -0.4222 |    -2.201 |     1.058 |   -0.2096 |
-#> |.....................|    0.2358 |   -0.4015 |...........|...........|
-#> |  100|     479.16873 |     1.004 |    -1.425 |   -0.9393 |   -0.9188 |
-#> |.....................|    -1.099 |    -1.064 |   -0.1743 |   -0.9206 |
-#> |.....................|   -0.7406 |    -1.114 |   -0.4991 |   -0.8797 |
-#> |.....................|    -1.083 |  -0.04303 |...........|...........|
-#> |    U|     479.16873 |     91.36 |    -5.625 |   -0.9158 |    -2.181 |
-#> |.....................|    -4.711 |    0.3766 |     1.121 |   0.05713 |
-#> |.....................|    0.8306 |    0.6860 |     1.619 |    0.9481 |
-#> |.....................|    0.6830 |     2.214 |...........|...........|
-#> |    X|     479.16873 |     91.36 |  0.003607 |    0.2858 |    0.1129 |
-#> |.....................|  0.008996 |    0.5931 |     1.121 |   0.05713 |
-#> |.....................|    0.8306 |    0.6860 |     1.619 |    0.9481 |
-#> |.....................|    0.6830 |     2.214 |...........|...........|
-#> |    F| Forward Diff. |    -3.833 |    0.6464 |   -0.2551 |  -0.03020 |
-#> |.....................|    0.2388 |   -0.2745 |     1.092 |     1.036 |
-#> |.....................|   -0.4378 |    -2.238 |     1.100 |   -0.2036 |
-#> |.....................|    0.2823 |   -0.3907 |...........|...........|
-#> |  101|     479.16547 |     1.005 |    -1.426 |   -0.9390 |   -0.9187 |
-#> |.....................|    -1.099 |    -1.063 |   -0.1745 |   -0.9206 |
-#> |.....................|   -0.7403 |    -1.113 |   -0.4993 |   -0.8795 |
-#> |.....................|    -1.083 |  -0.04283 |...........|...........|
-#> |    U|     479.16547 |     91.42 |    -5.626 |   -0.9155 |    -2.181 |
-#> |.....................|    -4.711 |    0.3767 |     1.121 |   0.05713 |
-#> |.....................|    0.8308 |    0.6865 |     1.619 |    0.9483 |
-#> |.....................|    0.6830 |     2.215 |...........|...........|
-#> |    X|     479.16547 |     91.42 |  0.003605 |    0.2859 |    0.1129 |
-#> |.....................|  0.008994 |    0.5931 |     1.121 |   0.05713 |
-#> |.....................|    0.8308 |    0.6865 |     1.619 |    0.9483 |
-#> |.....................|    0.6830 |     2.215 |...........|...........|
-#> |    F| Forward Diff. |     2.367 |    0.6482 |   -0.1602 |  -0.03907 |
-#> |.....................|    0.2347 |   -0.2874 |     1.147 |     1.057 |
-#> |.....................|   -0.4142 |    -2.141 |     1.081 |   -0.1748 |
-#> |.....................|    0.2414 |   -0.4049 |...........|...........|
-#> |  102|     479.16316 |     1.004 |    -1.426 |   -0.9389 |   -0.9187 |
-#> |.....................|    -1.099 |    -1.063 |   -0.1748 |   -0.9208 |
-#> |.....................|   -0.7401 |    -1.113 |   -0.4996 |   -0.8794 |
-#> |.....................|    -1.083 |  -0.04264 |...........|...........|
-#> |    U|     479.16316 |     91.36 |    -5.626 |   -0.9154 |    -2.181 |
-#> |.....................|    -4.711 |    0.3768 |     1.120 |   0.05713 |
-#> |.....................|    0.8310 |    0.6872 |     1.618 |    0.9484 |
-#> |.....................|    0.6829 |     2.215 |...........|...........|
-#> |    X|     479.16316 |     91.36 |  0.003603 |    0.2859 |    0.1129 |
-#> |.....................|  0.008992 |    0.5931 |     1.120 |   0.05713 |
-#> |.....................|    0.8310 |    0.6872 |     1.618 |    0.9484 |
-#> |.....................|    0.6829 |     2.215 |...........|...........|
-#> |    F| Forward Diff. |    -3.810 |    0.6431 |   -0.2376 |  -0.02872 |
-#> |.....................|    0.2384 |   -0.2689 |     1.073 |     1.021 |
-#> |.....................|   -0.4195 |    -2.179 |     2.025 |   -0.6985 |
-#> |.....................|   -0.1403 |   -0.3873 |...........|...........|
-#> |  103|     479.15976 |     1.005 |    -1.427 |   -0.9385 |   -0.9187 |
-#> |.....................|    -1.099 |    -1.063 |   -0.1751 |   -0.9208 |
-#> |.....................|   -0.7399 |    -1.112 |   -0.5000 |   -0.8792 |
-#> |.....................|    -1.083 |  -0.04242 |...........|...........|
-#> |    U|     479.15976 |     91.41 |    -5.627 |   -0.9150 |    -2.181 |
-#> |.....................|    -4.712 |    0.3768 |     1.120 |   0.05713 |
-#> |.....................|    0.8311 |    0.6876 |     1.618 |    0.9486 |
-#> |.....................|    0.6829 |     2.215 |...........|...........|
-#> |    X|     479.15976 |     91.41 |  0.003601 |    0.2860 |    0.1129 |
-#> |.....................|  0.008990 |    0.5931 |     1.120 |   0.05713 |
-#> |.....................|    0.8311 |    0.6876 |     1.618 |    0.9486 |
-#> |.....................|    0.6829 |     2.215 |...........|...........|
-#> |    F| Forward Diff. |     1.385 |    0.6444 |   -0.1513 |  -0.03575 |
-#> |.....................|    0.2363 |   -0.2788 |     1.057 |     1.037 |
-#> |.....................|   -0.4304 |    -2.135 |     1.940 |   -0.6607 |
-#> |.....................|   -0.1552 |   -0.4034 |...........|...........|
-#> |  104|     479.15697 |     1.004 |    -1.427 |   -0.9385 |   -0.9187 |
-#> |.....................|    -1.099 |    -1.063 |   -0.1754 |   -0.9212 |
-#> |.....................|   -0.7397 |    -1.111 |   -0.5007 |   -0.8790 |
-#> |.....................|    -1.083 |  -0.04228 |...........|...........|
-#> |    U|     479.15697 |     91.37 |    -5.627 |   -0.9150 |    -2.181 |
-#> |.....................|    -4.712 |    0.3769 |     1.120 |   0.05712 |
-#> |.....................|    0.8312 |    0.6883 |     1.617 |    0.9488 |
-#> |.....................|    0.6829 |     2.215 |...........|...........|
-#> |    X|     479.15697 |     91.37 |  0.003600 |    0.2860 |    0.1129 |
-#> |.....................|  0.008990 |    0.5931 |     1.120 |   0.05712 |
-#> |.....................|    0.8312 |    0.6883 |     1.617 |    0.9488 |
-#> |.....................|    0.6829 |     2.215 |...........|...........|
-#> |    F| Forward Diff. |    -2.828 |    0.6406 |   -0.2090 |  -0.02895 |
-#> |.....................|    0.2376 |   -0.2659 |     1.059 |    0.9695 |
-#> |.....................|   -0.4112 |    -2.078 |     1.041 |   -0.1304 |
-#> |.....................|    0.2608 |   -0.3859 |...........|...........|
-#> |  105|     479.15524 |     1.005 |    -1.427 |   -0.9384 |   -0.9187 |
-#> |.....................|    -1.099 |    -1.063 |   -0.1758 |   -0.9215 |
-#> |.....................|   -0.7396 |    -1.111 |   -0.5010 |   -0.8789 |
-#> |.....................|    -1.083 |  -0.04216 |...........|...........|
-#> |    U|     479.15524 |     91.45 |    -5.627 |   -0.9149 |    -2.181 |
-#> |.....................|    -4.712 |    0.3769 |     1.120 |   0.05711 |
-#> |.....................|    0.8313 |    0.6888 |     1.617 |    0.9489 |
-#> |.....................|    0.6828 |     2.215 |...........|...........|
-#> |    X|     479.15524 |     91.45 |  0.003599 |    0.2860 |    0.1129 |
-#> |.....................|  0.008989 |    0.5931 |     1.120 |   0.05711 |
-#> |.....................|    0.8313 |    0.6888 |     1.617 |    0.9489 |
-#> |.....................|    0.6828 |     2.215 |...........|...........|
-#> |    F| Forward Diff. |     5.191 |    0.6447 |   -0.1017 |  -0.04048 |
-#> |.....................|    0.2348 |   -0.2858 |     1.095 |     1.009 |
-#> |.....................|   -0.3975 |    -1.983 |     1.956 |   -0.5702 |
-#> |.....................|   -0.1591 |   -0.3996 |...........|...........|
-#> |  106|     479.15192 |     1.004 |    -1.428 |   -0.9381 |   -0.9186 |
-#> |.....................|    -1.100 |    -1.063 |   -0.1760 |   -0.9214 |
-#> |.....................|   -0.7393 |    -1.110 |   -0.5013 |   -0.8787 |
-#> |.....................|    -1.083 |  -0.04194 |...........|...........|
-#> |    U|     479.15192 |     91.38 |    -5.628 |   -0.9146 |    -2.181 |
-#> |.....................|    -4.712 |    0.3770 |     1.120 |   0.05711 |
-#> |.....................|    0.8315 |    0.6892 |     1.616 |    0.9490 |
-#> |.....................|    0.6828 |     2.216 |...........|...........|
-#> |    X|     479.15192 |     91.38 |  0.003597 |    0.2861 |    0.1129 |
-#> |.....................|  0.008987 |    0.5932 |     1.120 |   0.05711 |
-#> |.....................|    0.8315 |    0.6892 |     1.616 |    0.9490 |
-#> |.....................|    0.6828 |     2.216 |...........|...........|
-#> |    F| Forward Diff. |    -1.012 |    0.6390 |   -0.1711 |  -0.03027 |
-#> |.....................|    0.2366 |   -0.2653 |     1.098 |    0.9640 |
-#> |.....................|   -0.4101 |    -2.024 |    0.9749 |   -0.1142 |
-#> |.....................|    0.2645 |   -0.3871 |...........|...........|
-#> |  107|     479.14897 |     1.005 |    -1.428 |   -0.9380 |   -0.9186 |
-#> |.....................|    -1.100 |    -1.063 |   -0.1764 |   -0.9218 |
-#> |.....................|   -0.7392 |    -1.110 |   -0.5017 |   -0.8787 |
-#> |.....................|    -1.083 |  -0.04178 |...........|...........|
-#> |    U|     479.14897 |     91.42 |    -5.628 |   -0.9146 |    -2.181 |
-#> |.....................|    -4.712 |    0.3771 |     1.120 |   0.05710 |
-#> |.....................|    0.8317 |    0.6900 |     1.616 |    0.9491 |
-#> |.....................|    0.6827 |     2.216 |...........|...........|
-#> |    X|     479.14897 |     91.42 |  0.003596 |    0.2861 |    0.1129 |
-#> |.....................|  0.008986 |    0.5932 |     1.120 |   0.05710 |
-#> |.....................|    0.8317 |    0.6900 |     1.616 |    0.9491 |
-#> |.....................|    0.6827 |     2.216 |...........|...........|
-#> |  108|     479.14773 |     1.005 |    -1.428 |   -0.9379 |   -0.9186 |
-#> |.....................|    -1.100 |    -1.062 |   -0.1770 |   -0.9223 |
-#> |.....................|   -0.7390 |    -1.109 |   -0.5022 |   -0.8786 |
-#> |.....................|    -1.083 |  -0.04159 |...........|...........|
-#> |    U|     479.14773 |     91.47 |    -5.628 |   -0.9145 |    -2.181 |
-#> |.....................|    -4.712 |    0.3771 |     1.120 |   0.05708 |
-#> |.....................|    0.8318 |    0.6909 |     1.615 |    0.9491 |
-#> |.....................|    0.6826 |     2.216 |...........|...........|
-#> |    X|     479.14773 |     91.47 |  0.003595 |    0.2861 |    0.1129 |
-#> |.....................|  0.008985 |    0.5932 |     1.120 |   0.05708 |
-#> |.....................|    0.8318 |    0.6909 |     1.615 |    0.9491 |
-#> |.....................|    0.6826 |     2.216 |...........|...........|
-#> |    F| Forward Diff. |     7.333 |    0.6414 |  -0.06030 |  -0.04156 |
-#> |.....................|    0.2338 |   -0.2836 |     1.014 |     1.002 |
-#> |.....................|   -0.3897 |    -1.922 |    0.8816 |   -0.1288 |
-#> |.....................|    0.1940 |   -0.4011 |...........|...........|
-#> |  109|     479.14119 |     1.004 |    -1.430 |   -0.9374 |   -0.9185 |
-#> |.....................|    -1.100 |    -1.062 |   -0.1775 |   -0.9218 |
-#> |.....................|   -0.7383 |    -1.108 |   -0.5019 |   -0.8783 |
-#> |.....................|    -1.083 |  -0.04112 |...........|...........|
-#> |    U|     479.14119 |     91.39 |    -5.630 |   -0.9140 |    -2.181 |
-#> |.....................|    -4.713 |    0.3774 |     1.119 |   0.05710 |
-#> |.....................|    0.8323 |    0.6917 |     1.616 |    0.9495 |
-#> |.....................|    0.6826 |     2.217 |...........|...........|
-#> |    X|     479.14119 |     91.39 |  0.003588 |    0.2862 |    0.1129 |
-#> |.....................|  0.008979 |    0.5933 |     1.119 |   0.05710 |
-#> |.....................|    0.8323 |    0.6917 |     1.616 |    0.9495 |
-#> |.....................|    0.6826 |     2.217 |...........|...........|
-#> |    F| Forward Diff. |   -0.4299 |    0.6321 |   -0.1435 |  -0.02760 |
-#> |.....................|    0.2360 |   -0.2479 |     1.019 |    0.9518 |
-#> |.....................|   -0.3967 |    -1.860 |     1.900 |   -0.5922 |
-#> |.....................|   -0.1599 |   -0.3806 |...........|...........|
-#> |  110|     479.13501 |     1.005 |    -1.431 |   -0.9373 |   -0.9185 |
-#> |.....................|    -1.101 |    -1.062 |   -0.1783 |   -0.9226 |
-#> |.....................|   -0.7379 |    -1.106 |   -0.5035 |   -0.8778 |
-#> |.....................|    -1.083 |  -0.04080 |...........|...........|
-#> |    U|     479.13501 |     91.42 |    -5.631 |   -0.9139 |    -2.181 |
-#> |.....................|    -4.713 |    0.3775 |     1.119 |   0.05707 |
-#> |.....................|    0.8326 |    0.6932 |     1.614 |    0.9500 |
-#> |.....................|    0.6827 |     2.217 |...........|...........|
-#> |    X|     479.13501 |     91.42 |  0.003586 |    0.2862 |    0.1129 |
-#> |.....................|  0.008977 |    0.5933 |     1.119 |   0.05707 |
-#> |.....................|    0.8326 |    0.6932 |     1.614 |    0.9500 |
-#> |.....................|    0.6827 |     2.217 |...........|...........|
-#> |    F| Forward Diff. |     2.960 |    0.6324 |   -0.1010 |  -0.03176 |
-#> |.....................|    0.2344 |   -0.2516 |    0.9454 |    0.8792 |
-#> |.....................|   -0.3822 |    -1.742 |    0.9146 |  -0.04263 |
-#> |.....................|    0.2425 |   -0.3771 |...........|...........|
-#> |  111|     479.13244 |     1.004 |    -1.432 |   -0.9368 |   -0.9184 |
-#> |.....................|    -1.101 |    -1.061 |   -0.1790 |   -0.9224 |
-#> |.....................|   -0.7372 |    -1.105 |   -0.5036 |   -0.8775 |
-#> |.....................|    -1.083 |  -0.04025 |...........|...........|
-#> |    U|     479.13244 |     91.33 |    -5.632 |   -0.9135 |    -2.181 |
-#> |.....................|    -4.714 |    0.3778 |     1.119 |   0.05708 |
-#> |.....................|    0.8331 |    0.6941 |     1.614 |    0.9502 |
-#> |.....................|    0.6825 |     2.218 |...........|...........|
-#> |    X|     479.13244 |     91.33 |  0.003580 |    0.2863 |    0.1130 |
-#> |.....................|  0.008971 |    0.5933 |     1.119 |   0.05708 |
-#> |.....................|    0.8331 |    0.6941 |     1.614 |    0.9502 |
-#> |.....................|    0.6825 |     2.218 |...........|...........|
-#> |    F| Forward Diff. |    -5.808 |    0.6219 |   -0.1958 |  -0.01683 |
-#> |.....................|    0.2369 |   -0.2179 |    0.9347 |    0.8364 |
-#> |.....................|   -0.3987 |    -1.797 |    0.8150 |  -0.05765 |
-#> |.....................|    0.2618 |   -0.3704 |...........|...........|
-#> |  112|     479.12666 |     1.004 |    -1.434 |   -0.9365 |   -0.9183 |
-#> |.....................|    -1.102 |    -1.060 |   -0.1796 |   -0.9220 |
-#> |.....................|   -0.7365 |    -1.104 |   -0.5033 |   -0.8772 |
-#> |.....................|    -1.083 |  -0.03975 |...........|...........|
-#> |    U|     479.12666 |     91.40 |    -5.634 |   -0.9132 |    -2.181 |
-#> |.....................|    -4.714 |    0.3782 |     1.118 |   0.05709 |
-#> |.....................|    0.8336 |    0.6951 |     1.614 |    0.9505 |
-#> |.....................|    0.6824 |     2.218 |...........|...........|
-#> |    X|     479.12666 |     91.40 |  0.003574 |    0.2863 |    0.1130 |
-#> |.....................|  0.008965 |    0.5934 |     1.118 |   0.05709 |
-#> |.....................|    0.8336 |    0.6951 |     1.614 |    0.9505 |
-#> |.....................|    0.6824 |     2.218 |...........|...........|
-#> |    F| Forward Diff. |    0.9955 |    0.6218 |  -0.09617 |  -0.02448 |
-#> |.....................|    0.2342 |   -0.2176 |    0.9924 |    0.8560 |
-#> |.....................|   -0.3772 |    -1.645 |     1.883 |   -0.4422 |
-#> |.....................|   -0.1320 |   -0.3750 |...........|...........|
-#> |  113|     479.12255 |     1.004 |    -1.436 |   -0.9361 |   -0.9182 |
-#> |.....................|    -1.103 |    -1.060 |   -0.1805 |   -0.9221 |
-#> |.....................|   -0.7358 |    -1.103 |   -0.5043 |   -0.8768 |
-#> |.....................|    -1.083 |  -0.03920 |...........|...........|
-#> |    U|     479.12255 |     91.34 |    -5.636 |   -0.9129 |    -2.181 |
-#> |.....................|    -4.715 |    0.3784 |     1.118 |   0.05709 |
-#> |.....................|    0.8341 |    0.6962 |     1.613 |    0.9509 |
-#> |.....................|    0.6824 |     2.219 |...........|...........|
-#> |    X|     479.12255 |     91.34 |  0.003569 |    0.2864 |    0.1130 |
-#> |.....................|  0.008960 |    0.5935 |     1.118 |   0.05709 |
-#> |.....................|    0.8341 |    0.6962 |     1.613 |    0.9509 |
-#> |.....................|    0.6824 |     2.219 |...........|...........|
-#> |    F| Forward Diff. |    -4.522 |    0.6133 |   -0.1571 |  -0.01492 |
-#> |.....................|    0.2353 |   -0.1923 |    0.9045 |    0.7846 |
-#> |.....................|   -0.3572 |    -1.629 |    0.8508 |   0.03564 |
-#> |.....................|    0.2811 |   -0.3561 |...........|...........|
-#> |  114|     479.11855 |     1.005 |    -1.437 |   -0.9356 |   -0.9182 |
-#> |.....................|    -1.103 |    -1.059 |   -0.1812 |   -0.9217 |
-#> |.....................|   -0.7351 |    -1.102 |   -0.5043 |   -0.8766 |
-#> |.....................|    -1.084 |  -0.03859 |...........|...........|
-#> |    U|     479.11855 |     91.41 |    -5.637 |   -0.9124 |    -2.181 |
-#> |.....................|    -4.716 |    0.3787 |     1.118 |   0.05710 |
-#> |.....................|    0.8346 |    0.6968 |     1.613 |    0.9510 |
-#> |.....................|    0.6823 |     2.220 |...........|...........|
-#> |    X|     479.11855 |     91.41 |  0.003562 |    0.2865 |    0.1130 |
-#> |.....................|  0.008953 |    0.5936 |     1.118 |   0.05710 |
-#> |.....................|    0.8346 |    0.6968 |     1.613 |    0.9510 |
-#> |.....................|    0.6823 |     2.220 |...........|...........|
-#> |    F| Forward Diff. |     2.813 |    0.6131 |  -0.03713 |  -0.02450 |
-#> |.....................|    0.2319 |   -0.1976 |    0.8863 |    0.8390 |
-#> |.....................|   -0.3589 |    -1.516 |    0.8806 |   -0.4426 |
-#> |.....................|   -0.1647 |   -0.3784 |...........|...........|
-#> |  115|     479.11487 |     1.004 |    -1.439 |   -0.9352 |   -0.9181 |
-#> |.....................|    -1.104 |    -1.058 |   -0.1819 |   -0.9213 |
-#> |.....................|   -0.7344 |    -1.101 |   -0.5040 |   -0.8763 |
-#> |.....................|    -1.084 |  -0.03810 |...........|...........|
-#> |    U|     479.11487 |     91.37 |    -5.639 |   -0.9121 |    -2.180 |
-#> |.....................|    -4.716 |    0.3790 |     1.117 |   0.05711 |
-#> |.....................|    0.8352 |    0.6977 |     1.613 |    0.9514 |
-#> |.....................|    0.6823 |     2.220 |...........|...........|
-#> |    X|     479.11487 |     91.37 |  0.003555 |    0.2866 |    0.1130 |
-#> |.....................|  0.008947 |    0.5936 |     1.117 |   0.05711 |
-#> |.....................|    0.8352 |    0.6977 |     1.613 |    0.9514 |
-#> |.....................|    0.6823 |     2.220 |...........|...........|
-#> |    F| Forward Diff. |    -1.684 |    0.6054 |  -0.08346 |  -0.01559 |
-#> |.....................|    0.2328 |   -0.1708 |    0.9518 |    0.8099 |
-#> |.....................|   -0.3621 |    -1.485 |    0.9267 |   -0.3776 |
-#> |.....................|   -0.1041 |   -0.3537 |...........|...........|
-#> |  116|     479.11139 |     1.005 |    -1.441 |   -0.9347 |   -0.9181 |
-#> |.....................|    -1.105 |    -1.058 |   -0.1829 |   -0.9211 |
-#> |.....................|   -0.7337 |    -1.100 |   -0.5039 |   -0.8760 |
-#> |.....................|    -1.083 |  -0.03771 |...........|...........|
-#> |    U|     479.11139 |     91.41 |    -5.641 |   -0.9117 |    -2.180 |
-#> |.....................|    -4.717 |    0.3792 |     1.117 |   0.05712 |
-#> |.....................|    0.8357 |    0.6988 |     1.613 |    0.9517 |
-#> |.....................|    0.6824 |     2.221 |...........|...........|
-#> |    X|     479.11139 |     91.41 |  0.003549 |    0.2867 |    0.1130 |
-#> |.....................|  0.008941 |    0.5937 |     1.117 |   0.05712 |
-#> |.....................|    0.8357 |    0.6988 |     1.613 |    0.9517 |
-#> |.....................|    0.6824 |     2.221 |...........|...........|
-#> |    F| Forward Diff. |     3.241 |    0.6036 | 0.0009951 |  -0.02154 |
-#> |.....................|    0.2300 |   -0.1727 |    0.8524 |    0.8311 |
-#> |.....................|   -0.3642 |    -1.386 |     1.866 |   -0.3472 |
-#> |.....................|   -0.1024 |   -0.3634 |...........|...........|
-#> |  117|     479.10851 |     1.004 |    -1.443 |   -0.9342 |   -0.9180 |
-#> |.....................|    -1.105 |    -1.058 |   -0.1837 |   -0.9207 |
-#> |.....................|   -0.7329 |    -1.100 |   -0.5043 |   -0.8759 |
-#> |.....................|    -1.084 |  -0.03710 |...........|...........|
-#> |    U|     479.10851 |     91.37 |    -5.643 |   -0.9112 |    -2.180 |
-#> |.....................|    -4.718 |    0.3794 |     1.117 |   0.05713 |
-#> |.....................|    0.8363 |    0.6988 |     1.613 |    0.9517 |
-#> |.....................|    0.6823 |     2.222 |...........|...........|
-#> |    X|     479.10851 |     91.37 |  0.003542 |    0.2868 |    0.1130 |
-#> |.....................|  0.008933 |    0.5937 |     1.117 |   0.05713 |
-#> |.....................|    0.8363 |    0.6988 |     1.613 |    0.9517 |
-#> |.....................|    0.6823 |     2.222 |...........|...........|
-#> |    F| Forward Diff. |    -1.500 |    0.5956 |  -0.03344 |  -0.01385 |
-#> |.....................|    0.2306 |   -0.1498 |    0.8910 |    0.8240 |
-#> |.....................|   -0.3570 |    -1.405 |    0.8461 |   -0.3572 |
-#> |.....................|  -0.08808 |   -0.3487 |...........|...........|
-#> |  118|     479.10606 |     1.005 |    -1.445 |   -0.9338 |   -0.9180 |
-#> |.....................|    -1.106 |    -1.057 |   -0.1846 |   -0.9207 |
-#> |.....................|   -0.7320 |    -1.099 |   -0.5047 |   -0.8757 |
-#> |.....................|    -1.084 |  -0.03650 |...........|...........|
-#> |    U|     479.10606 |     91.43 |    -5.645 |   -0.9108 |    -2.180 |
-#> |.....................|    -4.719 |    0.3796 |     1.116 |   0.05713 |
-#> |.....................|    0.8369 |    0.6994 |     1.612 |    0.9519 |
-#> |.....................|    0.6822 |     2.222 |...........|...........|
-#> |    X|     479.10606 |     91.43 |  0.003535 |    0.2868 |    0.1130 |
-#> |.....................|  0.008927 |    0.5938 |     1.116 |   0.05713 |
-#> |.....................|    0.8369 |    0.6994 |     1.612 |    0.9519 |
-#> |.....................|    0.6822 |     2.222 |...........|...........|
-#> |    F| Forward Diff. |     5.260 |    0.5953 |   0.07226 |  -0.02302 |
-#> |.....................|    0.2275 |   -0.1573 |    0.8150 |    0.8159 |
-#> |.....................|   -0.3410 |    -1.340 |    0.8208 |    0.1422 |
-#> |.....................|    0.2750 |   -0.3500 |...........|...........|
-#> |  119|     479.10199 |     1.004 |    -1.447 |   -0.9337 |   -0.9181 |
-#> |.....................|    -1.107 |    -1.057 |   -0.1854 |   -0.9204 |
-#> |.....................|   -0.7311 |    -1.099 |   -0.5045 |   -0.8757 |
-#> |.....................|    -1.084 |  -0.03604 |...........|...........|
-#> |    U|     479.10199 |     91.37 |    -5.647 |   -0.9107 |    -2.180 |
-#> |.....................|    -4.720 |    0.3799 |     1.116 |   0.05714 |
-#> |.....................|    0.8375 |    0.6999 |     1.613 |    0.9520 |
-#> |.....................|    0.6821 |     2.223 |...........|...........|
-#> |    X|     479.10199 |     91.37 |  0.003528 |    0.2869 |    0.1130 |
-#> |.....................|  0.008919 |    0.5938 |     1.116 |   0.05714 |
-#> |.....................|    0.8375 |    0.6999 |     1.613 |    0.9520 |
-#> |.....................|    0.6821 |     2.223 |...........|...........|
-#> |    F| Forward Diff. |   -0.7698 |    0.5858 | -0.004343 |  -0.01418 |
-#> |.....................|    0.2278 |   -0.1298 |    0.8244 |    0.7686 |
-#> |.....................|   -0.3575 |    -1.372 |    0.8320 |   -0.3359 |
-#> |.....................|    0.2977 |   -0.3384 |...........|...........|
-#> |  120|     479.09844 |     1.005 |    -1.448 |   -0.9337 |   -0.9180 |
-#> |.....................|    -1.108 |    -1.056 |   -0.1863 |   -0.9208 |
-#> |.....................|   -0.7304 |    -1.097 |   -0.5051 |   -0.8752 |
-#> |.....................|    -1.084 |  -0.03534 |...........|...........|
-#> |    U|     479.09844 |     91.43 |    -5.648 |   -0.9108 |    -2.180 |
-#> |.....................|    -4.720 |    0.3801 |     1.116 |   0.05713 |
-#> |.....................|    0.8381 |    0.7011 |     1.612 |    0.9524 |
-#> |.....................|    0.6817 |     2.224 |...........|...........|
-#> |    X|     479.09844 |     91.43 |  0.003523 |    0.2868 |    0.1130 |
-#> |.....................|  0.008914 |    0.5939 |     1.116 |   0.05713 |
-#> |.....................|    0.8381 |    0.7011 |     1.612 |    0.9524 |
-#> |.....................|    0.6817 |     2.224 |...........|...........|
-#> |    F| Forward Diff. |     4.894 |    0.5851 |   0.05981 |  -0.02077 |
-#> |.....................|    0.2261 |   -0.1389 |    0.7622 |    0.7617 |
-#> |.....................|   -0.3411 |    -1.236 |    0.7863 |    0.1583 |
-#> |.....................|    0.2091 |   -0.3951 |...........|...........|
-#> |  121|     479.09485 |     1.004 |    -1.450 |   -0.9338 |   -0.9180 |
-#> |.....................|    -1.108 |    -1.056 |   -0.1867 |   -0.9202 |
-#> |.....................|   -0.7295 |    -1.097 |   -0.5051 |   -0.8750 |
-#> |.....................|    -1.085 |  -0.03445 |...........|...........|
-#> |    U|     479.09485 |     91.37 |    -5.650 |   -0.9108 |    -2.180 |
-#> |.....................|    -4.721 |    0.3803 |     1.116 |   0.05714 |
-#> |.....................|    0.8388 |    0.7016 |     1.612 |    0.9526 |
-#> |.....................|    0.6813 |     2.225 |...........|...........|
-#> |    X|     479.09485 |     91.37 |  0.003517 |    0.2868 |    0.1130 |
-#> |.....................|  0.008907 |    0.5939 |     1.116 |   0.05714 |
-#> |.....................|    0.8388 |    0.7016 |     1.612 |    0.9526 |
-#> |.....................|    0.6813 |     2.225 |...........|...........|
-#> |    F| Forward Diff. |    -1.077 |    0.5762 |  -0.02502 |  -0.01122 |
-#> |.....................|    0.2275 |   -0.1137 |    0.7953 |    0.7347 |
-#> |.....................|   -0.3473 |    -1.249 |    0.8683 |    0.1895 |
-#> |.....................|    0.2333 |   -0.3625 |...........|...........|
-#> |  122|     479.09211 |     1.005 |    -1.452 |   -0.9337 |   -0.9180 |
-#> |.....................|    -1.109 |    -1.055 |   -0.1878 |   -0.9202 |
-#> |.....................|   -0.7286 |    -1.096 |   -0.5055 |   -0.8752 |
-#> |.....................|    -1.085 |  -0.03372 |...........|...........|
-#> |    U|     479.09211 |     91.41 |    -5.652 |   -0.9107 |    -2.180 |
-#> |.....................|    -4.722 |    0.3805 |     1.115 |   0.05714 |
-#> |.....................|    0.8394 |    0.7021 |     1.612 |    0.9524 |
-#> |.....................|    0.6810 |     2.226 |...........|...........|
-#> |    X|     479.09211 |     91.41 |  0.003510 |    0.2868 |    0.1130 |
-#> |.....................|  0.008900 |    0.5940 |     1.115 |   0.05714 |
-#> |.....................|    0.8394 |    0.7021 |     1.612 |    0.9524 |
-#> |.....................|    0.6810 |     2.226 |...........|...........|
-#> |    F| Forward Diff. |     3.651 |    0.5754 |   0.04071 |  -0.01634 |
-#> |.....................|    0.2261 |   -0.1150 |    0.8084 |    0.7089 |
-#> |.....................|   -0.3268 |    -1.156 |    0.8610 |    0.1793 |
-#> |.....................|    0.2137 |   -0.3471 |...........|...........|
-#> |  123|     479.08947 |     1.004 |    -1.454 |   -0.9335 |   -0.9181 |
-#> |.....................|    -1.110 |    -1.055 |   -0.1890 |   -0.9199 |
-#> |.....................|   -0.7277 |    -1.096 |   -0.5056 |   -0.8754 |
-#> |.....................|    -1.085 |  -0.03307 |...........|...........|
-#> |    U|     479.08947 |     91.37 |    -5.654 |   -0.9105 |    -2.180 |
-#> |.....................|    -4.722 |    0.3808 |     1.115 |   0.05715 |
-#> |.....................|    0.8401 |    0.7021 |     1.611 |    0.9522 |
-#> |.....................|    0.6809 |     2.226 |...........|...........|
-#> |    X|     479.08947 |     91.37 |  0.003504 |    0.2869 |    0.1130 |
-#> |.....................|  0.008893 |    0.5941 |     1.115 |   0.05715 |
-#> |.....................|    0.8401 |    0.7021 |     1.611 |    0.9522 |
-#> |.....................|    0.6809 |     2.226 |...........|...........|
-#> |    F| Forward Diff. |   -0.8529 |    0.5679 | -0.006947 | -0.009666 |
-#> |.....................|    0.2263 |  -0.09399 |    0.7582 |    0.6848 |
-#> |.....................|   -0.3382 |    -1.232 |    0.7736 |   -0.3452 |
-#> |.....................|   -0.1950 |   -0.3796 |...........|...........|
-#> |  124|     479.08673 |     1.005 |    -1.456 |   -0.9331 |   -0.9181 |
-#> |.....................|    -1.111 |    -1.054 |   -0.1901 |   -0.9198 |
-#> |.....................|   -0.7269 |    -1.095 |   -0.5060 |   -0.8751 |
-#> |.....................|    -1.085 |  -0.03242 |...........|...........|
-#> |    U|     479.08673 |     91.42 |    -5.656 |   -0.9102 |    -2.180 |
-#> |.....................|    -4.723 |    0.3808 |     1.114 |   0.05716 |
-#> |.....................|    0.8406 |    0.7030 |     1.611 |    0.9525 |
-#> |.....................|    0.6810 |     2.227 |...........|...........|
-#> |    X|     479.08673 |     91.42 |  0.003498 |    0.2870 |    0.1130 |
-#> |.....................|  0.008887 |    0.5941 |     1.114 |   0.05716 |
-#> |.....................|    0.8406 |    0.7030 |     1.611 |    0.9525 |
-#> |.....................|    0.6810 |     2.227 |...........|...........|
-#> |    F| Forward Diff. |     4.055 |    0.5667 |   0.07240 |  -0.01542 |
-#> |.....................|    0.2241 |   -0.1033 |    0.7160 |    0.6904 |
-#> |.....................|   -0.3260 |    -1.123 |    0.7675 |    0.1856 |
-#> |.....................|    0.1986 |   -0.4973 |...........|...........|
-#> |  125|     479.08385 |     1.004 |    -1.457 |   -0.9328 |   -0.9181 |
-#> |.....................|    -1.112 |    -1.054 |   -0.1908 |   -0.9191 |
-#> |.....................|   -0.7261 |    -1.095 |   -0.5059 |   -0.8749 |
-#> |.....................|    -1.085 |  -0.03140 |...........|...........|
-#> |    U|     479.08385 |     91.37 |    -5.657 |   -0.9100 |    -2.180 |
-#> |.....................|    -4.724 |    0.3808 |     1.114 |   0.05718 |
-#> |.....................|    0.8412 |    0.7034 |     1.611 |    0.9527 |
-#> |.....................|    0.6808 |     2.228 |...........|...........|
-#> |    X|     479.08385 |     91.37 |  0.003491 |    0.2870 |    0.1130 |
-#> |.....................|  0.008879 |    0.5941 |     1.114 |   0.05718 |
-#> |.....................|    0.8412 |    0.7034 |     1.611 |    0.9527 |
-#> |.....................|    0.6808 |     2.228 |...........|...........|
-#> |    F| Forward Diff. |   -0.7735 |    0.5583 |   0.01997 | -0.008335 |
-#> |.....................|    0.2243 |  -0.08958 |    0.6952 |    0.6337 |
-#> |.....................|   -0.3199 |    -1.102 |    0.8222 |    0.2014 |
-#> |.....................|    0.2310 |   -0.4538 |...........|...........|
-#> |  126|     479.08143 |     1.005 |    -1.459 |   -0.9328 |   -0.9181 |
-#> |.....................|    -1.112 |    -1.054 |   -0.1918 |   -0.9191 |
-#> |.....................|   -0.7254 |    -1.094 |   -0.5066 |   -0.8749 |
-#> |.....................|    -1.086 |  -0.03018 |...........|...........|
-#> |    U|     479.08143 |     91.42 |    -5.659 |   -0.9100 |    -2.180 |
-#> |.....................|    -4.725 |    0.3810 |     1.113 |   0.05718 |
-#> |.....................|    0.8417 |    0.7042 |     1.610 |    0.9527 |
-#> |.....................|    0.6804 |     2.230 |...........|...........|
-#> |    X|     479.08143 |     91.42 |  0.003486 |    0.2870 |    0.1130 |
-#> |.....................|  0.008874 |    0.5941 |     1.113 |   0.05718 |
-#> |.....................|    0.8417 |    0.7042 |     1.610 |    0.9527 |
-#> |.....................|    0.6804 |     2.230 |...........|...........|
-#> |    F| Forward Diff. |     4.589 |    0.5568 |   0.08446 |  -0.01637 |
-#> |.....................|    0.2217 |  -0.09943 |    0.6530 |    0.6713 |
-#> |.....................|   -0.3160 |    -1.044 |    0.6971 |   -0.3035 |
-#> |.....................|   -0.2323 |   -0.3746 |...........|...........|
-#> |  127|     479.07858 |     1.004 |    -1.461 |   -0.9326 |   -0.9181 |
-#> |.....................|    -1.113 |    -1.054 |   -0.1923 |   -0.9184 |
-#> |.....................|   -0.7246 |    -1.093 |   -0.5066 |   -0.8747 |
-#> |.....................|    -1.086 |  -0.02916 |...........|...........|
-#> |    U|     479.07858 |     91.36 |    -5.661 |   -0.9098 |    -2.181 |
-#> |.....................|    -4.725 |    0.3811 |     1.113 |   0.05720 |
-#> |.....................|    0.8423 |    0.7045 |     1.610 |    0.9529 |
-#> |.....................|    0.6802 |     2.231 |...........|...........|
-#> |    X|     479.07858 |     91.36 |  0.003479 |    0.2870 |    0.1130 |
-#> |.....................|  0.008866 |    0.5941 |     1.113 |   0.05720 |
-#> |.....................|    0.8423 |    0.7045 |     1.610 |    0.9529 |
-#> |.....................|    0.6802 |     2.231 |...........|...........|
-#> |    F| Forward Diff. |    -1.147 |    0.5485 |   0.01974 | -0.006990 |
-#> |.....................|    0.2231 |  -0.08394 |    0.6583 |    0.6424 |
-#> |.....................|   -0.3232 |    -1.114 |    0.8219 |    0.1886 |
-#> |.....................|    0.1911 |   -0.3375 |...........|...........|
-#> |  128|     479.07618 |     1.004 |    -1.463 |   -0.9323 |   -0.9182 |
-#> |.....................|    -1.114 |    -1.054 |   -0.1929 |   -0.9181 |
-#> |.....................|   -0.7237 |    -1.093 |   -0.5068 |   -0.8746 |
-#> |.....................|    -1.086 |  -0.02850 |...........|...........|
-#> |    U|     479.07618 |     91.40 |    -5.663 |   -0.9095 |    -2.181 |
-#> |.....................|    -4.726 |    0.3811 |     1.113 |   0.05721 |
-#> |.....................|    0.8430 |    0.7050 |     1.610 |    0.9530 |
-#> |.....................|    0.6800 |     2.232 |...........|...........|
-#> |    X|     479.07618 |     91.40 |  0.003472 |    0.2871 |    0.1130 |
-#> |.....................|  0.008858 |    0.5941 |     1.113 |   0.05721 |
-#> |.....................|    0.8430 |    0.7050 |     1.610 |    0.9530 |
-#> |.....................|    0.6800 |     2.232 |...........|...........|
-#> |    F| Forward Diff. |     2.586 |    0.5458 |   0.07904 |  -0.01251 |
-#> |.....................|    0.2203 |  -0.08960 |    0.6458 |    0.6586 |
-#> |.....................|   -0.3031 |   -0.9906 |    0.7687 |    0.2646 |
-#> |.....................|    0.1721 |   -0.3284 |...........|...........|
-#> |  129|     479.07405 |     1.004 |    -1.465 |   -0.9322 |   -0.9183 |
-#> |.....................|    -1.115 |    -1.053 |   -0.1937 |   -0.9179 |
-#> |.....................|   -0.7228 |    -1.093 |   -0.5070 |   -0.8747 |
-#> |.....................|    -1.087 |  -0.02798 |...........|...........|
-#> |    U|     479.07405 |     91.36 |    -5.665 |   -0.9094 |    -2.181 |
-#> |.....................|    -4.727 |    0.3813 |     1.113 |   0.05721 |
-#> |.....................|    0.8437 |    0.7050 |     1.610 |    0.9529 |
-#> |.....................|    0.6797 |     2.233 |...........|...........|
-#> |    X|     479.07405 |     91.36 |  0.003465 |    0.2871 |    0.1130 |
-#> |.....................|  0.008850 |    0.5942 |     1.113 |   0.05721 |
-#> |.....................|    0.8437 |    0.7050 |     1.610 |    0.9529 |
-#> |.....................|    0.6797 |     2.233 |...........|...........|
-#> |    F| Forward Diff. |    -1.296 |    0.5389 |   0.03360 | -0.006173 |
-#> |.....................|    0.2208 |  -0.07255 |    0.6853 |    0.5995 |
-#> |.....................|   -0.2906 |    -1.015 |    0.7685 |    0.2327 |
-#> |.....................|    0.1765 |   -0.3245 |...........|...........|
-#> |  130|     479.07209 |     1.004 |    -1.467 |   -0.9321 |   -0.9183 |
-#> |.....................|    -1.116 |    -1.053 |   -0.1949 |   -0.9178 |
-#> |.....................|   -0.7220 |    -1.093 |   -0.5073 |   -0.8750 |
-#> |.....................|    -1.087 |  -0.02746 |...........|...........|
-#> |    U|     479.07209 |     91.39 |    -5.667 |   -0.9093 |    -2.181 |
-#> |.....................|    -4.728 |    0.3814 |     1.112 |   0.05721 |
-#> |.....................|    0.8442 |    0.7050 |     1.609 |    0.9526 |
-#> |.....................|    0.6796 |     2.233 |...........|...........|
-#> |    X|     479.07209 |     91.39 |  0.003458 |    0.2871 |    0.1130 |
-#> |.....................|  0.008841 |    0.5942 |     1.112 |   0.05721 |
-#> |.....................|    0.8442 |    0.7050 |     1.609 |    0.9526 |
-#> |.....................|    0.6796 |     2.233 |...........|...........|
-#> |    F| Forward Diff. |     2.160 |    0.5372 |   0.08826 |  -0.01153 |
-#> |.....................|    0.2184 |  -0.07756 |    0.6386 |    0.6404 |
-#> |.....................|   -0.2977 |   -0.9812 |    0.7463 |    0.2047 |
-#> |.....................|    0.1647 |   -0.3238 |...........|...........|
-#> |  131|     479.07029 |     1.004 |    -1.469 |   -0.9320 |   -0.9184 |
-#> |.....................|    -1.117 |    -1.053 |   -0.1960 |   -0.9175 |
-#> |.....................|   -0.7213 |    -1.093 |   -0.5075 |   -0.8752 |
-#> |.....................|    -1.087 |  -0.02689 |...........|...........|
-#> |    U|     479.07029 |     91.35 |    -5.669 |   -0.9092 |    -2.181 |
-#> |.....................|    -4.729 |    0.3815 |     1.112 |   0.05722 |
-#> |.....................|    0.8447 |    0.7049 |     1.609 |    0.9524 |
-#> |.....................|    0.6795 |     2.234 |...........|...........|
-#> |    X|     479.07029 |     91.35 |  0.003451 |    0.2872 |    0.1130 |
-#> |.....................|  0.008833 |    0.5942 |     1.112 |   0.05722 |
-#> |.....................|    0.8447 |    0.7049 |     1.609 |    0.9524 |
-#> |.....................|    0.6795 |     2.234 |...........|...........|
-#> |    F| Forward Diff. |    -1.487 |    0.5301 |   0.04502 | -0.006786 |
-#> |.....................|    0.2180 |  -0.06576 |    0.6433 |    0.5523 |
-#> |.....................|   -0.2822 |    -1.039 |     1.637 |   -0.2973 |
-#> |.....................|   -0.2152 |   -0.3175 |...........|...........|
-#> |  132|     479.06833 |     1.004 |    -1.471 |   -0.9316 |   -0.9185 |
-#> |.....................|    -1.118 |    -1.053 |   -0.1965 |   -0.9170 |
-#> |.....................|   -0.7207 |    -1.093 |   -0.5082 |   -0.8751 |
-#> |.....................|    -1.087 |  -0.02616 |...........|...........|
-#> |    U|     479.06833 |     91.38 |    -5.671 |   -0.9088 |    -2.181 |
-#> |.....................|    -4.730 |    0.3814 |     1.111 |   0.05724 |
-#> |.....................|    0.8452 |    0.7048 |     1.608 |    0.9525 |
-#> |.....................|    0.6792 |     2.235 |...........|...........|
-#> |    X|     479.06833 |     91.38 |  0.003444 |    0.2872 |    0.1129 |
-#> |.....................|  0.008825 |    0.5942 |     1.111 |   0.05724 |
-#> |.....................|    0.8452 |    0.7048 |     1.608 |    0.9525 |
-#> |.....................|    0.6792 |     2.235 |...........|...........|
-#> |    F| Forward Diff. |    0.6466 |    0.5255 |   0.09166 |  -0.01288 |
-#> |.....................|    0.2142 |  -0.07904 |    0.5622 |    0.5865 |
-#> |.....................|   -0.2779 |    -1.008 |    0.7011 |    0.1998 |
-#> |.....................|    0.1404 |   -0.3181 |...........|...........|
-#> |  133|     479.06868 |     1.003 |    -1.472 |   -0.9317 |   -0.9185 |
-#> |.....................|    -1.118 |    -1.053 |   -0.1973 |   -0.9180 |
-#> |.....................|   -0.7202 |    -1.092 |   -0.5093 |   -0.8754 |
-#> |.....................|    -1.087 |  -0.02567 |...........|...........|
-#> |    U|     479.06868 |     91.29 |    -5.672 |   -0.9090 |    -2.181 |
-#> |.....................|    -4.731 |    0.3814 |     1.111 |   0.05721 |
-#> |.....................|    0.8455 |    0.7062 |     1.607 |    0.9522 |
-#> |.....................|    0.6790 |     2.235 |...........|...........|
-#> |    X|     479.06868 |     91.29 |  0.003441 |    0.2872 |    0.1129 |
-#> |.....................|  0.008822 |    0.5942 |     1.111 |   0.05721 |
-#> |.....................|    0.8455 |    0.7062 |     1.607 |    0.9522 |
-#> |.....................|    0.6790 |     2.235 |...........|...........|
-#> |  134|     479.06735 |     1.004 |    -1.472 |   -0.9316 |   -0.9185 |
-#> |.....................|    -1.118 |    -1.053 |   -0.1969 |   -0.9175 |
-#> |.....................|   -0.7205 |    -1.092 |   -0.5087 |   -0.8753 |
-#> |.....................|    -1.087 |  -0.02593 |...........|...........|
-#> |    U|     479.06735 |     91.33 |    -5.672 |   -0.9089 |    -2.181 |
-#> |.....................|    -4.730 |    0.3814 |     1.111 |   0.05722 |
-#> |.....................|    0.8453 |    0.7054 |     1.608 |    0.9523 |
-#> |.....................|    0.6791 |     2.235 |...........|...........|
-#> |    X|     479.06735 |     91.33 |  0.003443 |    0.2872 |    0.1129 |
-#> |.....................|  0.008823 |    0.5942 |     1.111 |   0.05722 |
-#> |.....................|    0.8453 |    0.7054 |     1.608 |    0.9523 |
-#> |.....................|    0.6791 |     2.235 |...........|...........|
-#> |    F| Forward Diff. |    -3.476 |    0.5223 |   0.03269 | -0.003763 |
-#> |.....................|    0.2173 |  -0.06616 |    0.5281 |    0.5229 |
-#> |.....................|   -0.3041 |    -1.023 |     1.607 |   -0.2773 |
-#> |.....................|   -0.2325 |   -0.3192 |...........|...........|
-#> |  135|     479.06543 |     1.004 |    -1.472 |   -0.9319 |   -0.9185 |
-#> |.....................|    -1.118 |    -1.053 |   -0.1968 |   -0.9175 |
-#> |.....................|   -0.7201 |    -1.092 |   -0.5088 |   -0.8751 |
-#> |.....................|    -1.088 |  -0.02567 |...........|...........|
-#> |    U|     479.06543 |     91.36 |    -5.672 |   -0.9091 |    -2.181 |
-#> |.....................|    -4.731 |    0.3815 |     1.111 |   0.05722 |
-#> |.....................|    0.8456 |    0.7056 |     1.608 |    0.9525 |
-#> |.....................|    0.6790 |     2.235 |...........|...........|
-#> |    X|     479.06543 |     91.36 |  0.003439 |    0.2872 |    0.1129 |
-#> |.....................|  0.008820 |    0.5942 |     1.111 |   0.05722 |
-#> |.....................|    0.8456 |    0.7056 |     1.608 |    0.9525 |
-#> |.....................|    0.6790 |     2.235 |...........|...........|
-#> |  136|     479.06390 |     1.004 |    -1.474 |   -0.9324 |   -0.9185 |
-#> |.....................|    -1.119 |    -1.053 |   -0.1965 |   -0.9174 |
-#> |.....................|   -0.7194 |    -1.092 |   -0.5089 |   -0.8750 |
-#> |.....................|    -1.088 |  -0.02528 |...........|...........|
-#> |    U|      479.0639 |     91.36 |    -5.674 |   -0.9095 |    -2.181 |
-#> |.....................|    -4.732 |    0.3816 |     1.111 |   0.05723 |
-#> |.....................|    0.8461 |    0.7059 |     1.607 |    0.9526 |
-#> |.....................|    0.6786 |     2.236 |...........|...........|
-#> |    X|      479.0639 |     91.36 |  0.003434 |    0.2871 |    0.1129 |
-#> |.....................|  0.008813 |    0.5943 |     1.111 |   0.05723 |
-#> |.....................|    0.8461 |    0.7059 |     1.607 |    0.9526 |
-#> |.....................|    0.6786 |     2.236 |...........|...........|
-#> |  137|     479.05708 |     1.004 |    -1.481 |   -0.9346 |   -0.9186 |
-#> |.....................|    -1.123 |    -1.051 |   -0.1952 |   -0.9171 |
-#> |.....................|   -0.7164 |    -1.090 |   -0.5089 |   -0.8741 |
-#> |.....................|    -1.090 |  -0.02338 |...........|...........|
-#> |    U|     479.05708 |     91.37 |    -5.681 |   -0.9115 |    -2.181 |
-#> |.....................|    -4.735 |    0.3824 |     1.112 |   0.05724 |
-#> |.....................|    0.8483 |    0.7072 |     1.607 |    0.9535 |
-#> |.....................|    0.6769 |     2.238 |...........|...........|
-#> |    X|     479.05708 |     91.37 |  0.003409 |    0.2867 |    0.1129 |
-#> |.....................|  0.008783 |    0.5944 |     1.112 |   0.05724 |
-#> |.....................|    0.8483 |    0.7072 |     1.607 |    0.9535 |
-#> |.....................|    0.6769 |     2.238 |...........|...........|
-#> |  138|     479.03987 |     1.004 |    -1.510 |   -0.9434 |   -0.9188 |
-#> |.....................|    -1.136 |    -1.045 |   -0.1899 |   -0.9157 |
-#> |.....................|   -0.7043 |    -1.085 |   -0.5092 |   -0.8705 |
-#> |.....................|    -1.098 |  -0.01577 |...........|...........|
-#> |    U|     479.03987 |     91.37 |    -5.710 |   -0.9193 |    -2.181 |
-#> |.....................|    -4.749 |    0.3852 |     1.114 |   0.05728 |
-#> |.....................|    0.8571 |    0.7123 |     1.607 |    0.9569 |
-#> |.....................|    0.6702 |     2.247 |...........|...........|
-#> |    X|     479.03987 |     91.37 |  0.003311 |    0.2851 |    0.1129 |
-#> |.....................|  0.008662 |    0.5951 |     1.114 |   0.05728 |
-#> |.....................|    0.8571 |    0.7123 |     1.607 |    0.9569 |
-#> |.....................|    0.6702 |     2.247 |...........|...........|
-#> |    F| Forward Diff. |   -0.3651 |    0.4285 |   -0.5283 | -0.001988 |
-#> |.....................|    0.1991 |   0.06799 |    0.8278 |    0.7155 |
-#> |.....................|   -0.2362 |   -0.3851 |    0.6274 |    0.1204 |
-#> |.....................|   -0.9270 |   -0.3308 |...........|...........|
-#> |  139|     479.01407 |     1.005 |    -1.553 |   -0.9371 |   -0.9187 |
-#> |.....................|    -1.158 |    -1.041 |   -0.1978 |   -0.9162 |
-#> |.....................|   -0.6881 |    -1.086 |   -0.5088 |   -0.8721 |
-#> |.....................|    -1.097 |  -0.01436 |...........|...........|
-#> |    U|     479.01407 |     91.44 |    -5.753 |   -0.9138 |    -2.181 |
-#> |.....................|    -4.770 |    0.3869 |     1.111 |   0.05726 |
-#> |.....................|    0.8690 |    0.7117 |     1.608 |    0.9554 |
-#> |.....................|    0.6704 |     2.249 |...........|...........|
-#> |    X|     479.01407 |     91.44 |  0.003172 |    0.2862 |    0.1129 |
-#> |.....................|  0.008479 |    0.5955 |     1.111 |   0.05726 |
-#> |.....................|    0.8690 |    0.7117 |     1.608 |    0.9554 |
-#> |.....................|    0.6704 |     2.249 |...........|...........|
-#> |    F| Forward Diff. |     7.322 |    0.3385 |  -0.09736 | -0.005783 |
-#> |.....................|    0.1607 |    0.1322 |    0.5556 |    0.5176 |
-#> |.....................|   -0.1562 |   -0.2690 |     1.549 |  -0.03161 |
-#> |.....................|   -0.8578 |   -0.3240 |...........|...........|
-#> |  140|     478.99946 |     1.003 |    -1.595 |   -0.9294 |   -0.9194 |
-#> |.....................|    -1.179 |    -1.045 |   -0.1992 |   -0.9136 |
-#> |.....................|   -0.6715 |    -1.093 |   -0.5132 |   -0.8724 |
-#> |.....................|    -1.100 | -0.009543 |...........|...........|
-#> |    U|     478.99946 |     91.31 |    -5.795 |   -0.9069 |    -2.182 |
-#> |.....................|    -4.791 |    0.3851 |     1.110 |   0.05734 |
-#> |.....................|    0.8811 |    0.7049 |     1.602 |    0.9551 |
-#> |.....................|    0.6678 |     2.255 |...........|...........|
-#> |    X|     478.99946 |     91.31 |  0.003042 |    0.2876 |    0.1128 |
-#> |.....................|  0.008303 |    0.5951 |     1.110 |   0.05734 |
-#> |.....................|    0.8811 |    0.7049 |     1.602 |    0.9551 |
-#> |.....................|    0.6678 |     2.255 |...........|...........|
-#> |    F| Forward Diff. |    -5.440 |    0.2525 |    0.1677 |  0.001517 |
-#> |.....................|    0.1272 |   0.05864 |    0.6253 |    0.4352 |
-#> |.....................|   -0.1457 |   -0.7321 |     1.353 | 0.0009973 |
-#> |.....................|    -1.018 |   -0.3498 |...........|...........|
-#> |  141|     479.00064 |     1.004 |    -1.626 |   -0.9429 |   -0.9240 |
-#> |.....................|    -1.201 |    -1.064 |   -0.2165 |   -0.9169 |
-#> |.....................|   -0.6612 |    -1.100 |   -0.5189 |   -0.8809 |
-#> |.....................|    -1.100 | -0.001744 |...........|...........|
-#> |    U|     479.00064 |     91.38 |    -5.826 |   -0.9189 |    -2.186 |
-#> |.....................|    -4.814 |    0.3763 |     1.103 |   0.05724 |
-#> |.....................|    0.8887 |    0.6986 |     1.596 |    0.9470 |
-#> |.....................|    0.6683 |     2.264 |...........|...........|
-#> |    X|     479.00064 |     91.38 |  0.002950 |    0.2852 |    0.1123 |
-#> |.....................|  0.008117 |    0.5930 |     1.103 |   0.05724 |
-#> |.....................|    0.8887 |    0.6986 |     1.596 |    0.9470 |
-#> |.....................|    0.6683 |     2.264 |...........|...........|
-#> |  142|     478.99385 |     1.004 |    -1.610 |   -0.9359 |   -0.9216 |
-#> |.....................|    -1.190 |    -1.054 |   -0.2077 |   -0.9152 |
-#> |.....................|   -0.6665 |    -1.096 |   -0.5161 |   -0.8765 |
-#> |.....................|    -1.100 | -0.005738 |...........|...........|
-#> |    U|     478.99385 |     91.39 |    -5.810 |   -0.9127 |    -2.184 |
-#> |.....................|    -4.802 |    0.3808 |     1.107 |   0.05729 |
-#> |.....................|    0.8848 |    0.7019 |     1.599 |    0.9512 |
-#> |.....................|    0.6681 |     2.260 |...........|...........|
-#> |    X|     478.99385 |     91.39 |  0.002997 |    0.2864 |    0.1126 |
-#> |.....................|  0.008212 |    0.5941 |     1.107 |   0.05729 |
-#> |.....................|    0.8848 |    0.7019 |     1.599 |    0.9512 |
-#> |.....................|    0.6681 |     2.260 |...........|...........|
-#> |    F| Forward Diff. |     2.499 |    0.2382 |  -0.03703 |  -0.03958 |
-#> |.....................|   0.09629 |   -0.2111 |    0.3210 |    0.2393 |
-#> |.....................|   -0.1233 |   -0.7892 |     1.126 |   -0.4047 |
-#> |.....................|    -1.051 |   -0.3984 |...........|...........|
-#> |  143|     478.98455 |     1.004 |    -1.625 |   -0.9347 |   -0.9200 |
-#> |.....................|    -1.200 |    -1.054 |   -0.2131 |   -0.9088 |
-#> |.....................|   -0.6653 |    -1.094 |   -0.5167 |   -0.8757 |
-#> |.....................|    -1.099 |  0.008183 |...........|...........|
-#> |    U|     478.98455 |     91.36 |    -5.825 |   -0.9116 |    -2.182 |
-#> |.....................|    -4.813 |    0.3812 |     1.105 |   0.05748 |
-#> |.....................|    0.8857 |    0.7042 |     1.598 |    0.9520 |
-#> |.....................|    0.6689 |     2.277 |...........|...........|
-#> |    X|     478.98455 |     91.36 |  0.002951 |    0.2867 |    0.1128 |
-#> |.....................|  0.008125 |    0.5942 |     1.105 |   0.05748 |
-#> |.....................|    0.8857 |    0.7042 |     1.598 |    0.9520 |
-#> |.....................|    0.6689 |     2.277 |...........|...........|
-#> |    F| Forward Diff. |   -0.2799 |    0.1926 |  -0.02074 |  -0.02333 |
-#> |.....................|   0.08052 |   -0.1468 |    0.2817 |    0.3348 |
-#> |.....................|   -0.1470 |   -0.6425 |     1.062 |   -0.3208 |
-#> |.....................|   -0.8181 |   -0.3186 |...........|...........|
-#> |  144|     478.97736 |     1.005 |    -1.639 |   -0.9325 |   -0.9174 |
-#> |.....................|    -1.210 |    -1.043 |   -0.2100 |   -0.9166 |
-#> |.....................|   -0.6557 |    -1.093 |   -0.5206 |   -0.8754 |
-#> |.....................|    -1.097 |   0.01446 |...........|...........|
-#> |    U|     478.97736 |     91.42 |    -5.839 |   -0.9097 |    -2.180 |
-#> |.....................|    -4.822 |    0.3861 |     1.106 |   0.05725 |
-#> |.....................|    0.8927 |    0.7053 |     1.594 |    0.9522 |
-#> |.....................|    0.6711 |     2.284 |...........|...........|
-#> |    X|     478.97736 |     91.42 |  0.002912 |    0.2871 |    0.1131 |
-#> |.....................|  0.008047 |    0.5953 |     1.106 |   0.05725 |
-#> |.....................|    0.8927 |    0.7053 |     1.594 |    0.9522 |
-#> |.....................|    0.6711 |     2.284 |...........|...........|
-#> |    F| Forward Diff. |     5.719 |    0.1644 |    0.1764 | 0.0002018 |
-#> |.....................|   0.06754 |    0.1935 |  -0.08189 |   -0.1310 |
-#> |.....................|  -0.08678 |    -2.826 |    0.8338 |   -0.2552 |
-#> |.....................|   -0.4561 |   -0.1956 |...........|...........|
-#> |  145|     478.97194 |     1.004 |    -1.652 |   -0.9304 |   -0.9153 |
-#> |.....................|    -1.221 |    -1.039 |   -0.2044 |   -0.9254 |
-#> |.....................|   -0.6443 |    -1.087 |   -0.5238 |   -0.8740 |
-#> |.....................|    -1.092 |   0.01749 |...........|...........|
-#> |    U|     478.97194 |     91.40 |    -5.852 |   -0.9078 |    -2.178 |
-#> |.....................|    -4.833 |    0.3880 |     1.108 |   0.05699 |
-#> |.....................|    0.9010 |    0.7106 |     1.590 |    0.9536 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    X|     478.97194 |     91.40 |  0.002874 |    0.2875 |    0.1133 |
-#> |.....................|  0.007961 |    0.5958 |     1.108 |   0.05699 |
-#> |.....................|    0.9010 |    0.7106 |     1.590 |    0.9536 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    F| Forward Diff. |     2.925 |    0.1117 |    0.2312 |   0.02461 |
-#> |.....................|   0.04286 |    0.3818 |    0.1548 |   -0.1592 |
-#> |.....................|  -0.04325 |   -0.1382 |    0.7430 |   -0.2262 |
-#> |.....................|  -0.01070 |   -0.1316 |...........|...........|
-#> |  146|     479.08778 |    0.9990 |    -1.662 |   -0.9298 |   -0.9158 |
-#> |.....................|    -1.224 |    -1.050 |   -0.2095 |   -0.9175 |
-#> |.....................|   -0.6325 |    -1.087 |   -0.5258 |   -0.8715 |
-#> |.....................|    -1.094 |   0.02816 |...........|...........|
-#> |    U|     479.08778 |     90.91 |    -5.862 |   -0.9073 |    -2.178 |
-#> |.....................|    -4.836 |    0.3828 |     1.106 |   0.05722 |
-#> |.....................|    0.9096 |    0.7103 |     1.587 |    0.9559 |
-#> |.....................|    0.6733 |     2.301 |...........|...........|
-#> |    X|     479.08778 |     90.91 |  0.002845 |    0.2876 |    0.1132 |
-#> |.....................|  0.007936 |    0.5946 |     1.106 |   0.05722 |
-#> |.....................|    0.9096 |    0.7103 |     1.587 |    0.9559 |
-#> |.....................|    0.6733 |     2.301 |...........|...........|
-#> |  147|     478.99303 |     1.002 |    -1.652 |   -0.9306 |   -0.9153 |
-#> |.....................|    -1.221 |    -1.039 |   -0.2045 |   -0.9253 |
-#> |.....................|   -0.6442 |    -1.087 |   -0.5244 |   -0.8738 |
-#> |.....................|    -1.092 |   0.01760 |...........|...........|
-#> |    U|     478.99303 |     91.18 |    -5.852 |   -0.9080 |    -2.178 |
-#> |.....................|    -4.833 |    0.3879 |     1.108 |   0.05700 |
-#> |.....................|    0.9011 |    0.7107 |     1.589 |    0.9537 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    X|     478.99303 |     91.18 |  0.002874 |    0.2874 |    0.1133 |
-#> |.....................|  0.007961 |    0.5958 |     1.108 |   0.05700 |
-#> |.....................|    0.9011 |    0.7107 |     1.589 |    0.9537 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |  148|     478.97158 |     1.004 |    -1.652 |   -0.9304 |   -0.9153 |
-#> |.....................|    -1.221 |    -1.039 |   -0.2044 |   -0.9254 |
-#> |.....................|   -0.6443 |    -1.087 |   -0.5239 |   -0.8740 |
-#> |.....................|    -1.092 |   0.01751 |...........|...........|
-#> |    U|     478.97158 |     91.37 |    -5.852 |   -0.9078 |    -2.178 |
-#> |.....................|    -4.833 |    0.3880 |     1.108 |   0.05699 |
-#> |.....................|    0.9010 |    0.7106 |     1.590 |    0.9536 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    X|     478.97158 |     91.37 |  0.002874 |    0.2874 |    0.1133 |
-#> |.....................|  0.007961 |    0.5958 |     1.108 |   0.05699 |
-#> |.....................|    0.9010 |    0.7106 |     1.590 |    0.9536 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    F| Forward Diff. |   -0.1518 |    0.1094 |    0.1916 |   0.02921 |
-#> |.....................|   0.04385 |    0.3896 |   -0.2077 |   -0.4379 |
-#> |.....................|  -0.03471 |    -2.421 |    0.7262 |   -0.1589 |
-#> |.....................|   0.01110 |   -0.1305 |...........|...........|
-#> |  149|     478.97152 |     1.004 |    -1.652 |   -0.9304 |   -0.9153 |
-#> |.....................|    -1.221 |    -1.039 |   -0.2044 |   -0.9254 |
-#> |.....................|   -0.6443 |    -1.086 |   -0.5240 |   -0.8739 |
-#> |.....................|    -1.092 |   0.01753 |...........|...........|
-#> |    U|     478.97152 |     91.37 |    -5.852 |   -0.9078 |    -2.178 |
-#> |.....................|    -4.833 |    0.3880 |     1.108 |   0.05699 |
-#> |.....................|    0.9010 |    0.7109 |     1.590 |    0.9536 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    X|     478.97152 |     91.37 |  0.002874 |    0.2874 |    0.1133 |
-#> |.....................|  0.007961 |    0.5958 |     1.108 |   0.05699 |
-#> |.....................|    0.9010 |    0.7109 |     1.590 |    0.9536 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    C| Central Diff. |   -0.2246 |    0.1050 |    0.1574 |   0.02036 |
-#> |.....................|   0.04103 |    0.3470 |   -0.3387 |   -0.1919 |
-#> |.....................|   -0.1172 |   -0.1870 |    0.6243 |   -0.2341 |
-#> |.....................|  -0.06769 |   -0.1265 |...........|...........|
-#> |  150|     478.97142 |     1.004 |    -1.652 |   -0.9305 |   -0.9153 |
-#> |.....................|    -1.221 |    -1.039 |   -0.2042 |   -0.9253 |
-#> |.....................|   -0.6442 |    -1.086 |   -0.5242 |   -0.8739 |
-#> |.....................|    -1.092 |   0.01757 |...........|...........|
-#> |    U|     478.97142 |     91.38 |    -5.852 |   -0.9079 |    -2.178 |
-#> |.....................|    -4.833 |    0.3879 |     1.108 |   0.05700 |
-#> |.....................|    0.9011 |    0.7110 |     1.589 |    0.9537 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    X|     478.97142 |     91.38 |  0.002874 |    0.2874 |    0.1133 |
-#> |.....................|  0.007961 |    0.5958 |     1.108 |   0.05700 |
-#> |.....................|    0.9011 |    0.7110 |     1.589 |    0.9537 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    C| Central Diff. |    0.5593 |    0.1052 |    0.1640 |   0.01900 |
-#> |.....................|   0.04052 |    0.3419 |   -0.3227 |   -0.1646 |
-#> |.....................|   -0.1158 |   -0.1768 |    0.1839 |   -0.2151 |
-#> |.....................|  -0.04116 |   -0.1006 |...........|...........|
-#> |  151|     478.97143 |     1.004 |    -1.652 |   -0.9306 |   -0.9153 |
-#> |.....................|    -1.221 |    -1.039 |   -0.2041 |   -0.9252 |
-#> |.....................|   -0.6442 |    -1.086 |   -0.5243 |   -0.8738 |
-#> |.....................|    -1.092 |   0.01761 |...........|...........|
-#> |    U|     478.97143 |     91.36 |    -5.852 |   -0.9079 |    -2.178 |
-#> |.....................|    -4.833 |    0.3879 |     1.108 |   0.05700 |
-#> |.....................|    0.9011 |    0.7110 |     1.589 |    0.9538 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    X|     478.97143 |     91.36 |  0.002874 |    0.2874 |    0.1133 |
-#> |.....................|  0.007961 |    0.5958 |     1.108 |   0.05700 |
-#> |.....................|    0.9011 |    0.7110 |     1.589 |    0.9538 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |  152|     478.97137 |     1.004 |    -1.652 |   -0.9305 |   -0.9153 |
-#> |.....................|    -1.221 |    -1.039 |   -0.2042 |   -0.9253 |
-#> |.....................|   -0.6442 |    -1.086 |   -0.5242 |   -0.8738 |
-#> |.....................|    -1.092 |   0.01759 |...........|...........|
-#> |    U|     478.97137 |     91.37 |    -5.852 |   -0.9079 |    -2.178 |
-#> |.....................|    -4.833 |    0.3879 |     1.108 |   0.05700 |
-#> |.....................|    0.9011 |    0.7110 |     1.589 |    0.9537 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    X|     478.97137 |     91.37 |  0.002874 |    0.2874 |    0.1133 |
-#> |.....................|  0.007961 |    0.5958 |     1.108 |   0.05700 |
-#> |.....................|    0.9011 |    0.7110 |     1.589 |    0.9537 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    C| Central Diff. |   -0.4660 |    0.1043 |    0.1497 |   0.02048 |
-#> |.....................|   0.04080 |    0.3434 |   -0.3050 |   -0.1804 |
-#> |.....................|   -0.2015 |    -1.954 |    0.1460 |   -0.2263 |
-#> |.....................|  -0.03239 |   -0.1147 |...........|...........|
-#> |  153|     478.97135 |     1.004 |    -1.652 |   -0.9305 |   -0.9153 |
-#> |.....................|    -1.221 |    -1.039 |   -0.2041 |   -0.9253 |
-#> |.....................|   -0.6441 |    -1.086 |   -0.5242 |   -0.8738 |
-#> |.....................|    -1.092 |   0.01760 |...........|...........|
-#> |    U|     478.97135 |     91.36 |    -5.852 |   -0.9079 |    -2.178 |
-#> |.....................|    -4.833 |    0.3879 |     1.108 |   0.05700 |
-#> |.....................|    0.9012 |    0.7110 |     1.589 |    0.9538 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    X|     478.97135 |     91.36 |  0.002874 |    0.2874 |    0.1133 |
-#> |.....................|  0.007961 |    0.5958 |     1.108 |   0.05700 |
-#> |.....................|    0.9012 |    0.7110 |     1.589 |    0.9538 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    C| Central Diff. |   -0.8144 |    0.1038 |    0.1446 |   0.02101 |
-#> |.....................|   0.04083 |    0.3431 |   -0.3133 |   -0.1844 |
-#> |.....................|  -0.05440 |    -1.096 |    0.1463 |   -0.2004 |
-#> |.....................|    0.2780 |   -0.1269 |...........|...........|
-#> |  154|     478.97125 |     1.004 |    -1.652 |   -0.9305 |   -0.9153 |
-#> |.....................|    -1.221 |    -1.039 |   -0.2041 |   -0.9252 |
-#> |.....................|   -0.6441 |    -1.086 |   -0.5243 |   -0.8738 |
-#> |.....................|    -1.092 |   0.01762 |...........|...........|
-#> |    U|     478.97125 |     91.37 |    -5.852 |   -0.9079 |    -2.178 |
-#> |.....................|    -4.833 |    0.3879 |     1.108 |   0.05700 |
-#> |.....................|    0.9012 |    0.7111 |     1.589 |    0.9538 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    X|     478.97125 |     91.37 |  0.002874 |    0.2874 |    0.1133 |
-#> |.....................|  0.007961 |    0.5958 |     1.108 |   0.05700 |
-#> |.....................|    0.9012 |    0.7111 |     1.589 |    0.9538 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    C| Central Diff. |   0.03985 |    0.1039 |    0.1540 |   0.01970 |
-#> |.....................|   0.04056 |    0.3392 |   -0.3415 |   -0.1666 |
-#> |.....................|   -0.1386 |   -0.1574 |   0.08901 |   -0.2003 |
-#> |.....................|  -0.04000 |   -0.1187 |...........|...........|
-#> |  155|     478.97118 |     1.004 |    -1.652 |   -0.9306 |   -0.9153 |
-#> |.....................|    -1.221 |    -1.039 |   -0.2040 |   -0.9252 |
-#> |.....................|   -0.6440 |    -1.086 |   -0.5243 |   -0.8737 |
-#> |.....................|    -1.092 |   0.01765 |...........|...........|
-#> |    U|     478.97118 |     91.37 |    -5.852 |   -0.9080 |    -2.178 |
-#> |.....................|    -4.833 |    0.3878 |     1.108 |   0.05700 |
-#> |.....................|    0.9012 |    0.7112 |     1.589 |    0.9538 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    X|     478.97118 |     91.37 |  0.002874 |    0.2874 |    0.1133 |
-#> |.....................|  0.007961 |    0.5958 |     1.108 |   0.05700 |
-#> |.....................|    0.9012 |    0.7112 |     1.589 |    0.9538 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    C| Central Diff. |  -0.05720 |    0.1036 |    0.1507 |   0.01972 |
-#> |.....................|   0.04048 |    0.3375 |   -0.2940 |   -0.1684 |
-#> |.....................|   -0.1979 |    -1.920 |    0.1339 |   -0.2027 |
-#> |.....................|  -0.04399 |   -0.1216 |...........|...........|
-#> |  156|     478.97118 |     1.004 |    -1.652 |   -0.9306 |   -0.9153 |
-#> |.....................|    -1.221 |    -1.039 |   -0.2040 |   -0.9252 |
-#> |.....................|   -0.6440 |    -1.086 |   -0.5243 |   -0.8737 |
-#> |.....................|    -1.092 |   0.01765 |...........|...........|
-#> |    U|     478.97118 |     91.37 |    -5.852 |   -0.9080 |    -2.178 |
-#> |.....................|    -4.833 |    0.3878 |     1.108 |   0.05700 |
-#> |.....................|    0.9012 |    0.7112 |     1.589 |    0.9538 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> |    X|     478.97118 |     91.37 |  0.002874 |    0.2874 |    0.1133 |
-#> |.....................|  0.007961 |    0.5958 |     1.108 |   0.05700 |
-#> |.....................|    0.9012 |    0.7112 |     1.589 |    0.9538 |
-#> |.....................|    0.6749 |     2.288 |...........|...........|
-#> calculating covariance matrix
-#> done
-#> Calculating residuals/tables
-#> done
-
-# Two-component error by variable is possible with both estimation methods
-# Variance by variable is supported by 'saem' and 'focei'
-f_nlmixr_fomc_sfo_saem_obs_tc <- nlmixr(f_mmkin_tc["FOMC-SFO", ], est = "saem",
-  error_model = "obs_tc")
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#>  
-#> 1:    92.0624   -5.2854    0.1952    1.9494   -1.9431    2.8500    1.6150    0.7315    0.7220    0.4370    6.8425    0.4265    7.3797    0.5659
-#> 2:    92.7371   -5.3819    0.0345    2.0839   -2.0310    2.7075    1.5342    0.6949    0.8358    0.4151    7.2043    0.0003    8.1096    0.0003
-#> 3:    9.2941e+01  -5.7880e+00   1.0336e-01   2.5772e+00  -1.5152e+00   2.5721e+00   1.4575e+00   6.6018e-01   7.9403e-01   3.9439e-01   4.5749e+00   1.5986e-05   5.1354e+00   2.8796e-05
-#> 4:    92.6277   -5.8599    0.0858    2.5068   -1.3253    2.4435    1.3847    0.6272    0.7543    0.3747    3.4165    0.0001    3.9071    0.0016
-#> 5:    93.0289   -6.0258    0.0528    2.4932   -1.1961    2.3213    1.3154    0.5958    0.7166    0.3559    3.2552    0.0069    3.3744    0.0170
-#> 6:    93.2107   -6.2881    0.0143    2.4052   -1.1930    2.2053    2.2853    0.5660    0.6808    0.3381    2.8020    0.0086    3.1436    0.0256
-#> 7:    93.0563   -6.3624   -0.0104    2.3989   -1.1521    2.0950    2.4414    0.5377    0.6467    0.3212    2.6528    0.0209    2.8462    0.0289
-#> 8:    93.0567   -6.2699   -0.0303    2.3700   -1.0941    1.9903    2.5004    0.5204    0.6144    0.3052    2.3448    0.0314    2.5026    0.0349
-#> 9:    92.8366   -6.2013   -0.0507    2.3798   -1.0963    1.8907    2.6552    0.4943    0.5837    0.2899    2.2219    0.0368    2.2604    0.0448
-#> 10:    92.9069   -6.2499   -0.1116    2.3100   -1.0557    1.9625    3.9231    0.4696    0.5545    0.2754    2.0980    0.0359    2.1413    0.0325
-#> 11:    92.9942   -6.2134   -0.1037    2.3109   -1.0441    1.8643    3.7270    0.4755    0.5268    0.2616    1.9711    0.0372    1.9901    0.0355
-#> 12:    92.9262   -6.2511   -0.1133    2.2707   -1.0465    1.8430    4.3304    0.4697    0.5004    0.2486    1.8083    0.0346    1.9184    0.0356
-#> 13:    93.0761   -6.3559   -0.1106    2.2534   -1.0162    2.4826    5.2857    0.4685    0.4754    0.2361    1.7896    0.0331    1.9865    0.0342
-#> 14:    93.0929   -6.1852   -0.1058    2.2972   -1.0175    2.9964    5.0214    0.4451    0.4516    0.2243    1.8316    0.0309    1.9112    0.0348
-#> 15:    93.3343   -6.3408   -0.1025    2.2905   -0.9962    3.1132    4.9630    0.4594    0.4291    0.2131    1.8198    0.0338    1.9154    0.0372
-#> 16:    92.9959   -6.2227   -0.1016    2.2869   -1.0103    3.3338    4.7149    0.4598    0.4076    0.2025    1.8726    0.0327    1.9617    0.0361
-#> 17:    93.0394   -6.2586   -0.1027    2.2932   -0.9991    3.1671    4.8730    0.4591    0.3872    0.1923    1.8405    0.0336    2.0192    0.0242
-#> 18:    93.2374   -6.3410   -0.1110    2.2965   -0.9689    3.0087    5.4325    0.4632    0.3679    0.1827    1.9051    0.0351    1.9247    0.0277
-#> 19:    93.0557   -6.4503   -0.1011    2.2941   -0.9884    2.8583    6.2872    0.4742    0.3495    0.1736    1.8054    0.0345    1.9173    0.0260
-#> 20:    92.9280   -6.4945   -0.1018    2.2902   -0.9864    3.5934    6.8737    0.4751    0.3320    0.1649    1.7097    0.0372    1.9483    0.0225
-#> 21:    93.2023   -6.3418   -0.1033    2.2846   -0.9863    3.4138    6.5300    0.4710    0.3154    0.1567    1.7507    0.0318    1.9030    0.0249
-#> 22:    93.5494   -6.1985   -0.1078    2.2991   -1.0171    3.2431    6.2035    0.4475    0.2996    0.1488    1.7370    0.0342    1.8124    0.0282
-#> 23:    93.3588   -6.2577   -0.1084    2.2654   -0.9956    3.0809    5.8933    0.4393    0.2869    0.1481    1.6928    0.0380    1.8288    0.0254
-#> 24:    93.5705   -6.4876   -0.1083    2.2606   -1.0062    3.7095    6.7801    0.4459    0.2726    0.1684    1.7001    0.0377    1.9012    0.0249
-#> 25:    93.9726   -6.5638   -0.1239    2.2374   -1.0071    5.1357    6.6571    0.4608    0.2755    0.1600    1.6615    0.0382    1.8846    0.0213
-#> 26:    93.8894   -6.5073   -0.1120    2.2645   -1.0327    4.8789    6.3243    0.4473    0.3014    0.1520    1.7152    0.0340    1.8990    0.0254
-#> 27:    94.5348   -6.3868   -0.0891    2.3139   -1.0361    5.3856    6.0081    0.4250    0.3080    0.1453    1.7028    0.0385    1.7853    0.0304
-#> 28:    93.9221   -6.1747   -0.1039    2.3013   -1.0087    5.1163    5.7077    0.4214    0.3136    0.1634    1.6823    0.0340    1.7487    0.0353
-#> 29:    93.4946   -6.0264   -0.0940    2.3124   -1.0166    5.3744    5.4223    0.4404    0.3114    0.1813    1.6310    0.0370    1.7646    0.0367
-#> 30:    93.9287   -5.9114   -0.0967    2.3078   -1.0090    5.2017    5.1512    0.4381    0.3048    0.2091    1.5825    0.0393    1.7431    0.0312
-#> 31:    93.7065   -6.0174   -0.0928    2.2917   -0.9880    5.1935    4.8936    0.4352    0.3109    0.1986    1.5876    0.0392    1.8465    0.0280
-#> 32:    93.7675   -5.6444   -0.0918    2.3145   -0.9664    4.9338    4.6489    0.4332    0.3090    0.1918    1.6874    0.0332    1.7501    0.0331
-#> 33:    94.2589   -5.7637   -0.0865    2.3130   -0.9733    4.6871    4.4165    0.4235    0.2935    0.1865    1.7173    0.0355    1.7365    0.0334
-#> 34:    94.0788   -5.7432   -0.1022    2.3049   -0.9681    4.4528    4.1957    0.4319    0.2962    0.1772    1.6357    0.0361    1.4755    0.0574
-#> 35:    94.0798   -5.8549   -0.0929    2.2856   -0.9849    4.2301    3.9859    0.4391    0.2937    0.1734    1.6460    0.0275    1.7739    0.0379
-#> 36:    93.9997   -5.8708   -0.0890    2.2870   -1.0134    4.0186    3.7866    0.4268    0.2819    0.1840    1.5830    0.0258    1.8922    0.0320
-#> 37:    93.8186   -5.8979   -0.0973    2.2807   -1.0197    3.8177    3.5973    0.4280    0.2778    0.1799    1.5783    0.0282    1.7697    0.0404
-#> 38:    94.0728   -5.9601   -0.0936    2.3011   -1.0381    3.6268    3.4174    0.4186    0.2944    0.1864    1.5780    0.0294    1.5210    0.0558
-#> 39:    94.0504   -5.8302   -0.0995    2.2847   -1.0418    3.4455    3.2465    0.4240    0.2796    0.1771    1.6888    0.0242    1.7744    0.0366
-#> 40:    93.8918   -5.9418   -0.0988    2.2925   -1.0613    3.2732    3.0842    0.4144    0.2672    0.1837    1.7275    0.0232    1.7840    0.0357
-#> 41:    93.7961   -6.0741   -0.0896    2.2932   -1.0359    3.1095    3.2890    0.4236    0.2606    0.1782    1.7591    0.0212    1.8920    0.0273
-#> 42:    93.9458   -6.0319   -0.0909    2.3114   -1.0281    3.0544    3.1246    0.4196    0.2598    0.1839    1.6854    0.0310    1.7586    0.0308
-#> 43:    93.7623   -6.0165   -0.1056    2.2837   -1.0378    3.9092    3.2100    0.4298    0.2468    0.1747    1.7064    0.0286    1.6676    0.0397
-#> 44:    93.4300   -5.9019   -0.1114    2.2716   -1.0167    4.4100    3.0495    0.4476    0.2345    0.1687    1.7989    0.0253    1.7741    0.0299
-#> 45:    93.3475   -5.9962   -0.1231    2.2546   -1.0007    6.4879    3.3965    0.4528    0.2452    0.1602    1.7283    0.0276    1.7219    0.0379
-#> 46:    93.3100   -6.0073   -0.1255    2.2483   -0.9962    6.6009    3.5942    0.4520    0.2533    0.1568    1.6991    0.0258    1.1783    0.0706
-#> 47:    93.4422   -5.8442   -0.1286    2.2578   -0.9819    6.2709    3.4145    0.4492    0.2637    0.1694    1.6754    0.0317    1.3442    0.0599
-#> 48:    93.0996   -5.5881   -0.1307    2.2541   -0.9882    5.9573    3.2438    0.4480    0.2665    0.1695    1.7040    0.0285    1.6825    0.0426
-#> 49:    93.3649   -5.8011   -0.1260    2.2595   -0.9704    5.7230    3.0816    0.4399    0.2646    0.1715    1.6544    0.0297    1.6414    0.0418
-#> 50:    93.9331   -5.8731   -0.1195    2.2615   -0.9837    5.4368    2.9275    0.4453    0.2735    0.1940    1.6316    0.0289    1.6885    0.0392
-#> 51:    93.6092   -5.8721   -0.1237    2.2599   -1.0015    5.1650    2.7811    0.4413    0.2865    0.1939    1.6492    0.0272    1.7686    0.0358
-#> 52:    93.3008   -5.9775   -0.1277    2.2628   -0.9962    4.9067    3.1139    0.4438    0.2946    0.1963    1.5642    0.0337    1.7391    0.0335
-#> 53:    93.6347   -6.0805   -0.1189    2.2663   -1.0177    4.6614    3.5169    0.4335    0.2962    0.2043    1.5275    0.0343    1.7417    0.0366
-#> 54:    93.5781   -6.0412   -0.1166    2.2573   -1.0015    4.4283    3.3411    0.4395    0.2912    0.2080    1.5464    0.0346    1.7584    0.0359
-#> 55:    93.9675   -6.0867   -0.0952    2.2970   -0.9987    4.2069    3.6762    0.4550    0.2780    0.1988    1.5138    0.0405    1.6251    0.0472
-#> 56:    94.4069   -6.1375   -0.0943    2.2975   -1.0190    3.9966    4.2280    0.4550    0.2806    0.1945    1.5294    0.0425    1.6443    0.0468
-#> 57:    93.8076   -6.1618   -0.0936    2.2687   -1.0237    3.7967    4.3085    0.4524    0.2666    0.1897    1.5227    0.0414    1.6955    0.0438
-#> 58:    93.9188   -6.2272   -0.0947    2.2767   -1.0408    3.6069    4.6707    0.4536    0.2676    0.1873    1.5201    0.0425    1.5336    0.0550
-#> 59:    93.9572   -6.3460   -0.1074    2.2746   -1.0069    3.4266    5.8058    0.4614    0.2718    0.1919    1.5533    0.0417    1.6227    0.0460
-#> 60:    93.5430   -6.1622   -0.1048    2.2861   -0.9959    3.2552    5.5155    0.4535    0.2848    0.1823    1.4745    0.0431    1.5242    0.0522
-#> 61:    93.8016   -6.4079   -0.1065    2.2897   -1.0325    3.0925    5.9252    0.4583    0.2901    0.1732    1.5364    0.0365    1.4623    0.0550
-#> 62:    93.4249   -6.2284   -0.0967    2.3126   -1.0208    2.9378    5.6289    0.4429    0.2756    0.1645    1.6111    0.0325    1.3996    0.0618
-#> 63:    93.2335   -6.0996   -0.1051    2.3047   -0.9976    2.7909    5.3475    0.4292    0.2719    0.1633    1.6010    0.0326    1.5115    0.0494
-#> 64:    92.7091   -6.1109   -0.1041    2.3032   -0.9746    3.2610    5.0801    0.4301    0.2793    0.1751    1.5979    0.0302    1.3867    0.0575
-#> 65:    92.6059   -6.0049   -0.1077    2.3062   -0.9853    3.0979    4.8261    0.4316    0.2826    0.1714    1.6357    0.0272    1.3931    0.0543
-#> 66:    92.7778   -6.0856   -0.1040    2.3057   -0.9828    2.9430    4.5848    0.4362    0.2888    0.1628    1.6126    0.0316    1.4340    0.0505
-#> 67:    93.0325   -6.1775   -0.1085    2.3122   -0.9714    2.7959    4.3790    0.4464    0.2843    0.1547    1.6090    0.0354    1.4966    0.0448
-#> 68:    92.8987   -5.8741   -0.1089    2.3184   -0.9567    2.6561    4.1601    0.4389    0.2866    0.1470    1.5888    0.0347    1.4492    0.0507
-#> 69:    92.7300   -6.0473   -0.1070    2.3082   -0.9739    2.5233    4.0183    0.4371    0.3158    0.1527    1.5904    0.0298    1.5387    0.0477
-#> 70:    92.5285   -6.0962   -0.1115    2.3179   -0.9785    2.4856    4.0612    0.4380    0.3059    0.1504    1.5237    0.0402    1.4541    0.0463
-#> 71:    92.3975   -6.2090   -0.1269    2.2819   -0.9713    2.3613    4.3811    0.4173    0.2906    0.1520    1.5388    0.0316    1.3713    0.0584
-#> 72:    92.1593   -6.2214   -0.1217    2.2950   -0.9481    2.2433    5.1205    0.4227    0.2760    0.1605    1.5431    0.0312    1.5797    0.0459
-#> 73:    92.1195   -6.6667   -0.1244    2.3076   -0.9642    2.1311    7.6538    0.4124    0.2622    0.1525    1.4505    0.0375    1.2810    0.0595
-#> 74:    92.2191   -6.6665   -0.1278    2.2989   -0.9703    2.0246    7.2711    0.4098    0.2491    0.1666    1.4309    0.0384    1.2717    0.0638
-#> 75:    92.4656   -6.8881   -0.1274    2.3011   -0.9595    1.9233    8.3835    0.4147    0.2367    0.1656    1.4181    0.0424    1.2498    0.0620
-#> 76:    92.4593   -6.2323   -0.1203    2.2912   -0.9799    1.8272    7.9643    0.3967    0.2301    0.1596    1.5448    0.0336    1.6758    0.0359
-#> 77:    92.4501   -6.1123   -0.1219    2.2889   -0.9426    1.7358    7.5661    0.4049    0.2299    0.1594    1.5380    0.0327    1.6947    0.0364
-#> 78:    92.5059   -6.0339   -0.1198    2.2985   -0.9544    1.6490    7.1878    0.4007    0.2422    0.1568    1.5722    0.0302    1.5665    0.0415
-#> 79:    92.4302   -6.6428   -0.1141    2.3119   -0.9421    1.5666    9.0889    0.3986    0.2340    0.1489    1.5029    0.0306    1.1894    0.0638
-#> 80:    92.5305   -6.3036   -0.1127    2.3099   -0.9406    1.9062    8.6344    0.4091    0.2327    0.1648    1.5558    0.0308    1.0136    0.0749
-#> 81:    92.6652   -6.0832   -0.1167    2.2994   -0.9552    2.3641    8.2027    0.4142    0.2348    0.1566    1.6232    0.0300    1.1320    0.0712
-#> 82:    92.5109   -6.1524   -0.1100    2.3037   -0.9686    2.2459    7.7926    0.4145    0.2381    0.1695    1.6128    0.0306    1.6145    0.0413
-#> 83:    92.6455   -6.3979   -0.1059    2.3245   -0.9573    2.1336    8.1077    0.4060    0.2348    0.1667    1.6039    0.0304    1.6251    0.0419
-#> 84:    92.5768   -6.3469   -0.0979    2.3177   -0.9346    2.0269    8.2125    0.4141    0.2439    0.1720    1.6334    0.0302    1.5803    0.0450
-#> 85:    92.7920   -6.3536   -0.0969    2.3363   -0.9389    1.9256    8.1820    0.4035    0.2512    0.1713    1.5815    0.0338    1.1193    0.0719
-#> 86:    92.8571   -6.2567   -0.0911    2.3426   -0.9633    1.8293    8.1211    0.4008    0.2659    0.1627    1.5840    0.0356    1.2425    0.0639
-#> 87:    92.9101   -6.1557   -0.0937    2.3326   -0.9624    1.7378    7.7151    0.3950    0.2839    0.1546    1.6017    0.0354    1.0600    0.0766
-#> 88:    92.7649   -6.2151   -0.0881    2.3275   -0.9967    1.6509    7.3293    0.4046    0.2697    0.1469    1.6092    0.0302    1.1839    0.0693
-#> 89:    92.9350   -5.9222   -0.0903    2.3372   -0.9612    1.5684    6.9628    0.4058    0.2818    0.1395    1.5957    0.0335    1.5450    0.0444
-#> 90:    92.7895   -5.9348   -0.0890    2.3457   -0.9601    1.4900    6.6147    0.4070    0.2705    0.1430    1.5716    0.0378    1.4918    0.0439
-#> 91:    93.0113   -5.9302   -0.0997    2.3316   -0.9489    1.4155    6.2840    0.4424    0.2929    0.1410    1.5582    0.0377    1.2459    0.0582
-#> 92:    92.8603   -6.3366   -0.0918    2.3356   -0.9938    1.3447    5.9698    0.4287    0.2929    0.1531    1.4906    0.0398    1.2421    0.0605
-#> 93:    92.8094   -6.1097   -0.0953    2.3382   -0.9996    1.2775    5.6713    0.4309    0.2783    0.1597    1.4317    0.0468    1.2694    0.0584
-#> 94:    92.7100   -6.1043   -0.0909    2.3287   -0.9928    1.3828    5.3877    0.4337    0.2698    0.1517    1.4173    0.0489    1.4335    0.0476
-#> 95:    92.2055   -6.1792   -0.0889    2.3553   -0.9983    1.3137    5.1183    0.4209    0.3273    0.1566    1.4865    0.0417    1.2485    0.0681
-#> 96:    92.3225   -6.2710   -0.0811    2.3734   -1.0043    1.3428    4.8624    0.4121    0.3110    0.1532    1.5817    0.0374    1.5209    0.0532
-#> 97:    92.2983   -6.3023   -0.0776    2.3615   -0.9801    1.2757    4.6193    0.4221    0.3018    0.1455    1.5971    0.0337    1.2137    0.0719
-#> 98:    92.1433   -6.3114   -0.0935    2.3269   -0.9866    1.2227    4.8121    0.4327    0.2907    0.1694    1.5524    0.0303    1.1779    0.0727
-#> 99:    92.1631   -6.3090   -0.0908    2.3197   -0.9891    1.1615    4.9271    0.4169    0.2859    0.1736    1.5303    0.0334    1.6227    0.0511
-#> 100:    92.1185   -6.3603   -0.0950    2.3280   -1.0209    1.1035    5.0957    0.4213    0.2924    0.1817    1.5991    0.0330    1.7197    0.0445
-#> 101:    92.3964   -6.0447   -0.0898    2.3347   -1.0164    1.0483    4.8409    0.4251    0.2778    0.1727    1.5708    0.0422    1.6197    0.0461
-#> 102:    92.6597   -6.2545   -0.0954    2.3264   -1.0206    0.9959    4.5989    0.4218    0.2736    0.1640    1.5853    0.0408    1.5912    0.0455
-#> 103:    92.7866   -6.3292   -0.0933    2.3148   -1.0013    0.9461    4.8935    0.4234    0.2599    0.1688    1.6299    0.0399    1.5921    0.0445
-#> 104:    92.8098   -6.2608   -0.1009    2.3014   -0.9947    0.8988    4.7750    0.4306    0.2548    0.1813    1.6363    0.0378    1.6713    0.0427
-#> 105:    92.8300   -5.9827   -0.1028    2.3155   -0.9896    0.8538    4.5362    0.4339    0.2664    0.1722    1.6079    0.0397    1.3691    0.0573
-#> 106:    92.8218   -6.1138   -0.1024    2.3462   -0.9750    0.8299    4.3094    0.4494    0.2530    0.1636    1.5761    0.0389    1.2857    0.0595
-#> 107:    92.9304   -6.0063   -0.1002    2.3269   -0.9778    0.7884    4.0939    0.4600    0.2404    0.1620    1.6499    0.0373    1.2101    0.0675
-#> 108:    92.9072   -6.0928   -0.0991    2.3183   -0.9732    0.7489    4.4394    0.4584    0.2518    0.1539    1.6509    0.0332    1.2346    0.0670
-#> 109:    92.7504   -6.1545   -0.0862    2.3423   -0.9618    0.7115    4.7501    0.4371    0.2766    0.1465    1.5755    0.0349    1.1552    0.0701
-#> 110:    92.9277   -6.3786   -0.0904    2.3468   -0.9402    0.6759    5.8620    0.4328    0.2821    0.1703    1.4661    0.0439    1.3292    0.0609
-#> 111:    92.8023   -5.8686   -0.0886    2.3653   -0.9417    0.7635    5.5689    0.4288    0.2680    0.1618    1.4278    0.0502    1.4715    0.0468
-#> 112:    92.9411   -5.8095   -0.0883    2.3625   -0.9322    0.8592    5.2905    0.4562    0.2586    0.1537    1.3920    0.0513    1.1766    0.0648
-#> 113:    92.9845   -6.0499   -0.0761    2.3626   -0.9533    0.8163    5.0259    0.4403    0.2595    0.1532    1.4306    0.0450    1.1416    0.0645
-#> 114:    92.7735   -6.0605   -0.0694    2.3497   -0.9646    0.7754    4.7746    0.4394    0.2682    0.1576    1.4866    0.0344    1.1127    0.0745
-#> 115:    92.7048   -6.1327   -0.0702    2.3427   -0.9910    0.7367    4.5359    0.4257    0.2736    0.1497    1.5045    0.0413    1.2783    0.0677
-#> 116:    92.7131   -6.0115   -0.0751    2.3370   -0.9899    0.6998    4.3091    0.4187    0.2638    0.1422    1.6036    0.0325    1.1109    0.0748
-#> 117:    92.7720   -5.9163   -0.0709    2.3503   -0.9566    0.6648    4.0937    0.4185    0.2555    0.1417    1.6016    0.0297    1.0778    0.0774
-#> 118:    92.9182   -5.9312   -0.0812    2.3436   -0.9731    0.6316    3.8890    0.4084    0.2667    0.1400    1.5698    0.0320    1.2364    0.0665
-#> 119:    92.9546   -5.9622   -0.0870    2.3330   -0.9934    0.6000    3.6945    0.4035    0.2867    0.1486    1.5364    0.0343    1.5892    0.0489
-#> 120:    92.9168   -6.0966   -0.0905    2.3301   -1.0045    0.5700    3.6677    0.3988    0.2871    0.1567    1.5378    0.0349    1.0886    0.0796
-#> 121:    92.7767   -6.1038   -0.0802    2.3396   -0.9815    0.5981    4.3032    0.3803    0.2884    0.1684    1.4788    0.0335    1.0886    0.0796
-#> 122:    92.8439   -6.2425   -0.0799    2.3323   -0.9987    0.6537    4.5745    0.3884    0.2834    0.1600    1.4786    0.0346    1.2146    0.0682
-#> 123:    92.8219   -5.7869   -0.0872    2.3478   -0.9619    0.7886    4.3458    0.3951    0.2887    0.1658    1.4827    0.0341    1.3911    0.0559
-#> 124:    92.7930   -5.7551   -0.0819    2.3559   -0.9809    0.8922    4.1285    0.3907    0.2972    0.1575    1.5329    0.0330    1.3824    0.0594
-#> 125:    92.7488   -5.9406   -0.0819    2.3550   -0.9797    0.8476    3.9221    0.3907    0.2996    0.1733    1.5096    0.0333    1.3148    0.0667
-#> 126:    92.7926   -5.7106   -0.0824    2.3560   -0.9653    0.8052    3.7260    0.3918    0.3018    0.1854    1.4237    0.0381    1.2607    0.0639
-#> 127:    92.9153   -5.6682   -0.0717    2.3654   -0.9645    0.7649    3.5397    0.3722    0.2948    0.1784    1.4679    0.0415    1.2310    0.0695
-#> 128:    92.8827   -5.7984   -0.0783    2.3813   -1.0047    1.1012    3.3627    0.3802    0.2997    0.1694    1.5187    0.0442    1.2884    0.0649
-#> 129:    92.8727   -5.7191   -0.0785    2.3426   -0.9857    1.0461    3.1946    0.3784    0.2984    0.1610    1.4757    0.0398    1.1695    0.0775
-#> 130:    92.8689   -5.8036   -0.0935    2.3123   -0.9783    0.9938    3.0348    0.4184    0.2980    0.1723    1.5143    0.0319    1.2298    0.0738
-#> 131:    92.8733   -5.6707   -0.0988    2.3045   -0.9936    1.3313    2.8831    0.4277    0.2831    0.1816    1.5919    0.0329    1.5260    0.0533
-#> 132:    92.5761   -5.7773   -0.0925    2.3211   -0.9661    1.2647    2.7389    0.4216    0.2815    0.1995    1.5306    0.0321    1.5863    0.0520
-#> 133:    92.4512   -5.7800   -0.0920    2.3269   -0.9625    1.2015    2.6020    0.4242    0.2674    0.1955    1.5669    0.0288    1.4087    0.0606
-#> 134:    92.5625   -5.7968   -0.0965    2.3271   -0.9728    1.1414    2.4719    0.4201    0.2753    0.1945    1.5935    0.0311    1.5348    0.0534
-#> 135:    92.3448   -5.6624   -0.0961    2.3303   -0.9600    1.0843    2.3483    0.4193    0.2728    0.1983    1.6245    0.0305    1.6281    0.0506
-#> 136:    92.3407   -5.7523   -0.0932    2.3208   -0.9897    1.0301    2.3267    0.4107    0.2668    0.1884    1.5933    0.0358    1.2970    0.0657
-#> 137:    92.3940   -6.0148   -0.1046    2.2981   -0.9866    0.9786    3.1382    0.4166    0.3012    0.1790    1.5077    0.0385    1.1944    0.0723
-#> 138:    92.3556   -5.9912   -0.1039    2.2969   -0.9920    0.9297    3.2144    0.4208    0.3039    0.1703    1.5042    0.0378    1.2588    0.0717
-#> 139:    92.5548   -5.9253   -0.1177    2.2723   -1.0079    0.8832    3.2648    0.4049    0.3263    0.1618    1.5558    0.0382    1.2673    0.0698
-#> 140:    92.6546   -6.0596   -0.1368    2.2659   -0.9922    0.8390    3.3893    0.3846    0.3100    0.1537    1.5475    0.0355    1.3190    0.0629
-#> 141:    92.6661   -5.9744   -0.1379    2.2793   -0.9754    0.8287    3.2725    0.3800    0.3178    0.1528    1.5076    0.0361    1.4087    0.0540
-#> 142:    92.5681   -5.7650   -0.1033    2.3249   -0.9613    0.7872    3.1089    0.3610    0.3564    0.1701    1.4733    0.0332    1.2603    0.0720
-#> 143:    92.4184   -5.6070   -0.1033    2.3520   -0.9764    0.7479    2.9534    0.3591    0.3758    0.1674    1.5420    0.0390    1.3280    0.0614
-#> 144:    92.5354   -5.6144   -0.0978    2.3801   -0.9425    0.7105    2.8058    0.3538    0.3606    0.1722    1.4884    0.0400    1.3455    0.0620
-#> 145:    92.4207   -5.6541   -0.0746    2.3873   -0.9633    0.6750    2.6655    0.3361    0.3426    0.1718    1.4981    0.0416    1.2440    0.0685
-#> 146:    92.3058   -5.6608   -0.0731    2.3755   -0.9732    0.6412    2.5322    0.3193    0.3304    0.1719    1.6391    0.0348    1.1788    0.0743
-#> 147:    92.4067   -5.7615   -0.0746    2.3775   -0.9903    0.6091    2.4056    0.3148    0.3311    0.1709    1.6695    0.0314    1.2931    0.0676
-#> 148:    92.3739   -5.8812   -0.0820    2.3644   -0.9823    0.5787    2.7260    0.3332    0.3296    0.1794    1.6168    0.0303    1.3206    0.0670
-#> 149:    92.4456   -5.8277   -0.0921    2.3508   -0.9924    0.5498    2.8750    0.3368    0.3305    0.1917    1.5602    0.0302    1.3622    0.0608
-#> 150:    92.5049   -5.7964   -0.1003    2.3353   -0.9809    0.5223    2.7312    0.3291    0.3634    0.1874    1.5035    0.0301    1.4002    0.0615
-#> 151:    92.3292   -6.0377   -0.1039    2.3301   -0.9866    0.4962    3.3342    0.3348    0.3626    0.1780    1.4819    0.0298    1.3217    0.0672
-#> 152:    92.3747   -6.0460   -0.1023    2.3154   -1.0242    0.5079    3.4530    0.3371    0.3518    0.1674    1.6034    0.0296    1.2304    0.0749
-#> 153:    92.3909   -5.8707   -0.1008    2.3284   -0.9897    0.5623    2.8180    0.3480    0.3792    0.1749    1.4953    0.0291    1.3442    0.0677
-#> 154:    92.2532   -5.9313   -0.0991    2.3232   -0.9839    0.5340    3.3946    0.3502    0.3723    0.1729    1.4837    0.0280    1.1452    0.0776
-#> 155:    92.1782   -6.1012   -0.0988    2.3339   -0.9600    0.3900    3.9676    0.3593    0.3704    0.1531    1.4927    0.0286    1.1848    0.0730
-#> 156:    92.2225   -5.8387   -0.0991    2.3393   -0.9459    0.3294    3.0685    0.3598    0.3808    0.1568    1.5540    0.0318    1.3419    0.0671
-#> 157:    92.2411   -5.7045   -0.1038    2.3578   -0.9252    0.2797    2.5238    0.3716    0.3579    0.1653    1.4704    0.0373    1.1959    0.0686
-#> 158:    92.2865   -5.6692   -0.1009    2.3771   -0.9532    0.2840    2.4144    0.3592    0.3610    0.1641    1.5065    0.0389    1.1780    0.0674
-#> 159:    92.2771   -5.7526   -0.0782    2.3632   -0.9771    0.2996    2.7295    0.3357    0.3779    0.1606    1.5818    0.0366    1.1512    0.0781
-#> 160:    92.3400   -5.8039   -0.0811    2.3615   -0.9453    0.2707    2.7305    0.3373    0.3834    0.1528    1.4765    0.0370    1.1427    0.0756
-#> 161:    92.4180   -5.7448   -0.0961    2.3653   -0.9508    0.2965    2.6051    0.3666    0.3833    0.1647    1.4581    0.0364    0.9817    0.0827
-#> 162:    92.4487   -5.8952   -0.0889    2.3460   -0.9646    0.2370    3.1413    0.3460    0.3801    0.1571    1.4528    0.0346    1.0006    0.0798
-#> 163:    92.5251   -5.8567   -0.0987    2.3342   -0.9615    0.1453    2.9917    0.3535    0.3735    0.1452    1.4521    0.0330    1.0498    0.0766
-#> 164:    92.5949   -6.1580   -0.1008    2.3332   -0.9749    0.1095    4.1797    0.3586    0.3767    0.1355    1.4659    0.0310    1.0218    0.0797
-#> 165:    92.5794   -6.0542   -0.1001    2.3321   -0.9795    0.1332    4.2924    0.3588    0.3752    0.1386    1.4858    0.0313    0.9836    0.0812
-#> 166:    92.6686   -6.0065   -0.0960    2.3623   -0.9532    0.1465    4.0810    0.3439    0.3683    0.1647    1.3929    0.0372    0.9354    0.0837
-#> 167:    92.7086   -6.2096   -0.0895    2.3656   -0.9552    0.1938    4.6857    0.3325    0.3519    0.1681    1.4281    0.0362    1.0329    0.0784
-#> 168:    92.6096   -6.0709   -0.0880    2.3595   -0.9474    0.2141    4.1277    0.3379    0.3527    0.1620    1.4264    0.0347    0.9627    0.0836
-#> 169:    92.5365   -5.9418   -0.0919    2.3546   -0.9575    0.3620    3.7767    0.3489    0.3589    0.1609    1.4761    0.0360    1.1348    0.0745
-#> 170:    92.6270   -5.8404   -0.0935    2.3562   -0.9517    0.3312    3.2506    0.3552    0.3607    0.1560    1.4506    0.0383    1.0731    0.0722
-#> 171:    92.5606   -5.9213   -0.0899    2.3513   -0.9554    0.4399    3.5587    0.3599    0.3646    0.1385    1.4779    0.0349    0.9844    0.0775
-#> 172:    92.3630   -5.7066   -0.0765    2.3798   -0.9314    0.5208    2.5578    0.3458    0.3657    0.1547    1.4900    0.0348    1.0485    0.0765
-#> 173:    92.2527   -5.5811   -0.0713    2.4173   -0.9221    0.8674    2.2100    0.3448    0.3370    0.1513    1.5403    0.0445    1.4403    0.0518
-#> 174:    92.3852   -5.5348   -0.0712    2.4066   -0.9033    0.7543    2.1568    0.3457    0.3324    0.1482    1.5322    0.0407    1.2744    0.0623
-#> 175:    92.4798   -5.5494   -0.0712    2.4004   -0.9100    0.5675    2.0147    0.3457    0.3333    0.1629    1.5229    0.0383    1.2917    0.0655
-#> 176:    92.5881   -5.5613   -0.0675    2.4180   -0.9188    0.4011    2.0736    0.3413    0.3487    0.1781    1.5149    0.0389    1.1499    0.0669
-#> 177:    92.6015   -5.4951   -0.0494    2.4324   -0.9525    0.4992    1.9009    0.3629    0.3353    0.1919    1.4881    0.0393    1.2289    0.0650
-#> 178:    92.6317   -5.4943   -0.0505    2.4373   -0.9298    0.5087    1.6116    0.3631    0.3324    0.1906    1.4475    0.0454    1.0764    0.0701
-#> 179:    92.7043   -5.5326   -0.0419    2.4386   -0.9376    0.4350    1.8241    0.3577    0.3757    0.1991    1.4445    0.0424    0.9626    0.0833
-#> 180:    92.7457   -5.5591   -0.0371    2.4684   -0.9450    0.3973    1.7797    0.3507    0.3707    0.1944    1.4392    0.0415    1.0784    0.0764
-#> 181:    92.6287   -5.5741   -0.0368    2.4489   -0.9459    0.4744    1.8016    0.3502    0.3544    0.1970    1.4317    0.0392    0.9225    0.0848
-#> 182:    92.6121   -5.5593   -0.0316    2.4610   -0.9345    0.6054    1.9206    0.3492    0.3538    0.1855    1.4410    0.0367    0.8977    0.0878
-#> 183:    92.4258   -5.4737   -0.0393    2.4592   -0.9319    0.8062    1.7845    0.3528    0.3544    0.1649    1.4545    0.0409    1.0723    0.0751
-#> 184:    92.3939   -5.5961   -0.0479    2.4268   -0.9435    1.0246    2.2534    0.3497    0.3289    0.1363    1.5022    0.0370    1.1058    0.0729
-#> 185:    92.4673   -5.5415   -0.0525    2.4157   -0.9058    0.8296    2.2848    0.3406    0.3314    0.1706    1.4935    0.0367    1.1362    0.0722
-#> 186:    92.4122   -5.6594   -0.0574    2.4466   -0.9430    0.9133    2.3350    0.3327    0.3596    0.1506    1.4450    0.0404    1.2273    0.0629
-#> 187:    92.5416   -5.5472   -0.0521    2.4393   -0.9261    0.9731    1.9228    0.3208    0.3673    0.1421    1.4890    0.0409    1.2553    0.0626
-#> 188:    92.5502   -5.6425   -0.0591    2.4345   -0.9246    0.9315    2.2041    0.3184    0.3639    0.1319    1.4896    0.0392    1.0986    0.0684
-#> 189:    92.4180   -5.6737   -0.0504    2.4448   -0.9191    0.9006    2.4647    0.3102    0.3743    0.1648    1.4649    0.0397    1.1320    0.0742
-#> 190:    92.5821   -5.5823   -0.0363    2.4588   -0.9205    0.9862    2.2692    0.2820    0.4087    0.1459    1.3938    0.0412    0.9562    0.0815
-#> 191:    92.3708   -5.5825   -0.0418    2.4621   -0.9231    0.9867    2.4743    0.2890    0.4196    0.1445    1.4619    0.0403    0.9630    0.0811
-#> 192:    92.2628   -5.5337   -0.0366    2.4392   -0.9194    0.6944    2.2771    0.2909    0.4169    0.1279    1.4745    0.0363    0.8601    0.0892
-#> 193:    92.4854   -5.6303   -0.0352    2.4484   -0.9316    0.4403    2.3253    0.2928    0.4109    0.1282    1.4768    0.0399    0.8886    0.0871
-#> 194:    92.4900   -5.5824   -0.0372    2.4648   -0.9451    0.4891    2.6428    0.2899    0.4160    0.1331    1.5124    0.0412    0.9340    0.0853
-#> 195:    92.4685   -5.7658   -0.0357    2.4659   -0.9217    0.4549    3.3767    0.2921    0.4171    0.1552    1.5062    0.0396    1.0336    0.0817
-#> 196:    92.4125   -5.7544   -0.0255    2.4834   -0.9230    0.4146    3.1963    0.3000    0.4369    0.1501    1.4560    0.0430    0.9942    0.0813
-#> 197:    92.3284   -5.9347   -0.0305    2.4860   -0.9448    0.4115    3.5642    0.3129    0.4314    0.1740    1.3441    0.0473    1.0954    0.0723
-#> 198:    92.3428   -5.9255   -0.0266    2.4822   -0.9463    0.3258    3.4818    0.3185    0.4163    0.1716    1.3868    0.0447    0.9452    0.0788
-#> 199:    92.1692   -6.0683   -0.0227    2.4860   -0.9495    0.2685    4.4044    0.3149    0.4064    0.1824    1.3558    0.0478    1.0294    0.0749
-#> 200:    92.0965   -6.1541   -0.0261    2.4793   -0.9288    0.2210    4.4026    0.3265    0.4200    0.1772    1.3348    0.0441    1.0018    0.0761
-#> 201:    92.1362   -6.1170   -0.0244    2.4776   -0.9237    0.1801    4.4160    0.3276    0.4303    0.1732    1.3479    0.0418    0.9419    0.0809
-#> 202:    92.1114   -6.0898   -0.0233    2.4862   -0.9253    0.1506    4.4494    0.3286    0.4305    0.1656    1.3473    0.0440    0.9394    0.0802
-#> 203:    92.0893   -6.1307   -0.0233    2.4894   -0.9258    0.1510    4.7958    0.3310    0.4233    0.1673    1.3396    0.0457    0.9617    0.0788
-#> 204:    92.0870   -6.0914   -0.0230    2.4867   -0.9234    0.1589    4.6265    0.3316    0.4237    0.1643    1.3478    0.0456    0.9509    0.0793
-#> 205:    92.0800   -6.0960   -0.0228    2.4867   -0.9256    0.1613    4.6319    0.3321    0.4226    0.1623    1.3399    0.0463    0.9547    0.0789
-#> 206:    92.1037   -6.0869   -0.0238    2.4833   -0.9264    0.1648    4.5547    0.3341    0.4186    0.1606    1.3351    0.0466    0.9453    0.0797
-#> 207:    92.1212   -6.0561   -0.0247    2.4821   -0.9299    0.1677    4.3736    0.3363    0.4150    0.1602    1.3394    0.0467    0.9552    0.0790
-#> 208:    92.1203   -6.0351   -0.0260    2.4804   -0.9309    0.1616    4.2520    0.3369    0.4120    0.1613    1.3366    0.0466    0.9667    0.0785
-#> 209:    92.1169   -6.0133   -0.0277    2.4792   -0.9300    0.1596    4.1237    0.3352    0.4111    0.1616    1.3344    0.0464    0.9741    0.0778
-#> 210:    92.1195   -5.9866   -0.0289    2.4752   -0.9287    0.1586    3.9853    0.3352    0.4091    0.1602    1.3410    0.0461    0.9708    0.0778
-#> 211:    92.1243   -5.9458   -0.0316    2.4687   -0.9287    0.1606    3.8383    0.3366    0.4094    0.1607    1.3525    0.0455    0.9759    0.0778
-#> 212:    92.1384   -5.9338   -0.0345    2.4640   -0.9280    0.1635    3.7875    0.3375    0.4105    0.1594    1.3589    0.0454    0.9800    0.0776
-#> 213:    92.1481   -5.9191   -0.0379    2.4587   -0.9269    0.1629    3.7150    0.3375    0.4100    0.1586    1.3673    0.0449    0.9839    0.0775
-#> 214:    92.1523   -5.9189   -0.0408    2.4542   -0.9270    0.1593    3.7061    0.3375    0.4092    0.1579    1.3731    0.0446    0.9847    0.0773
-#> 215:    92.1548   -5.9183   -0.0429    2.4499   -0.9269    0.1604    3.7075    0.3369    0.4095    0.1574    1.3765    0.0442    0.9821    0.0775
-#> 216:    92.1547   -5.9171   -0.0450    2.4455   -0.9270    0.1600    3.6967    0.3368    0.4100    0.1571    1.3811    0.0438    0.9830    0.0776
-#> 217:    92.1556   -5.9141   -0.0468    2.4422   -0.9281    0.1580    3.6732    0.3361    0.4102    0.1578    1.3864    0.0435    0.9995    0.0770
-#> 218:    92.1587   -5.9173   -0.0477    2.4395   -0.9287    0.1545    3.6822    0.3351    0.4112    0.1580    1.3882    0.0432    1.0001    0.0772
-#> 219:    92.1590   -5.9188   -0.0483    2.4374   -0.9303    0.1540    3.6595    0.3341    0.4132    0.1578    1.3889    0.0430    0.9983    0.0775
-#> 220:    92.1614   -5.9303   -0.0493    2.4353   -0.9321    0.1559    3.6914    0.3336    0.4141    0.1581    1.3914    0.0427    1.0003    0.0775
-#> 221:    92.1657   -5.9455   -0.0504    2.4328   -0.9344    0.1585    3.7569    0.3329    0.4140    0.1591    1.3938    0.0424    1.0064    0.0773
-#> 222:    92.1697   -5.9320   -0.0515    2.4306   -0.9358    0.1617    3.6783    0.3321    0.4145    0.1600    1.3992    0.0421    1.0107    0.0772
-#> 223:    92.1754   -5.9205   -0.0525    2.4280   -0.9375    0.1630    3.6233    0.3313    0.4158    0.1604    1.4072    0.0416    1.0216    0.0770
-#> 224:    92.1809   -5.9149   -0.0534    2.4264   -0.9386    0.1623    3.5812    0.3306    0.4167    0.1607    1.4130    0.0413    1.0349    0.0764
-#> 225:    92.1872   -5.9099   -0.0543    2.4243   -0.9390    0.1619    3.5446    0.3299    0.4174    0.1607    1.4152    0.0411    1.0348    0.0766
-#> 226:    92.1935   -5.9046   -0.0554    2.4224   -0.9396    0.1631    3.5046    0.3299    0.4183    0.1608    1.4157    0.0409    1.0375    0.0766
-#> 227:    92.2026   -5.8964   -0.0567    2.4198   -0.9400    0.1637    3.4591    0.3303    0.4183    0.1614    1.4144    0.0408    1.0444    0.0763
-#> 228:    92.2069   -5.8852   -0.0578    2.4175   -0.9407    0.1633    3.4091    0.3308    0.4185    0.1621    1.4144    0.0407    1.0485    0.0763
-#> 229:    92.2122   -5.8844   -0.0591    2.4145   -0.9418    0.1631    3.3899    0.3314    0.4194    0.1622    1.4173    0.0404    1.0514    0.0763
-#> 230:    92.2183   -5.8907   -0.0604    2.4116   -0.9416    0.1640    3.4053    0.3319    0.4202    0.1616    1.4200    0.0401    1.0527    0.0764
-#> 231:    92.2246   -5.8895   -0.0619    2.4087   -0.9422    0.1651    3.3985    0.3323    0.4208    0.1609    1.4234    0.0400    1.0560    0.0762
-#> 232:    92.2282   -5.8840   -0.0632    2.4058   -0.9423    0.1641    3.3771    0.3327    0.4215    0.1609    1.4266    0.0398    1.0585    0.0762
-#> 233:    92.2294   -5.8775   -0.0645    2.4032   -0.9424    0.1620    3.3481    0.3335    0.4216    0.1607    1.4311    0.0395    1.0600    0.0763
-#> 234:    92.2311   -5.8709   -0.0658    2.4006   -0.9421    0.1626    3.3242    0.3343    0.4220    0.1602    1.4340    0.0393    1.0604    0.0764
-#> 235:    92.2312   -5.8656   -0.0668    2.3985   -0.9420    0.1608    3.3023    0.3350    0.4225    0.1596    1.4381    0.0391    1.0600    0.0765
-#> 236:    92.2289   -5.8633   -0.0675    2.3974   -0.9423    0.1599    3.2811    0.3352    0.4227    0.1589    1.4392    0.0390    1.0594    0.0765
-#> 237:    92.2251   -5.8641   -0.0683    2.3960   -0.9435    0.1586    3.2734    0.3351    0.4226    0.1588    1.4403    0.0389    1.0623    0.0765
-#> 238:    92.2242   -5.8633   -0.0690    2.3949   -0.9443    0.1579    3.2547    0.3349    0.4230    0.1590    1.4409    0.0389    1.0659    0.0765
-#> 239:    92.2250   -5.8612   -0.0693    2.3951   -0.9449    0.1558    3.2309    0.3346    0.4234    0.1599    1.4396    0.0389    1.0740    0.0762
-#> 240:    92.2264   -5.8597   -0.0696    2.3949   -0.9446    0.1550    3.2124    0.3342    0.4234    0.1603    1.4401    0.0388    1.0791    0.0760
-#> 241:    92.2281   -5.8562   -0.0699    2.3948   -0.9449    0.1544    3.1933    0.3339    0.4236    0.1604    1.4411    0.0388    1.0825    0.0760
-#> 242:    92.2289   -5.8512   -0.0703    2.3942   -0.9450    0.1534    3.1709    0.3338    0.4235    0.1606    1.4421    0.0388    1.0870    0.0760
-#> 243:    92.2296   -5.8489   -0.0708    2.3934   -0.9446    0.1531    3.1689    0.3342    0.4230    0.1605    1.4423    0.0387    1.0876    0.0760
-#> 244:    92.2311   -5.8446   -0.0715    2.3929   -0.9443    0.1528    3.1630    0.3349    0.4228    0.1604    1.4429    0.0387    1.0916    0.0759
-#> 245:    92.2338   -5.8421   -0.0718    2.3924   -0.9443    0.1528    3.1616    0.3352    0.4224    0.1610    1.4438    0.0387    1.0980    0.0755
-#> 246:    92.2361   -5.8389   -0.0721    2.3918   -0.9439    0.1525    3.1525    0.3354    0.4216    0.1620    1.4438    0.0388    1.1018    0.0753
-#> 247:    92.2374   -5.8388   -0.0724    2.3917   -0.9434    0.1510    3.1605    0.3356    0.4212    0.1629    1.4438    0.0389    1.1050    0.0751
-#> 248:    92.2360   -5.8367   -0.0728    2.3918   -0.9432    0.1505    3.1559    0.3360    0.4207    0.1638    1.4437    0.0389    1.1090    0.0748
-#> 249:    92.2361   -5.8351   -0.0732    2.3914   -0.9435    0.1499    3.1521    0.3363    0.4204    0.1646    1.4433    0.0389    1.1117    0.0748
-#> 250:    92.2353   -5.8349   -0.0733    2.3906   -0.9436    0.1502    3.1607    0.3365    0.4202    0.1646    1.4457    0.0388    1.1107    0.0749
-#> 251:    92.2343   -5.8318   -0.0736    2.3903   -0.9430    0.1494    3.1513    0.3367    0.4201    0.1648    1.4453    0.0387    1.1093    0.0750
-#> 252:    92.2356   -5.8244   -0.0739    2.3895   -0.9424    0.1477    3.1240    0.3369    0.4200    0.1651    1.4460    0.0386    1.1083    0.0750
-#> 253:    92.2367   -5.8188   -0.0742    2.3890   -0.9423    0.1465    3.1025    0.3369    0.4200    0.1649    1.4477    0.0385    1.1092    0.0750
-#> 254:    92.2392   -5.8154   -0.0747    2.3880   -0.9421    0.1458    3.0888    0.3372    0.4195    0.1644    1.4494    0.0384    1.1080    0.0750
-#> 255:    92.2404   -5.8131   -0.0751    2.3870   -0.9417    0.1451    3.0778    0.3375    0.4191    0.1639    1.4501    0.0383    1.1070    0.0751
-#> 256:    92.2408   -5.8109   -0.0753    2.3867   -0.9413    0.1445    3.0740    0.3376    0.4192    0.1633    1.4510    0.0382    1.1064    0.0751
-#> 257:    92.2413   -5.8066   -0.0754    2.3866   -0.9409    0.1446    3.0636    0.3376    0.4191    0.1628    1.4522    0.0382    1.1080    0.0750
-#> 258:    92.2412   -5.8035   -0.0754    2.3869   -0.9404    0.1436    3.0502    0.3372    0.4191    0.1623    1.4534    0.0381    1.1057    0.0751
-#> 259:    92.2399   -5.7996   -0.0753    2.3871   -0.9399    0.1427    3.0357    0.3370    0.4195    0.1621    1.4540    0.0380    1.1037    0.0752
-#> 260:    92.2389   -5.7955   -0.0755    2.3872   -0.9391    0.1420    3.0251    0.3366    0.4199    0.1619    1.4555    0.0380    1.1041    0.0752
-#> 261:    92.2378   -5.7941   -0.0755    2.3875   -0.9385    0.1412    3.0240    0.3362    0.4201    0.1613    1.4575    0.0380    1.1048    0.0751
-#> 262:    92.2361   -5.7920   -0.0756    2.3879   -0.9379    0.1407    3.0182    0.3358    0.4205    0.1607    1.4581    0.0381    1.1047    0.0750
-#> 263:    92.2338   -5.7891   -0.0754    2.3883   -0.9375    0.1407    3.0072    0.3356    0.4211    0.1603    1.4585    0.0381    1.1041    0.0750
-#> 264:    92.2313   -5.7882   -0.0752    2.3886   -0.9371    0.1407    3.0009    0.3355    0.4217    0.1601    1.4574    0.0381    1.1036    0.0750
-#> 265:    92.2312   -5.7843   -0.0752    2.3883   -0.9372    0.1402    2.9872    0.3358    0.4220    0.1599    1.4577    0.0381    1.1026    0.0750
-#> 266:    92.2312   -5.7800   -0.0753    2.3880   -0.9370    0.1396    2.9708    0.3363    0.4223    0.1597    1.4584    0.0381    1.1019    0.0750
-#> 267:    92.2306   -5.7785   -0.0755    2.3878   -0.9372    0.1397    2.9619    0.3368    0.4227    0.1595    1.4578    0.0381    1.1021    0.0750
-#> 268:    92.2287   -5.7803   -0.0758    2.3870   -0.9372    0.1394    2.9777    0.3375    0.4226    0.1594    1.4578    0.0380    1.1032    0.0749
-#> 269:    92.2265   -5.7804   -0.0761    2.3865   -0.9371    0.1399    2.9816    0.3382    0.4226    0.1592    1.4589    0.0380    1.1058    0.0747
-#> 270:    92.2236   -5.7811   -0.0765    2.3860   -0.9369    0.1411    2.9893    0.3386    0.4227    0.1591    1.4597    0.0380    1.1081    0.0745
-#> 271:    92.2211   -5.7793   -0.0769    2.3852   -0.9365    0.1421    2.9888    0.3390    0.4228    0.1591    1.4606    0.0379    1.1083    0.0745
-#> 272:    92.2187   -5.7773   -0.0773    2.3845   -0.9361    0.1423    2.9810    0.3396    0.4232    0.1589    1.4617    0.0378    1.1076    0.0746
-#> 273:    92.2164   -5.7769   -0.0776    2.3838   -0.9356    0.1427    2.9809    0.3402    0.4240    0.1589    1.4615    0.0378    1.1073    0.0746
-#> 274:    92.2145   -5.7763   -0.0778    2.3836   -0.9355    0.1434    2.9795    0.3407    0.4248    0.1589    1.4615    0.0378    1.1069    0.0746
-#> 275:    92.2133   -5.7762   -0.0779    2.3836   -0.9352    0.1436    2.9837    0.3410    0.4253    0.1589    1.4621    0.0378    1.1064    0.0746
-#> 276:    92.2123   -5.7764   -0.0781    2.3835   -0.9348    0.1431    2.9889    0.3414    0.4255    0.1589    1.4632    0.0378    1.1073    0.0746
-#> 277:    92.2113   -5.7771   -0.0781    2.3839   -0.9347    0.1423    2.9925    0.3423    0.4264    0.1589    1.4630    0.0378    1.1104    0.0744
-#> 278:    92.2099   -5.7774   -0.0780    2.3841   -0.9349    0.1418    2.9927    0.3429    0.4270    0.1590    1.4634    0.0378    1.1127    0.0742
-#> 279:    92.2087   -5.7798   -0.0779    2.3844   -0.9352    0.1413    2.9997    0.3437    0.4276    0.1590    1.4630    0.0378    1.1133    0.0742
-#> 280:    92.2077   -5.7802   -0.0778    2.3841   -0.9358    0.1407    2.9971    0.3445    0.4284    0.1586    1.4634    0.0378    1.1136    0.0742
-#> 281:    92.2061   -5.7814   -0.0777    2.3837   -0.9362    0.1401    3.0004    0.3452    0.4291    0.1582    1.4629    0.0378    1.1133    0.0743
-#> 282:    92.2058   -5.7802   -0.0777    2.3834   -0.9363    0.1386    2.9994    0.3459    0.4297    0.1579    1.4634    0.0378    1.1126    0.0743
-#> 283:    92.2057   -5.7780   -0.0778    2.3828   -0.9361    0.1376    2.9917    0.3469    0.4298    0.1576    1.4645    0.0378    1.1147    0.0742
-#> 284:    92.2051   -5.7788   -0.0780    2.3824   -0.9360    0.1367    2.9968    0.3479    0.4300    0.1573    1.4647    0.0378    1.1149    0.0741
-#> 285:    92.2041   -5.7793   -0.0782    2.3821   -0.9362    0.1359    2.9941    0.3487    0.4302    0.1573    1.4653    0.0378    1.1164    0.0740
-#> 286:    92.2040   -5.7803   -0.0783    2.3819   -0.9364    0.1352    2.9957    0.3495    0.4304    0.1573    1.4655    0.0378    1.1180    0.0738
-#> 287:    92.2044   -5.7809   -0.0784    2.3817   -0.9365    0.1348    2.9961    0.3502    0.4304    0.1572    1.4657    0.0379    1.1178    0.0738
-#> 288:    92.2043   -5.7835   -0.0785    2.3814   -0.9366    0.1350    3.0073    0.3509    0.4304    0.1572    1.4658    0.0379    1.1184    0.0738
-#> 289:    92.2041   -5.7845   -0.0787    2.3809   -0.9364    0.1347    3.0126    0.3516    0.4304    0.1571    1.4653    0.0379    1.1190    0.0737
-#> 290:    92.2032   -5.7852   -0.0788    2.3807   -0.9363    0.1349    3.0161    0.3521    0.4304    0.1568    1.4656    0.0379    1.1191    0.0737
-#> 291:    92.2019   -5.7848   -0.0790    2.3802   -0.9363    0.1356    3.0155    0.3528    0.4300    0.1565    1.4664    0.0380    1.1210    0.0736
-#> 292:    92.2012   -5.7846   -0.0792    2.3799   -0.9363    0.1361    3.0167    0.3535    0.4296    0.1563    1.4670    0.0380    1.1223    0.0735
-#> 293:    92.2007   -5.7845   -0.0793    2.3795   -0.9363    0.1365    3.0175    0.3542    0.4291    0.1561    1.4681    0.0380    1.1236    0.0734
-#> 294:    92.2009   -5.7850   -0.0795    2.3791   -0.9360    0.1365    3.0189    0.3550    0.4287    0.1560    1.4682    0.0380    1.1243    0.0733
-#> 295:    92.2009   -5.7865   -0.0797    2.3786   -0.9360    0.1360    3.0279    0.3556    0.4286    0.1558    1.4689    0.0380    1.1243    0.0734
-#> 296:    92.2007   -5.7878   -0.0798    2.3781   -0.9362    0.1358    3.0345    0.3562    0.4283    0.1555    1.4694    0.0379    1.1247    0.0734
-#> 297:    92.1992   -5.7891   -0.0801    2.3774   -0.9364    0.1358    3.0403    0.3568    0.4278    0.1554    1.4699    0.0379    1.1267    0.0734
-#> 298:    92.1978   -5.7892   -0.0803    2.3768   -0.9366    0.1357    3.0383    0.3573    0.4274    0.1553    1.4706    0.0378    1.1276    0.0734
-#> 299:    92.1968   -5.7906   -0.0805    2.3763   -0.9369    0.1353    3.0408    0.3579    0.4269    0.1553    1.4712    0.0378    1.1282    0.0733
-#> 300:    92.1954   -5.7929   -0.0807    2.3760   -0.9369    0.1352    3.0477    0.3583    0.4265    0.1551    1.4716    0.0379    1.1286    0.0733
-#> 301:    92.1941   -5.7934   -0.0809    2.3757   -0.9369    0.1352    3.0483    0.3588    0.4261    0.1548    1.4727    0.0378    1.1288    0.0732
-#> 302:    92.1929   -5.7949   -0.0811    2.3754   -0.9370    0.1354    3.0560    0.3592    0.4256    0.1548    1.4728    0.0379    1.1296    0.0731
-#> 303:    92.1919   -5.7972   -0.0813    2.3751   -0.9368    0.1352    3.0671    0.3597    0.4250    0.1550    1.4730    0.0379    1.1302    0.0731
-#> 304:    92.1906   -5.8018   -0.0814    2.3750   -0.9368    0.1349    3.0935    0.3602    0.4245    0.1552    1.4731    0.0379    1.1314    0.0730
-#> 305:    92.1897   -5.8063   -0.0817    2.3744   -0.9370    0.1350    3.1211    0.3606    0.4238    0.1554    1.4727    0.0379    1.1323    0.0730
-#> 306:    92.1896   -5.8116   -0.0820    2.3740   -0.9373    0.1347    3.1571    0.3610    0.4233    0.1555    1.4727    0.0379    1.1351    0.0728
-#> 307:    92.1895   -5.8156   -0.0822    2.3735   -0.9373    0.1341    3.1826    0.3613    0.4226    0.1552    1.4741    0.0379    1.1374    0.0726
-#> 308:    92.1899   -5.8202   -0.0824    2.3732   -0.9376    0.1338    3.2124    0.3617    0.4220    0.1554    1.4745    0.0379    1.1408    0.0724
-#> 309:    92.1903   -5.8232   -0.0827    2.3728   -0.9377    0.1337    3.2330    0.3620    0.4213    0.1554    1.4749    0.0379    1.1419    0.0724
-#> 310:    92.1902   -5.8249   -0.0828    2.3727   -0.9378    0.1335    3.2463    0.3621    0.4207    0.1554    1.4752    0.0379    1.1435    0.0723
-#> 311:    92.1910   -5.8267   -0.0828    2.3726   -0.9378    0.1335    3.2581    0.3623    0.4200    0.1554    1.4754    0.0379    1.1441    0.0722
-#> 312:    92.1918   -5.8271   -0.0829    2.3726   -0.9378    0.1333    3.2567    0.3624    0.4195    0.1552    1.4751    0.0380    1.1432    0.0723
-#> 313:    92.1926   -5.8260   -0.0829    2.3725   -0.9380    0.1334    3.2497    0.3626    0.4190    0.1552    1.4751    0.0380    1.1434    0.0723
-#> 314:    92.1934   -5.8256   -0.0829    2.3724   -0.9381    0.1330    3.2426    0.3628    0.4185    0.1553    1.4746    0.0380    1.1441    0.0722
-#> 315:    92.1938   -5.8237   -0.0829    2.3724   -0.9384    0.1326    3.2327    0.3630    0.4179    0.1555    1.4746    0.0380    1.1468    0.0721
-#> 316:    92.1950   -5.8235   -0.0829    2.3722   -0.9385    0.1324    3.2283    0.3631    0.4172    0.1557    1.4745    0.0380    1.1476    0.0721
-#> 317:    92.1963   -5.8239   -0.0829    2.3722   -0.9385    0.1322    3.2260    0.3633    0.4167    0.1560    1.4741    0.0380    1.1481    0.0721
-#> 318:    92.1975   -5.8242   -0.0829    2.3722   -0.9387    0.1321    3.2240    0.3634    0.4163    0.1559    1.4740    0.0380    1.1477    0.0722
-#> 319:    92.1990   -5.8250   -0.0829    2.3721   -0.9387    0.1320    3.2215    0.3634    0.4159    0.1560    1.4736    0.0381    1.1496    0.0720
-#> 320:    92.2003   -5.8256   -0.0829    2.3722   -0.9386    0.1322    3.2199    0.3635    0.4155    0.1561    1.4730    0.0381    1.1508    0.0719
-#> 321:    92.2018   -5.8249   -0.0829    2.3723   -0.9386    0.1326    3.2150    0.3635    0.4151    0.1562    1.4727    0.0381    1.1514    0.0718
-#> 322:    92.2031   -5.8239   -0.0829    2.3724   -0.9386    0.1333    3.2081    0.3635    0.4147    0.1561    1.4729    0.0381    1.1527    0.0717
-#> 323:    92.2045   -5.8244   -0.0829    2.3725   -0.9384    0.1336    3.2065    0.3635    0.4143    0.1562    1.4729    0.0381    1.1541    0.0716
-#> 324:    92.2060   -5.8228   -0.0828    2.3726   -0.9383    0.1339    3.1996    0.3635    0.4139    0.1562    1.4729    0.0382    1.1562    0.0714
-#> 325:    92.2071   -5.8212   -0.0828    2.3727   -0.9383    0.1339    3.1921    0.3636    0.4135    0.1563    1.4733    0.0382    1.1580    0.0713
-#> 326:    92.2083   -5.8201   -0.0826    2.3728   -0.9382    0.1340    3.1888    0.3639    0.4134    0.1562    1.4734    0.0382    1.1587    0.0713
-#> 327:    92.2095   -5.8185   -0.0825    2.3729   -0.9379    0.1340    3.1831    0.3641    0.4134    0.1562    1.4737    0.0382    1.1592    0.0713
-#> 328:    92.2105   -5.8188   -0.0823    2.3731   -0.9379    0.1338    3.1836    0.3643    0.4132    0.1561    1.4736    0.0383    1.1589    0.0713
-#> 329:    92.2115   -5.8182   -0.0821    2.3732   -0.9381    0.1339    3.1807    0.3646    0.4129    0.1561    1.4737    0.0383    1.1585    0.0713
-#> 330:    92.2127   -5.8181   -0.0819    2.3734   -0.9381    0.1338    3.1827    0.3648    0.4127    0.1563    1.4735    0.0383    1.1578    0.0714
-#> 331:    92.2134   -5.8180   -0.0815    2.3739   -0.9381    0.1340    3.1837    0.3647    0.4128    0.1566    1.4735    0.0383    1.1575    0.0714
-#> 332:    92.2136   -5.8184   -0.0811    2.3746   -0.9379    0.1340    3.1847    0.3647    0.4130    0.1570    1.4728    0.0384    1.1577    0.0714
-#> 333:    92.2133   -5.8180   -0.0807    2.3753   -0.9376    0.1340    3.1853    0.3646    0.4132    0.1572    1.4725    0.0384    1.1573    0.0714
-#> 334:    92.2136   -5.8173   -0.0803    2.3760   -0.9374    0.1342    3.1838    0.3645    0.4133    0.1576    1.4720    0.0385    1.1570    0.0714
-#> 335:    92.2139   -5.8187   -0.0800    2.3769   -0.9372    0.1344    3.1947    0.3643    0.4135    0.1576    1.4714    0.0386    1.1567    0.0714
-#> 336:    92.2134   -5.8198   -0.0796    2.3777   -0.9370    0.1348    3.2008    0.3641    0.4135    0.1577    1.4706    0.0387    1.1557    0.0714
-#> 337:    92.2130   -5.8201   -0.0792    2.3784   -0.9370    0.1357    3.2050    0.3640    0.4137    0.1579    1.4703    0.0388    1.1558    0.0714
-#> 338:    92.2130   -5.8190   -0.0787    2.3791   -0.9368    0.1362    3.2036    0.3638    0.4139    0.1580    1.4708    0.0388    1.1558    0.0714
-#> 339:    92.2132   -5.8177   -0.0783    2.3798   -0.9368    0.1369    3.2006    0.3637    0.4142    0.1581    1.4712    0.0388    1.1551    0.0714
-#> 340:    92.2137   -5.8167   -0.0778    2.3806   -0.9366    0.1376    3.1984    0.3636    0.4143    0.1581    1.4712    0.0388    1.1540    0.0715
-#> 341:    92.2141   -5.8145   -0.0773    2.3814   -0.9364    0.1378    3.1916    0.3635    0.4142    0.1581    1.4712    0.0389    1.1529    0.0715
-#> 342:    92.2142   -5.8123   -0.0769    2.3821   -0.9364    0.1383    3.1840    0.3634    0.4142    0.1581    1.4718    0.0389    1.1513    0.0716
-#> 343:    92.2139   -5.8109   -0.0764    2.3830   -0.9364    0.1389    3.1806    0.3632    0.4142    0.1581    1.4721    0.0389    1.1501    0.0716
-#> 344:    92.2137   -5.8117   -0.0759    2.3839   -0.9366    0.1390    3.1830    0.3631    0.4144    0.1582    1.4711    0.0390    1.1492    0.0717
-#> 345:    92.2133   -5.8118   -0.0754    2.3849   -0.9368    0.1391    3.1827    0.3630    0.4146    0.1582    1.4703    0.0391    1.1488    0.0717
-#> 346:    92.2127   -5.8113   -0.0748    2.3858   -0.9369    0.1389    3.1793    0.3629    0.4147    0.1581    1.4700    0.0391    1.1475    0.0717
-#> 347:    92.2121   -5.8107   -0.0743    2.3867   -0.9371    0.1386    3.1748    0.3628    0.4149    0.1579    1.4701    0.0392    1.1463    0.0718
-#> 348:    92.2106   -5.8109   -0.0738    2.3876   -0.9374    0.1385    3.1726    0.3626    0.4151    0.1577    1.4704    0.0392    1.1453    0.0719
-#> 349:    92.2096   -5.8111   -0.0732    2.3883   -0.9377    0.1382    3.1703    0.3626    0.4151    0.1575    1.4705    0.0392    1.1448    0.0719
-#> 350:    92.2088   -5.8108   -0.0727    2.3890   -0.9378    0.1380    3.1674    0.3625    0.4152    0.1574    1.4704    0.0392    1.1439    0.0720
-#> 351:    92.2077   -5.8103   -0.0722    2.3899   -0.9379    0.1379    3.1634    0.3623    0.4154    0.1572    1.4701    0.0393    1.1432    0.0720
-#> 352:    92.2069   -5.8103   -0.0718    2.3906   -0.9381    0.1380    3.1626    0.3623    0.4154    0.1570    1.4701    0.0393    1.1425    0.0721
-#> 353:    92.2058   -5.8107   -0.0714    2.3913   -0.9381    0.1382    3.1629    0.3624    0.4154    0.1570    1.4695    0.0394    1.1426    0.0720
-#> 354:    92.2046   -5.8102   -0.0710    2.3921   -0.9381    0.1384    3.1576    0.3624    0.4154    0.1571    1.4691    0.0394    1.1424    0.0720
-#> 355:    92.2034   -5.8084   -0.0707    2.3928   -0.9381    0.1388    3.1501    0.3624    0.4154    0.1570    1.4686    0.0395    1.1414    0.0721
-#> 356:    92.2027   -5.8079   -0.0703    2.3935   -0.9382    0.1392    3.1463    0.3626    0.4155    0.1569    1.4682    0.0396    1.1405    0.0721
-#> 357:    92.2019   -5.8084   -0.0698    2.3943   -0.9382    0.1390    3.1444    0.3628    0.4156    0.1569    1.4665    0.0397    1.1403    0.0721
-#> 358:    92.2014   -5.8085   -0.0694    2.3950   -0.9381    0.1389    3.1413    0.3630    0.4158    0.1569    1.4662    0.0398    1.1398    0.0722
-#> 359:    92.2005   -5.8091   -0.0689    2.3956   -0.9383    0.1387    3.1393    0.3633    0.4159    0.1570    1.4664    0.0398    1.1401    0.0722
-#> 360:    92.1994   -5.8091   -0.0685    2.3962   -0.9385    0.1385    3.1362    0.3635    0.4159    0.1572    1.4664    0.0398    1.1413    0.0722
-#> 361:    92.1983   -5.8094   -0.0682    2.3966   -0.9386    0.1384    3.1340    0.3638    0.4159    0.1573    1.4669    0.0398    1.1420    0.0722
-#> 362:    92.1976   -5.8086   -0.0678    2.3971   -0.9389    0.1380    3.1277    0.3639    0.4160    0.1573    1.4671    0.0398    1.1414    0.0723
-#> 363:    92.1967   -5.8081   -0.0675    2.3976   -0.9389    0.1377    3.1239    0.3641    0.4161    0.1573    1.4669    0.0399    1.1412    0.0723
-#> 364:    92.1960   -5.8073   -0.0671    2.3982   -0.9390    0.1373    3.1208    0.3643    0.4161    0.1572    1.4668    0.0399    1.1411    0.0723
-#> 365:    92.1958   -5.8066   -0.0667    2.3988   -0.9389    0.1369    3.1164    0.3645    0.4160    0.1572    1.4672    0.0399    1.1416    0.0723
-#> 366:    92.1956   -5.8063   -0.0664    2.3992   -0.9390    0.1364    3.1127    0.3650    0.4156    0.1573    1.4674    0.0399    1.1425    0.0723
-#> 367:    92.1952   -5.8056   -0.0661    2.3996   -0.9389    0.1361    3.1082    0.3652    0.4155    0.1574    1.4675    0.0399    1.1416    0.0723
-#> 368:    92.1948   -5.8059   -0.0658    2.4001   -0.9389    0.1359    3.1068    0.3655    0.4154    0.1575    1.4671    0.0399    1.1406    0.0724
-#> 369:    92.1948   -5.8064   -0.0655    2.4005   -0.9388    0.1360    3.1055    0.3658    0.4152    0.1576    1.4669    0.0399    1.1408    0.0724
-#> 370:    92.1951   -5.8072   -0.0652    2.4010   -0.9389    0.1361    3.1060    0.3660    0.4151    0.1576    1.4669    0.0399    1.1406    0.0724
-#> 371:    92.1956   -5.8080   -0.0649    2.4015   -0.9390    0.1362    3.1095    0.3662    0.4150    0.1576    1.4669    0.0400    1.1411    0.0724
-#> 372:    92.1962   -5.8096   -0.0645    2.4020   -0.9390    0.1363    3.1168    0.3665    0.4149    0.1576    1.4667    0.0400    1.1411    0.0724
-#> 373:    92.1968   -5.8098   -0.0642    2.4025   -0.9392    0.1363    3.1154    0.3666    0.4147    0.1576    1.4664    0.0400    1.1418    0.0723
-#> 374:    92.1972   -5.8098   -0.0640    2.4029   -0.9395    0.1363    3.1117    0.3667    0.4146    0.1576    1.4661    0.0401    1.1421    0.0723
-#> 375:    92.1979   -5.8101   -0.0637    2.4032   -0.9397    0.1364    3.1090    0.3668    0.4143    0.1577    1.4654    0.0401    1.1425    0.0723
-#> 376:    92.1981   -5.8106   -0.0635    2.4035   -0.9399    0.1363    3.1084    0.3669    0.4142    0.1576    1.4650    0.0401    1.1423    0.0723
-#> 377:    92.1986   -5.8104   -0.0633    2.4039   -0.9399    0.1360    3.1053    0.3670    0.4142    0.1576    1.4645    0.0402    1.1424    0.0723
-#> 378:    92.1989   -5.8104   -0.0631    2.4043   -0.9399    0.1358    3.1026    0.3671    0.4142    0.1577    1.4638    0.0402    1.1421    0.0723
-#> 379:    92.1990   -5.8114   -0.0628    2.4047   -0.9399    0.1355    3.1068    0.3671    0.4141    0.1577    1.4636    0.0402    1.1413    0.0724
-#> 380:    92.1989   -5.8119   -0.0627    2.4048   -0.9400    0.1351    3.1095    0.3673    0.4136    0.1577    1.4634    0.0402    1.1413    0.0724
-#> 381:    92.1989   -5.8127   -0.0627    2.4048   -0.9400    0.1349    3.1152    0.3676    0.4131    0.1577    1.4631    0.0403    1.1408    0.0723
-#> 382:    92.1994   -5.8126   -0.0627    2.4049   -0.9399    0.1348    3.1188    0.3678    0.4126    0.1576    1.4635    0.0403    1.1403    0.0723
-#> 383:    92.2000   -5.8129   -0.0626    2.4049   -0.9397    0.1346    3.1256    0.3681    0.4120    0.1576    1.4637    0.0403    1.1396    0.0723
-#> 384:    92.2006   -5.8133   -0.0626    2.4050   -0.9396    0.1347    3.1290    0.3683    0.4115    0.1575    1.4641    0.0402    1.1389    0.0723
-#> 385:    92.2015   -5.8131   -0.0626    2.4050   -0.9394    0.1350    3.1287    0.3686    0.4110    0.1575    1.4642    0.0402    1.1382    0.0723
-#> 386:    92.2023   -5.8140   -0.0625    2.4049   -0.9391    0.1349    3.1324    0.3690    0.4104    0.1574    1.4647    0.0402    1.1374    0.0723
-#> 387:    92.2030   -5.8147   -0.0625    2.4050   -0.9390    0.1349    3.1345    0.3693    0.4099    0.1572    1.4652    0.0402    1.1366    0.0724
-#> 388:    92.2040   -5.8157   -0.0625    2.4050   -0.9389    0.1349    3.1381    0.3696    0.4094    0.1570    1.4652    0.0402    1.1362    0.0724
-#> 389:    92.2051   -5.8156   -0.0625    2.4051   -0.9387    0.1349    3.1373    0.3699    0.4090    0.1570    1.4653    0.0402    1.1354    0.0724
-#> 390:    92.2063   -5.8152   -0.0625    2.4051   -0.9386    0.1349    3.1350    0.3702    0.4087    0.1570    1.4655    0.0402    1.1345    0.0725
-#> 391:    92.2076   -5.8160   -0.0625    2.4051   -0.9384    0.1350    3.1380    0.3705    0.4083    0.1571    1.4656    0.0402    1.1341    0.0725
-#> 392:    92.2086   -5.8166   -0.0626    2.4049   -0.9384    0.1349    3.1397    0.3707    0.4081    0.1572    1.4658    0.0402    1.1345    0.0725
-#> 393:    92.2095   -5.8168   -0.0626    2.4047   -0.9383    0.1348    3.1405    0.3708    0.4080    0.1573    1.4659    0.0402    1.1344    0.0725
-#> 394:    92.2107   -5.8174   -0.0627    2.4045   -0.9382    0.1347    3.1433    0.3710    0.4079    0.1575    1.4660    0.0401    1.1342    0.0725
-#> 395:    92.2118   -5.8174   -0.0628    2.4043   -0.9380    0.1346    3.1437    0.3711    0.4078    0.1575    1.4661    0.0401    1.1343    0.0725
-#> 396:    92.2127   -5.8170   -0.0629    2.4041   -0.9379    0.1344    3.1424    0.3712    0.4077    0.1575    1.4664    0.0401    1.1342    0.0725
-#> 397:    92.2137   -5.8161   -0.0630    2.4040   -0.9376    0.1342    3.1386    0.3713    0.4076    0.1577    1.4667    0.0401    1.1341    0.0725
-#> 398:    92.2146   -5.8152   -0.0633    2.4036   -0.9374    0.1341    3.1344    0.3713    0.4075    0.1578    1.4671    0.0401    1.1334    0.0725
-#> 399:    92.2157   -5.8138   -0.0635    2.4032   -0.9373    0.1340    3.1296    0.3714    0.4074    0.1578    1.4678    0.0401    1.1336    0.0726
-#> 400:    92.2165   -5.8131   -0.0638    2.4027   -0.9372    0.1340    3.1262    0.3715    0.4072    0.1579    1.4681    0.0400    1.1332    0.0726
-#> 401:    92.2173   -5.8118   -0.0641    2.4022   -0.9372    0.1341    3.1220    0.3716    0.4069    0.1579    1.4686    0.0400    1.1339    0.0726
-#> 402:    92.2181   -5.8107   -0.0643    2.4018   -0.9370    0.1344    3.1192    0.3718    0.4065    0.1580    1.4694    0.0400    1.1338    0.0726
-#> 403:    92.2190   -5.8099   -0.0646    2.4013   -0.9371    0.1348    3.1166    0.3720    0.4061    0.1581    1.4700    0.0400    1.1344    0.0725
-#> 404:    92.2198   -5.8104   -0.0649    2.4008   -0.9372    0.1348    3.1161    0.3723    0.4058    0.1582    1.4704    0.0399    1.1357    0.0725
-#> 405:    92.2203   -5.8107   -0.0652    2.4004   -0.9372    0.1348    3.1177    0.3725    0.4055    0.1582    1.4705    0.0400    1.1358    0.0724
-#> 406:    92.2204   -5.8103   -0.0653    2.4002   -0.9371    0.1348    3.1157    0.3724    0.4051    0.1582    1.4709    0.0400    1.1361    0.0724
-#> 407:    92.2201   -5.8094   -0.0655    2.4001   -0.9369    0.1348    3.1121    0.3724    0.4048    0.1583    1.4713    0.0400    1.1360    0.0724
-#> 408:    92.2201   -5.8087   -0.0657    2.3999   -0.9368    0.1350    3.1085    0.3724    0.4044    0.1582    1.4714    0.0400    1.1360    0.0723
-#> 409:    92.2201   -5.8083   -0.0658    2.3998   -0.9365    0.1355    3.1073    0.3724    0.4043    0.1582    1.4713    0.0401    1.1358    0.0723
-#> 410:    92.2196   -5.8094   -0.0659    2.3996   -0.9365    0.1361    3.1123    0.3724    0.4041    0.1582    1.4712    0.0401    1.1357    0.0723
-#> 411:    92.2192   -5.8099   -0.0661    2.3994   -0.9366    0.1363    3.1168    0.3724    0.4038    0.1582    1.4715    0.0401    1.1354    0.0723
-#> 412:    92.2187   -5.8105   -0.0662    2.3993   -0.9365    0.1365    3.1215    0.3725    0.4035    0.1582    1.4716    0.0401    1.1359    0.0723
-#> 413:    92.2185   -5.8109   -0.0663    2.3992   -0.9365    0.1367    3.1268    0.3725    0.4031    0.1583    1.4719    0.0401    1.1357    0.0723
-#> 414:    92.2183   -5.8111   -0.0665    2.3987   -0.9365    0.1370    3.1286    0.3727    0.4026    0.1582    1.4724    0.0400    1.1349    0.0723
-#> 415:    92.2181   -5.8122   -0.0667    2.3983   -0.9366    0.1370    3.1351    0.3729    0.4021    0.1581    1.4726    0.0400    1.1341    0.0724
-#> 416:    92.2180   -5.8133   -0.0669    2.3979   -0.9367    0.1372    3.1409    0.3731    0.4015    0.1578    1.4734    0.0400    1.1333    0.0724
-#> 417:    92.2176   -5.8138   -0.0671    2.3976   -0.9368    0.1374    3.1426    0.3733    0.4009    0.1576    1.4739    0.0400    1.1325    0.0724
-#> 418:    92.2173   -5.8150   -0.0673    2.3973   -0.9369    0.1376    3.1479    0.3735    0.4003    0.1575    1.4740    0.0400    1.1316    0.0725
-#> 419:    92.2174   -5.8154   -0.0674    2.3970   -0.9369    0.1375    3.1497    0.3736    0.3998    0.1574    1.4741    0.0400    1.1314    0.0724
-#> 420:    92.2175   -5.8154   -0.0676    2.3968   -0.9369    0.1375    3.1489    0.3737    0.3993    0.1574    1.4742    0.0400    1.1315    0.0724
-#> 421:    92.2176   -5.8154   -0.0678    2.3964   -0.9369    0.1374    3.1485    0.3739    0.3989    0.1573    1.4743    0.0400    1.1312    0.0724
-#> 422:    92.2174   -5.8155   -0.0680    2.3961   -0.9370    0.1375    3.1483    0.3741    0.3985    0.1572    1.4744    0.0400    1.1309    0.0723
-#> 423:    92.2170   -5.8156   -0.0681    2.3958   -0.9371    0.1375    3.1481    0.3742    0.3980    0.1571    1.4741    0.0400    1.1308    0.0723
-#> 424:    92.2169   -5.8168   -0.0683    2.3956   -0.9372    0.1374    3.1524    0.3744    0.3976    0.1571    1.4740    0.0400    1.1316    0.0722
-#> 425:    92.2167   -5.8171   -0.0685    2.3954   -0.9372    0.1373    3.1520    0.3744    0.3972    0.1571    1.4736    0.0401    1.1317    0.0722
-#> 426:    92.2164   -5.8170   -0.0687    2.3951   -0.9372    0.1373    3.1502    0.3745    0.3968    0.1570    1.4734    0.0401    1.1320    0.0722
-#> 427:    92.2166   -5.8169   -0.0688    2.3949   -0.9372    0.1372    3.1480    0.3745    0.3964    0.1570    1.4734    0.0401    1.1317    0.0721
-#> 428:    92.2166   -5.8170   -0.0689    2.3948   -0.9374    0.1371    3.1460    0.3745    0.3959    0.1570    1.4735    0.0401    1.1315    0.0721
-#> 429:    92.2162   -5.8171   -0.0691    2.3946   -0.9374    0.1369    3.1446    0.3745    0.3954    0.1570    1.4736    0.0401    1.1316    0.0721
-#> 430:    92.2158   -5.8178   -0.0692    2.3944   -0.9375    0.1370    3.1464    0.3745    0.3950    0.1570    1.4736    0.0401    1.1314    0.0721
-#> 431:    92.2153   -5.8180   -0.0693    2.3942   -0.9375    0.1371    3.1470    0.3745    0.3946    0.1570    1.4735    0.0401    1.1314    0.0721
-#> 432:    92.2150   -5.8182   -0.0695    2.3940   -0.9375    0.1372    3.1477    0.3746    0.3942    0.1570    1.4735    0.0401    1.1315    0.0721
-#> 433:    92.2145   -5.8189   -0.0696    2.3938   -0.9375    0.1374    3.1512    0.3746    0.3938    0.1571    1.4736    0.0400    1.1323    0.0720
-#> 434:    92.2141   -5.8186   -0.0697    2.3936   -0.9373    0.1376    3.1530    0.3746    0.3933    0.1571    1.4736    0.0400    1.1330    0.0719
-#> 435:    92.2133   -5.8187   -0.0699    2.3934   -0.9373    0.1381    3.1571    0.3747    0.3929    0.1570    1.4738    0.0400    1.1325    0.0720
-#> 436:    92.2129   -5.8180   -0.0700    2.3932   -0.9374    0.1380    3.1544    0.3746    0.3925    0.1570    1.4740    0.0400    1.1332    0.0719
-#> 437:    92.2122   -5.8186   -0.0702    2.3930   -0.9375    0.1380    3.1574    0.3746    0.3921    0.1570    1.4739    0.0400    1.1342    0.0718
-#> 438:    92.2114   -5.8187   -0.0703    2.3928   -0.9376    0.1380    3.1583    0.3745    0.3918    0.1569    1.4740    0.0400    1.1346    0.0718
-#> 439:    92.2104   -5.8181   -0.0705    2.3925   -0.9377    0.1381    3.1568    0.3744    0.3914    0.1568    1.4743    0.0400    1.1352    0.0718
-#> 440:    92.2095   -5.8178   -0.0706    2.3923   -0.9377    0.1381    3.1555    0.3743    0.3910    0.1566    1.4745    0.0400    1.1349    0.0718
-#> 441:    92.2088   -5.8176   -0.0707    2.3923   -0.9378    0.1381    3.1559    0.3742    0.3907    0.1565    1.4748    0.0400    1.1349    0.0718
-#> 442:    92.2081   -5.8172   -0.0708    2.3921   -0.9379    0.1383    3.1539    0.3741    0.3903    0.1564    1.4754    0.0400    1.1350    0.0717
-#> 443:    92.2074   -5.8171   -0.0709    2.3920   -0.9380    0.1387    3.1526    0.3740    0.3901    0.1563    1.4756    0.0400    1.1349    0.0717
-#> 444:    92.2068   -5.8175   -0.0711    2.3918   -0.9380    0.1390    3.1533    0.3739    0.3898    0.1562    1.4758    0.0400    1.1353    0.0717
-#> 445:    92.2061   -5.8180   -0.0712    2.3915   -0.9382    0.1394    3.1529    0.3737    0.3896    0.1562    1.4758    0.0400    1.1355    0.0717
-#> 446:    92.2054   -5.8177   -0.0714    2.3912   -0.9384    0.1398    3.1496    0.3735    0.3894    0.1562    1.4760    0.0399    1.1367    0.0716
-#> 447:    92.2051   -5.8180   -0.0716    2.3910   -0.9385    0.1400    3.1484    0.3734    0.3891    0.1563    1.4762    0.0399    1.1370    0.0715
-#> 448:    92.2053   -5.8189   -0.0717    2.3909   -0.9387    0.1405    3.1499    0.3732    0.3889    0.1563    1.4764    0.0399    1.1377    0.0715
-#> 449:    92.2054   -5.8195   -0.0718    2.3908   -0.9388    0.1411    3.1497    0.3730    0.3887    0.1562    1.4768    0.0399    1.1382    0.0715
-#> 450:    92.2054   -5.8205   -0.0719    2.3906   -0.9390    0.1417    3.1528    0.3728    0.3885    0.1562    1.4769    0.0399    1.1378    0.0715
-#> 451:    92.2053   -5.8213   -0.0720    2.3905   -0.9391    0.1423    3.1544    0.3725    0.3883    0.1561    1.4774    0.0399    1.1379    0.0715
-#> 452:    92.2054   -5.8218   -0.0720    2.3905   -0.9393    0.1426    3.1541    0.3722    0.3882    0.1560    1.4779    0.0398    1.1378    0.0715
-#> 453:    92.2054   -5.8217   -0.0721    2.3903   -0.9395    0.1428    3.1530    0.3721    0.3880    0.1559    1.4785    0.0398    1.1378    0.0715
-#> 454:    92.2053   -5.8214   -0.0722    2.3901   -0.9395    0.1431    3.1508    0.3720    0.3878    0.1559    1.4786    0.0398    1.1375    0.0715
-#> 455:    92.2052   -5.8220   -0.0724    2.3898   -0.9396    0.1433    3.1519    0.3720    0.3875    0.1559    1.4791    0.0398    1.1379    0.0715
-#> 456:    92.2053   -5.8230   -0.0727    2.3894   -0.9397    0.1434    3.1544    0.3720    0.3873    0.1560    1.4793    0.0398    1.1384    0.0714
-#> 457:    92.2053   -5.8240   -0.0729    2.3889   -0.9398    0.1437    3.1568    0.3720    0.3869    0.1559    1.4793    0.0398    1.1393    0.0714
-#> 458:    92.2051   -5.8245   -0.0731    2.3885   -0.9399    0.1440    3.1571    0.3721    0.3865    0.1558    1.4797    0.0397    1.1404    0.0713
-#> 459:    92.2045   -5.8246   -0.0732    2.3882   -0.9402    0.1442    3.1562    0.3721    0.3862    0.1558    1.4801    0.0397    1.1407    0.0713
-#> 460:    92.2040   -5.8244   -0.0734    2.3878   -0.9403    0.1442    3.1536    0.3722    0.3859    0.1558    1.4806    0.0397    1.1406    0.0713
-#> 461:    92.2030   -5.8245   -0.0736    2.3874   -0.9404    0.1444    3.1517    0.3722    0.3856    0.1557    1.4811    0.0397    1.1412    0.0713
-#> 462:    92.2022   -5.8253   -0.0738    2.3870   -0.9405    0.1445    3.1531    0.3723    0.3853    0.1556    1.4817    0.0396    1.1425    0.0712
-#> 463:    92.2014   -5.8260   -0.0740    2.3866   -0.9405    0.1449    3.1545    0.3724    0.3849    0.1556    1.4823    0.0396    1.1441    0.0711
-#> 464:    92.2008   -5.8257   -0.0742    2.3862   -0.9405    0.1453    3.1522    0.3726    0.3845    0.1555    1.4828    0.0396    1.1451    0.0711
-#> 465:    92.2002   -5.8256   -0.0744    2.3859   -0.9404    0.1458    3.1511    0.3727    0.3842    0.1555    1.4830    0.0396    1.1459    0.0710
-#> 466:    92.1997   -5.8256   -0.0747    2.3855   -0.9403    0.1463    3.1516    0.3728    0.3839    0.1555    1.4834    0.0396    1.1476    0.0709
-#> 467:    92.1993   -5.8258   -0.0749    2.3850   -0.9404    0.1468    3.1521    0.3730    0.3836    0.1555    1.4835    0.0395    1.1490    0.0708
-#> 468:    92.1990   -5.8259   -0.0752    2.3846   -0.9404    0.1473    3.1546    0.3731    0.3834    0.1555    1.4837    0.0395    1.1500    0.0708
-#> 469:    92.1987   -5.8263   -0.0753    2.3844   -0.9403    0.1479    3.1598    0.3731    0.3831    0.1555    1.4839    0.0395    1.1504    0.0707
-#> 470:    92.1987   -5.8267   -0.0755    2.3841   -0.9403    0.1482    3.1611    0.3730    0.3829    0.1555    1.4839    0.0395    1.1496    0.0708
-#> 471:    92.1987   -5.8269   -0.0756    2.3839   -0.9404    0.1482    3.1627    0.3730    0.3826    0.1555    1.4839    0.0395    1.1492    0.0708
-#> 472:    92.1983   -5.8269   -0.0758    2.3838   -0.9403    0.1480    3.1618    0.3729    0.3823    0.1555    1.4839    0.0395    1.1493    0.0708
-#> 473:    92.1980   -5.8264   -0.0760    2.3836   -0.9402    0.1478    3.1602    0.3728    0.3820    0.1554    1.4839    0.0395    1.1489    0.0708
-#> 474:    92.1976   -5.8256   -0.0762    2.3834   -0.9402    0.1475    3.1565    0.3727    0.3818    0.1554    1.4842    0.0395    1.1487    0.0708
-#> 475:    92.1971   -5.8252   -0.0763    2.3832   -0.9402    0.1473    3.1543    0.3726    0.3816    0.1553    1.4845    0.0395    1.1487    0.0707
-#> 476:    92.1965   -5.8250   -0.0765    2.3830   -0.9402    0.1469    3.1523    0.3725    0.3814    0.1552    1.4846    0.0395    1.1484    0.0707
-#> 477:    92.1960   -5.8242   -0.0766    2.3827   -0.9402    0.1465    3.1483    0.3724    0.3811    0.1552    1.4849    0.0395    1.1483    0.0708
-#> 478:    92.1955   -5.8236   -0.0767    2.3826   -0.9402    0.1463    3.1447    0.3722    0.3808    0.1553    1.4854    0.0395    1.1481    0.0708
-#> 479:    92.1952   -5.8232   -0.0769    2.3824   -0.9401    0.1462    3.1421    0.3722    0.3805    0.1554    1.4857    0.0395    1.1478    0.0708
-#> 480:    92.1948   -5.8235   -0.0770    2.3822   -0.9400    0.1461    3.1426    0.3721    0.3803    0.1554    1.4862    0.0395    1.1478    0.0708
-#> 481:    92.1947   -5.8240   -0.0772    2.3820   -0.9399    0.1459    3.1455    0.3721    0.3801    0.1554    1.4868    0.0395    1.1483    0.0708
-#> 482:    92.1948   -5.8244   -0.0774    2.3817   -0.9399    0.1456    3.1476    0.3720    0.3799    0.1553    1.4873    0.0395    1.1488    0.0708
-#> 483:    92.1944   -5.8247   -0.0776    2.3815   -0.9397    0.1455    3.1487    0.3719    0.3797    0.1553    1.4876    0.0394    1.1494    0.0708
-#> 484:    92.1941   -5.8249   -0.0778    2.3811   -0.9396    0.1454    3.1493    0.3719    0.3795    0.1554    1.4879    0.0394    1.1501    0.0707
-#> 485:    92.1940   -5.8252   -0.0780    2.3809   -0.9396    0.1453    3.1501    0.3718    0.3793    0.1554    1.4881    0.0394    1.1503    0.0707
-#> 486:    92.1936   -5.8249   -0.0781    2.3807   -0.9395    0.1453    3.1486    0.3717    0.3792    0.1554    1.4884    0.0394    1.1508    0.0707
-#> 487:    92.1935   -5.8248   -0.0783    2.3804   -0.9394    0.1453    3.1485    0.3716    0.3791    0.1553    1.4887    0.0393    1.1507    0.0707
-#> 488:    92.1932   -5.8246   -0.0785    2.3800   -0.9394    0.1454    3.1478    0.3715    0.3788    0.1552    1.4892    0.0393    1.1510    0.0707
-#> 489:    92.1931   -5.8241   -0.0787    2.3796   -0.9394    0.1455    3.1468    0.3715    0.3787    0.1551    1.4895    0.0393    1.1514    0.0706
-#> 490:    92.1934   -5.8242   -0.0790    2.3793   -0.9393    0.1456    3.1478    0.3715    0.3786    0.1551    1.4898    0.0393    1.1528    0.0706
-#> 491:    92.1936   -5.8241   -0.0792    2.3788   -0.9392    0.1455    3.1472    0.3715    0.3785    0.1551    1.4900    0.0393    1.1533    0.0706
-#> 492:    92.1940   -5.8234   -0.0794    2.3783   -0.9391    0.1455    3.1449    0.3714    0.3783    0.1551    1.4903    0.0392    1.1538    0.0705
-#> 493:    92.1943   -5.8230   -0.0797    2.3779   -0.9390    0.1455    3.1426    0.3714    0.3783    0.1552    1.4907    0.0392    1.1541    0.0705
-#> 494:    92.1946   -5.8226   -0.0799    2.3774   -0.9390    0.1458    3.1405    0.3713    0.3782    0.1551    1.4911    0.0392    1.1541    0.0706
-#> 495:    92.1948   -5.8219   -0.0802    2.3770   -0.9391    0.1459    3.1366    0.3712    0.3782    0.1551    1.4916    0.0392    1.1543    0.0706
-#> 496:    92.1948   -5.8213   -0.0804    2.3766   -0.9392    0.1460    3.1331    0.3711    0.3781    0.1552    1.4920    0.0392    1.1556    0.0705
-#> 497:    92.1949   -5.8213   -0.0806    2.3762   -0.9393    0.1462    3.1326    0.3711    0.3780    0.1553    1.4923    0.0391    1.1564    0.0705
-#> 498:    92.1950   -5.8215   -0.0808    2.3758   -0.9394    0.1462    3.1331    0.3710    0.3779    0.1553    1.4926    0.0391    1.1568    0.0705
-#> 499:    92.1953   -5.8219   -0.0810    2.3754   -0.9395    0.1461    3.1343    0.3709    0.3778    0.1554    1.4929    0.0391    1.1567    0.0705
-#> 500:    92.1957   -5.8232   -0.0812    2.3751   -0.9395    0.1459    3.1411    0.3709    0.3776    0.1554    1.4931    0.0391    1.1575    0.0705
-#> Calculating covariance matrix
-#> 
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> Needed Covariates:
-#> [1] "CMT"
-#> Calculating residuals/tables
-#> done
-f_nlmixr_fomc_sfo_focei_obs_tc <- nlmixr(f_mmkin_tc["FOMC-SFO", ], est = "focei",
-  error_model = "obs_tc")
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → calculate jacobian
-#> 
-#> → calculate sensitivities
-#> 
-#> → calculate ∂(f)/∂(η)
-#> 
-#> → calculate ∂(R²)/∂(η)
-#> 
-#> → finding duplicate expressions in inner model...
-#> 
-#> → optimizing duplicate expressions in inner model...
-#> 
-#> → finding duplicate expressions in EBE model...
-#> 
-#> → optimizing duplicate expressions in EBE model...
-#> 
-#> → compiling inner model...
-#>  
-#> ✔ done
-#> → finding duplicate expressions in FD model...
-#> 
-#> → optimizing duplicate expressions in FD model...
-#> 
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> → compiling events FD model...
-#>  
-#> ✔ done
-#> Needed Covariates:
-#> [1] "CMT"
-#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> |    #| Objective Fun |  parent_0 |  log_k_A1 |f_parent_qlogis | log_alpha |
-#> |.....................|  log_beta |sigma_low_parent |rsd_high_parent |sigma_low_A1 |
-#> |.....................|rsd_high_A1 |        o1 |        o2 |        o3 |
-#> |.....................|        o4 |        o5 |...........|...........|
-#> |    1|     500.20030 |     1.000 |    -1.000 |   -0.9113 |   -0.8944 |
-#> |.....................|   -0.8454 |   -0.8678 |   -0.8916 |   -0.8678 |
-#> |.....................|   -0.8916 |   -0.8767 |   -0.8743 |   -0.8675 |
-#> |.....................|   -0.8704 |   -0.8704 |...........|...........|
-#> |    U|      500.2003 |     93.00 |    -5.300 |   -0.9400 |   -0.1100 |
-#> |.....................|     2.300 |     1.200 |   0.03000 |     1.200 |
-#> |.....................|   0.03000 |    0.7598 |    0.8758 |     1.214 |
-#> |.....................|     1.068 |     1.071 |...........|...........|
-#> |    X|      500.2003 |     93.00 |  0.004992 |    0.2809 |    0.8958 |
-#> |.....................|     9.974 |     1.200 |   0.03000 |     1.200 |
-#> |.....................|   0.03000 |    0.7598 |    0.8758 |     1.214 |
-#> |.....................|     1.068 |     1.071 |...........|...........|
-#> |    G|    Gill Diff. |     48.88 |     2.383 |    0.1231 |    0.1986 |
-#> |.....................|    0.1571 |    -68.85 |    -20.11 |     3.616 |
-#> |.....................|    -2.292 |    0.6250 |     11.41 |    -12.48 |
-#> |.....................|    -9.903 |    -10.91 |...........|...........|
-#> |    2|     2737.7532 |    0.4556 |    -1.027 |   -0.9127 |   -0.8966 |
-#> |.....................|   -0.8471 |   -0.1009 |   -0.6676 |   -0.9080 |
-#> |.....................|   -0.8660 |   -0.8837 |    -1.001 |   -0.7285 |
-#> |.....................|   -0.7601 |   -0.7489 |...........|...........|
-#> |    U|     2737.7532 |     42.37 |    -5.327 |   -0.9413 |   -0.1122 |
-#> |.....................|     2.298 |     1.660 |   0.03336 |     1.176 |
-#> |.....................|   0.03038 |    0.7545 |    0.7645 |     1.383 |
-#> |.....................|     1.185 |     1.201 |...........|...........|
-#> |    X|     2737.7532 |     42.37 |  0.004861 |    0.2806 |    0.8939 |
-#> |.....................|     9.957 |     1.660 |   0.03336 |     1.176 |
-#> |.....................|   0.03038 |    0.7545 |    0.7645 |     1.383 |
-#> |.....................|     1.185 |     1.201 |...........|...........|
-#> |    3|     513.07755 |    0.9456 |    -1.003 |   -0.9114 |   -0.8946 |
-#> |.....................|   -0.8455 |   -0.7911 |   -0.8692 |   -0.8718 |
-#> |.....................|   -0.8890 |   -0.8774 |   -0.8871 |   -0.8536 |
-#> |.....................|   -0.8594 |   -0.8582 |...........|...........|
-#> |    U|     513.07755 |     87.94 |    -5.303 |   -0.9401 |   -0.1102 |
-#> |.....................|     2.300 |     1.246 |   0.03034 |     1.198 |
-#> |.....................|   0.03004 |    0.7593 |    0.8646 |     1.231 |
-#> |.....................|     1.079 |     1.084 |...........|...........|
-#> |    X|     513.07755 |     87.94 |  0.004978 |    0.2809 |    0.8956 |
-#> |.....................|     9.972 |     1.246 |   0.03034 |     1.198 |
-#> |.....................|   0.03004 |    0.7593 |    0.8646 |     1.231 |
-#> |.....................|     1.079 |     1.084 |...........|...........|
-#> |    4|     499.28604 |    0.9888 |    -1.001 |   -0.9113 |   -0.8945 |
-#> |.....................|   -0.8454 |   -0.8520 |   -0.8870 |   -0.8686 |
-#> |.....................|   -0.8910 |   -0.8769 |   -0.8770 |   -0.8646 |
-#> |.....................|   -0.8682 |   -0.8679 |...........|...........|
-#> |    U|     499.28604 |     91.96 |    -5.301 |   -0.9400 |   -0.1100 |
-#> |.....................|     2.300 |     1.209 |   0.03007 |     1.200 |
-#> |.....................|   0.03001 |    0.7597 |    0.8735 |     1.218 |
-#> |.....................|     1.070 |     1.074 |...........|...........|
-#> |    X|     499.28604 |     91.96 |  0.004989 |    0.2809 |    0.8958 |
-#> |.....................|     9.974 |     1.209 |   0.03007 |     1.200 |
-#> |.....................|   0.03001 |    0.7597 |    0.8735 |     1.218 |
-#> |.....................|     1.070 |     1.074 |...........|...........|
-#> |    F| Forward Diff. |    -111.5 |     2.236 |   -0.2057 |    0.1035 |
-#> |.....................|   -0.1971 |    -66.17 |    -21.17 |     4.107 |
-#> |.....................|    -1.586 |     1.583 |     8.991 |    -11.70 |
-#> |.....................|    -9.625 |    -10.49 |...........|...........|
-#> |    5|     497.76004 |     1.001 |    -1.001 |   -0.9113 |   -0.8945 |
-#> |.....................|   -0.8454 |   -0.8366 |   -0.8822 |   -0.8695 |
-#> |.....................|   -0.8906 |   -0.8771 |   -0.8792 |   -0.8619 |
-#> |.....................|   -0.8660 |   -0.8654 |...........|...........|
-#> |    U|     497.76004 |     93.05 |    -5.301 |   -0.9400 |   -0.1101 |
-#> |.....................|     2.300 |     1.219 |   0.03014 |     1.199 |
-#> |.....................|   0.03001 |    0.7595 |    0.8715 |     1.221 |
-#> |.....................|     1.072 |     1.076 |...........|...........|
-#> |    X|     497.76004 |     93.05 |  0.004986 |    0.2809 |    0.8958 |
-#> |.....................|     9.974 |     1.219 |   0.03014 |     1.199 |
-#> |.....................|   0.03001 |    0.7595 |    0.8715 |     1.221 |
-#> |.....................|     1.072 |     1.076 |...........|...........|
-#> |    F| Forward Diff. |     56.91 |     2.356 |    0.1468 |    0.2109 |
-#> |.....................|    0.1761 |    -64.61 |    -18.67 |     3.291 |
-#> |.....................|    -1.680 |     1.108 |     8.338 |    -11.70 |
-#> |.....................|    -9.518 |    -10.47 |...........|...........|
-#> |    6|     496.73820 |    0.9899 |    -1.002 |   -0.9113 |   -0.8945 |
-#> |.....................|   -0.8454 |   -0.8205 |   -0.8775 |   -0.8703 |
-#> |.....................|   -0.8902 |   -0.8774 |   -0.8813 |   -0.8590 |
-#> |.....................|   -0.8636 |   -0.8628 |...........|...........|
-#> |    U|      496.7382 |     92.06 |    -5.302 |   -0.9400 |   -0.1101 |
-#> |.....................|     2.300 |     1.228 |   0.03021 |     1.198 |
-#> |.....................|   0.03002 |    0.7593 |    0.8696 |     1.225 |
-#> |.....................|     1.075 |     1.079 |...........|...........|
-#> |    X|      496.7382 |     92.06 |  0.004983 |    0.2809 |    0.8957 |
-#> |.....................|     9.974 |     1.228 |   0.03021 |     1.198 |
-#> |.....................|   0.03002 |    0.7593 |    0.8696 |     1.225 |
-#> |.....................|     1.075 |     1.079 |...........|...........|
-#> |    F| Forward Diff. |    -94.52 |     2.222 |   -0.1721 |    0.1131 |
-#> |.....................|   -0.1712 |    -62.76 |    -19.55 |     3.974 |
-#> |.....................|    -1.718 |     1.304 |     7.360 |    -11.47 |
-#> |.....................|    -9.402 |    -10.21 |...........|...........|
-#> |    7|     495.33979 |     1.001 |    -1.002 |   -0.9113 |   -0.8946 |
-#> |.....................|   -0.8454 |   -0.8044 |   -0.8726 |   -0.8713 |
-#> |.....................|   -0.8897 |   -0.8777 |   -0.8834 |   -0.8560 |
-#> |.....................|   -0.8612 |   -0.8602 |...........|...........|
-#> |    U|     495.33979 |     93.05 |    -5.302 |   -0.9400 |   -0.1102 |
-#> |.....................|     2.300 |     1.238 |   0.03028 |     1.198 |
-#> |.....................|   0.03003 |    0.7591 |    0.8679 |     1.228 |
-#> |.....................|     1.077 |     1.082 |...........|...........|
-#> |    X|     495.33979 |     93.05 |  0.004981 |    0.2809 |    0.8957 |
-#> |.....................|     9.974 |     1.238 |   0.03028 |     1.198 |
-#> |.....................|   0.03003 |    0.7591 |    0.8679 |     1.228 |
-#> |.....................|     1.077 |     1.082 |...........|...........|
-#> |    F| Forward Diff. |     56.11 |     2.327 |    0.1520 |    0.2091 |
-#> |.....................|    0.1742 |    -61.13 |    -17.23 |     3.435 |
-#> |.....................|    -1.620 |     1.132 |     9.399 |    -11.44 |
-#> |.....................|    -9.328 |    -10.19 |...........|...........|
-#> |    8|     494.31617 |    0.9904 |    -1.003 |   -0.9113 |   -0.8946 |
-#> |.....................|   -0.8455 |   -0.7881 |   -0.8680 |   -0.8722 |
-#> |.....................|   -0.8893 |   -0.8780 |   -0.8859 |   -0.8530 |
-#> |.....................|   -0.8587 |   -0.8575 |...........|...........|
-#> |    U|     494.31617 |     92.11 |    -5.303 |   -0.9400 |   -0.1102 |
-#> |.....................|     2.300 |     1.248 |   0.03035 |     1.197 |
-#> |.....................|   0.03003 |    0.7589 |    0.8657 |     1.232 |
-#> |.....................|     1.080 |     1.085 |...........|...........|
-#> |    X|     494.31617 |     92.11 |  0.004977 |    0.2809 |    0.8956 |
-#> |.....................|     9.973 |     1.248 |   0.03035 |     1.197 |
-#> |.....................|   0.03003 |    0.7589 |    0.8657 |     1.232 |
-#> |.....................|     1.080 |     1.085 |...........|...........|
-#> |    F| Forward Diff. |    -86.81 |     2.198 |   -0.1566 |    0.1238 |
-#> |.....................|   -0.1638 |    -59.37 |    -18.02 |     4.057 |
-#> |.....................|    -1.591 |     1.325 |     8.479 |    -11.19 |
-#> |.....................|    -9.201 |    -9.937 |...........|...........|
-#> |    9|     493.00423 |     1.001 |    -1.003 |   -0.9113 |   -0.8947 |
-#> |.....................|   -0.8454 |   -0.7718 |   -0.8631 |   -0.8732 |
-#> |.....................|   -0.8888 |   -0.8783 |   -0.8883 |   -0.8499 |
-#> |.....................|   -0.8562 |   -0.8548 |...........|...........|
-#> |    U|     493.00423 |     93.05 |    -5.303 |   -0.9400 |   -0.1103 |
-#> |.....................|     2.300 |     1.258 |   0.03043 |     1.197 |
-#> |.....................|   0.03004 |    0.7586 |    0.8635 |     1.236 |
-#> |.....................|     1.083 |     1.088 |...........|...........|
-#> |    X|     493.00423 |     93.05 |  0.004974 |    0.2809 |    0.8956 |
-#> |.....................|     9.974 |     1.258 |   0.03043 |     1.197 |
-#> |.....................|   0.03004 |    0.7586 |    0.8635 |     1.236 |
-#> |.....................|     1.083 |     1.088 |...........|...........|
-#> |    F| Forward Diff. |     54.84 |     2.286 |    0.1404 |    0.2142 |
-#> |.....................|    0.1628 |    -57.96 |    -15.94 |     3.372 |
-#> |.....................|    -1.642 |     1.184 |     9.036 |    -11.17 |
-#> |.....................|    -9.110 |    -9.901 |...........|...........|
-#> |   10|     491.99601 |    0.9908 |    -1.004 |   -0.9114 |   -0.8947 |
-#> |.....................|   -0.8455 |   -0.7552 |   -0.8585 |   -0.8742 |
-#> |.....................|   -0.8884 |   -0.8786 |   -0.8910 |   -0.8467 |
-#> |.....................|   -0.8536 |   -0.8520 |...........|...........|
-#> |    U|     491.99601 |     92.15 |    -5.304 |   -0.9401 |   -0.1103 |
-#> |.....................|     2.300 |     1.268 |   0.03050 |     1.196 |
-#> |.....................|   0.03005 |    0.7584 |    0.8612 |     1.239 |
-#> |.....................|     1.085 |     1.091 |...........|...........|
-#> |    X|     491.99601 |     92.15 |  0.004971 |    0.2809 |    0.8956 |
-#> |.....................|     9.973 |     1.268 |   0.03050 |     1.196 |
-#> |.....................|   0.03005 |    0.7584 |    0.8612 |     1.239 |
-#> |.....................|     1.085 |     1.091 |...........|...........|
-#> |    F| Forward Diff. |    -80.67 |     2.171 |   -0.1367 |    0.1256 |
-#> |.....................|   -0.1610 |    -56.13 |    -16.61 |     4.047 |
-#> |.....................|    -1.607 |     1.226 |     8.142 |    -10.92 |
-#> |.....................|    -8.982 |    -9.644 |...........|...........|
-#> |   11|     490.76421 |     1.000 |    -1.005 |   -0.9113 |   -0.8948 |
-#> |.....................|   -0.8455 |   -0.7388 |   -0.8538 |   -0.8754 |
-#> |.....................|   -0.8879 |   -0.8790 |   -0.8935 |   -0.8435 |
-#> |.....................|   -0.8510 |   -0.8492 |...........|...........|
-#> |    U|     490.76421 |     93.04 |    -5.305 |   -0.9401 |   -0.1104 |
-#> |.....................|     2.300 |     1.277 |   0.03057 |     1.195 |
-#> |.....................|   0.03006 |    0.7581 |    0.8590 |     1.243 |
-#> |.....................|     1.088 |     1.094 |...........|...........|
-#> |    X|     490.76421 |     93.04 |  0.004968 |    0.2809 |    0.8955 |
-#> |.....................|     9.973 |     1.277 |   0.03057 |     1.195 |
-#> |.....................|   0.03006 |    0.7581 |    0.8590 |     1.243 |
-#> |.....................|     1.088 |     1.094 |...........|...........|
-#> |    F| Forward Diff. |     54.34 |     2.256 |    0.1715 |    0.2224 |
-#> |.....................|    0.1653 |    -54.87 |    -14.72 |     3.299 |
-#> |.....................|    -1.777 |     1.023 |     8.651 |    -10.90 |
-#> |.....................|    -8.887 |    -9.594 |...........|...........|
-#> |   12|     489.76286 |    0.9913 |    -1.005 |   -0.9114 |   -0.8948 |
-#> |.....................|   -0.8455 |   -0.7220 |   -0.8492 |   -0.8764 |
-#> |.....................|   -0.8873 |   -0.8793 |   -0.8962 |   -0.8402 |
-#> |.....................|   -0.8483 |   -0.8462 |...........|...........|
-#> |    U|     489.76286 |     92.19 |    -5.305 |   -0.9401 |   -0.1104 |
-#> |.....................|     2.300 |     1.287 |   0.03063 |     1.195 |
-#> |.....................|   0.03006 |    0.7579 |    0.8566 |     1.247 |
-#> |.....................|     1.091 |     1.097 |...........|...........|
-#> |    X|     489.76286 |     92.19 |  0.004965 |    0.2809 |    0.8955 |
-#> |.....................|     9.973 |     1.287 |   0.03063 |     1.195 |
-#> |.....................|   0.03006 |    0.7579 |    0.8566 |     1.247 |
-#> |.....................|     1.091 |     1.097 |...........|...........|
-#> |    F| Forward Diff. |    -73.18 |     2.145 |   -0.1190 |    0.1261 |
-#> |.....................|   -0.1580 |    -53.08 |    -15.27 |     4.015 |
-#> |.....................|    -1.639 |     1.110 |     7.813 |    -10.65 |
-#> |.....................|    -8.743 |    -9.338 |...........|...........|
-#> |   13|     488.61493 |     1.000 |    -1.006 |   -0.9114 |   -0.8949 |
-#> |.....................|   -0.8455 |   -0.7053 |   -0.8446 |   -0.8776 |
-#> |.....................|   -0.8867 |   -0.8796 |   -0.8989 |   -0.8368 |
-#> |.....................|   -0.8455 |   -0.8433 |...........|...........|
-#> |    U|     488.61493 |     93.04 |    -5.306 |   -0.9401 |   -0.1105 |
-#> |.....................|     2.300 |     1.297 |   0.03070 |     1.194 |
-#> |.....................|   0.03007 |    0.7577 |    0.8543 |     1.252 |
-#> |.....................|     1.094 |     1.100 |...........|...........|
-#> |    X|     488.61493 |     93.04 |  0.004961 |    0.2809 |    0.8954 |
-#> |.....................|     9.973 |     1.297 |   0.03070 |     1.194 |
-#> |.....................|   0.03007 |    0.7577 |    0.8543 |     1.252 |
-#> |.....................|     1.094 |     1.100 |...........|...........|
-#> |    F| Forward Diff. |     54.41 |     2.230 |    0.1889 |    0.2376 |
-#> |.....................|    0.1637 |    -52.01 |    -13.54 |     3.223 |
-#> |.....................|    -1.937 |    0.8847 |     10.07 |    -10.59 |
-#> |.....................|    -8.650 |    -9.282 |...........|...........|
-#> |   14|     487.61806 |    0.9919 |    -1.007 |   -0.9114 |   -0.8949 |
-#> |.....................|   -0.8455 |   -0.6884 |   -0.8402 |   -0.8788 |
-#> |.....................|   -0.8861 |   -0.8798 |   -0.9022 |   -0.8333 |
-#> |.....................|   -0.8427 |   -0.8402 |...........|...........|
-#> |    U|     487.61806 |     92.24 |    -5.307 |   -0.9401 |   -0.1105 |
-#> |.....................|     2.300 |     1.308 |   0.03077 |     1.193 |
-#> |.....................|   0.03008 |    0.7575 |    0.8514 |     1.256 |
-#> |.....................|     1.097 |     1.103 |...........|...........|
-#> |    X|     487.61806 |     92.24 |  0.004958 |    0.2809 |    0.8953 |
-#> |.....................|     9.973 |     1.308 |   0.03077 |     1.193 |
-#> |.....................|   0.03008 |    0.7575 |    0.8514 |     1.256 |
-#> |.....................|     1.097 |     1.103 |...........|...........|
-#> |    F| Forward Diff. |    -64.97 |     2.116 |  -0.09941 |    0.1372 |
-#> |.....................|   -0.1475 |    -50.35 |    -14.02 |     3.916 |
-#> |.....................|    -1.790 |    0.8979 |     9.163 |    -10.32 |
-#> |.....................|    -8.505 |    -9.022 |...........|...........|
-#> |   15|     486.55968 |     1.001 |    -1.008 |   -0.9114 |   -0.8950 |
-#> |.....................|   -0.8455 |   -0.6717 |   -0.8358 |   -0.8800 |
-#> |.....................|   -0.8854 |   -0.8801 |   -0.9058 |   -0.8297 |
-#> |.....................|   -0.8398 |   -0.8372 |...........|...........|
-#> |    U|     486.55968 |     93.05 |    -5.308 |   -0.9401 |   -0.1106 |
-#> |.....................|     2.300 |     1.318 |   0.03084 |     1.193 |
-#> |.....................|   0.03009 |    0.7573 |    0.8482 |     1.260 |
-#> |.....................|     1.100 |     1.107 |...........|...........|
-#> |    X|     486.55968 |     93.05 |  0.004954 |    0.2809 |    0.8953 |
-#> |.....................|     9.973 |     1.318 |   0.03084 |     1.193 |
-#> |.....................|   0.03009 |    0.7573 |    0.8482 |     1.260 |
-#> |.....................|     1.100 |     1.107 |...........|...........|
-#> |    F| Forward Diff. |     55.08 |     2.188 |    0.1916 |    0.2341 |
-#> |.....................|    0.1660 |    -48.95 |    -12.27 |     3.347 |
-#> |.....................|    -1.726 |    0.9589 |     6.446 |    -10.30 |
-#> |.....................|    -8.390 |    -8.950 |...........|...........|
-#> |   16|     485.60262 |    0.9920 |    -1.008 |   -0.9115 |   -0.8951 |
-#> |.....................|   -0.8455 |   -0.6547 |   -0.8316 |   -0.8813 |
-#> |.....................|   -0.8847 |   -0.8804 |   -0.9083 |   -0.8260 |
-#> |.....................|   -0.8367 |   -0.8340 |...........|...........|
-#> |    U|     485.60262 |     92.26 |    -5.308 |   -0.9402 |   -0.1107 |
-#> |.....................|     2.300 |     1.328 |   0.03090 |     1.192 |
-#> |.....................|   0.03010 |    0.7571 |    0.8460 |     1.265 |
-#> |.....................|     1.104 |     1.110 |...........|...........|
-#> |    X|     485.60262 |     92.26 |  0.004950 |    0.2809 |    0.8952 |
-#> |.....................|     9.973 |     1.328 |   0.03090 |     1.192 |
-#> |.....................|   0.03010 |    0.7571 |    0.8460 |     1.265 |
-#> |.....................|     1.104 |     1.110 |...........|...........|
-#> |    F| Forward Diff. |    -62.47 |     2.078 |  -0.09882 |    0.1294 |
-#> |.....................|   -0.1587 |    -47.42 |    -12.81 |     3.926 |
-#> |.....................|    -1.683 |    0.9415 |     5.611 |    -10.02 |
-#> |.....................|    -8.237 |    -8.679 |...........|...........|
-#> |   17|     484.58535 |     1.000 |    -1.009 |   -0.9115 |   -0.8952 |
-#> |.....................|   -0.8455 |   -0.6375 |   -0.8274 |   -0.8829 |
-#> |.....................|   -0.8840 |   -0.8807 |   -0.9099 |   -0.8222 |
-#> |.....................|   -0.8336 |   -0.8307 |...........|...........|
-#> |    U|     484.58535 |     93.02 |    -5.309 |   -0.9402 |   -0.1107 |
-#> |.....................|     2.300 |     1.338 |   0.03096 |     1.191 |
-#> |.....................|   0.03011 |    0.7568 |    0.8446 |     1.269 |
-#> |.....................|     1.107 |     1.114 |...........|...........|
-#> |    X|     484.58535 |     93.02 |  0.004946 |    0.2809 |    0.8952 |
-#> |.....................|     9.973 |     1.338 |   0.03096 |     1.191 |
-#> |.....................|   0.03011 |    0.7568 |    0.8446 |     1.269 |
-#> |.....................|     1.107 |     1.114 |...........|...........|
-#> |    F| Forward Diff. |     50.15 |     2.155 |    0.1960 |    0.2225 |
-#> |.....................|    0.1509 |    -46.14 |    -11.19 |     3.405 |
-#> |.....................|    -1.652 |     1.035 |     7.536 |    -9.951 |
-#> |.....................|    -8.121 |    -8.609 |...........|...........|
-#> |   18|     483.66860 |    0.9923 |    -1.010 |   -0.9115 |   -0.8952 |
-#> |.....................|   -0.8455 |   -0.6203 |   -0.8235 |   -0.8844 |
-#> |.....................|   -0.8833 |   -0.8810 |   -0.9123 |   -0.8182 |
-#> |.....................|   -0.8303 |   -0.8273 |...........|...........|
-#> |    U|      483.6686 |     92.29 |    -5.310 |   -0.9402 |   -0.1108 |
-#> |.....................|     2.300 |     1.348 |   0.03102 |     1.190 |
-#> |.....................|   0.03012 |    0.7565 |    0.8425 |     1.274 |
-#> |.....................|     1.110 |     1.117 |...........|...........|
-#> |    X|      483.6686 |     92.29 |  0.004942 |    0.2809 |    0.8951 |
-#> |.....................|     9.973 |     1.348 |   0.03102 |     1.190 |
-#> |.....................|   0.03012 |    0.7565 |    0.8425 |     1.274 |
-#> |.....................|     1.110 |     1.117 |...........|...........|
-#> |    F| Forward Diff. |    -57.62 |     2.059 |  -0.07549 |    0.1395 |
-#> |.....................|   -0.1501 |    -44.74 |    -11.66 |     3.913 |
-#> |.....................|    -1.664 |    0.8845 |     6.781 |    -9.703 |
-#> |.....................|    -7.961 |    -8.325 |...........|...........|
-#> |   19|     482.71012 |     1.000 |    -1.011 |   -0.9115 |   -0.8953 |
-#> |.....................|   -0.8455 |   -0.6032 |   -0.8198 |   -0.8861 |
-#> |.....................|   -0.8825 |   -0.8814 |   -0.9153 |   -0.8141 |
-#> |.....................|   -0.8270 |   -0.8239 |...........|...........|
-#> |    U|     482.71012 |     93.02 |    -5.311 |   -0.9402 |   -0.1109 |
-#> |.....................|     2.300 |     1.359 |   0.03108 |     1.189 |
-#> |.....................|   0.03014 |    0.7563 |    0.8399 |     1.279 |
-#> |.....................|     1.114 |     1.121 |...........|...........|
-#> |    X|     482.71012 |     93.02 |  0.004937 |    0.2809 |    0.8950 |
-#> |.....................|     9.973 |     1.359 |   0.03108 |     1.189 |
-#> |.....................|   0.03014 |    0.7563 |    0.8399 |     1.279 |
-#> |.....................|     1.114 |     1.121 |...........|...........|
-#> |    F| Forward Diff. |     48.98 |     2.122 |    0.2043 |    0.2315 |
-#> |.....................|    0.1449 |    -43.47 |    -10.15 |     3.365 |
-#> |.....................|    -1.703 |    0.9582 |     7.160 |    -9.600 |
-#> |.....................|    -7.838 |    -8.245 |...........|...........|
-#> |   20|     481.83107 |    0.9926 |    -1.012 |   -0.9116 |   -0.8954 |
-#> |.....................|   -0.8455 |   -0.5860 |   -0.8164 |   -0.8879 |
-#> |.....................|   -0.8817 |   -0.8818 |   -0.9184 |   -0.8098 |
-#> |.....................|   -0.8235 |   -0.8203 |...........|...........|
-#> |    U|     481.83107 |     92.31 |    -5.312 |   -0.9403 |   -0.1110 |
-#> |.....................|     2.300 |     1.369 |   0.03113 |     1.188 |
-#> |.....................|   0.03015 |    0.7560 |    0.8372 |     1.284 |
-#> |.....................|     1.118 |     1.125 |...........|...........|
-#> |    X|     481.83107 |     92.31 |  0.004932 |    0.2808 |    0.8949 |
-#> |.....................|     9.973 |     1.369 |   0.03113 |     1.188 |
-#> |.....................|   0.03015 |    0.7560 |    0.8372 |     1.284 |
-#> |.....................|     1.118 |     1.125 |...........|...........|
-#> |    F| Forward Diff. |    -54.27 |     2.027 |  -0.06740 |    0.1414 |
-#> |.....................|   -0.1465 |    -41.84 |    -10.48 |     3.798 |
-#> |.....................|    -1.730 |    0.8044 |     6.401 |    -9.335 |
-#> |.....................|    -7.662 |    -7.960 |...........|...........|
-#> |   21|     480.92878 |     1.000 |    -1.013 |   -0.9117 |   -0.8955 |
-#> |.....................|   -0.8455 |   -0.5689 |   -0.8133 |   -0.8899 |
-#> |.....................|   -0.8807 |   -0.8821 |   -0.9215 |   -0.8053 |
-#> |.....................|   -0.8199 |   -0.8166 |...........|...........|
-#> |    U|     480.92878 |     93.01 |    -5.313 |   -0.9403 |   -0.1111 |
-#> |.....................|     2.300 |     1.379 |   0.03117 |     1.187 |
-#> |.....................|   0.03016 |    0.7557 |    0.8345 |     1.290 |
-#> |.....................|     1.122 |     1.129 |...........|...........|
-#> |    X|     480.92878 |     93.01 |  0.004927 |    0.2808 |    0.8948 |
-#> |.....................|     9.973 |     1.379 |   0.03117 |     1.187 |
-#> |.....................|   0.03016 |    0.7557 |    0.8345 |     1.290 |
-#> |.....................|     1.122 |     1.129 |...........|...........|
-#> |    F| Forward Diff. |     47.18 |     2.077 |    0.1996 |    0.2200 |
-#> |.....................|    0.1318 |    -41.07 |    -9.197 |     3.259 |
-#> |.....................|    -1.748 |    0.9101 |     6.743 |    -9.229 |
-#> |.....................|    -7.511 |    -7.855 |...........|...........|
-#> |   22|     480.07574 |    0.9930 |    -1.014 |   -0.9117 |   -0.8956 |
-#> |.....................|   -0.8455 |   -0.5517 |   -0.8106 |   -0.8919 |
-#> |.....................|   -0.8795 |   -0.8825 |   -0.9247 |   -0.8007 |
-#> |.....................|   -0.8161 |   -0.8129 |...........|...........|
-#> |    U|     480.07574 |     92.35 |    -5.314 |   -0.9404 |   -0.1112 |
-#> |.....................|     2.300 |     1.390 |   0.03121 |     1.186 |
-#> |.....................|   0.03018 |    0.7555 |    0.8317 |     1.295 |
-#> |.....................|     1.126 |     1.133 |...........|...........|
-#> |    X|     480.07574 |     92.35 |  0.004921 |    0.2808 |    0.8947 |
-#> |.....................|     9.973 |     1.390 |   0.03121 |     1.186 |
-#> |.....................|   0.03018 |    0.7555 |    0.8317 |     1.295 |
-#> |.....................|     1.126 |     1.133 |...........|...........|
-#> |    F| Forward Diff. |    -48.22 |     1.995 |  -0.04658 |    0.1415 |
-#> |.....................|   -0.1316 |    -39.56 |    -9.522 |     3.639 |
-#> |.....................|    -1.878 |    0.6154 |     4.556 |    -8.937 |
-#> |.....................|    -7.320 |    -7.563 |...........|...........|
-#> |   23|     479.25211 |     1.000 |    -1.015 |   -0.9118 |   -0.8957 |
-#> |.....................|   -0.8454 |   -0.5343 |   -0.8082 |   -0.8940 |
-#> |.....................|   -0.8781 |   -0.8826 |   -0.9261 |   -0.7958 |
-#> |.....................|   -0.8122 |   -0.8090 |...........|...........|
-#> |    U|     479.25211 |     93.02 |    -5.315 |   -0.9405 |   -0.1113 |
-#> |.....................|     2.300 |     1.400 |   0.03125 |     1.184 |
-#> |.....................|   0.03020 |    0.7553 |    0.8305 |     1.301 |
-#> |.....................|     1.130 |     1.137 |...........|...........|
-#> |    X|     479.25211 |     93.02 |  0.004915 |    0.2808 |    0.8946 |
-#> |.....................|     9.974 |     1.400 |   0.03125 |     1.184 |
-#> |.....................|   0.03020 |    0.7553 |    0.8305 |     1.301 |
-#> |.....................|     1.130 |     1.137 |...........|...........|
-#> |    F| Forward Diff. |     48.39 |     2.048 |    0.2189 |    0.2175 |
-#> |.....................|    0.1393 |    -38.80 |    -8.286 |     3.169 |
-#> |.....................|    -1.757 |    0.9021 |     6.456 |    -8.802 |
-#> |.....................|    -7.165 |    -7.452 |...........|...........|
-#> |   24|     478.42395 |    0.9935 |    -1.017 |   -0.9119 |   -0.8959 |
-#> |.....................|   -0.8454 |   -0.5169 |   -0.8064 |   -0.8963 |
-#> |.....................|   -0.8766 |   -0.8829 |   -0.9277 |   -0.7908 |
-#> |.....................|   -0.8081 |   -0.8051 |...........|...........|
-#> |    U|     478.42395 |     92.40 |    -5.317 |   -0.9406 |   -0.1115 |
-#> |.....................|     2.300 |     1.411 |   0.03128 |     1.183 |
-#> |.....................|   0.03022 |    0.7552 |    0.8290 |     1.307 |
-#> |.....................|     1.134 |     1.141 |...........|...........|
-#> |    X|     478.42395 |     92.40 |  0.004909 |    0.2808 |    0.8945 |
-#> |.....................|     9.974 |     1.411 |   0.03128 |     1.183 |
-#> |.....................|   0.03022 |    0.7552 |    0.8290 |     1.307 |
-#> |.....................|     1.134 |     1.141 |...........|...........|
-#> |    F| Forward Diff. |    -41.65 |     1.977 |  -0.02866 |    0.1453 |
-#> |.....................|   -0.1180 |    -37.67 |    -8.677 |     3.579 |
-#> |.....................|    -1.774 |    0.6894 |     5.855 |    -8.506 |
-#> |.....................|    -6.962 |    -7.153 |...........|...........|
-#> |   25|     477.65816 |     1.000 |    -1.018 |   -0.9120 |   -0.8960 |
-#> |.....................|   -0.8454 |   -0.4997 |   -0.8051 |   -0.8988 |
-#> |.....................|   -0.8750 |   -0.8832 |   -0.9313 |   -0.7859 |
-#> |.....................|   -0.8042 |   -0.8013 |...........|...........|
-#> |    U|     477.65816 |     93.02 |    -5.318 |   -0.9406 |   -0.1116 |
-#> |.....................|     2.300 |     1.421 |   0.03130 |     1.181 |
-#> |.....................|   0.03025 |    0.7549 |    0.8259 |     1.313 |
-#> |.....................|     1.138 |     1.145 |...........|...........|
-#> |    X|     477.65816 |     93.02 |  0.004901 |    0.2808 |    0.8944 |
-#> |.....................|     9.974 |     1.421 |   0.03130 |     1.181 |
-#> |.....................|   0.03025 |    0.7549 |    0.8259 |     1.313 |
-#> |.....................|     1.138 |     1.145 |...........|...........|
-#> |    F| Forward Diff. |     47.50 |     2.013 |    0.2278 |    0.2145 |
-#> |.....................|    0.1415 |    -36.68 |    -7.460 |     3.039 |
-#> |.....................|    -1.807 |    0.8669 |     6.124 |    -8.373 |
-#> |.....................|    -6.814 |    -7.074 |...........|...........|
-#> |   26|     476.87668 |    0.9936 |    -1.020 |   -0.9121 |   -0.8962 |
-#> |.....................|   -0.8454 |   -0.4825 |   -0.8047 |   -0.9014 |
-#> |.....................|   -0.8732 |   -0.8836 |   -0.9351 |   -0.7808 |
-#> |.....................|   -0.8001 |   -0.7975 |...........|...........|
-#> |    U|     476.87668 |     92.41 |    -5.320 |   -0.9408 |   -0.1117 |
-#> |.....................|     2.300 |     1.431 |   0.03130 |     1.180 |
-#> |.....................|   0.03028 |    0.7546 |    0.8226 |     1.319 |
-#> |.....................|     1.143 |     1.149 |...........|...........|
-#> |    X|     476.87668 |     92.41 |  0.004893 |    0.2807 |    0.8943 |
-#> |.....................|     9.974 |     1.431 |   0.03130 |     1.180 |
-#> |.....................|   0.03028 |    0.7546 |    0.8226 |     1.319 |
-#> |.....................|     1.143 |     1.149 |...........|...........|
-#> |    F| Forward Diff. |    -40.64 |     1.935 |  -0.02164 |    0.1511 |
-#> |.....................|   -0.1127 |    -35.59 |    -7.858 |     3.450 |
-#> |.....................|    -1.805 |    0.6731 |     3.945 |    -8.048 |
-#> |.....................|    -6.589 |    -6.756 |...........|...........|
-#> |   27|     476.16299 |     1.000 |    -1.022 |   -0.9123 |   -0.8963 |
-#> |.....................|   -0.8454 |   -0.4651 |   -0.8047 |   -0.9041 |
-#> |.....................|   -0.8711 |   -0.8840 |   -0.9355 |   -0.7757 |
-#> |.....................|   -0.7959 |   -0.7936 |...........|...........|
-#> |    U|     476.16299 |     93.01 |    -5.322 |   -0.9409 |   -0.1119 |
-#> |.....................|     2.300 |     1.442 |   0.03130 |     1.178 |
-#> |.....................|   0.03031 |    0.7543 |    0.8222 |     1.326 |
-#> |.....................|     1.147 |     1.153 |...........|...........|
-#> |    X|     476.16299 |     93.01 |  0.004885 |    0.2807 |    0.8941 |
-#> |.....................|     9.974 |     1.442 |   0.03130 |     1.178 |
-#> |.....................|   0.03031 |    0.7543 |    0.8222 |     1.326 |
-#> |.....................|     1.147 |     1.153 |...........|...........|
-#> |    F| Forward Diff. |     44.38 |     1.982 |    0.2331 |    0.2213 |
-#> |.....................|    0.1467 |    -34.64 |    -6.709 |     2.894 |
-#> |.....................|    -1.888 |    0.7760 |     4.358 |    -7.901 |
-#> |.....................|    -6.419 |    -6.620 |...........|...........|
-#> |   28|     475.47434 |    0.9938 |    -1.024 |   -0.9125 |   -0.8966 |
-#> |.....................|   -0.8454 |   -0.4477 |   -0.8058 |   -0.9069 |
-#> |.....................|   -0.8685 |   -0.8844 |   -0.9328 |   -0.7706 |
-#> |.....................|   -0.7919 |   -0.7898 |...........|...........|
-#> |    U|     475.47434 |     92.43 |    -5.324 |   -0.9411 |   -0.1122 |
-#> |.....................|     2.300 |     1.452 |   0.03129 |     1.177 |
-#> |.....................|   0.03035 |    0.7540 |    0.8246 |     1.332 |
-#> |.....................|     1.151 |     1.157 |...........|...........|
-#> |    X|     475.47434 |     92.43 |  0.004875 |    0.2807 |    0.8939 |
-#> |.....................|     9.974 |     1.452 |   0.03129 |     1.177 |
-#> |.....................|   0.03035 |    0.7540 |    0.8246 |     1.332 |
-#> |.....................|     1.151 |     1.157 |...........|...........|
-#> |    F| Forward Diff. |    -38.01 |     1.932 |  -0.02542 |    0.1483 |
-#> |.....................|   -0.1147 |    -33.71 |    -7.114 |     3.216 |
-#> |.....................|    -1.879 |    0.6267 |     4.067 |    -7.573 |
-#> |.....................|    -6.213 |    -6.338 |...........|...........|
-#> |   29|     474.82575 |    0.9998 |    -1.026 |   -0.9126 |   -0.8968 |
-#> |.....................|   -0.8454 |   -0.4303 |   -0.8075 |   -0.9096 |
-#> |.....................|   -0.8656 |   -0.8846 |   -0.9310 |   -0.7657 |
-#> |.....................|   -0.7878 |   -0.7862 |...........|...........|
-#> |    U|     474.82575 |     92.98 |    -5.326 |   -0.9413 |   -0.1124 |
-#> |.....................|     2.300 |     1.462 |   0.03126 |     1.175 |
-#> |.....................|   0.03039 |    0.7538 |    0.8261 |     1.338 |
-#> |.....................|     1.156 |     1.161 |...........|...........|
-#> |    X|     474.82575 |     92.98 |  0.004864 |    0.2806 |    0.8937 |
-#> |.....................|     9.974 |     1.462 |   0.03126 |     1.175 |
-#> |.....................|   0.03039 |    0.7538 |    0.8261 |     1.338 |
-#> |.....................|     1.156 |     1.161 |...........|...........|
-#> |    F| Forward Diff. |     40.83 |     1.980 |    0.2123 |    0.2125 |
-#> |.....................|    0.1324 |    -32.65 |    -6.032 |     2.979 |
-#> |.....................|    -1.922 |    0.7692 |     4.596 |    -7.426 |
-#> |.....................|    -6.058 |    -6.217 |...........|...........|
-#> |   30|     474.18202 |    0.9939 |    -1.028 |   -0.9128 |   -0.8971 |
-#> |.....................|   -0.8454 |   -0.4131 |   -0.8106 |   -0.9130 |
-#> |.....................|   -0.8620 |   -0.8851 |   -0.9307 |   -0.7608 |
-#> |.....................|   -0.7838 |   -0.7828 |...........|...........|
-#> |    U|     474.18202 |     92.44 |    -5.328 |   -0.9414 |   -0.1127 |
-#> |.....................|     2.300 |     1.473 |   0.03121 |     1.173 |
-#> |.....................|   0.03044 |    0.7535 |    0.8264 |     1.344 |
-#> |.....................|     1.160 |     1.165 |...........|...........|
-#> |    X|     474.18202 |     92.44 |  0.004852 |    0.2806 |    0.8935 |
-#> |.....................|     9.974 |     1.473 |   0.03121 |     1.173 |
-#> |.....................|   0.03044 |    0.7535 |    0.8264 |     1.344 |
-#> |.....................|     1.160 |     1.165 |...........|...........|
-#> |    F| Forward Diff. |    -37.33 |     1.920 |  -0.03157 |    0.1462 |
-#> |.....................|   -0.1145 |    -31.92 |    -6.433 |     3.018 |
-#> |.....................|    -1.919 |    0.6114 |     5.640 |    -7.155 |
-#> |.....................|    -5.876 |    -5.958 |...........|...........|
-#> |   31|     473.55376 |    0.9995 |    -1.031 |   -0.9130 |   -0.8973 |
-#> |.....................|   -0.8454 |   -0.3971 |   -0.8148 |   -0.9162 |
-#> |.....................|   -0.8581 |   -0.8855 |   -0.9368 |   -0.7563 |
-#> |.....................|   -0.7800 |   -0.7797 |...........|...........|
-#> |    U|     473.55376 |     92.95 |    -5.331 |   -0.9416 |   -0.1129 |
-#> |.....................|     2.300 |     1.482 |   0.03115 |     1.171 |
-#> |.....................|   0.03050 |    0.7531 |    0.8211 |     1.349 |
-#> |.....................|     1.164 |     1.168 |...........|...........|
-#> |    X|     473.55376 |     92.95 |  0.004838 |    0.2806 |    0.8932 |
-#> |.....................|     9.974 |     1.482 |   0.03115 |     1.171 |
-#> |.....................|   0.03050 |    0.7531 |    0.8211 |     1.349 |
-#> |.....................|     1.164 |     1.168 |...........|...........|
-#> |   32|     472.90182 |    0.9995 |    -1.035 |   -0.9132 |   -0.8977 |
-#> |.....................|   -0.8453 |   -0.3799 |   -0.8225 |   -0.9204 |
-#> |.....................|   -0.8527 |   -0.8861 |   -0.9447 |   -0.7510 |
-#> |.....................|   -0.7757 |   -0.7763 |...........|...........|
-#> |    U|     472.90182 |     92.96 |    -5.335 |   -0.9418 |   -0.1133 |
-#> |.....................|     2.300 |     1.493 |   0.03104 |     1.168 |
-#> |.....................|   0.03058 |    0.7527 |    0.8141 |     1.356 |
-#> |.....................|     1.169 |     1.172 |...........|...........|
-#> |    X|     472.90182 |     92.96 |  0.004819 |    0.2805 |    0.8929 |
-#> |.....................|     9.975 |     1.493 |   0.03104 |     1.168 |
-#> |.....................|   0.03058 |    0.7527 |    0.8141 |     1.356 |
-#> |.....................|     1.169 |     1.172 |...........|...........|
-#> |   33|     469.90339 |    0.9997 |    -1.054 |   -0.9142 |   -0.8996 |
-#> |.....................|   -0.8452 |   -0.2944 |   -0.8611 |   -0.9412 |
-#> |.....................|   -0.8255 |   -0.8889 |   -0.9843 |   -0.7249 |
-#> |.....................|   -0.7539 |   -0.7597 |...........|...........|
-#> |    U|     469.90339 |     92.98 |    -5.354 |   -0.9427 |   -0.1152 |
-#> |.....................|     2.300 |     1.544 |   0.03046 |     1.156 |
-#> |.....................|   0.03099 |    0.7505 |    0.7794 |     1.387 |
-#> |.....................|     1.192 |     1.190 |...........|...........|
-#> |    X|     469.90339 |     92.98 |  0.004727 |    0.2803 |    0.8912 |
-#> |.....................|     9.976 |     1.544 |   0.03046 |     1.156 |
-#> |.....................|   0.03099 |    0.7505 |    0.7794 |     1.387 |
-#> |.....................|     1.192 |     1.190 |...........|...........|
-#> |   34|     461.71523 |     1.001 |    -1.134 |   -0.9184 |   -0.9072 |
-#> |.....................|   -0.8447 |   0.05742 |    -1.020 |    -1.027 |
-#> |.....................|   -0.7136 |   -0.9005 |    -1.147 |   -0.6175 |
-#> |.....................|   -0.6642 |   -0.6913 |...........|...........|
-#> |    U|     461.71523 |     93.05 |    -5.434 |   -0.9467 |   -0.1228 |
-#> |.....................|     2.301 |     1.755 |   0.02808 |     1.105 |
-#> |.....................|   0.03267 |    0.7417 |    0.6368 |     1.518 |
-#> |.....................|     1.288 |     1.263 |...........|...........|
-#> |    X|     461.71523 |     93.05 |  0.004366 |    0.2795 |    0.8844 |
-#> |.....................|     9.981 |     1.755 |   0.02808 |     1.105 |
-#> |.....................|   0.03267 |    0.7417 |    0.6368 |     1.518 |
-#> |.....................|     1.288 |     1.263 |...........|...........|
-#> |    F| Forward Diff. |     11.20 |     1.045 |     1.020 |    0.3495 |
-#> |.....................|    0.7923 |    -15.00 |   -0.3969 |    -1.315 |
-#> |.....................|    -3.031 |    0.2676 |    -6.780 |    -1.078 |
-#> |.....................|  -0.09081 |    -1.463 |...........|...........|
-#> |   35|     459.94653 |     1.009 |    -1.206 |   -0.9768 |   -0.9283 |
-#> |.....................|   -0.8884 |    0.4547 |    -1.238 |   -0.9419 |
-#> |.....................|   -0.5030 |   -0.9080 |   -0.7892 |   -0.6450 |
-#> |.....................|   -0.7313 |   -0.6959 |...........|...........|
-#> |    U|     459.94653 |     93.85 |    -5.506 |    -1.002 |   -0.1439 |
-#> |.....................|     2.257 |     1.993 |   0.02480 |     1.155 |
-#> |.....................|   0.03583 |    0.7361 |    0.9504 |     1.484 |
-#> |.....................|     1.216 |     1.258 |...........|...........|
-#> |    X|     459.94653 |     93.85 |  0.004064 |    0.2686 |    0.8660 |
-#> |.....................|     9.554 |     1.993 |   0.02480 |     1.155 |
-#> |.....................|   0.03583 |    0.7361 |    0.9504 |     1.484 |
-#> |.....................|     1.216 |     1.258 |...........|...........|
-#> |    F| Forward Diff. |     117.0 |     1.389 |    -1.721 |   -0.1200 |
-#> |.....................|  0.004314 |    -5.763 |     2.093 |     3.426 |
-#> |.....................|    -1.378 |     2.600 |     15.14 |    -1.236 |
-#> |.....................|    -4.018 |    -1.529 |...........|...........|
-#> |   36|     458.11528 |     1.003 |    -1.307 |   -0.9477 |   -0.9422 |
-#> |.....................|   -0.9430 |    0.6906 |    -1.630 |   -0.8850 |
-#> |.....................|   -0.1864 |    -1.043 |   -0.8947 |   -0.8359 |
-#> |.....................|   -0.7822 |   -0.7759 |...........|...........|
-#> |    U|     458.11528 |     93.30 |    -5.607 |   -0.9742 |   -0.1578 |
-#> |.....................|     2.202 |     2.135 |   0.01893 |     1.190 |
-#> |.....................|   0.04058 |    0.6334 |    0.8579 |     1.253 |
-#> |.....................|     1.162 |     1.172 |...........|...........|
-#> |    X|     458.11528 |     93.30 |  0.003671 |    0.2740 |    0.8540 |
-#> |.....................|     9.046 |     2.135 |   0.01893 |     1.190 |
-#> |.....................|   0.04058 |    0.6334 |    0.8579 |     1.253 |
-#> |.....................|     1.162 |     1.172 |...........|...........|
-#> |    F| Forward Diff. |    -4.502 |    0.8367 |   -0.1865 |   -0.1361 |
-#> |.....................|   -0.6555 |    -2.945 |     1.425 |     8.523 |
-#> |.....................|   -0.6882 |    -2.700 |     7.982 |    -9.961 |
-#> |.....................|    -6.514 |    -5.474 |...........|...........|
-#> |   37|     454.42202 |     1.008 |    -1.411 |   -0.9501 |   -0.9563 |
-#> |.....................|   -0.9900 |    0.8215 |    -2.099 |    -1.032 |
-#> |.....................|    0.1520 |    -1.049 |   -0.9274 |   -0.7533 |
-#> |.....................|   -0.7158 |   -0.7241 |...........|...........|
-#> |    U|     454.42202 |     93.74 |    -5.711 |   -0.9765 |   -0.1719 |
-#> |.....................|     2.155 |     2.214 |   0.01188 |     1.102 |
-#> |.....................|   0.04565 |    0.6287 |    0.8293 |     1.353 |
-#> |.....................|     1.233 |     1.228 |...........|...........|
-#> |    X|     454.42202 |     93.74 |  0.003311 |    0.2736 |    0.8421 |
-#> |.....................|     8.631 |     2.214 |   0.01188 |     1.102 |
-#> |.....................|   0.04565 |    0.6287 |    0.8293 |     1.353 |
-#> |.....................|     1.233 |     1.228 |...........|...........|
-#> |   38|     451.48622 |     1.000 |    -1.659 |   -0.9551 |   -0.9914 |
-#> |.....................|    -1.111 |     1.029 |    -2.892 |    -1.353 |
-#> |.....................|    0.9897 |    -1.076 |   -0.9627 |   -0.6147 |
-#> |.....................|   -0.5957 |   -0.6379 |...........|...........|
-#> |    U|     451.48622 |     93.01 |    -5.959 |   -0.9812 |   -0.2070 |
-#> |.....................|     2.035 |     2.338 | 5.960e-07 |    0.9088 |
-#> |.....................|   0.05822 |    0.6083 |    0.7984 |     1.521 |
-#> |.....................|     1.361 |     1.320 |...........|...........|
-#> |    X|     451.48622 |     93.01 |  0.002583 |    0.2727 |    0.8130 |
-#> |.....................|     7.651 |     2.338 | 5.960e-07 |    0.9088 |
-#> |.....................|   0.05822 |    0.6083 |    0.7984 |     1.521 |
-#> |.....................|     1.361 |     1.320 |...........|...........|
-#> |    F| Forward Diff. |    -68.34 |   0.03355 |   0.09905 |    -1.306 |
-#> |.....................|    -5.058 |    -1.204 |  -0.09883 |    -1.076 |
-#> |.....................|    -2.726 |    -4.145 |     7.646 |   -0.5743 |
-#> |.....................|     2.003 |     2.613 |...........|...........|
-#> |   39|     453.25472 |     1.003 |    -2.027 |    -1.069 |   -0.8933 |
-#> |.....................|   -0.6960 |     1.084 |    -2.892 |    -1.695 |
-#> |.....................|     2.689 |   -0.4882 |    -1.206 |   -0.2814 |
-#> |.....................|   -0.7545 |   -0.8496 |...........|...........|
-#> |    U|     453.25472 |     93.31 |    -6.327 |    -1.089 |   -0.1089 |
-#> |.....................|     2.449 |     2.371 | 5.960e-07 |    0.7037 |
-#> |.....................|   0.08370 |     1.055 |    0.5857 |     1.926 |
-#> |.....................|     1.191 |     1.093 |...........|...........|
-#> |    X|     453.25472 |     93.31 |  0.001787 |    0.2519 |    0.8968 |
-#> |.....................|     11.58 |     2.371 | 5.960e-07 |    0.7037 |
-#> |.....................|   0.08370 |     1.055 |    0.5857 |     1.926 |
-#> |.....................|     1.191 |     1.093 |...........|...........|
-#> |   40|     449.59369 |     1.000 |    -1.818 |    -1.010 |   -0.9508 |
-#> |.....................|   -0.9364 |     1.052 |    -2.892 |    -1.498 |
-#> |.....................|     1.730 |   -0.8175 |    -1.073 |   -0.4671 |
-#> |.....................|   -0.6691 |   -0.7270 |...........|...........|
-#> |    U|     449.59369 |     93.04 |    -6.118 |    -1.033 |   -0.1664 |
-#> |.....................|     2.209 |     2.352 | 5.960e-07 |    0.8216 |
-#> |.....................|   0.06933 |    0.8048 |    0.7021 |     1.700 |
-#> |.....................|     1.282 |     1.225 |...........|...........|
-#> |    X|     449.59369 |     93.04 |  0.002202 |    0.2625 |    0.8467 |
-#> |.....................|     9.106 |     2.352 | 5.960e-07 |    0.8216 |
-#> |.....................|   0.06933 |    0.8048 |    0.7021 |     1.700 |
-#> |.....................|     1.282 |     1.225 |...........|...........|
-#> |    F| Forward Diff. |    -128.1 |    0.1096 |    -3.510 |   -0.1773 |
-#> |.....................|   -0.1823 |    -1.358 | -0.002263 |     1.313 |
-#> |.....................|    -1.294 |     5.530 |     5.100 |     4.831 |
-#> |.....................|    -1.292 |    -3.851 |...........|...........|
-#> |   41|     472.13387 |     1.020 |    -1.985 |   -0.7592 |   -0.7822 |
-#> |.....................|   -0.2976 |     1.062 |    -2.892 |    -1.866 |
-#> |.....................|     3.141 |   -0.7519 |    -1.136 |   -0.6405 |
-#> |.....................|   -0.7706 |   -0.2153 |...........|...........|
-#> |    U|     472.13387 |     94.83 |    -6.285 |   -0.7970 |  0.002176 |
-#> |.....................|     2.848 |     2.358 | 5.960e-07 |    0.6009 |
-#> |.....................|   0.09049 |    0.8547 |    0.6467 |     1.490 |
-#> |.....................|     1.174 |     1.773 |...........|...........|
-#> |    X|     472.13387 |     94.83 |  0.001864 |    0.3107 |     1.002 |
-#> |.....................|     17.25 |     2.358 | 5.960e-07 |    0.6009 |
-#> |.....................|   0.09049 |    0.8547 |    0.6467 |     1.490 |
-#> |.....................|     1.174 |     1.773 |...........|...........|
-#> |   42|     454.13083 |     1.030 |    -1.841 |   -0.9756 |   -0.9280 |
-#> |.....................|   -0.8501 |     1.054 |    -2.892 |    -1.548 |
-#> |.....................|     1.921 |   -0.8098 |    -1.082 |   -0.4916 |
-#> |.....................|   -0.6825 |   -0.6571 |...........|...........|
-#> |    U|     454.13083 |     95.82 |    -6.141 |    -1.000 |   -0.1436 |
-#> |.....................|     2.295 |     2.353 | 5.960e-07 |    0.7917 |
-#> |.....................|   0.07219 |    0.8106 |    0.6936 |     1.671 |
-#> |.....................|     1.268 |     1.299 |...........|...........|
-#> |    X|     454.13083 |     95.82 |  0.002153 |    0.2688 |    0.8663 |
-#> |.....................|     9.927 |     2.353 | 5.960e-07 |    0.7917 |
-#> |.....................|   0.07219 |    0.8106 |    0.6936 |     1.671 |
-#> |.....................|     1.268 |     1.299 |...........|...........|
-#> |   43|     454.81886 |     1.032 |    -1.823 |    -1.002 |   -0.9459 |
-#> |.....................|   -0.9179 |     1.053 |    -2.892 |    -1.509 |
-#> |.....................|     1.771 |   -0.8169 |    -1.076 |   -0.4733 |
-#> |.....................|   -0.6717 |   -0.7113 |...........|...........|
-#> |    U|     454.81886 |     95.94 |    -6.123 |    -1.025 |   -0.1614 |
-#> |.....................|     2.227 |     2.352 | 5.960e-07 |    0.8150 |
-#> |.....................|   0.06994 |    0.8052 |    0.6994 |     1.693 |
-#> |.....................|     1.280 |     1.241 |...........|...........|
-#> |    X|     454.81886 |     95.94 |  0.002192 |    0.2640 |    0.8509 |
-#> |.....................|     9.277 |     2.352 | 5.960e-07 |    0.8150 |
-#> |.....................|   0.06994 |    0.8052 |    0.6994 |     1.693 |
-#> |.....................|     1.280 |     1.241 |...........|...........|
-#> |   44|     449.57011 |     1.014 |    -1.818 |    -1.010 |   -0.9508 |
-#> |.....................|   -0.9364 |     1.053 |    -2.892 |    -1.499 |
-#> |.....................|     1.730 |   -0.8181 |    -1.073 |   -0.4676 |
-#> |.....................|   -0.6690 |   -0.7267 |...........|...........|
-#> |    U|     449.57011 |     94.27 |    -6.118 |    -1.033 |   -0.1664 |
-#> |.....................|     2.209 |     2.352 | 5.995e-07 |    0.8215 |
-#> |.....................|   0.06933 |    0.8044 |    0.7016 |     1.700 |
-#> |.....................|     1.283 |     1.225 |...........|...........|
-#> |    X|     449.57011 |     94.27 |  0.002202 |    0.2626 |    0.8467 |
-#> |.....................|     9.106 |     2.352 | 5.995e-07 |    0.8215 |
-#> |.....................|   0.06933 |    0.8044 |    0.7016 |     1.700 |
-#> |.....................|     1.283 |     1.225 |...........|...........|
-#> |    F| Forward Diff. |     126.9 |    0.1582 |    -2.201 |   0.05331 |
-#> |.....................|    0.4695 |   -0.6265 |   0.01503 |    0.4241 |
-#> |.....................|    -1.337 |     5.854 |     6.688 |     4.536 |
-#> |.....................|    -1.410 |    -4.016 |...........|...........|
-#> |   45|     449.14922 |     1.007 |    -1.818 |    -1.010 |   -0.9508 |
-#> |.....................|   -0.9364 |     1.053 |    -2.892 |    -1.499 |
-#> |.....................|     1.730 |   -0.8183 |    -1.074 |   -0.4678 |
-#> |.....................|   -0.6689 |   -0.7265 |...........|...........|
-#> |    U|     449.14922 |     93.66 |    -6.118 |    -1.033 |   -0.1664 |
-#> |.....................|     2.209 |     2.352 | 5.960e-07 |    0.8215 |
-#> |.....................|   0.06933 |    0.8042 |    0.7014 |     1.699 |
-#> |.....................|     1.283 |     1.225 |...........|...........|
-#> |    X|     449.14922 |     93.66 |  0.002202 |    0.2626 |    0.8467 |
-#> |.....................|     9.106 |     2.352 | 5.960e-07 |    0.8215 |
-#> |.....................|   0.06933 |    0.8042 |    0.7014 |     1.699 |
-#> |.....................|     1.283 |     1.225 |...........|...........|
-#> |    F| Forward Diff. |   -0.4066 |    0.1367 |    -2.828 |  -0.06013 |
-#> |.....................|    0.1445 |   -0.8286 |   0.01677 |    0.9213 |
-#> |.....................|    -1.224 |     4.943 |     4.017 |     5.223 |
-#> |.....................|    -1.311 |    -3.922 |...........|...........|
-#> |   46|     449.08136 |     1.007 |    -1.818 |    -1.008 |   -0.9507 |
-#> |.....................|   -0.9365 |     1.053 |    -2.892 |    -1.499 |
-#> |.....................|     1.731 |   -0.8217 |    -1.076 |   -0.4714 |
-#> |.....................|   -0.6680 |   -0.7238 |...........|...........|
-#> |    U|     449.08136 |     93.68 |    -6.118 |    -1.031 |   -0.1663 |
-#> |.....................|     2.209 |     2.353 | 5.960e-07 |    0.8212 |
-#> |.....................|   0.06934 |    0.8016 |    0.6990 |     1.695 |
-#> |.....................|     1.284 |     1.228 |...........|...........|
-#> |    X|     449.08136 |     93.68 |  0.002202 |    0.2629 |    0.8468 |
-#> |.....................|     9.105 |     2.353 | 5.960e-07 |    0.8212 |
-#> |.....................|   0.06934 |    0.8016 |    0.6990 |     1.695 |
-#> |.....................|     1.284 |     1.228 |...........|...........|
-#> |   47|     448.89872 |     1.008 |    -1.819 |    -1.002 |   -0.9506 |
-#> |.....................|   -0.9368 |     1.055 |    -2.892 |    -1.501 |
-#> |.....................|     1.734 |   -0.8317 |    -1.084 |   -0.4820 |
-#> |.....................|   -0.6654 |   -0.7159 |...........|...........|
-#> |    U|     448.89872 |     93.76 |    -6.119 |    -1.025 |   -0.1662 |
-#> |.....................|     2.209 |     2.354 | 5.960e-07 |    0.8200 |
-#> |.....................|   0.06938 |    0.7940 |    0.6918 |     1.682 |
-#> |.....................|     1.286 |     1.237 |...........|...........|
-#> |    X|     448.89872 |     93.76 |  0.002202 |    0.2640 |    0.8469 |
-#> |.....................|     9.102 |     2.354 | 5.960e-07 |    0.8200 |
-#> |.....................|   0.06938 |    0.7940 |    0.6918 |     1.682 |
-#> |.....................|     1.286 |     1.237 |...........|...........|
-#> |   48|     448.46351 |     1.011 |    -1.820 |   -0.9792 |   -0.9501 |
-#> |.....................|   -0.9380 |     1.062 |    -2.892 |    -1.509 |
-#> |.....................|     1.744 |   -0.8718 |    -1.117 |   -0.5244 |
-#> |.....................|   -0.6547 |   -0.6840 |...........|...........|
-#> |    U|     448.46351 |     94.07 |    -6.120 |    -1.004 |   -0.1657 |
-#> |.....................|     2.207 |     2.358 | 5.960e-07 |    0.8155 |
-#> |.....................|   0.06953 |    0.7635 |    0.6633 |     1.631 |
-#> |.....................|     1.298 |     1.271 |...........|...........|
-#> |    X|     448.46351 |     94.07 |  0.002199 |    0.2682 |    0.8473 |
-#> |.....................|     9.092 |     2.358 | 5.960e-07 |    0.8155 |
-#> |.....................|   0.06953 |    0.7635 |    0.6633 |     1.631 |
-#> |.....................|     1.298 |     1.271 |...........|...........|
-#> |    F| Forward Diff. |     75.37 |    0.2597 |   -0.1569 |   0.03608 |
-#> |.....................|    0.3501 |   -0.3601 |  -0.01324 |    0.5025 |
-#> |.....................|    -1.327 |     4.308 |    0.9122 |     2.456 |
-#> |.....................|   -0.5631 |    -1.887 |...........|...........|
-#> |   49|     448.12149 |     1.008 |    -1.833 |   -0.9950 |   -0.9378 |
-#> |.....................|   -0.8937 |     1.062 |    -2.892 |    -1.543 |
-#> |.....................|     1.827 |   -0.8899 |    -1.115 |   -0.5324 |
-#> |.....................|   -0.6574 |   -0.6703 |...........|...........|
-#> |    U|     448.12149 |     93.73 |    -6.133 |    -1.019 |   -0.1534 |
-#> |.....................|     2.252 |     2.358 | 5.960e-07 |    0.7948 |
-#> |.....................|   0.07077 |    0.7498 |    0.6653 |     1.621 |
-#> |.....................|     1.295 |     1.285 |...........|...........|
-#> |    X|     448.12149 |     93.73 |  0.002169 |    0.2653 |    0.8578 |
-#> |.....................|     9.504 |     2.358 | 5.960e-07 |    0.7948 |
-#> |.....................|   0.07077 |    0.7498 |    0.6653 |     1.621 |
-#> |.....................|     1.295 |     1.285 |...........|...........|
-#> |    F| Forward Diff. |     13.78 |    0.2222 |    -1.381 |    0.2569 |
-#> |.....................|     1.259 |   -0.5740 |  -0.02850 |    0.1620 |
-#> |.....................|    -1.241 |     3.503 |    0.9893 |     2.205 |
-#> |.....................|   -0.7124 |    -1.054 |...........|...........|
-#> |   50|     447.94443 |     1.007 |    -1.844 |   -0.9902 |   -0.9390 |
-#> |.....................|   -0.9059 |     1.062 |    -2.881 |    -1.561 |
-#> |.....................|     1.911 |   -0.9357 |    -1.119 |   -0.5167 |
-#> |.....................|   -0.6474 |   -0.7008 |...........|...........|
-#> |    U|     447.94443 |     93.62 |    -6.144 |    -1.014 |   -0.1546 |
-#> |.....................|     2.239 |     2.358 | 0.0001615 |    0.7838 |
-#> |.....................|   0.07204 |    0.7150 |    0.6617 |     1.640 |
-#> |.....................|     1.306 |     1.253 |...........|...........|
-#> |    X|     447.94443 |     93.62 |  0.002146 |    0.2662 |    0.8567 |
-#> |.....................|     9.388 |     2.358 | 0.0001615 |    0.7838 |
-#> |.....................|   0.07204 |    0.7150 |    0.6617 |     1.640 |
-#> |.....................|     1.306 |     1.253 |...........|...........|
-#> |    F| Forward Diff. |    -5.879 |    0.2071 |    -1.215 |    0.2527 |
-#> |.....................|    0.8228 |   -0.5096 |  -0.06036 |    0.4983 |
-#> |.....................|    -1.183 |     1.766 |     2.266 |     2.617 |
-#> |.....................|   -0.3179 |    -2.389 |...........|...........|
-#> |   51|     447.77390 |     1.007 |    -1.858 |    -1.003 |   -0.9470 |
-#> |.....................|   -0.9285 |     1.056 |    -2.855 |    -1.583 |
-#> |.....................|     2.006 |   -0.9406 |    -1.128 |   -0.5198 |
-#> |.....................|   -0.6539 |   -0.6964 |...........|...........|
-#> |    U|      447.7739 |     93.69 |    -6.158 |    -1.026 |   -0.1626 |
-#> |.....................|     2.217 |     2.354 | 0.0005494 |    0.7710 |
-#> |.....................|   0.07347 |    0.7113 |    0.6533 |     1.636 |
-#> |.....................|     1.299 |     1.257 |...........|...........|
-#> |    X|      447.7739 |     93.69 |  0.002117 |    0.2639 |    0.8500 |
-#> |.....................|     9.179 |     2.354 | 0.0005494 |    0.7710 |
-#> |.....................|   0.07347 |    0.7113 |    0.6533 |     1.636 |
-#> |.....................|     1.299 |     1.257 |...........|...........|
-#> |   52|     447.56301 |     1.006 |    -1.897 |    -1.041 |   -0.9708 |
-#> |.....................|   -0.9958 |     1.039 |    -2.777 |    -1.647 |
-#> |.....................|     2.291 |   -0.9540 |    -1.156 |   -0.5273 |
-#> |.....................|   -0.6737 |   -0.6848 |...........|...........|
-#> |    U|     447.56301 |     93.51 |    -6.197 |    -1.061 |   -0.1864 |
-#> |.....................|     2.150 |     2.344 |  0.001717 |    0.7326 |
-#> |.....................|   0.07774 |    0.7011 |    0.6293 |     1.627 |
-#> |.....................|     1.278 |     1.270 |...........|...........|
-#> |    X|     447.56301 |     93.51 |  0.002035 |    0.2570 |    0.8300 |
-#> |.....................|     8.581 |     2.344 |  0.001717 |    0.7326 |
-#> |.....................|   0.07774 |    0.7011 |    0.6293 |     1.627 |
-#> |.....................|     1.278 |     1.270 |...........|...........|
-#> |    F| Forward Diff. |    -30.60 |    0.2182 |    -4.075 |   -0.4855 |
-#> |.....................|    -1.237 |   -0.6626 |   -0.1062 |    0.6612 |
-#> |.....................|   -0.6049 |     1.074 |     1.318 |     2.279 |
-#> |.....................|    -1.614 |    -1.745 |...........|...........|
-#> |   53|     447.16930 |     1.007 |    -1.971 |   -0.9627 |   -0.9652 |
-#> |.....................|   -0.9709 |     1.044 |    -2.781 |    -1.732 |
-#> |.....................|     2.691 |   -0.9472 |    -1.156 |   -0.5162 |
-#> |.....................|   -0.6828 |   -0.6632 |...........|...........|
-#> |    U|      447.1693 |     93.67 |    -6.271 |   -0.9883 |   -0.1807 |
-#> |.....................|     2.174 |     2.347 |  0.001652 |    0.6812 |
-#> |.....................|   0.08374 |    0.7063 |    0.6288 |     1.641 |
-#> |.....................|     1.268 |     1.293 |...........|...........|
-#> |    X|      447.1693 |     93.67 |  0.001890 |    0.2713 |    0.8346 |
-#> |.....................|     8.798 |     2.347 |  0.001652 |    0.6812 |
-#> |.....................|   0.08374 |    0.7063 |    0.6288 |     1.641 |
-#> |.....................|     1.268 |     1.293 |...........|...........|
-#> |    F| Forward Diff. |    -3.693 |    0.1048 |    0.8560 |   -0.3278 |
-#> |.....................|   -0.6115 |   -0.5188 |  -0.09596 |    0.9789 |
-#> |.....................|   0.02585 |     1.094 |     1.548 |     2.318 |
-#> |.....................|    -2.079 |   -0.9259 |...........|...........|
-#> |   54|     447.68852 |     1.013 |    -2.042 |    -1.008 |   -0.9421 |
-#> |.....................|   -0.9288 |     1.034 |    -2.709 |    -1.852 |
-#> |.....................|     3.037 |   -0.9368 |    -1.153 |   -0.6162 |
-#> |.....................|   -0.5399 |   -0.6984 |...........|...........|
-#> |    U|     447.68852 |     94.21 |    -6.342 |    -1.031 |   -0.1577 |
-#> |.....................|     2.217 |     2.341 |  0.002735 |    0.6094 |
-#> |.....................|   0.08893 |    0.7142 |    0.6313 |     1.519 |
-#> |.....................|     1.420 |     1.255 |...........|...........|
-#> |    X|     447.68852 |     94.21 |  0.001761 |    0.2629 |    0.8541 |
-#> |.....................|     9.176 |     2.341 |  0.002735 |    0.6094 |
-#> |.....................|   0.08893 |    0.7142 |    0.6313 |     1.519 |
-#> |.....................|     1.420 |     1.255 |...........|...........|
-#> |   55|     447.15405 |     1.011 |    -1.991 |   -0.9760 |   -0.9584 |
-#> |.....................|   -0.9586 |     1.042 |    -2.761 |    -1.767 |
-#> |.....................|     2.789 |   -0.9450 |    -1.157 |   -0.5460 |
-#> |.....................|   -0.6410 |   -0.6726 |...........|...........|
-#> |    U|     447.15405 |     94.04 |    -6.291 |    -1.001 |   -0.1740 |
-#> |.....................|     2.187 |     2.346 |  0.001959 |    0.6605 |
-#> |.....................|   0.08521 |    0.7080 |    0.6287 |     1.605 |
-#> |.....................|     1.312 |     1.283 |...........|...........|
-#> |    X|     447.15405 |     94.04 |  0.001852 |    0.2688 |    0.8403 |
-#> |.....................|     8.906 |     2.346 |  0.001959 |    0.6605 |
-#> |.....................|   0.08521 |    0.7080 |    0.6287 |     1.605 |
-#> |.....................|     1.312 |     1.283 |...........|...........|
-#> |    F| Forward Diff. |     53.59 |   0.07914 |    0.2662 |   -0.1234 |
-#> |.....................|   -0.1097 |   -0.6518 |  -0.06086 |    0.6193 |
-#> |.....................|  -0.05679 |     1.445 |    0.6511 |     1.197 |
-#> |.....................|   -0.1794 |    -1.326 |...........|...........|
-#> |   56|     447.09915 |     1.005 |    -2.002 |   -0.9768 |   -0.9545 |
-#> |.....................|   -0.9567 |     1.042 |    -2.752 |    -1.789 |
-#> |.....................|     2.838 |   -0.9392 |    -1.155 |   -0.5617 |
-#> |.....................|   -0.6261 |   -0.6787 |...........|...........|
-#> |    U|     447.09915 |     93.47 |    -6.302 |    -1.002 |   -0.1701 |
-#> |.....................|     2.189 |     2.346 |  0.002096 |    0.6471 |
-#> |.....................|   0.08594 |    0.7123 |    0.6298 |     1.586 |
-#> |.....................|     1.328 |     1.276 |...........|...........|
-#> |    X|     447.09915 |     93.47 |  0.001833 |    0.2686 |    0.8436 |
-#> |.....................|     8.923 |     2.346 |  0.002096 |    0.6471 |
-#> |.....................|   0.08594 |    0.7123 |    0.6298 |     1.586 |
-#> |.....................|     1.328 |     1.276 |...........|...........|
-#> |    F| Forward Diff. |    -33.97 |   0.05091 |   -0.1219 |  -0.09607 |
-#> |.....................|   -0.3249 |   -0.8735 |   -0.1278 |    0.5888 |
-#> |.....................|   0.06635 |     1.636 |    -1.923 |    0.5172 |
-#> |.....................|    0.5270 |    -1.419 |...........|...........|
-#> |   57|     447.01951 |     1.007 |    -2.009 |   -0.9874 |   -0.9450 |
-#> |.....................|   -0.9329 |     1.053 |    -2.780 |    -1.808 |
-#> |.....................|     2.841 |   -0.9693 |    -1.155 |   -0.5556 |
-#> |.....................|   -0.6514 |   -0.6721 |...........|...........|
-#> |    U|     447.01951 |     93.64 |    -6.309 |    -1.012 |   -0.1606 |
-#> |.....................|     2.212 |     2.352 |  0.001680 |    0.6361 |
-#> |.....................|   0.08598 |    0.6895 |    0.6300 |     1.593 |
-#> |.....................|     1.301 |     1.283 |...........|...........|
-#> |    X|     447.01951 |     93.64 |  0.001820 |    0.2667 |    0.8517 |
-#> |.....................|     9.138 |     2.352 |  0.001680 |    0.6361 |
-#> |.....................|   0.08598 |    0.6895 |    0.6300 |     1.593 |
-#> |.....................|     1.301 |     1.283 |...........|...........|
-#> |    F| Forward Diff. |    -6.500 |   0.04518 |   -0.6412 |    0.1616 |
-#> |.....................|    0.3106 |   -0.6054 |  -0.07873 |   -0.1077 |
-#> |.....................|   -0.1002 |    0.2460 |     1.553 |    0.4490 |
-#> |.....................|   -0.8245 |    -1.132 |...........|...........|
-#> |   58|     447.04861 |     1.009 |    -2.019 |   -0.9927 |   -0.9476 |
-#> |.....................|   -0.9252 |     1.054 |    -2.796 |    -1.779 |
-#> |.....................|     2.878 |   -0.9737 |    -1.157 |   -0.5487 |
-#> |.....................|   -0.6291 |   -0.6521 |...........|...........|
-#> |    U|     447.04861 |     93.85 |    -6.319 |    -1.017 |   -0.1632 |
-#> |.....................|     2.220 |     2.353 |  0.001429 |    0.6532 |
-#> |.....................|   0.08654 |    0.6862 |    0.6280 |     1.601 |
-#> |.....................|     1.325 |     1.305 |...........|...........|
-#> |    X|     447.04861 |     93.85 |  0.001802 |    0.2657 |    0.8494 |
-#> |.....................|     9.209 |     2.353 |  0.001429 |    0.6532 |
-#> |.....................|   0.08654 |    0.6862 |    0.6280 |     1.601 |
-#> |.....................|     1.325 |     1.305 |...........|...........|
-#> |   59|     447.01937 |     1.009 |    -2.012 |   -0.9891 |   -0.9459 |
-#> |.....................|   -0.9304 |     1.053 |    -2.785 |    -1.798 |
-#> |.....................|     2.853 |   -0.9708 |    -1.156 |   -0.5534 |
-#> |.....................|   -0.6439 |   -0.6653 |...........|...........|
-#> |    U|     447.01937 |     93.80 |    -6.312 |    -1.013 |   -0.1615 |
-#> |.....................|     2.215 |     2.353 |  0.001597 |    0.6418 |
-#> |.....................|   0.08617 |    0.6884 |    0.6292 |     1.596 |
-#> |.....................|     1.309 |     1.291 |...........|...........|
-#> |    X|     447.01937 |     93.80 |  0.001814 |    0.2664 |    0.8509 |
-#> |.....................|     9.161 |     2.353 |  0.001597 |    0.6418 |
-#> |.....................|   0.08617 |    0.6884 |    0.6292 |     1.596 |
-#> |.....................|     1.309 |     1.291 |...........|...........|
-#> |    F| Forward Diff. |     15.62 |   0.04451 |   -0.6370 |    0.1658 |
-#> |.....................|    0.4720 |   -0.4967 |  -0.06076 |    0.2478 |
-#> |.....................|   0.07878 |    0.2929 |    0.7908 |    0.7364 |
-#> |.....................|   -0.2169 |   -0.8458 |...........|...........|
-#> |   60|     447.00331 |     1.007 |    -2.016 |   -0.9874 |   -0.9487 |
-#> |.....................|   -0.9321 |     1.057 |    -2.790 |    -1.800 |
-#> |.....................|     2.856 |   -0.9696 |    -1.156 |   -0.5575 |
-#> |.....................|   -0.6423 |   -0.6633 |...........|...........|
-#> |    U|     447.00331 |     93.68 |    -6.316 |    -1.012 |   -0.1643 |
-#> |.....................|     2.213 |     2.355 |  0.001526 |    0.6406 |
-#> |.....................|   0.08622 |    0.6893 |    0.6295 |     1.591 |
-#> |.....................|     1.311 |     1.293 |...........|...........|
-#> |    X|     447.00331 |     93.68 |  0.001807 |    0.2667 |    0.8485 |
-#> |.....................|     9.146 |     2.355 |  0.001526 |    0.6406 |
-#> |.....................|   0.08622 |    0.6893 |    0.6295 |     1.591 |
-#> |.....................|     1.311 |     1.293 |...........|...........|
-#> |    F| Forward Diff. |    -1.749 |   0.03581 |   -0.6032 |   0.06997 |
-#> |.....................|    0.3775 |   -0.4012 |  -0.08782 |    0.2553 |
-#> |.....................|  0.001918 |    0.1783 |     1.513 |    0.3567 |
-#> |.....................|   -0.3333 |   -0.7379 |...........|...........|
-#> |   61|     446.99944 |     1.008 |    -2.018 |   -0.9851 |   -0.9476 |
-#> |.....................|   -0.9359 |     1.058 |    -2.787 |    -1.806 |
-#> |.....................|     2.859 |   -0.9671 |    -1.156 |   -0.5614 |
-#> |.....................|   -0.6427 |   -0.6650 |...........|...........|
-#> |    U|     446.99944 |     93.70 |    -6.318 |    -1.009 |   -0.1632 |
-#> |.....................|     2.209 |     2.355 |  0.001564 |    0.6369 |
-#> |.....................|   0.08626 |    0.6911 |    0.6291 |     1.586 |
-#> |.....................|     1.311 |     1.291 |...........|...........|
-#> |    X|     446.99944 |     93.70 |  0.001804 |    0.2671 |    0.8494 |
-#> |.....................|     9.111 |     2.355 |  0.001564 |    0.6369 |
-#> |.....................|   0.08626 |    0.6911 |    0.6291 |     1.586 |
-#> |.....................|     1.311 |     1.291 |...........|...........|
-#> |    F| Forward Diff. |     2.474 |   0.03546 |   -0.4554 |    0.1057 |
-#> |.....................|    0.2777 |   -0.4692 |  -0.06549 |   0.06429 |
-#> |.....................|  -0.09650 |    0.2331 |    0.6150 |    0.1626 |
-#> |.....................|   -0.3753 |   -0.8072 |...........|...........|
-#> |   62|     446.99641 |     1.007 |    -2.020 |   -0.9846 |   -0.9460 |
-#> |.....................|   -0.9366 |     1.059 |    -2.790 |    -1.808 |
-#> |.....................|     2.868 |   -0.9676 |    -1.156 |   -0.5621 |
-#> |.....................|   -0.6420 |   -0.6633 |...........|...........|
-#> |    U|     446.99641 |     93.67 |    -6.320 |    -1.009 |   -0.1616 |
-#> |.....................|     2.209 |     2.356 |  0.001530 |    0.6356 |
-#> |.....................|   0.08639 |    0.6908 |    0.6287 |     1.585 |
-#> |.....................|     1.311 |     1.293 |...........|...........|
-#> |    X|     446.99641 |     93.67 |  0.001800 |    0.2672 |    0.8508 |
-#> |.....................|     9.105 |     2.356 |  0.001530 |    0.6356 |
-#> |.....................|   0.08639 |    0.6908 |    0.6287 |     1.585 |
-#> |.....................|     1.311 |     1.293 |...........|...........|
-#> |    F| Forward Diff. |    -2.070 |   0.03317 |   -0.4443 |    0.1488 |
-#> |.....................|    0.2478 |   -0.4968 |  -0.07674 |   0.09423 |
-#> |.....................|  -0.05318 |    0.2365 |    0.6058 |    0.5619 |
-#> |.....................|   -0.3013 |   -0.7224 |...........|...........|
-#> |   63|     446.99641 |     1.007 |    -2.020 |   -0.9846 |   -0.9460 |
-#> |.....................|   -0.9366 |     1.059 |    -2.790 |    -1.808 |
-#> |.....................|     2.868 |   -0.9676 |    -1.156 |   -0.5621 |
-#> |.....................|   -0.6420 |   -0.6633 |...........|...........|
-#> |    U|     446.99641 |     93.67 |    -6.320 |    -1.009 |   -0.1616 |
-#> |.....................|     2.209 |     2.356 |  0.001530 |    0.6356 |
-#> |.....................|   0.08639 |    0.6908 |    0.6287 |     1.585 |
-#> |.....................|     1.311 |     1.293 |...........|...........|
-#> |    X|     446.99641 |     93.67 |  0.001800 |    0.2672 |    0.8508 |
-#> |.....................|     9.105 |     2.356 |  0.001530 |    0.6356 |
-#> |.....................|   0.08639 |    0.6908 |    0.6287 |     1.585 |
-#> |.....................|     1.311 |     1.293 |...........|...........|
-#> calculating covariance matrix
-#> done
-#> Calculating residuals/tables
-#> done
-f_nlmixr_dfop_sfo_saem_obs_tc <- nlmixr(f_mmkin_tc["DFOP-SFO", ], est = "saem",
-  error_model = "obs_tc")
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#>  
-#> 1:    90.7519   -4.8586   -1.7674   -3.5599   -2.0059    0.5800    4.8899    1.4250    1.1400    2.6923    0.4845    0.4370   10.2815    0.0004    9.0437    0.4047
-#> 2:    9.0763e+01  -5.2004e+00  -1.9605e+00  -4.2009e+00  -1.8767e+00   2.0341e-01   4.6454e+00   1.3537e+00   1.0830e+00   2.7771e+00   4.6027e-01   5.1181e-01   6.3469e+00   4.0033e-04   6.8216e+00   9.0448e-05
-#> 3:    9.0656e+01  -5.4820e+00  -2.0937e+00  -4.0962e+00  -1.5381e+00  -1.7136e-02   4.4131e+00   1.2861e+00   1.0288e+00   3.5620e+00   4.3726e-01   6.1217e-01   4.8763e+00   4.1436e-05   5.4967e+00   1.0148e-05
-#> 4:    9.0543e+01  -5.7744e+00  -2.1074e+00  -4.0393e+00  -1.3603e+00  -2.3531e-01   5.0162e+00   1.2218e+00   1.0041e+00   3.3839e+00   4.1540e-01   5.8157e-01   4.1029e+00   2.1466e-04   4.2869e+00   1.9419e-06
-#> 5:    91.1621   -6.0534   -2.0430   -4.0508   -1.2523   -0.2043    6.1015    1.1715    1.1998    3.2147    0.3946    0.5525    3.5979    0.0187    3.8221    0.0271
-#> 6:    91.1179   -5.9892   -2.0082   -4.1363   -1.1428   -0.1930    5.7964    1.1960    1.2360    3.4525    0.3749    0.5293    3.3091    0.0209    3.6230    0.0284
-#> 7:    91.6680   -5.9609   -2.0492   -4.1163   -1.0919   -0.1505    5.6134    1.6750    1.3055    3.2799    0.3631    0.5028    3.2412    0.0254    3.5108    0.0371
-#> 8:    91.6903   -5.9346   -2.0630   -4.0790   -1.1130   -0.0963    5.3327    2.2525    1.3524    3.1159    0.3449    0.4777    2.6165    0.0445    2.8556    0.0576
-#> 9:    92.2564   -5.7600   -2.0460   -4.1144   -1.0635   -0.0594    5.9616    2.1399    1.2848    2.9601    0.3277    0.4538    2.3593    0.0295    2.5704    0.0491
-#> 10:    92.2425   -5.7990   -2.0052   -4.0409   -1.0387   -0.1141    6.9547    2.1239    1.2205    2.8121    0.3113    0.4311    2.3237    0.0323    2.4227    0.0421
-#> 11:    92.4404   -5.6829   -2.0866   -4.0010   -1.0214   -0.0587    6.6790    2.0177    1.1595    2.6715    0.2957    0.4096    1.9963    0.0407    2.2478    0.0501
-#> 12:    92.0713   -5.8051   -2.1699   -4.0539   -0.9807    0.0174    6.7885    2.1380    1.1811    2.6017    0.2810    0.3891    1.8480    0.0502    2.0516    0.0522
-#> 13:    91.7214   -5.6954   -2.1579   -4.0944   -0.9935   -0.0195    6.4491    2.0311    1.1221    2.4716    0.2669    0.3696    1.8299    0.0531    1.9271    0.0520
-#> 14:    91.1978   -5.6733   -2.1988   -4.0794   -0.9387    0.0091    6.1267    1.9295    1.1589    2.3480    0.2536    0.3511    1.6357    0.0470    1.8899    0.0639
-#> 15:    91.3746   -5.5864   -2.1484   -4.1356   -0.9126    0.0045    5.8203    1.8330    1.2078    2.3265    0.2409    0.3336    1.6218    0.0428    1.6558    0.0725
-#> 16:    91.5646   -5.4931   -2.1474   -4.1242   -0.9148    0.0179    5.5293    1.7414    1.1474    2.2733    0.2288    0.3169    1.6467    0.0377    1.6977    0.0600
-#> 17:    91.4767   -5.5885   -2.1424   -4.1386   -0.9308    0.0602    5.2528    1.9428    1.2141    2.1762    0.2174    0.3343    1.4916    0.0424    1.4326    0.0717
-#> 18:    90.9989   -5.6364   -2.1601   -4.1606   -0.9676    0.0694    4.9902    1.8457    1.2521    2.2899    0.2065    0.3279    1.4504    0.0471    1.4267    0.0700
-#> 19:    91.4050   -5.7347   -2.0985   -4.1476   -0.9656    0.0668    4.7407    2.3263    1.4064    2.2061    0.1962    0.3296    1.3679    0.0485    1.2735    0.0844
-#> 20:    91.2707   -5.7623   -2.1155   -4.1538   -0.9601    0.0425    4.5037    2.6509    1.3408    2.1958    0.1864    0.3576    1.3736    0.0452    1.3454    0.0743
-#> 21:    91.6878   -5.8143   -2.1261   -4.1649   -0.9325    0.0333    4.7695    2.8996    1.3244    2.1300    0.1771    0.3509    1.4793    0.0508    1.0333    0.0839
-#> 22:    91.5363   -5.9047   -2.1358   -4.1655   -0.9207    0.0339    4.5310    3.4408    1.3022    2.1829    0.1682    0.3378    1.4260    0.0488    0.9436    0.0877
-#> 23:    91.9969   -5.9565   -2.1378   -4.1609   -0.9243    0.0701    4.3045    3.7239    1.3446    2.2424    0.1598    0.3209    1.4182    0.0412    0.9205    0.0873
-#> 24:    92.2835   -5.9272   -2.0883   -4.1651   -0.9248    0.0834    4.0892    3.7780    1.2773    2.2187    0.1518    0.3049    1.4749    0.0427    0.9837    0.0802
-#> 25:    92.3389   -6.1292   -2.1033   -4.2473   -0.9069    0.0593    3.8848    4.7059    1.2740    2.4323    0.1442    0.2896    1.3656    0.0493    0.9299    0.0798
-#> 26:    91.9840   -5.9821   -2.1124   -4.2150   -0.9100    0.1076    3.6905    4.4706    1.2103    2.4699    0.1458    0.2751    1.3200    0.0504    0.8256    0.0912
-#> 27:    92.4671   -5.8765   -2.0910   -4.2169   -0.9356    0.0483    3.5060    4.2471    1.2302    2.4791    0.1385    0.2614    1.4252    0.0520    0.8191    0.0836
-#> 28:    92.4130   -5.9480   -2.0870   -4.2191   -0.9338    0.0866    3.3859    4.1337    1.2210    2.4685    0.1412    0.2557    1.3860    0.0484    0.9189    0.0770
-#> 29:    92.3064   -5.7845   -2.0759   -4.2321   -0.9270    0.0855    4.2691    3.9271    1.3369    2.5457    0.1341    0.2922    1.3848    0.0513    0.9658    0.0785
-#> 30:    92.2109   -5.9347   -2.0725   -4.2042   -0.9074    0.0481    5.5659    3.9234    1.2701    2.4184    0.1370    0.2776    1.2925    0.0560    0.9058    0.0806
-#> 31:    91.8912   -5.7466   -2.0912   -4.1504   -0.9087    0.0443    5.2876    3.7272    1.2690    2.2975    0.1301    0.2637    1.3348    0.0517    0.8672    0.0840
-#> 32:    92.3866   -5.8560   -2.0979   -4.1547   -0.9044    0.0335    5.0232    3.5408    1.2761    2.3185    0.1307    0.2505    1.3558    0.0487    0.9422    0.0791
-#> 33:    92.4555   -5.6989   -2.0956   -4.1479   -0.9038    0.0447    4.7720    3.3638    1.3253    2.2962    0.1242    0.2380    1.4321    0.0432    0.8961    0.0799
-#> 34:    92.6307   -5.8831   -2.0769   -4.1319   -0.8946    0.0430    4.5334    3.7151    1.2785    2.2638    0.1201    0.2261    1.4076    0.0457    0.8269    0.0813
-#> 35:    92.5659   -5.9100   -2.0748   -4.1482   -0.9079    0.0563    4.6634    3.7452    1.3141    2.3378    0.1168    0.2148    1.3571    0.0451    0.8317    0.0831
-#> 36:    92.5738   -5.8574   -2.0981   -4.1214   -0.8963    0.0302    5.3272    3.7371    1.3359    2.2776    0.1331    0.2041    1.3308    0.0480    0.8953    0.0791
-#> 37:    92.1615   -5.7137   -2.0922   -4.1178   -0.9035    0.0455    5.4894    3.5503    1.2691    2.2508    0.1473    0.1939    1.3692    0.0495    0.9358    0.0800
-#> 38:    92.4421   -5.6978   -2.0905   -4.1275   -0.9052    0.0108    5.4295    3.3728    1.2057    2.2119    0.1432    0.1842    1.3421    0.0549    0.8932    0.0781
-#> 39:    92.3995   -5.6121   -2.0804   -4.1275   -0.8903    0.0270    5.1580    3.2041    1.1454    2.2119    0.1360    0.1978    1.3353    0.0524    0.9062    0.0775
-#> 40:    92.5616   -5.7907   -2.1099   -4.1127   -0.9074    0.0501    4.9001    3.0439    1.1582    2.1723    0.1387    0.1879    1.2981    0.0510    0.9517    0.0797
-#> 41:    92.2655   -5.6532   -2.0631   -4.1437   -0.9128    0.0346    4.6551    2.8917    1.1202    2.1498    0.1403    0.1785    1.4500    0.0461    0.7394    0.0903
-#> 42:    92.3218   -5.4916   -2.1072   -4.1312   -0.9310    0.0360    4.4224    2.7471    1.1648    2.1428    0.1332    0.1695    1.4034    0.0508    0.8131    0.0854
-#> 43:    92.6165   -5.5145   -2.0838   -4.1239   -0.9215    0.0347    4.2012    2.6098    1.1892    2.1202    0.1463    0.1611    1.3416    0.0507    0.8213    0.0847
-#> 44:    92.5385   -5.5590   -2.0872   -4.1376   -0.9210    0.0672    3.9912    2.4793    1.1416    2.2253    0.1450    0.1530    1.4008    0.0352    0.8639    0.0847
-#> 45:    92.2152   -5.6170   -2.1014   -4.1657   -0.9331    0.0781    3.7916    2.4382    1.1250    2.2378    0.1516    0.1556    1.4612    0.0329    1.0091    0.0820
-#> 46:    91.8943   -5.6650   -2.1329   -4.1649   -0.9241    0.1060    3.6020    2.6448    1.0705    2.3112    0.1441    0.1549    1.5047    0.0384    1.0179    0.0805
-#> 47:    91.8153   -5.5910   -2.1514   -4.1919   -0.9169    0.0885    3.4219    2.5125    1.0386    2.3140    0.1506    0.1620    1.4759    0.0375    1.1021    0.0740
-#> 48:    91.6295   -5.5438   -2.1516   -4.1570   -0.8742    0.0851    3.2508    2.3869    1.0816    2.1983    0.1630    0.1786    1.4024    0.0405    1.1135    0.0732
-#> 49:    91.4363   -5.5847   -2.1732   -4.1794   -0.8634    0.0948    3.0883    2.4829    1.0865    2.2378    0.1549    0.1697    1.4314    0.0434    1.0529    0.0742
-#> 50:    91.3634   -5.5794   -2.1613   -4.1507   -0.8849    0.0862    2.9339    2.6404    1.0829    2.2519    0.1493    0.1612    1.3704    0.0446    1.0081    0.0736
-#> 51:    91.2150   -5.5503   -2.1675   -4.1432   -0.8749    0.1178    2.7872    2.7368    1.0605    2.2261    0.1418    0.1532    1.4312    0.0418    1.0380    0.0781
-#> 52:    91.4343   -5.6336   -2.2138   -4.1552   -0.8867    0.1391    2.6677    2.7022    1.0857    2.2588    0.1493    0.1455    1.3220    0.0469    0.9272    0.0761
-#> 53:    91.3310   -5.5185   -2.2340   -4.1430   -0.8855    0.1545    2.9130    2.5670    1.0720    2.3074    0.1532    0.1385    1.3224    0.0503    0.9688    0.0723
-#> 54:    91.4342   -5.5008   -2.2086   -4.1777   -0.8720    0.1688    2.8202    2.4387    1.0624    2.4253    0.1631    0.1315    1.3186    0.0429    0.9425    0.0723
-#> 55:    91.4983   -5.5944   -2.1709   -4.1211   -0.8638    0.1168    3.4789    2.5154    1.0549    2.3041    0.1557    0.1279    1.3800    0.0423    0.9620    0.0727
-#> 56:    91.5954   -5.5317   -2.1881   -4.1263   -0.8627    0.1366    4.1396    2.3896    1.0732    2.2684    0.1562    0.1221    1.3285    0.0431    1.0156    0.0708
-#> 57:    91.6591   -5.3839   -2.2082   -4.1122   -0.8929    0.1457    4.5073    2.2701    1.0672    2.3639    0.1539    0.1160    1.4074    0.0478    0.9796    0.0722
-#> 58:    91.7434   -5.3597   -2.2068   -4.1214   -0.8912    0.1437    4.2819    2.1566    1.0605    2.4496    0.1667    0.1109    1.4274    0.0450    1.0782    0.0676
-#> 59:    91.6597   -5.4672   -2.1918   -4.1412   -0.9021    0.1657    4.0678    2.0488    1.1306    2.5245    0.1888    0.1054    1.4745    0.0391    1.1492    0.0670
-#> 60:    91.7565   -5.4513   -2.2051   -4.1618   -0.9013    0.1554    3.8644    1.9464    1.1728    2.6191    0.1793    0.1001    1.4135    0.0402    1.1572    0.0665
-#> 61:    91.9484   -5.5390   -2.1973   -4.1611   -0.9011    0.1318    3.6712    1.8963    1.1460    2.6242    0.1704    0.0951    1.3855    0.0481    1.1109    0.0634
-#> 62:    92.1661   -5.4985   -2.1729   -4.1352   -0.8887    0.1327    4.3155    1.8588    1.1087    2.5551    0.1633    0.0995    1.3847    0.0444    1.0736    0.0656
-#> 63:    92.1727   -5.4086   -2.1610   -4.1488   -0.8998    0.1451    4.6019    1.7659    1.1413    2.6020    0.1718    0.1152    1.4299    0.0404    1.2202    0.0603
-#> 64:    92.4331   -5.5220   -2.1121   -4.1300   -0.9428    0.1211    5.0354    1.8121    1.0982    2.6157    0.1775    0.1209    1.4168    0.0348    1.2148    0.0625
-#> 65:    92.1871   -5.6089   -2.1258   -4.1412   -0.9127    0.1399    4.7836    2.1060    1.1568    2.5971    0.1757    0.1148    1.4000    0.0336    1.0305    0.0707
-#> 66:    92.1419   -5.7752   -2.1344   -4.1493   -0.9237    0.1494    4.5444    2.7076    1.1563    2.6439    0.1740    0.1091    1.4238    0.0341    1.0285    0.0688
-#> 67:    92.1187   -5.5967   -2.1430   -4.1460   -0.9074    0.1245    4.3172    2.5722    1.2052    2.6139    0.1868    0.1104    1.4100    0.0381    1.0508    0.0703
-#> 68:    92.1123   -5.6882   -2.1481   -4.1269   -0.9083    0.1206    4.1014    2.5548    1.2021    2.4832    0.1781    0.1462    1.3099    0.0417    1.0099    0.0713
-#> 69:    92.2511   -5.6923   -2.1456   -4.1315   -0.9077    0.1421    4.3551    2.6261    1.1850    2.3591    0.1692    0.1389    1.3546    0.0416    0.9516    0.0762
-#> 70:    92.0291   -5.7376   -2.1689   -4.1364   -0.8908    0.1407    4.1373    3.0520    1.1595    2.2495    0.1608    0.1465    1.3226    0.0436    0.9904    0.0711
-#> 71:    91.7690   -5.7223   -2.1773   -4.1986   -0.9036    0.1831    3.9304    2.8994    1.1015    2.4335    0.1527    0.1602    1.3135    0.0450    0.9564    0.0722
-#> 72:    91.4802   -5.7302   -2.2079   -4.2000   -0.8990    0.2112    3.7339    3.2965    1.1222    2.4612    0.1451    0.1622    1.3222    0.0426    1.0215    0.0717
-#> 73:    91.1247   -5.7803   -2.1827   -4.2214   -0.8876    0.1385    3.5472    3.2786    1.1612    2.5216    0.1650    0.1541    1.2811    0.0493    1.0076    0.0696
-#> 74:    90.9765   -5.6534   -2.1808   -4.2511   -0.8824    0.1308    3.8553    3.1146    1.1389    2.8140    0.1725    0.1464    1.2895    0.0518    1.0100    0.0707
-#> 75:    90.4805   -5.7293   -2.1481   -4.2613   -0.8704    0.1395    4.1255    2.9589    1.1623    2.7523    0.1713    0.1391    1.3112    0.0483    0.9439    0.0788
-#> 76:    90.3958   -5.7635   -2.1508   -4.2426   -0.8841    0.1402    4.7427    3.0223    1.2187    2.7243    0.1789    0.1321    1.3065    0.0468    0.9303    0.0758
-#> 77:    90.7518   -5.6517   -2.1498   -4.2773   -0.8730    0.1688    5.9340    2.8712    1.1840    2.8530    0.1828    0.1255    1.3553    0.0422    0.9755    0.0696
-#> 78:    91.0443   -5.7462   -2.1351   -4.2601   -0.8848    0.1746    5.6373    2.9912    1.1312    2.7659    0.1887    0.1192    1.3303    0.0410    0.8578    0.0744
-#> 79:    90.9631   -5.7307   -2.1618   -4.2593   -0.8965    0.1944    5.7520    3.1324    1.1206    2.8212    0.1875    0.1340    1.3519    0.0449    0.9006    0.0799
-#> 80:    90.8703   -5.7665   -2.1989   -4.2476   -0.9122    0.1933    5.4644    3.4527    1.1063    2.7920    0.1781    0.1273    1.3014    0.0497    0.9305    0.0792
-#> 81:    90.7781   -5.8702   -2.1789   -4.2821   -0.8828    0.1793    5.1912    3.7553    1.0662    3.0568    0.1807    0.1209    1.3120    0.0472    0.9808    0.0772
-#> 82:    90.8137   -6.1164   -2.2001   -4.3046   -0.8912    0.1916    4.9316    4.9023    1.0714    3.1363    0.1716    0.1149    1.2724    0.0539    1.0644    0.0693
-#> 83:    90.9900   -6.2077   -2.1695   -4.3121   -0.8924    0.1722    6.7123    5.3290    1.1120    3.2733    0.1741    0.1091    1.2822    0.0510    1.0142    0.0715
-#> 84:    90.8158   -6.3282   -2.1595   -4.2907   -0.9096    0.1818    6.3767    5.9725    1.1342    3.2384    0.1763    0.1037    1.2704    0.0420    0.8891    0.0834
-#> 85:    90.5926   -6.2052   -2.1643   -4.2780   -0.9000    0.1579    6.0579    5.6739    1.1472    3.0765    0.1751    0.0985    1.3263    0.0433    0.9484    0.0814
-#> 86:    90.3804   -6.2707   -2.1470   -4.2627   -0.9260    0.1650    5.7550    5.5542    1.1135    2.9227    0.1956    0.0936    1.2747    0.0447    0.9731    0.0780
-#> 87:    90.8425   -6.4455   -2.1135   -4.2273   -0.9294    0.1491    5.4672    6.8599    1.0716    2.7765    0.1858    0.0928    1.3204    0.0427    1.0005    0.0744
-#> 88:    91.2019   -6.2302   -2.1362   -4.1982   -0.9333    0.1615    5.1939    6.5169    1.1221    2.7203    0.1841    0.0928    1.2689    0.0466    0.9914    0.0771
-#> 89:    90.9907   -6.4173   -2.1174   -4.2493   -0.9182    0.1628    4.9342    6.2408    1.1719    2.9614    0.1749    0.1021    1.3580    0.0403    1.0171    0.0775
-#> 90:    91.1666   -6.5154   -2.1219   -4.2011   -0.9210    0.1594    4.6875    7.4895    1.1930    2.8133    0.1745    0.0970    1.2500    0.0432    0.9467    0.0799
-#> 91:    91.0165   -6.5918   -2.1465   -4.2231   -0.9079    0.1382    4.9772    7.3172    1.1706    2.6789    0.1810    0.1032    1.2958    0.0458    1.1223    0.0639
-#> 92:    91.5386   -6.6567   -2.1376   -4.2247   -0.9358    0.1696    5.5955    7.4188    1.1543    2.6339    0.1754    0.0980    1.2894    0.0463    0.9927    0.0764
-#> 93:    92.2552   -6.5096   -2.1645   -4.2340   -0.9393    0.1798    5.3157    7.0479    1.1612    2.6312    0.1718    0.0931    1.3698    0.0431    1.2649    0.0579
-#> 94:    91.7588   -6.4124   -2.1795   -4.2305   -0.9265    0.1842    5.8275    6.6955    1.1988    2.6403    0.1891    0.0884    1.3022    0.0481    1.0741    0.0713
-#> 95:    91.6694   -6.2975   -2.1946   -4.2442   -0.9392    0.2004    5.5361    6.3607    1.1399    2.7164    0.1796    0.1027    1.2519    0.0513    1.0982    0.0724
-#> 96:    91.2252   -6.0124   -2.2316   -4.2701   -0.8946    0.2375    5.2593    6.0427    1.0829    2.7921    0.2024    0.1147    1.3343    0.0426    1.3064    0.0560
-#> 97:    91.0388   -5.9178   -2.2563   -4.2703   -0.9093    0.2304    5.6825    5.7405    1.0890    2.7678    0.2113    0.1090    1.3517    0.0484    1.4160    0.0493
-#> 98:    90.9013   -6.1325   -2.2597   -4.2776   -0.9133    0.2447    5.7546    5.4535    1.1028    2.6806    0.2130    0.1182    1.2983    0.0451    1.2436    0.0584
-#> 99:    91.2086   -6.0047   -2.2719   -4.2972   -0.9136    0.2738    5.4668    5.1808    1.1776    2.7160    0.2132    0.1123    1.3301    0.0431    1.1850    0.0628
-#> 100:    91.3181   -5.9175   -2.2311   -4.3202   -0.8947    0.2844    5.1935    4.9218    1.1187    2.8660    0.2289    0.1471    1.3409    0.0371    0.9566    0.0806
-#> 101:    91.5112   -5.7721   -2.2292   -4.3060   -0.8842    0.3006    6.3617    4.6757    1.0628    2.7227    0.2174    0.1500    1.3269    0.0407    1.2002    0.0592
-#> 102:    91.5205   -5.9982   -2.2162   -4.3041   -0.8813    0.3065    7.7957    4.4419    1.0320    2.7176    0.2290    0.1474    1.3218    0.0392    0.9685    0.0783
-#> 103:    91.2416   -5.7012   -2.2204   -4.3198   -0.8610    0.3180    7.4059    4.2198    1.0242    2.5817    0.2175    0.1714    1.3003    0.0395    0.9472    0.0825
-#> 104:    91.2662   -5.8136   -2.2357   -4.3063   -0.8700    0.3110    7.0356    4.0088    1.0024    2.4701    0.2067    0.1939    1.2806    0.0407    1.0387    0.0743
-#> 105:    91.4688   -5.7922   -2.2204   -4.3319   -0.8703    0.2767    6.6838    3.8084    0.9751    2.6368    0.1963    0.1967    1.3320    0.0470    1.2043    0.0580
-#> 106:    91.3665   -5.8505   -2.2225   -4.3614   -0.8757    0.2922    7.1982    3.6180    1.0018    2.6378    0.1865    0.2132    1.2613    0.0464    1.0683    0.0693
-#> 107:    91.4934   -5.8933   -2.1993   -4.3433   -0.9112    0.3267    6.8383    3.7379    0.9616    2.5329    0.1772    0.2169    1.2911    0.0449    1.0688    0.0731
-#> 108:    92.1268   -5.7807   -2.1863   -4.4348   -0.9273    0.3235    6.4964    3.5510    1.0093    2.9025    0.1718    0.2061    1.3153    0.0414    0.8982    0.0796
-#> 109:    91.6585   -5.9778   -2.2083   -4.3550   -0.9061    0.3339    6.1715    4.5778    1.0600    2.7574    0.1755    0.2163    1.2754    0.0382    0.8100    0.0868
-#> 110:    92.0456   -5.6784   -2.2236   -4.3483   -0.8911    0.3022    5.8630    4.3489    1.0427    2.6195    0.1667    0.2472    1.3782    0.0336    0.7819    0.0931
-#> 111:    92.2862   -5.6624   -2.1985   -4.3680   -0.9178    0.3156    5.5698    4.1315    1.0149    2.5443    0.1622    0.2348    1.3541    0.0415    0.7848    0.0868
-#> 112:    92.5436   -5.6572   -2.2134   -4.3290   -0.9267    0.3025    5.2913    3.9249    1.0720    2.5118    0.1541    0.2231    1.3798    0.0385    0.9087    0.0799
-#> 113:    92.5970   -5.6263   -2.2030   -4.3044   -0.9123    0.2856    5.0268    3.7287    1.1371    2.4674    0.1764    0.2119    1.3007    0.0455    0.8651    0.0850
-#> 114:    92.9227   -5.6379   -2.2032   -4.2926   -0.9187    0.3282    4.7754    3.5422    1.1022    2.4105    0.1676    0.2013    1.3103    0.0439    0.9003    0.0815
-#> 115:    92.7678   -5.8033   -2.1888   -4.2988   -0.9406    0.3026    4.5367    3.3651    1.1127    2.5043    0.1592    0.1913    1.3643    0.0420    0.9649    0.0800
-#> 116:    92.0655   -5.8531   -2.2033   -4.2989   -0.9487    0.3013    4.3098    3.6792    1.1260    2.4981    0.1513    0.1817    1.2783    0.0445    0.9812    0.0818
-#> 117:    92.2258   -5.7861   -2.2095   -4.3393   -0.9399    0.2998    4.0943    3.4952    1.0697    2.7102    0.1437    0.1752    1.3037    0.0426    0.9067    0.0786
-#> 118:    92.3560   -5.8080   -2.2058   -4.3166   -0.9480    0.2743    4.6025    3.3205    1.0709    2.6198    0.1432    0.1747    1.2850    0.0481    0.9236    0.0769
-#> 119:    92.0489   -5.7726   -2.1972   -4.2740   -0.9087    0.2627    4.3723    3.1544    1.0892    2.4888    0.1620    0.1660    1.2659    0.0435    0.8389    0.0832
-#> 120:    91.9163   -5.8211   -2.2101   -4.2770   -0.9142    0.2674    4.1537    3.1700    1.0985    2.5003    0.1795    0.1577    1.2289    0.0454    0.9280    0.0826
-#> 121:    92.0274   -5.7601   -2.1916   -4.2686   -0.9055    0.2571    3.9460    3.1181    1.1026    2.3985    0.1908    0.1498    1.3015    0.0432    0.9363    0.0807
-#> 122:    92.2933   -5.7972   -2.2019   -4.2888   -0.8932    0.2679    3.7487    3.1755    1.0809    2.3976    0.1843    0.1636    1.2918    0.0433    0.8760    0.0803
-#> 123:    92.3361   -5.8903   -2.1745   -4.3386   -0.9157    0.2665    3.5613    3.8794    1.1308    2.5838    0.1751    0.1555    1.3219    0.0421    0.8987    0.0806
-#> 124:    92.5677   -6.0471   -2.1638   -4.2764   -0.9325    0.2645    3.3832    4.6152    1.1336    2.4546    0.1664    0.1526    1.2938    0.0375    0.9412    0.0798
-#> 125:    92.7852   -5.9841   -2.1661   -4.2825   -0.9373    0.2866    3.2141    4.3844    1.0770    2.3788    0.1581    0.1727    1.3137    0.0417    0.9228    0.0733
-#> 126:    92.7867   -5.9126   -2.1636   -4.2413   -0.9141    0.2756    3.0534    4.1652    1.0857    2.2921    0.1502    0.1994    1.2428    0.0450    0.8206    0.0795
-#> 127:    92.8733   -5.9110   -2.1546   -4.2269   -0.9258    0.2531    2.9007    3.9569    1.0914    2.3822    0.1426    0.2029    1.3043    0.0369    0.8206    0.0795
-#> 128:    93.0457   -5.9202   -2.1505   -4.2076   -0.9466    0.2463    3.3353    3.7591    1.0647    2.3012    0.1355    0.2180    1.3420    0.0385    0.8503    0.0803
-#> 129:    92.9207   -5.9882   -2.1704   -4.2204   -0.9319    0.2464    4.3160    4.4368    1.1187    2.3415    0.1386    0.2316    1.2546    0.0435    0.8777    0.0830
-#> 130:    92.2660   -6.2043   -2.1712   -4.2251   -0.9276    0.2186    4.4370    5.1440    1.0817    2.3426    0.1338    0.2200    1.2733    0.0476    0.9132    0.0753
-#> 131:    92.1286   -6.4163   -2.1634   -4.2642   -0.9223    0.2300    4.2151    6.2253    1.0614    2.5012    0.1333    0.2090    1.2690    0.0430    0.8201    0.0814
-#> 132:    92.0287   -6.4297   -2.1522   -4.2717   -0.9259    0.2250    4.0044    6.1979    1.0791    2.5146    0.1314    0.1985    1.2736    0.0449    0.8671    0.0784
-#> 133:    91.6843   -6.1415   -2.1685   -4.2553   -0.9349    0.2209    3.8041    5.8880    1.1445    2.4277    0.1248    0.2026    1.3381    0.0426    0.9129    0.0858
-#> 134:    91.6928   -6.1408   -2.1467   -4.2709   -0.9270    0.2648    3.6139    5.5936    1.0873    2.5602    0.1305    0.1925    1.3202    0.0416    0.7626    0.0936
-#> 135:    91.7984   -6.0371   -2.1673   -4.2572   -0.9497    0.2480    3.4332    5.3139    1.0649    2.4322    0.1389    0.1829    1.2592    0.0544    0.9459    0.0831
-#> 136:    91.9754   -6.1770   -2.1769   -4.2311   -0.9401    0.2435    3.2616    5.0482    1.0717    2.3106    0.1691    0.1737    1.3170    0.0436    1.0497    0.0816
-#> 137:    92.1546   -6.1216   -2.1731   -4.2278   -0.9401    0.2492    3.0985    4.9378    1.0200    2.1950    0.1606    0.1988    1.4019    0.0421    1.0200    0.0766
-#> 138:    92.2370   -5.9463   -2.1794   -4.1949   -0.9321    0.2460    2.9436    4.6909    1.0203    2.1200    0.1535    0.1947    1.3378    0.0425    0.9448    0.0804
-#> 139:    92.2025   -5.8849   -2.1820   -4.1868   -0.9200    0.2294    2.9458    4.4564    0.9875    2.1260    0.1759    0.2080    1.3244    0.0428    1.0110    0.0778
-#> 140:    91.8182   -5.7494   -2.1569   -4.1998   -0.9095    0.2318    2.7985    4.2336    1.0015    2.1507    0.1830    0.2113    1.3502    0.0432    0.7716    0.0922
-#> 141:    91.8292   -5.9568   -2.1640   -4.2109   -0.9122    0.2130    4.4608    4.0219    1.0180    2.1032    0.1739    0.2057    1.3594    0.0419    0.8088    0.0883
-#> 142:    91.9995   -6.0927   -2.1471   -4.2313   -0.9091    0.1875    4.5415    4.7705    1.0571    2.1286    0.1810    0.1954    1.4145    0.0406    0.8943    0.0847
-#> 143:    91.9160   -5.9892   -2.1546   -4.2043   -0.9355    0.1819    4.3145    4.5320    1.1337    2.1453    0.1888    0.2208    1.3449    0.0394    1.0910    0.0797
-#> 144:    92.0136   -5.9765   -2.1643   -4.2346   -0.9448    0.2455    4.3041    4.3054    1.1130    2.1300    0.1817    0.3253    1.3828    0.0340    1.0535    0.0873
-#> 145:    92.3893   -6.2224   -2.1211   -4.2316   -0.9405    0.2285    5.2279    4.9099    1.0573    2.1037    0.1727    0.3091    1.3797    0.0340    1.0160    0.0832
-#> 146:    92.6097   -6.2204   -2.1406   -4.2210   -0.9217    0.1762    4.9665    5.4466    1.0724    2.1658    0.1640    0.2936    1.4421    0.0408    1.2412    0.0674
-#> 147:    92.8499   -6.0091   -2.1165   -4.2234   -0.9682    0.1783    4.7182    5.1743    1.0188    2.1714    0.1722    0.2789    1.4545    0.0397    1.4472    0.0556
-#> 148:    92.6602   -5.8003   -2.1059   -4.2132   -0.9282    0.2102    4.4823    4.9156    1.0106    2.1075    0.1880    0.2684    1.4013    0.0413    1.0748    0.0758
-#> 149:    92.7388   -5.8727   -2.1569   -4.2185   -0.9266    0.1868    4.2581    4.6698    1.1447    2.0851    0.1786    0.2550    1.3137    0.0413    0.9963    0.0723
-#> 150:    92.7348   -5.7926   -2.1184   -4.2257   -0.9324    0.1966    4.0452    4.4363    1.1760    2.1508    0.1697    0.2704    1.3792    0.0363    0.8204    0.0889
-#> 151:    92.7968   -5.7301   -2.1179   -4.1959   -0.9275    0.1927    3.8430    4.2145    1.1707    2.1702    0.1842    0.2569    1.3789    0.0387    0.7890    0.0873
-#> 152:    92.9011   -5.7417   -2.1622   -4.2086   -0.9215    0.1784    2.0089    3.0670    1.1984    2.2253    0.1814    0.2507    1.3431    0.0395    0.9622    0.0780
-#> 153:    92.8020   -5.7707   -2.1494   -4.2128   -0.9228    0.1818    2.2261    2.9648    1.1192    2.3058    0.1749    0.2548    1.3671    0.0369    0.9507    0.0744
-#> 154:    92.5217   -5.8043   -2.1447   -4.2074   -0.9303    0.1766    2.7638    3.1314    1.1141    2.2814    0.1811    0.2389    1.3250    0.0408    1.0538    0.0689
-#> 155:    92.8765   -5.5586   -2.1275   -4.1639   -0.9320    0.1434    2.4217    2.4658    1.1231    2.1314    0.1746    0.2426    1.3785    0.0407    0.9682    0.0796
-#> 156:    93.0074   -5.6819   -2.1343   -4.1819   -0.9382    0.1587    1.4756    2.7496    1.1200    2.1700    0.1849    0.2320    1.3643    0.0395    1.0875    0.0653
-#> 157:    92.7950   -5.6827   -2.1178   -4.1808   -0.9553    0.1585    1.1607    2.5156    1.1129    2.2109    0.1724    0.2366    1.4045    0.0374    1.1322    0.0676
-#> 158:    92.7684   -5.7106   -2.0933   -4.2149   -0.9717    0.1602    1.4884    2.6532    1.1269    2.1388    0.1838    0.2666    1.4009    0.0348    0.8728    0.0832
-#> 159:    93.0980   -5.8911   -2.1297   -4.2160   -0.9660    0.1407    1.6034    3.3765    1.1182    2.1661    0.1705    0.2804    1.3557    0.0430    1.0076    0.0776
-#> 160:    93.1849   -5.9433   -2.1177   -4.1735   -0.9436    0.1324    1.8692    4.0887    1.1252    2.0213    0.1642    0.2922    1.3251    0.0386    0.8586    0.0820
-#> 161:    93.4771   -5.7768   -2.0899   -4.1697   -0.9670    0.1043    2.0938    2.9110    1.1069    1.9538    0.1820    0.3046    1.3270    0.0413    0.8220    0.0855
-#> 162:    93.4961   -5.6516   -2.0965   -4.1633   -0.9708    0.1263    2.2053    2.3022    1.1179    1.9555    0.1758    0.2891    1.3158    0.0417    0.9943    0.0768
-#> 163:    93.1627   -5.5944   -2.1527   -4.1633   -0.9488    0.1452    2.9600    2.3291    1.1027    1.9555    0.1766    0.3000    1.3626    0.0376    0.9790    0.0743
-#> 164:    92.7951   -5.6646   -2.1539   -4.1699   -0.9447    0.1863    2.9195    2.7599    1.0794    1.9511    0.1651    0.2918    1.4091    0.0357    1.1005    0.0709
-#> 165:    92.6045   -5.5927   -2.1842   -4.1770   -0.9436    0.1939    2.2014    2.3213    1.0622    1.9775    0.1671    0.2899    1.3945    0.0372    1.0533    0.0694
-#> 166:    92.6660   -5.5922   -2.1438   -4.1611   -0.9441    0.1767    1.8951    2.3445    1.1025    2.0399    0.1802    0.2802    1.4229    0.0354    1.1552    0.0682
-#> 167:    92.4353   -5.5118   -2.1415   -4.1730   -0.9124    0.1827    1.5029    1.8145    1.0701    2.0090    0.1727    0.2642    1.4525    0.0362    1.0577    0.0754
-#> 168:    92.3761   -5.5522   -2.1625   -4.1911   -0.9114    0.1782    1.2703    2.0808    1.0814    2.0588    0.1810    0.2658    1.3973    0.0364    0.9874    0.0729
-#> 169:    92.5240   -5.6102   -2.1396   -4.1793   -0.8972    0.1722    1.3115    2.2750    1.0759    2.0910    0.2147    0.2549    1.3553    0.0392    0.9770    0.0759
-#> 170:    92.3827   -5.5942   -2.1231   -4.1847   -0.9338    0.1525    1.5707    2.3778    1.0542    2.0824    0.2042    0.2519    1.4424    0.0363    1.1270    0.0687
-#> 171:    92.1706   -5.6171   -2.1619   -4.1926   -0.9056    0.1390    1.0935    2.2869    1.1239    2.1697    0.1946    0.2624    1.2980    0.0411    0.9988    0.0740
-#> 172:    92.1491   -5.5704   -2.1447   -4.1913   -0.9285    0.1649    1.0292    2.2160    1.1231    2.1905    0.1860    0.2518    1.3154    0.0375    1.0152    0.0772
-#> 173:    91.9987   -5.5411   -2.1434   -4.1803   -0.9056    0.1585    0.6511    1.9989    1.0892    2.2283    0.1899    0.2413    1.3814    0.0380    1.1733    0.0693
-#> 174:    92.0377   -5.5419   -2.1081   -4.1928   -0.9057    0.1418    0.9013    2.0933    1.1813    2.2773    0.1756    0.2559    1.4419    0.0343    0.9942    0.0801
-#> 175:    92.0266   -5.5125   -2.1014   -4.1775   -0.9119    0.1371    0.7194    2.0624    1.1848    2.2328    0.1754    0.2504    1.3987    0.0353    1.0838    0.0728
-#> 176:    92.0365   -5.5658   -2.0914   -4.1646   -0.8956    0.1096    0.7557    2.0588    1.1642    2.1610    0.1617    0.2722    1.3658    0.0347    0.9405    0.0757
-#> 177:    91.8661   -5.6799   -2.0950   -4.1695   -0.9010    0.1193    0.8835    2.8899    1.1394    2.1886    0.1809    0.2777    1.3841    0.0351    0.9178    0.0794
-#> 178:    91.9392   -5.7853   -2.1139   -4.1711   -0.9190    0.1222    0.6673    3.0461    1.1712    2.1948    0.1576    0.2237    1.3623    0.0383    0.9060    0.0795
-#> 179:    92.0116   -5.7560   -2.1418   -4.1711   -0.9153    0.1034    0.4356    2.9139    1.1653    2.1948    0.1497    0.2364    1.3387    0.0392    0.9327    0.0793
-#> 180:    92.1013   -5.7920   -2.1368   -4.1654   -0.9059    0.0912    0.3859    3.2592    1.1357    2.1744    0.1570    0.2337    1.3622    0.0408    1.0299    0.0739
-#> 181:    92.1032   -5.8125   -2.1260   -4.1791   -0.9404    0.1731    0.4091    3.0817    1.1113    2.2356    0.1572    0.2742    1.4509    0.0340    0.9180    0.0865
-#> 182:    92.1315   -5.7991   -2.1327   -4.1737   -0.9319    0.1519    0.3145    3.0292    1.1520    2.1360    0.1661    0.2482    1.4105    0.0361    1.1338    0.0748
-#> 183:    92.1350   -6.0470   -2.1264   -4.1707   -0.9525    0.1787    0.2045    3.8296    1.1229    2.1369    0.1735    0.2453    1.3132    0.0350    1.0507    0.0759
-#> 184:    92.0539   -5.9856   -2.1289   -4.1968   -0.9281    0.1789    0.1166    3.9425    1.0558    2.2320    0.1658    0.2253    1.3390    0.0355    1.1271    0.0720
-#> 185:    92.0755   -6.0524   -2.1385   -4.2076   -0.9313    0.1794    0.1193    4.2430    1.0465    2.3571    0.1566    0.2152    1.3777    0.0368    1.2013    0.0631
-#> 186:    92.1639   -6.0663   -2.1399   -4.1869   -0.9311    0.1817    0.1392    4.4053    1.0495    2.4857    0.1532    0.2331    1.3751    0.0365    1.0497    0.0697
-#> 187:    92.1759   -6.3052   -2.1469   -4.2221   -0.9428    0.1970    0.1356    5.5622    0.9953    2.3367    0.1451    0.2359    1.3754    0.0367    1.0969    0.0656
-#> 188:    92.1744   -6.0494   -2.1406   -4.2445   -0.9595    0.2089    0.1364    4.3818    0.9882    2.4074    0.1480    0.2364    1.3709    0.0396    1.1259    0.0642
-#> 189:    92.1989   -6.1255   -2.1138   -4.2037   -0.9368    0.1796    0.1444    4.6756    0.9840    2.3786    0.1502    0.2303    1.3979    0.0393    1.2011    0.0630
-#> 190:    92.0944   -6.1343   -2.1536   -4.2106   -0.9267    0.2105    0.1288    4.4977    1.0475    2.3593    0.1443    0.2396    1.3247    0.0384    1.1304    0.0711
-#> 191:    92.1238   -6.0639   -2.1462   -4.2883   -0.9311    0.2155    0.1246    4.1066    1.0428    2.6836    0.1442    0.2344    1.4041    0.0344    1.1631    0.0684
-#> 192:    92.1328   -6.0743   -2.1232   -4.3119   -0.9586    0.2319    0.1192    4.1348    1.0020    2.7067    0.1466    0.2515    1.4039    0.0355    1.0021    0.0772
-#> 193:    92.0881   -5.8697   -2.1298   -4.2691   -0.9309    0.2295    0.1050    3.4476    0.9879    2.5496    0.1344    0.2348    1.4677    0.0351    1.0332    0.0705
-#> 194:    92.1086   -5.7557   -2.1176   -4.3249   -0.9029    0.2183    0.0702    2.7793    1.0043    2.8853    0.1460    0.2213    1.4733    0.0325    1.0929    0.0681
-#> 195:    92.1265   -5.8976   -2.1506   -4.2932   -0.9267    0.2511    0.0593    3.4959    0.9881    2.6806    0.1278    0.2505    1.6138    0.0350    1.1327    0.0703
-#> 196:    92.1316   -5.7018   -2.1627   -4.2889   -0.9278    0.2392    0.0717    2.9210    1.0160    2.7067    0.1470    0.2350    1.5063    0.0418    1.0525    0.0734
-#> 197:    92.1756   -5.7899   -2.1604   -4.2819   -0.9248    0.2765    0.0754    2.9991    1.0167    2.6170    0.1465    0.2314    1.4982    0.0387    1.0504    0.0774
-#> 198:    92.2153   -5.8248   -2.1571   -4.2245   -0.9350    0.2195    0.0651    3.0128    0.9196    2.3123    0.1451    0.2363    1.3965    0.0453    1.1561    0.0650
-#> 199:    92.1935   -5.8187   -2.1505   -4.2123   -0.9452    0.2406    0.0535    3.0017    0.9553    2.2771    0.1338    0.2415    1.4485    0.0407    1.0647    0.0699
-#> 200:    92.2308   -5.6732   -2.1578   -4.2182   -0.9324    0.2330    0.0618    2.4070    1.0687    2.2978    0.1513    0.2199    1.4101    0.0385    1.0283    0.0741
-#> 201:    92.2305   -5.6796   -2.1604   -4.2064   -0.9320    0.2262    0.0530    2.4360    1.0551    2.2994    0.1529    0.2219    1.3653    0.0407    1.0115    0.0757
-#> 202:    92.2259   -5.7201   -2.1550   -4.2058   -0.9263    0.2208    0.0461    2.6422    1.0351    2.2888    0.1520    0.2100    1.3739    0.0418    1.0474    0.0730
-#> 203:    92.2212   -5.7539   -2.1457   -4.2037   -0.9303    0.2163    0.0422    2.8480    1.0403    2.2723    0.1465    0.2070    1.3973    0.0404    1.0518    0.0729
-#> 204:    92.2164   -5.8068   -2.1371   -4.2093   -0.9300    0.2163    0.0383    3.1313    1.0426    2.2984    0.1423    0.2091    1.4025    0.0391    1.0284    0.0737
-#> 205:    92.2120   -5.8371   -2.1369   -4.2142   -0.9308    0.2156    0.0347    3.2786    1.0392    2.3249    0.1390    0.2048    1.4115    0.0385    1.0161    0.0733
-#> 206:    92.2071   -5.8681   -2.1391   -4.2176   -0.9287    0.2158    0.0336    3.4917    1.0442    2.3461    0.1388    0.2041    1.4017    0.0394    0.9977    0.0735
-#> 207:    92.2078   -5.8966   -2.1424   -4.2230   -0.9286    0.2181    0.0337    3.6741    1.0456    2.3743    0.1369    0.2009    1.3988    0.0397    0.9792    0.0740
-#> 208:    92.2077   -5.8972   -2.1459   -4.2249   -0.9300    0.2208    0.0340    3.6775    1.0460    2.3889    0.1362    0.1985    1.3969    0.0394    0.9729    0.0742
-#> 209:    92.2091   -5.8831   -2.1488   -4.2271   -0.9326    0.2227    0.0337    3.6019    1.0465    2.4005    0.1380    0.1967    1.3949    0.0395    0.9745    0.0741
-#> 210:    92.2115   -5.8806   -2.1490   -4.2282   -0.9349    0.2238    0.0324    3.5652    1.0516    2.4211    0.1386    0.1979    1.3941    0.0391    0.9820    0.0740
-#> 211:    92.2151   -5.8791   -2.1516   -4.2291   -0.9363    0.2258    0.0318    3.5315    1.0458    2.4465    0.1390    0.1989    1.3918    0.0394    0.9901    0.0735
-#> 212:    92.2189   -5.8789   -2.1532   -4.2297   -0.9380    0.2269    0.0312    3.4989    1.0434    2.4718    0.1409    0.1993    1.3884    0.0394    1.0007    0.0732
-#> 213:    92.2226   -5.8714   -2.1556   -4.2287   -0.9395    0.2255    0.0313    3.4460    1.0440    2.4800    0.1413    0.1993    1.3859    0.0397    1.0157    0.0722
-#> 214:    92.2233   -5.8706   -2.1553   -4.2279   -0.9394    0.2237    0.0309    3.4283    1.0431    2.4809    0.1414    0.2003    1.3849    0.0399    1.0186    0.0720
-#> 215:    92.2242   -5.8750   -2.1536   -4.2285   -0.9390    0.2212    0.0312    3.4442    1.0455    2.4800    0.1417    0.2015    1.3830    0.0401    1.0126    0.0723
-#> 216:    92.2252   -5.8788   -2.1521   -4.2277   -0.9393    0.2192    0.0316    3.4718    1.0459    2.4791    0.1410    0.2028    1.3817    0.0402    1.0046    0.0726
-#> 217:    92.2255   -5.8869   -2.1516   -4.2268   -0.9400    0.2177    0.0322    3.5295    1.0456    2.4751    0.1407    0.2042    1.3814    0.0401    1.0011    0.0729
-#> 218:    92.2230   -5.8819   -2.1511   -4.2259   -0.9400    0.2164    0.0327    3.5004    1.0473    2.4693    0.1399    0.2051    1.3784    0.0401    0.9962    0.0731
-#> 219:    92.2206   -5.8761   -2.1499   -4.2269   -0.9393    0.2156    0.0325    3.4736    1.0494    2.4667    0.1399    0.2066    1.3794    0.0399    0.9925    0.0734
-#> 220:    92.2185   -5.8775   -2.1494   -4.2267   -0.9380    0.2150    0.0331    3.4894    1.0511    2.4596    0.1396    0.2090    1.3788    0.0398    0.9881    0.0734
-#> 221:    92.2180   -5.8774   -2.1499   -4.2271   -0.9369    0.2142    0.0328    3.4873    1.0518    2.4559    0.1399    0.2109    1.3776    0.0399    0.9842    0.0735
-#> 222:    92.2191   -5.8833   -2.1503   -4.2280   -0.9359    0.2127    0.0328    3.5384    1.0518    2.4533    0.1400    0.2114    1.3778    0.0400    0.9825    0.0735
-#> 223:    92.2199   -5.8831   -2.1486   -4.2288   -0.9343    0.2112    0.0326    3.5474    1.0539    2.4515    0.1396    0.2127    1.3795    0.0398    0.9806    0.0735
-#> 224:    92.2206   -5.8870   -2.1467   -4.2283   -0.9331    0.2093    0.0324    3.5619    1.0550    2.4482    0.1395    0.2133    1.3805    0.0395    0.9792    0.0735
-#> 225:    92.2218   -5.8929   -2.1459   -4.2289   -0.9328    0.2086    0.0322    3.6001    1.0548    2.4492    0.1388    0.2142    1.3804    0.0393    0.9809    0.0734
-#> 226:    92.2228   -5.8909   -2.1440   -4.2293   -0.9322    0.2082    0.0320    3.6007    1.0566    2.4513    0.1383    0.2143    1.3826    0.0390    0.9815    0.0737
-#> 227:    92.2234   -5.8838   -2.1444   -4.2304   -0.9319    0.2088    0.0319    3.5748    1.0551    2.4562    0.1381    0.2140    1.3814    0.0390    0.9836    0.0736
-#> 228:    92.2243   -5.8835   -2.1444   -4.2314   -0.9326    0.2093    0.0317    3.5756    1.0526    2.4607    0.1377    0.2143    1.3824    0.0389    0.9901    0.0733
-#> 229:    92.2251   -5.8916   -2.1442   -4.2307   -0.9330    0.2095    0.0318    3.6344    1.0501    2.4580    0.1371    0.2148    1.3850    0.0388    0.9930    0.0733
-#> 230:    92.2250   -5.8951   -2.1442   -4.2303   -0.9334    0.2107    0.0318    3.6533    1.0475    2.4550    0.1369    0.2150    1.3872    0.0387    0.9953    0.0734
-#> 231:    92.2247   -5.8964   -2.1444   -4.2300   -0.9345    0.2119    0.0322    3.6564    1.0446    2.4549    0.1368    0.2151    1.3899    0.0388    0.9991    0.0733
-#> 232:    92.2230   -5.8982   -2.1451   -4.2306   -0.9352    0.2132    0.0326    3.6643    1.0422    2.4591    0.1365    0.2155    1.3934    0.0388    1.0052    0.0729
-#> 233:    92.2223   -5.9022   -2.1455   -4.2327   -0.9354    0.2141    0.0329    3.6824    1.0396    2.4697    0.1362    0.2165    1.3970    0.0388    1.0107    0.0726
-#> 234:    92.2200   -5.9075   -2.1457   -4.2324   -0.9348    0.2140    0.0335    3.7056    1.0364    2.4735    0.1366    0.2174    1.3977    0.0388    1.0163    0.0723
-#> 235:    92.2171   -5.9094   -2.1457   -4.2338   -0.9342    0.2142    0.0342    3.7222    1.0339    2.4854    0.1372    0.2189    1.3999    0.0389    1.0228    0.0721
-#> 236:    92.2161   -5.9195   -2.1464   -4.2368   -0.9340    0.2140    0.0346    3.7789    1.0329    2.4986    0.1376    0.2200    1.4007    0.0389    1.0281    0.0721
-#> 237:    92.2163   -5.9214   -2.1469   -4.2390   -0.9330    0.2143    0.0347    3.7862    1.0329    2.5074    0.1378    0.2195    1.4030    0.0389    1.0320    0.0719
-#> 238:    92.2165   -5.9203   -2.1473   -4.2399   -0.9326    0.2143    0.0347    3.7781    1.0336    2.5100    0.1381    0.2186    1.4031    0.0388    1.0347    0.0719
-#> 239:    92.2173   -5.9212   -2.1471   -4.2403   -0.9325    0.2136    0.0344    3.7908    1.0350    2.5128    0.1384    0.2175    1.4021    0.0389    1.0352    0.0718
-#> 240:    92.2178   -5.9217   -2.1470   -4.2394   -0.9322    0.2133    0.0342    3.8082    1.0363    2.5118    0.1384    0.2169    1.4025    0.0387    1.0345    0.0719
-#> 241:    92.2177   -5.9200   -2.1470   -4.2383   -0.9318    0.2136    0.0340    3.8123    1.0381    2.5110    0.1385    0.2161    1.4028    0.0387    1.0336    0.0720
-#> 242:    92.2170   -5.9109   -2.1478   -4.2371   -0.9308    0.2136    0.0340    3.7766    1.0387    2.5090    0.1385    0.2157    1.4027    0.0386    1.0322    0.0720
-#> 243:    92.2165   -5.9029   -2.1484   -4.2371   -0.9300    0.2140    0.0340    3.7433    1.0389    2.5128    0.1386    0.2150    1.4032    0.0385    1.0342    0.0720
-#> 244:    92.2161   -5.8998   -2.1489   -4.2374   -0.9294    0.2143    0.0340    3.7242    1.0392    2.5173    0.1386    0.2148    1.4030    0.0384    1.0343    0.0720
-#> 245:    92.2153   -5.9048   -2.1494   -4.2370   -0.9291    0.2149    0.0339    3.7491    1.0399    2.5182    0.1386    0.2146    1.4019    0.0383    1.0317    0.0722
-#> 246:    92.2147   -5.9093   -2.1498   -4.2371   -0.9289    0.2156    0.0339    3.7727    1.0409    2.5218    0.1384    0.2145    1.4016    0.0382    1.0309    0.0724
-#> 247:    92.2143   -5.9124   -2.1503   -4.2368   -0.9286    0.2159    0.0338    3.7972    1.0408    2.5232    0.1383    0.2144    1.4012    0.0382    1.0297    0.0725
-#> 248:    92.2137   -5.9122   -2.1500   -4.2367   -0.9286    0.2160    0.0336    3.8036    1.0409    2.5245    0.1382    0.2141    1.4022    0.0381    1.0272    0.0727
-#> 249:    92.2133   -5.9101   -2.1501   -4.2364   -0.9288    0.2160    0.0334    3.7984    1.0406    2.5268    0.1383    0.2136    1.4031    0.0381    1.0273    0.0726
-#> 250:    92.2139   -5.9115   -2.1502   -4.2368   -0.9289    0.2167    0.0335    3.8015    1.0412    2.5326    0.1380    0.2132    1.4035    0.0381    1.0261    0.0727
-#> 251:    92.2132   -5.9123   -2.1502   -4.2373   -0.9297    0.2170    0.0338    3.8015    1.0421    2.5362    0.1376    0.2126    1.4053    0.0379    1.0274    0.0727
-#> 252:    92.2128   -5.9106   -2.1502   -4.2366   -0.9299    0.2174    0.0338    3.7931    1.0427    2.5345    0.1371    0.2120    1.4062    0.0379    1.0262    0.0728
-#> 253:    92.2118   -5.9098   -2.1492   -4.2364   -0.9297    0.2173    0.0340    3.8011    1.0420    2.5338    0.1369    0.2121    1.4074    0.0378    1.0232    0.0731
-#> 254:    92.2107   -5.9104   -2.1479   -4.2362   -0.9296    0.2171    0.0341    3.8085    1.0398    2.5330    0.1366    0.2123    1.4093    0.0377    1.0230    0.0731
-#> 255:    92.2103   -5.9133   -2.1466   -4.2359   -0.9299    0.2166    0.0341    3.8219    1.0381    2.5346    0.1363    0.2122    1.4105    0.0377    1.0230    0.0731
-#> 256:    92.2094   -5.9171   -2.1453   -4.2356   -0.9299    0.2161    0.0341    3.8498    1.0366    2.5366    0.1362    0.2123    1.4114    0.0375    1.0239    0.0731
-#> 257:    92.2091   -5.9169   -2.1441   -4.2353   -0.9302    0.2153    0.0341    3.8529    1.0347    2.5385    0.1360    0.2118    1.4126    0.0375    1.0265    0.0729
-#> 258:    92.2089   -5.9191   -2.1431   -4.2349   -0.9301    0.2145    0.0340    3.8608    1.0331    2.5392    0.1359    0.2119    1.4126    0.0375    1.0282    0.0728
-#> 259:    92.2093   -5.9249   -2.1426   -4.2337   -0.9301    0.2145    0.0341    3.8853    1.0321    2.5385    0.1361    0.2120    1.4114    0.0374    1.0280    0.0728
-#> 260:    92.2095   -5.9297   -2.1415   -4.2328   -0.9303    0.2146    0.0339    3.9108    1.0302    2.5367    0.1358    0.2125    1.4112    0.0373    1.0265    0.0729
-#> 261:    92.2096   -5.9341   -2.1407   -4.2321   -0.9307    0.2147    0.0338    3.9343    1.0278    2.5343    0.1356    0.2131    1.4121    0.0373    1.0272    0.0728
-#> 262:    92.2094   -5.9342   -2.1398   -4.2312   -0.9310    0.2149    0.0336    3.9314    1.0254    2.5313    0.1356    0.2139    1.4115    0.0372    1.0249    0.0729
-#> 263:    92.2088   -5.9376   -2.1388   -4.2304   -0.9313    0.2153    0.0334    3.9452    1.0232    2.5289    0.1357    0.2143    1.4109    0.0371    1.0228    0.0731
-#> 264:    92.2077   -5.9410   -2.1379   -4.2301   -0.9317    0.2153    0.0333    3.9571    1.0204    2.5265    0.1356    0.2147    1.4105    0.0371    1.0224    0.0731
-#> 265:    92.2069   -5.9454   -2.1374   -4.2296   -0.9322    0.2154    0.0332    3.9800    1.0182    2.5230    0.1356    0.2147    1.4115    0.0371    1.0232    0.0730
-#> 266:    92.2067   -5.9463   -2.1370   -4.2291   -0.9324    0.2155    0.0330    3.9809    1.0165    2.5217    0.1354    0.2148    1.4121    0.0371    1.0220    0.0730
-#> 267:    92.2064   -5.9492   -2.1368   -4.2282   -0.9329    0.2154    0.0328    3.9874    1.0150    2.5199    0.1357    0.2150    1.4124    0.0370    1.0233    0.0729
-#> 268:    92.2065   -5.9468   -2.1360   -4.2276   -0.9333    0.2155    0.0328    3.9722    1.0133    2.5171    0.1362    0.2155    1.4133    0.0369    1.0243    0.0729
-#> 269:    92.2066   -5.9438   -2.1352   -4.2267   -0.9335    0.2151    0.0328    3.9526    1.0122    2.5142    0.1367    0.2154    1.4140    0.0369    1.0244    0.0728
-#> 270:    92.2067   -5.9388   -2.1351   -4.2259   -0.9339    0.2151    0.0326    3.9283    1.0112    2.5114    0.1370    0.2157    1.4137    0.0368    1.0240    0.0729
-#> 271:    92.2069   -5.9350   -2.1344   -4.2252   -0.9342    0.2152    0.0324    3.9072    1.0107    2.5094    0.1370    0.2158    1.4136    0.0367    1.0222    0.0730
-#> 272:    92.2069   -5.9317   -2.1341   -4.2246   -0.9348    0.2153    0.0321    3.8870    1.0104    2.5082    0.1372    0.2157    1.4139    0.0366    1.0219    0.0731
-#> 273:    92.2068   -5.9289   -2.1340   -4.2240   -0.9348    0.2152    0.0320    3.8711    1.0101    2.5075    0.1373    0.2159    1.4146    0.0366    1.0232    0.0730
-#> 274:    92.2067   -5.9271   -2.1337   -4.2239   -0.9350    0.2153    0.0318    3.8569    1.0101    2.5085    0.1377    0.2157    1.4144    0.0366    1.0239    0.0731
-#> 275:    92.2063   -5.9264   -2.1339   -4.2235   -0.9353    0.2156    0.0317    3.8476    1.0097    2.5078    0.1382    0.2157    1.4143    0.0365    1.0256    0.0730
-#> 276:    92.2059   -5.9271   -2.1339   -4.2231   -0.9354    0.2160    0.0316    3.8417    1.0097    2.5074    0.1387    0.2156    1.4132    0.0365    1.0260    0.0730
-#> 277:    92.2059   -5.9283   -2.1342   -4.2225   -0.9356    0.2163    0.0316    3.8412    1.0094    2.5073    0.1393    0.2155    1.4122    0.0364    1.0283    0.0729
-#> 278:    92.2062   -5.9278   -2.1341   -4.2220   -0.9361    0.2166    0.0318    3.8331    1.0081    2.5069    0.1397    0.2154    1.4117    0.0364    1.0321    0.0727
-#> 279:    92.2061   -5.9264   -2.1341   -4.2214   -0.9363    0.2168    0.0319    3.8188    1.0072    2.5051    0.1402    0.2155    1.4111    0.0364    1.0342    0.0726
-#> 280:    92.2057   -5.9263   -2.1344   -4.2211   -0.9365    0.2167    0.0321    3.8114    1.0072    2.5061    0.1406    0.2148    1.4108    0.0365    1.0361    0.0725
-#> 281:    92.2048   -5.9269   -2.1344   -4.2208   -0.9365    0.2166    0.0324    3.8082    1.0076    2.5077    0.1410    0.2142    1.4098    0.0365    1.0363    0.0726
-#> 282:    92.2045   -5.9257   -2.1347   -4.2205   -0.9366    0.2165    0.0328    3.8040    1.0082    2.5092    0.1413    0.2138    1.4090    0.0365    1.0364    0.0726
-#> 283:    92.2038   -5.9235   -2.1348   -4.2201   -0.9363    0.2163    0.0331    3.7955    1.0089    2.5108    0.1415    0.2134    1.4086    0.0365    1.0362    0.0726
-#> 284:    92.2032   -5.9234   -2.1348   -4.2198   -0.9359    0.2162    0.0335    3.7945    1.0100    2.5118    0.1420    0.2129    1.4083    0.0365    1.0362    0.0726
-#> 285:    92.2028   -5.9236   -2.1347   -4.2193   -0.9360    0.2161    0.0339    3.7930    1.0104    2.5124    0.1422    0.2125    1.4080    0.0365    1.0373    0.0725
-#> 286:    92.2020   -5.9221   -2.1344   -4.2187   -0.9355    0.2156    0.0341    3.7872    1.0104    2.5134    0.1425    0.2121    1.4074    0.0364    1.0377    0.0725
-#> 287:    92.2013   -5.9213   -2.1341   -4.2183   -0.9354    0.2154    0.0343    3.7888    1.0098    2.5151    0.1428    0.2119    1.4075    0.0364    1.0390    0.0724
-#> 288:    92.2003   -5.9195   -2.1339   -4.2182   -0.9355    0.2152    0.0343    3.7831    1.0090    2.5180    0.1430    0.2116    1.4082    0.0364    1.0408    0.0723
-#> 289:    92.1995   -5.9186   -2.1339   -4.2182   -0.9355    0.2154    0.0343    3.7805    1.0083    2.5217    0.1429    0.2115    1.4085    0.0364    1.0426    0.0722
-#> 290:    92.1984   -5.9180   -2.1339   -4.2177   -0.9354    0.2153    0.0343    3.7767    1.0080    2.5219    0.1427    0.2113    1.4083    0.0365    1.0429    0.0721
-#> 291:    92.1975   -5.9167   -2.1334   -4.2175   -0.9355    0.2151    0.0343    3.7701    1.0080    2.5230    0.1427    0.2108    1.4083    0.0364    1.0439    0.0721
-#> 292:    92.1971   -5.9175   -2.1330   -4.2166   -0.9356    0.2144    0.0342    3.7722    1.0081    2.5227    0.1426    0.2107    1.4079    0.0364    1.0443    0.0721
-#> 293:    92.1963   -5.9188   -2.1330   -4.2157   -0.9357    0.2141    0.0342    3.7768    1.0083    2.5242    0.1425    0.2103    1.4073    0.0364    1.0439    0.0721
-#> 294:    92.1953   -5.9189   -2.1328   -4.2157   -0.9357    0.2136    0.0344    3.7727    1.0078    2.5294    0.1427    0.2095    1.4079    0.0364    1.0456    0.0720
-#> 295:    92.1946   -5.9171   -2.1329   -4.2153   -0.9355    0.2135    0.0345    3.7623    1.0081    2.5331    0.1426    0.2090    1.4080    0.0364    1.0462    0.0720
-#> 296:    92.1940   -5.9154   -2.1329   -4.2150   -0.9354    0.2130    0.0346    3.7523    1.0082    2.5354    0.1425    0.2084    1.4075    0.0365    1.0463    0.0720
-#> 297:    92.1934   -5.9128   -2.1330   -4.2145   -0.9351    0.2127    0.0349    3.7395    1.0084    2.5373    0.1423    0.2079    1.4072    0.0365    1.0453    0.0720
-#> 298:    92.1932   -5.9128   -2.1332   -4.2138   -0.9347    0.2120    0.0350    3.7372    1.0085    2.5368    0.1423    0.2075    1.4068    0.0365    1.0449    0.0720
-#> 299:    92.1927   -5.9120   -2.1333   -4.2131   -0.9344    0.2112    0.0352    3.7324    1.0088    2.5366    0.1422    0.2070    1.4059    0.0366    1.0441    0.0721
-#> 300:    92.1921   -5.9097   -2.1335   -4.2122   -0.9343    0.2105    0.0353    3.7211    1.0096    2.5357    0.1425    0.2066    1.4050    0.0367    1.0443    0.0721
-#> 301:    92.1915   -5.9081   -2.1337   -4.2116   -0.9343    0.2098    0.0355    3.7110    1.0104    2.5355    0.1427    0.2061    1.4041    0.0368    1.0448    0.0721
-#> 302:    92.1912   -5.9067   -2.1340   -4.2108   -0.9342    0.2092    0.0355    3.7052    1.0114    2.5348    0.1428    0.2055    1.4036    0.0369    1.0442    0.0722
-#> 303:    92.1913   -5.9039   -2.1342   -4.2113   -0.9342    0.2087    0.0355    3.6925    1.0123    2.5408    0.1430    0.2049    1.4028    0.0369    1.0436    0.0723
-#> 304:    92.1920   -5.9012   -2.1342   -4.2119   -0.9342    0.2081    0.0356    3.6781    1.0129    2.5476    0.1432    0.2044    1.4026    0.0369    1.0436    0.0723
-#> 305:    92.1923   -5.8984   -2.1343   -4.2123   -0.9341    0.2076    0.0354    3.6633    1.0134    2.5525    0.1434    0.2038    1.4022    0.0370    1.0434    0.0724
-#> 306:    92.1926   -5.8977   -2.1343   -4.2121   -0.9343    0.2072    0.0354    3.6603    1.0144    2.5567    0.1436    0.2030    1.4022    0.0369    1.0431    0.0724
-#> 307:    92.1931   -5.8970   -2.1346   -4.2124   -0.9344    0.2068    0.0353    3.6555    1.0154    2.5617    0.1438    0.2021    1.4017    0.0370    1.0431    0.0725
-#> 308:    92.1935   -5.8963   -2.1347   -4.2127   -0.9343    0.2062    0.0351    3.6486    1.0166    2.5665    0.1439    0.2012    1.4017    0.0370    1.0431    0.0724
-#> 309:    92.1934   -5.8965   -2.1349   -4.2130   -0.9344    0.2058    0.0350    3.6454    1.0180    2.5711    0.1439    0.2003    1.4013    0.0370    1.0427    0.0725
-#> 310:    92.1935   -5.8965   -2.1349   -4.2133   -0.9345    0.2055    0.0350    3.6401    1.0193    2.5761    0.1439    0.1993    1.4013    0.0371    1.0418    0.0725
-#> 311:    92.1931   -5.8976   -2.1349   -4.2139   -0.9346    0.2052    0.0349    3.6416    1.0207    2.5820    0.1437    0.1982    1.4015    0.0370    1.0411    0.0726
-#> 312:    92.1928   -5.8995   -2.1350   -4.2149   -0.9349    0.2053    0.0350    3.6472    1.0222    2.5902    0.1437    0.1972    1.4018    0.0370    1.0412    0.0727
-#> 313:    92.1922   -5.8999   -2.1350   -4.2159   -0.9352    0.2055    0.0350    3.6450    1.0236    2.5989    0.1436    0.1962    1.4017    0.0369    1.0407    0.0728
-#> 314:    92.1913   -5.9021   -2.1353   -4.2171   -0.9353    0.2055    0.0350    3.6532    1.0244    2.6086    0.1437    0.1951    1.4019    0.0369    1.0409    0.0728
-#> 315:    92.1905   -5.9033   -2.1358   -4.2178   -0.9354    0.2055    0.0351    3.6591    1.0252    2.6142    0.1438    0.1941    1.4018    0.0369    1.0420    0.0728
-#> 316:    92.1895   -5.9043   -2.1358   -4.2186   -0.9352    0.2053    0.0352    3.6648    1.0266    2.6207    0.1441    0.1934    1.4016    0.0369    1.0420    0.0729
-#> 317:    92.1888   -5.9041   -2.1359   -4.2200   -0.9352    0.2052    0.0352    3.6673    1.0278    2.6312    0.1444    0.1926    1.4014    0.0369    1.0416    0.0729
-#> 318:    92.1879   -5.9039   -2.1360   -4.2212   -0.9352    0.2052    0.0354    3.6670    1.0292    2.6380    0.1446    0.1919    1.4010    0.0369    1.0403    0.0730
-#> 319:    92.1871   -5.9046   -2.1361   -4.2222   -0.9353    0.2052    0.0354    3.6709    1.0306    2.6432    0.1448    0.1912    1.4008    0.0369    1.0394    0.0731
-#> 320:    92.1863   -5.9023   -2.1365   -4.2229   -0.9355    0.2052    0.0355    3.6602    1.0318    2.6466    0.1448    0.1903    1.4011    0.0369    1.0398    0.0731
-#> 321:    92.1855   -5.8996   -2.1368   -4.2236   -0.9354    0.2053    0.0355    3.6491    1.0329    2.6505    0.1448    0.1895    1.4017    0.0369    1.0402    0.0731
-#> 322:    92.1850   -5.8979   -2.1370   -4.2243   -0.9353    0.2057    0.0356    3.6399    1.0341    2.6534    0.1447    0.1888    1.4020    0.0368    1.0394    0.0732
-#> 323:    92.1844   -5.8984   -2.1371   -4.2251   -0.9352    0.2059    0.0356    3.6431    1.0346    2.6566    0.1447    0.1882    1.4026    0.0368    1.0389    0.0733
-#> 324:    92.1838   -5.8967   -2.1372   -4.2257   -0.9353    0.2062    0.0356    3.6392    1.0351    2.6598    0.1445    0.1875    1.4031    0.0368    1.0382    0.0734
-#> 325:    92.1835   -5.8936   -2.1374   -4.2264   -0.9351    0.2066    0.0355    3.6288    1.0352    2.6633    0.1444    0.1869    1.4043    0.0367    1.0391    0.0734
-#> 326:    92.1837   -5.8936   -2.1376   -4.2276   -0.9350    0.2071    0.0354    3.6296    1.0354    2.6684    0.1444    0.1865    1.4043    0.0367    1.0380    0.0735
-#> 327:    92.1837   -5.8943   -2.1378   -4.2289   -0.9347    0.2076    0.0354    3.6348    1.0357    2.6746    0.1444    0.1860    1.4043    0.0366    1.0380    0.0735
-#> 328:    92.1838   -5.8953   -2.1380   -4.2297   -0.9345    0.2081    0.0354    3.6456    1.0360    2.6776    0.1444    0.1856    1.4043    0.0366    1.0379    0.0735
-#> 329:    92.1836   -5.8974   -2.1383   -4.2305   -0.9342    0.2085    0.0356    3.6591    1.0361    2.6802    0.1444    0.1852    1.4043    0.0366    1.0385    0.0735
-#> 330:    92.1832   -5.8994   -2.1387   -4.2305   -0.9342    0.2088    0.0358    3.6715    1.0364    2.6798    0.1443    0.1849    1.4037    0.0367    1.0378    0.0736
-#> 331:    92.1826   -5.8983   -2.1391   -4.2302   -0.9342    0.2091    0.0357    3.6670    1.0368    2.6800    0.1442    0.1845    1.4038    0.0367    1.0379    0.0736
-#> 332:    92.1824   -5.8959   -2.1396   -4.2301   -0.9341    0.2097    0.0357    3.6576    1.0375    2.6792    0.1442    0.1842    1.4034    0.0367    1.0372    0.0737
-#> 333:    92.1826   -5.8937   -2.1401   -4.2304   -0.9340    0.2104    0.0356    3.6487    1.0383    2.6798    0.1442    0.1838    1.4029    0.0367    1.0360    0.0738
-#> 334:    92.1825   -5.8911   -2.1407   -4.2311   -0.9339    0.2112    0.0355    3.6378    1.0390    2.6825    0.1444    0.1834    1.4025    0.0367    1.0349    0.0739
-#> 335:    92.1830   -5.8887   -2.1411   -4.2317   -0.9336    0.2118    0.0355    3.6294    1.0396    2.6850    0.1444    0.1830    1.4022    0.0367    1.0338    0.0740
-#> 336:    92.1834   -5.8872   -2.1413   -4.2324   -0.9334    0.2124    0.0356    3.6249    1.0402    2.6880    0.1444    0.1825    1.4024    0.0367    1.0339    0.0740
-#> 337:    92.1835   -5.8869   -2.1416   -4.2334   -0.9332    0.2131    0.0356    3.6252    1.0411    2.6926    0.1443    0.1821    1.4029    0.0366    1.0330    0.0741
-#> 338:    92.1839   -5.8882   -2.1418   -4.2346   -0.9333    0.2137    0.0357    3.6332    1.0421    2.6972    0.1441    0.1815    1.4036    0.0366    1.0324    0.0742
-#> 339:    92.1845   -5.8869   -2.1420   -4.2358   -0.9332    0.2143    0.0357    3.6261    1.0428    2.7021    0.1439    0.1810    1.4043    0.0366    1.0322    0.0742
-#> 340:    92.1846   -5.8863   -2.1421   -4.2367   -0.9331    0.2147    0.0357    3.6242    1.0436    2.7060    0.1439    0.1804    1.4049    0.0365    1.0328    0.0743
-#> 341:    92.1848   -5.8847   -2.1421   -4.2378   -0.9330    0.2150    0.0356    3.6177    1.0442    2.7099    0.1439    0.1798    1.4056    0.0366    1.0334    0.0743
-#> 342:    92.1848   -5.8838   -2.1421   -4.2390   -0.9330    0.2154    0.0355    3.6114    1.0449    2.7151    0.1438    0.1792    1.4064    0.0365    1.0332    0.0743
-#> 343:    92.1849   -5.8840   -2.1423   -4.2398   -0.9330    0.2157    0.0353    3.6109    1.0459    2.7191    0.1438    0.1785    1.4060    0.0366    1.0334    0.0743
-#> 344:    92.1851   -5.8839   -2.1423   -4.2406   -0.9330    0.2159    0.0352    3.6092    1.0467    2.7229    0.1440    0.1779    1.4060    0.0365    1.0338    0.0743
-#> 345:    92.1850   -5.8841   -2.1424   -4.2414   -0.9331    0.2162    0.0352    3.6070    1.0472    2.7263    0.1441    0.1774    1.4056    0.0365    1.0341    0.0743
-#> 346:    92.1848   -5.8839   -2.1424   -4.2420   -0.9333    0.2164    0.0352    3.6048    1.0479    2.7292    0.1443    0.1769    1.4058    0.0365    1.0344    0.0743
-#> 347:    92.1846   -5.8835   -2.1425   -4.2427   -0.9334    0.2166    0.0353    3.6017    1.0495    2.7330    0.1444    0.1763    1.4053    0.0365    1.0343    0.0743
-#> 348:    92.1846   -5.8825   -2.1427   -4.2434   -0.9336    0.2168    0.0353    3.5968    1.0508    2.7362    0.1445    0.1757    1.4051    0.0365    1.0343    0.0743
-#> 349:    92.1846   -5.8820   -2.1432   -4.2444   -0.9337    0.2172    0.0352    3.5937    1.0519    2.7412    0.1446    0.1752    1.4047    0.0365    1.0343    0.0743
-#> 350:    92.1845   -5.8817   -2.1435   -4.2454   -0.9338    0.2179    0.0351    3.5899    1.0526    2.7460    0.1448    0.1747    1.4042    0.0365    1.0339    0.0744
-#> 351:    92.1844   -5.8824   -2.1439   -4.2468   -0.9338    0.2184    0.0350    3.5917    1.0535    2.7531    0.1448    0.1740    1.4041    0.0365    1.0336    0.0744
-#> 352:    92.1840   -5.8840   -2.1442   -4.2482   -0.9338    0.2189    0.0350    3.6013    1.0543    2.7603    0.1450    0.1734    1.4044    0.0364    1.0342    0.0744
-#> 353:    92.1838   -5.8848   -2.1445   -4.2492   -0.9336    0.2194    0.0349    3.6030    1.0552    2.7652    0.1451    0.1730    1.4043    0.0364    1.0338    0.0744
-#> 354:    92.1838   -5.8835   -2.1449   -4.2501   -0.9336    0.2197    0.0349    3.5961    1.0563    2.7697    0.1452    0.1723    1.4044    0.0364    1.0342    0.0744
-#> 355:    92.1837   -5.8826   -2.1453   -4.2511   -0.9335    0.2199    0.0348    3.5910    1.0569    2.7757    0.1451    0.1718    1.4053    0.0364    1.0348    0.0744
-#> 356:    92.1835   -5.8826   -2.1456   -4.2520   -0.9334    0.2198    0.0348    3.5922    1.0577    2.7815    0.1451    0.1712    1.4054    0.0364    1.0352    0.0744
-#> 357:    92.1834   -5.8818   -2.1457   -4.2525   -0.9334    0.2198    0.0349    3.5894    1.0588    2.7852    0.1449    0.1706    1.4058    0.0364    1.0354    0.0744
-#> 358:    92.1834   -5.8808   -2.1459   -4.2531   -0.9334    0.2197    0.0348    3.5861    1.0600    2.7891    0.1449    0.1701    1.4062    0.0364    1.0361    0.0744
-#> 359:    92.1833   -5.8799   -2.1459   -4.2533   -0.9333    0.2197    0.0350    3.5822    1.0607    2.7903    0.1448    0.1696    1.4063    0.0364    1.0360    0.0744
-#> 360:    92.1831   -5.8792   -2.1460   -4.2534   -0.9332    0.2196    0.0351    3.5787    1.0613    2.7914    0.1446    0.1691    1.4065    0.0364    1.0361    0.0744
-#> 361:    92.1831   -5.8785   -2.1460   -4.2542   -0.9331    0.2196    0.0351    3.5771    1.0620    2.7969    0.1445    0.1688    1.4072    0.0364    1.0366    0.0744
-#> 362:    92.1832   -5.8780   -2.1462   -4.2547   -0.9331    0.2195    0.0351    3.5750    1.0625    2.8017    0.1443    0.1683    1.4079    0.0363    1.0369    0.0744
-#> 363:    92.1830   -5.8788   -2.1464   -4.2551   -0.9331    0.2192    0.0351    3.5785    1.0630    2.8057    0.1443    0.1677    1.4081    0.0363    1.0377    0.0743
-#> 364:    92.1829   -5.8778   -2.1466   -4.2554   -0.9332    0.2193    0.0350    3.5747    1.0634    2.8092    0.1443    0.1672    1.4084    0.0363    1.0386    0.0743
-#> 365:    92.1830   -5.8782   -2.1466   -4.2558   -0.9332    0.2192    0.0350    3.5771    1.0638    2.8135    0.1443    0.1667    1.4086    0.0363    1.0385    0.0743
-#> 366:    92.1830   -5.8795   -2.1465   -4.2564   -0.9332    0.2190    0.0350    3.5838    1.0645    2.8190    0.1444    0.1661    1.4086    0.0363    1.0390    0.0743
-#> 367:    92.1826   -5.8801   -2.1465   -4.2569   -0.9333    0.2191    0.0349    3.5867    1.0652    2.8232    0.1445    0.1657    1.4086    0.0362    1.0388    0.0744
-#> 368:    92.1824   -5.8799   -2.1465   -4.2571   -0.9333    0.2193    0.0348    3.5859    1.0654    2.8252    0.1445    0.1653    1.4088    0.0362    1.0385    0.0744
-#> 369:    92.1822   -5.8803   -2.1467   -4.2572   -0.9333    0.2193    0.0348    3.5846    1.0653    2.8261    0.1444    0.1648    1.4086    0.0362    1.0393    0.0744
-#> 370:    92.1820   -5.8802   -2.1469   -4.2575   -0.9333    0.2195    0.0348    3.5822    1.0653    2.8273    0.1444    0.1645    1.4088    0.0362    1.0396    0.0744
-#> 371:    92.1818   -5.8806   -2.1470   -4.2575   -0.9333    0.2198    0.0348    3.5819    1.0649    2.8277    0.1443    0.1642    1.4091    0.0362    1.0403    0.0743
-#> 372:    92.1818   -5.8804   -2.1473   -4.2580   -0.9332    0.2202    0.0348    3.5795    1.0645    2.8300    0.1441    0.1640    1.4096    0.0362    1.0418    0.0743
-#> 373:    92.1816   -5.8812   -2.1475   -4.2580   -0.9332    0.2203    0.0348    3.5816    1.0644    2.8298    0.1441    0.1639    1.4100    0.0362    1.0439    0.0741
-#> 374:    92.1815   -5.8817   -2.1477   -4.2578   -0.9333    0.2203    0.0349    3.5819    1.0641    2.8282    0.1440    0.1641    1.4099    0.0362    1.0443    0.0741
-#> 375:    92.1817   -5.8828   -2.1479   -4.2574   -0.9335    0.2204    0.0351    3.5853    1.0636    2.8267    0.1440    0.1642    1.4100    0.0362    1.0457    0.0740
-#> 376:    92.1819   -5.8826   -2.1479   -4.2573   -0.9338    0.2206    0.0353    3.5843    1.0634    2.8246    0.1440    0.1643    1.4100    0.0362    1.0464    0.0740
-#> 377:    92.1819   -5.8826   -2.1480   -4.2572   -0.9339    0.2206    0.0354    3.5819    1.0633    2.8225    0.1440    0.1644    1.4097    0.0363    1.0470    0.0739
-#> 378:    92.1819   -5.8821   -2.1481   -4.2571   -0.9340    0.2205    0.0355    3.5777    1.0633    2.8206    0.1440    0.1644    1.4093    0.0363    1.0468    0.0739
-#> 379:    92.1819   -5.8823   -2.1481   -4.2573   -0.9340    0.2205    0.0356    3.5746    1.0633    2.8201    0.1439    0.1645    1.4092    0.0363    1.0468    0.0739
-#> 380:    92.1820   -5.8809   -2.1481   -4.2570   -0.9340    0.2205    0.0356    3.5665    1.0634    2.8178    0.1439    0.1647    1.4093    0.0363    1.0463    0.0739
-#> 381:    92.1823   -5.8795   -2.1481   -4.2568   -0.9338    0.2204    0.0357    3.5586    1.0635    2.8170    0.1439    0.1648    1.4095    0.0363    1.0456    0.0740
-#> 382:    92.1828   -5.8783   -2.1481   -4.2571   -0.9339    0.2203    0.0357    3.5514    1.0636    2.8183    0.1441    0.1649    1.4093    0.0363    1.0462    0.0740
-#> 383:    92.1827   -5.8773   -2.1480   -4.2569   -0.9340    0.2202    0.0357    3.5459    1.0633    2.8173    0.1441    0.1650    1.4094    0.0363    1.0465    0.0739
-#> 384:    92.1825   -5.8763   -2.1482   -4.2568   -0.9341    0.2202    0.0357    3.5397    1.0636    2.8165    0.1441    0.1650    1.4094    0.0363    1.0467    0.0739
-#> 385:    92.1822   -5.8761   -2.1483   -4.2567   -0.9341    0.2201    0.0357    3.5363    1.0641    2.8160    0.1440    0.1650    1.4094    0.0363    1.0469    0.0739
-#> 386:    92.1820   -5.8763   -2.1485   -4.2567   -0.9342    0.2200    0.0356    3.5365    1.0645    2.8157    0.1441    0.1648    1.4092    0.0364    1.0478    0.0738
-#> 387:    92.1819   -5.8767   -2.1486   -4.2567   -0.9343    0.2201    0.0358    3.5383    1.0652    2.8156    0.1442    0.1646    1.4090    0.0364    1.0480    0.0738
-#> 388:    92.1818   -5.8772   -2.1488   -4.2569   -0.9344    0.2202    0.0359    3.5400    1.0656    2.8153    0.1443    0.1645    1.4086    0.0364    1.0480    0.0738
-#> 389:    92.1816   -5.8765   -2.1489   -4.2569   -0.9344    0.2203    0.0359    3.5369    1.0660    2.8145    0.1443    0.1644    1.4083    0.0364    1.0476    0.0738
-#> 390:    92.1815   -5.8761   -2.1490   -4.2569   -0.9343    0.2205    0.0359    3.5349    1.0664    2.8136    0.1444    0.1644    1.4080    0.0364    1.0472    0.0738
-#> 391:    92.1814   -5.8749   -2.1492   -4.2572   -0.9343    0.2207    0.0359    3.5313    1.0668    2.8153    0.1445    0.1643    1.4077    0.0364    1.0465    0.0739
-#> 392:    92.1812   -5.8733   -2.1494   -4.2571   -0.9344    0.2210    0.0359    3.5248    1.0674    2.8141    0.1445    0.1642    1.4073    0.0364    1.0457    0.0739
-#> 393:    92.1811   -5.8727   -2.1497   -4.2570   -0.9345    0.2212    0.0359    3.5226    1.0679    2.8127    0.1445    0.1642    1.4071    0.0364    1.0457    0.0739
-#> 394:    92.1811   -5.8712   -2.1500   -4.2572   -0.9346    0.2214    0.0360    3.5174    1.0684    2.8132    0.1446    0.1641    1.4067    0.0364    1.0456    0.0739
-#> 395:    92.1810   -5.8714   -2.1501   -4.2579   -0.9348    0.2217    0.0361    3.5182    1.0685    2.8171    0.1445    0.1641    1.4065    0.0364    1.0452    0.0740
-#> 396:    92.1809   -5.8711   -2.1501   -4.2582   -0.9350    0.2220    0.0363    3.5161    1.0681    2.8184    0.1446    0.1639    1.4063    0.0364    1.0447    0.0740
-#> 397:    92.1809   -5.8707   -2.1503   -4.2585   -0.9352    0.2222    0.0363    3.5119    1.0684    2.8197    0.1446    0.1637    1.4065    0.0364    1.0442    0.0740
-#> 398:    92.1808   -5.8703   -2.1503   -4.2591   -0.9354    0.2224    0.0363    3.5084    1.0689    2.8218    0.1447    0.1634    1.4064    0.0364    1.0445    0.0740
-#> 399:    92.1806   -5.8711   -2.1503   -4.2596   -0.9355    0.2226    0.0364    3.5114    1.0691    2.8234    0.1447    0.1629    1.4061    0.0364    1.0447    0.0740
-#> 400:    92.1806   -5.8713   -2.1503   -4.2601   -0.9356    0.2229    0.0366    3.5113    1.0695    2.8253    0.1448    0.1626    1.4059    0.0364    1.0440    0.0740
-#> 401:    92.1804   -5.8709   -2.1503   -4.2604   -0.9357    0.2231    0.0367    3.5089    1.0696    2.8266    0.1448    0.1624    1.4058    0.0364    1.0440    0.0740
-#> 402:    92.1801   -5.8705   -2.1502   -4.2606   -0.9358    0.2232    0.0368    3.5071    1.0695    2.8268    0.1447    0.1621    1.4060    0.0364    1.0447    0.0740
-#> 403:    92.1800   -5.8708   -2.1503   -4.2610   -0.9359    0.2234    0.0369    3.5083    1.0697    2.8271    0.1447    0.1618    1.4056    0.0365    1.0448    0.0739
-#> 404:    92.1798   -5.8709   -2.1505   -4.2612   -0.9360    0.2237    0.0369    3.5085    1.0699    2.8262    0.1447    0.1616    1.4055    0.0365    1.0449    0.0739
-#> 405:    92.1795   -5.8705   -2.1503   -4.2613   -0.9360    0.2239    0.0370    3.5059    1.0698    2.8254    0.1448    0.1615    1.4052    0.0364    1.0449    0.0739
-#> 406:    92.1792   -5.8710   -2.1504   -4.2613   -0.9359    0.2243    0.0371    3.5069    1.0696    2.8244    0.1449    0.1614    1.4049    0.0364    1.0447    0.0739
-#> 407:    92.1788   -5.8718   -2.1505   -4.2614   -0.9359    0.2243    0.0372    3.5092    1.0697    2.8234    0.1449    0.1614    1.4046    0.0364    1.0448    0.0739
-#> 408:    92.1786   -5.8729   -2.1505   -4.2615   -0.9360    0.2245    0.0373    3.5140    1.0699    2.8223    0.1449    0.1612    1.4045    0.0365    1.0455    0.0739
-#> 409:    92.1784   -5.8740   -2.1506   -4.2615   -0.9360    0.2246    0.0373    3.5192    1.0700    2.8213    0.1450    0.1610    1.4042    0.0365    1.0462    0.0738
-#> 410:    92.1782   -5.8753   -2.1505   -4.2616   -0.9361    0.2246    0.0373    3.5248    1.0705    2.8205    0.1450    0.1607    1.4040    0.0365    1.0465    0.0738
-#> 411:    92.1780   -5.8758   -2.1503   -4.2619   -0.9362    0.2247    0.0374    3.5249    1.0707    2.8204    0.1449    0.1605    1.4043    0.0364    1.0467    0.0738
-#> 412:    92.1778   -5.8759   -2.1502   -4.2621   -0.9363    0.2248    0.0374    3.5238    1.0707    2.8209    0.1448    0.1602    1.4045    0.0364    1.0466    0.0738
-#> 413:    92.1779   -5.8759   -2.1501   -4.2623   -0.9364    0.2249    0.0374    3.5225    1.0711    2.8213    0.1448    0.1600    1.4043    0.0364    1.0460    0.0738
-#> 414:    92.1781   -5.8754   -2.1500   -4.2622   -0.9364    0.2250    0.0374    3.5205    1.0710    2.8203    0.1448    0.1599    1.4047    0.0364    1.0456    0.0738
-#> 415:    92.1781   -5.8750   -2.1499   -4.2623   -0.9363    0.2251    0.0374    3.5187    1.0709    2.8190    0.1448    0.1598    1.4050    0.0364    1.0448    0.0738
-#> 416:    92.1783   -5.8747   -2.1500   -4.2624   -0.9363    0.2252    0.0375    3.5216    1.0708    2.8187    0.1448    0.1598    1.4052    0.0364    1.0440    0.0738
-#> 417:    92.1783   -5.8738   -2.1500   -4.2625   -0.9362    0.2252    0.0375    3.5219    1.0712    2.8188    0.1447    0.1597    1.4055    0.0364    1.0438    0.0739
-#> 418:    92.1784   -5.8735   -2.1501   -4.2627   -0.9360    0.2254    0.0375    3.5222    1.0715    2.8193    0.1448    0.1596    1.4057    0.0364    1.0438    0.0739
-#> 419:    92.1784   -5.8725   -2.1501   -4.2629   -0.9358    0.2255    0.0376    3.5190    1.0719    2.8202    0.1447    0.1594    1.4060    0.0364    1.0436    0.0739
-#> 420:    92.1785   -5.8713   -2.1500   -4.2633   -0.9357    0.2256    0.0377    3.5152    1.0723    2.8213    0.1447    0.1592    1.4065    0.0364    1.0439    0.0738
-#> 421:    92.1786   -5.8697   -2.1500   -4.2639   -0.9355    0.2257    0.0377    3.5100    1.0728    2.8232    0.1448    0.1592    1.4068    0.0364    1.0436    0.0739
-#> 422:    92.1787   -5.8683   -2.1502   -4.2645   -0.9352    0.2260    0.0377    3.5051    1.0732    2.8258    0.1448    0.1592    1.4069    0.0364    1.0432    0.0739
-#> 423:    92.1788   -5.8667   -2.1504   -4.2653   -0.9350    0.2262    0.0377    3.4992    1.0736    2.8292    0.1448    0.1592    1.4071    0.0364    1.0435    0.0738
-#> 424:    92.1789   -5.8659   -2.1505   -4.2661   -0.9349    0.2263    0.0378    3.4972    1.0739    2.8324    0.1448    0.1591    1.4069    0.0364    1.0439    0.0738
-#> 425:    92.1788   -5.8649   -2.1505   -4.2669   -0.9349    0.2263    0.0378    3.4947    1.0740    2.8358    0.1448    0.1590    1.4071    0.0364    1.0438    0.0738
-#> 426:    92.1788   -5.8643   -2.1506   -4.2677   -0.9348    0.2265    0.0377    3.4922    1.0743    2.8389    0.1448    0.1589    1.4070    0.0365    1.0437    0.0738
-#> 427:    92.1785   -5.8637   -2.1506   -4.2683   -0.9347    0.2266    0.0378    3.4895    1.0747    2.8425    0.1448    0.1588    1.4068    0.0365    1.0434    0.0738
-#> 428:    92.1783   -5.8627   -2.1507   -4.2689   -0.9347    0.2268    0.0378    3.4870    1.0749    2.8464    0.1447    0.1586    1.4070    0.0365    1.0434    0.0738
-#> 429:    92.1782   -5.8617   -2.1509   -4.2696   -0.9347    0.2271    0.0379    3.4845    1.0752    2.8500    0.1446    0.1584    1.4072    0.0365    1.0439    0.0738
-#> 430:    92.1783   -5.8608   -2.1510   -4.2701   -0.9347    0.2274    0.0379    3.4830    1.0755    2.8526    0.1446    0.1582    1.4075    0.0365    1.0443    0.0738
-#> 431:    92.1784   -5.8606   -2.1511   -4.2704   -0.9348    0.2275    0.0379    3.4825    1.0757    2.8532    0.1446    0.1580    1.4076    0.0365    1.0439    0.0738
-#> 432:    92.1784   -5.8610   -2.1512   -4.2707   -0.9350    0.2275    0.0378    3.4833    1.0761    2.8539    0.1447    0.1578    1.4079    0.0365    1.0443    0.0738
-#> 433:    92.1783   -5.8618   -2.1512   -4.2711   -0.9351    0.2276    0.0378    3.4867    1.0768    2.8554    0.1447    0.1577    1.4078    0.0366    1.0440    0.0738
-#> 434:    92.1784   -5.8612   -2.1513   -4.2714   -0.9350    0.2278    0.0378    3.4858    1.0774    2.8564    0.1448    0.1577    1.4074    0.0365    1.0430    0.0739
-#> 435:    92.1783   -5.8610   -2.1513   -4.2718   -0.9348    0.2279    0.0377    3.4874    1.0779    2.8581    0.1448    0.1576    1.4072    0.0366    1.0423    0.0739
-#> 436:    92.1781   -5.8610   -2.1513   -4.2721   -0.9346    0.2280    0.0376    3.4879    1.0789    2.8598    0.1448    0.1575    1.4070    0.0365    1.0417    0.0739
-#> 437:    92.1781   -5.8610   -2.1511   -4.2726   -0.9345    0.2279    0.0376    3.4886    1.0794    2.8618    0.1449    0.1574    1.4071    0.0365    1.0417    0.0739
-#> 438:    92.1781   -5.8609   -2.1510   -4.2730   -0.9345    0.2280    0.0375    3.4893    1.0797    2.8641    0.1449    0.1573    1.4075    0.0365    1.0420    0.0739
-#> 439:    92.1781   -5.8608   -2.1509   -4.2734   -0.9343    0.2280    0.0374    3.4894    1.0803    2.8659    0.1449    0.1573    1.4076    0.0365    1.0421    0.0739
-#> 440:    92.1780   -5.8603   -2.1510   -4.2737   -0.9343    0.2279    0.0374    3.4885    1.0808    2.8674    0.1448    0.1573    1.4079    0.0365    1.0430    0.0738
-#> 441:    92.1779   -5.8600   -2.1510   -4.2738   -0.9342    0.2279    0.0373    3.4899    1.0811    2.8686    0.1447    0.1574    1.4086    0.0365    1.0445    0.0737
-#> 442:    92.1779   -5.8600   -2.1509   -4.2737   -0.9343    0.2278    0.0372    3.4925    1.0814    2.8691    0.1447    0.1575    1.4088    0.0365    1.0451    0.0737
-#> 443:    92.1780   -5.8598   -2.1509   -4.2739   -0.9341    0.2278    0.0372    3.4949    1.0819    2.8705    0.1447    0.1576    1.4092    0.0365    1.0453    0.0737
-#> 444:    92.1779   -5.8593   -2.1510   -4.2742   -0.9340    0.2277    0.0371    3.4951    1.0824    2.8717    0.1447    0.1576    1.4096    0.0365    1.0455    0.0737
-#> 445:    92.1777   -5.8593   -2.1511   -4.2744   -0.9338    0.2275    0.0371    3.4999    1.0828    2.8729    0.1448    0.1576    1.4100    0.0365    1.0461    0.0736
-#> 446:    92.1774   -5.8600   -2.1511   -4.2748   -0.9338    0.2274    0.0372    3.5051    1.0837    2.8747    0.1449    0.1576    1.4099    0.0365    1.0464    0.0736
-#> 447:    92.1771   -5.8604   -2.1512   -4.2751   -0.9338    0.2273    0.0373    3.5087    1.0844    2.8758    0.1449    0.1575    1.4097    0.0365    1.0467    0.0736
-#> 448:    92.1769   -5.8607   -2.1513   -4.2756   -0.9336    0.2272    0.0374    3.5124    1.0849    2.8778    0.1449    0.1575    1.4098    0.0365    1.0470    0.0735
-#> 449:    92.1768   -5.8611   -2.1515   -4.2759   -0.9337    0.2270    0.0374    3.5165    1.0853    2.8789    0.1449    0.1575    1.4101    0.0365    1.0473    0.0735
-#> 450:    92.1766   -5.8611   -2.1515   -4.2762   -0.9337    0.2269    0.0374    3.5158    1.0859    2.8800    0.1448    0.1576    1.4102    0.0365    1.0474    0.0735
-#> 451:    92.1762   -5.8615   -2.1514   -4.2765   -0.9337    0.2267    0.0374    3.5202    1.0866    2.8812    0.1447    0.1576    1.4104    0.0365    1.0477    0.0735
-#> 452:    92.1761   -5.8622   -2.1514   -4.2767   -0.9337    0.2264    0.0374    3.5232    1.0871    2.8824    0.1447    0.1576    1.4103    0.0365    1.0479    0.0734
-#> 453:    92.1760   -5.8621   -2.1514   -4.2776   -0.9336    0.2261    0.0373    3.5247    1.0878    2.8901    0.1447    0.1576    1.4103    0.0365    1.0480    0.0734
-#> 454:    92.1759   -5.8611   -2.1513   -4.2781   -0.9335    0.2259    0.0373    3.5206    1.0882    2.8939    0.1448    0.1575    1.4104    0.0365    1.0483    0.0734
-#> 455:    92.1758   -5.8599   -2.1513   -4.2788   -0.9336    0.2258    0.0372    3.5151    1.0887    2.9010    0.1448    0.1575    1.4104    0.0365    1.0485    0.0734
-#> 456:    92.1760   -5.8583   -2.1512   -4.2797   -0.9335    0.2258    0.0372    3.5086    1.0892    2.9081    0.1448    0.1574    1.4105    0.0365    1.0483    0.0734
-#> 457:    92.1761   -5.8575   -2.1513   -4.2804   -0.9334    0.2257    0.0371    3.5041    1.0896    2.9144    0.1449    0.1574    1.4103    0.0365    1.0480    0.0733
-#> 458:    92.1763   -5.8569   -2.1512   -4.2813   -0.9334    0.2257    0.0370    3.5014    1.0901    2.9227    0.1449    0.1574    1.4102    0.0365    1.0476    0.0734
-#> 459:    92.1763   -5.8565   -2.1512   -4.2816   -0.9334    0.2256    0.0370    3.4991    1.0908    2.9248    0.1449    0.1573    1.4100    0.0365    1.0471    0.0734
-#> 460:    92.1764   -5.8557   -2.1513   -4.2818   -0.9333    0.2256    0.0370    3.4957    1.0915    2.9258    0.1449    0.1572    1.4097    0.0365    1.0466    0.0734
-#> 461:    92.1765   -5.8550   -2.1515   -4.2822   -0.9333    0.2255    0.0370    3.4923    1.0921    2.9296    0.1449    0.1571    1.4097    0.0365    1.0464    0.0734
-#> 462:    92.1764   -5.8546   -2.1517   -4.2824   -0.9333    0.2256    0.0370    3.4897    1.0925    2.9319    0.1448    0.1569    1.4093    0.0365    1.0463    0.0733
-#> 463:    92.1763   -5.8539   -2.1519   -4.2830   -0.9333    0.2256    0.0369    3.4863    1.0928    2.9373    0.1449    0.1568    1.4093    0.0366    1.0463    0.0733
-#> 464:    92.1763   -5.8532   -2.1520   -4.2833   -0.9333    0.2257    0.0370    3.4825    1.0933    2.9405    0.1448    0.1567    1.4093    0.0366    1.0462    0.0733
-#> 465:    92.1762   -5.8528   -2.1521   -4.2837   -0.9335    0.2257    0.0370    3.4795    1.0938    2.9433    0.1448    0.1567    1.4093    0.0366    1.0464    0.0733
-#> 466:    92.1762   -5.8530   -2.1523   -4.2840   -0.9336    0.2256    0.0370    3.4780    1.0943    2.9462    0.1448    0.1566    1.4089    0.0366    1.0466    0.0733
-#> 467:    92.1764   -5.8529   -2.1524   -4.2846   -0.9337    0.2256    0.0371    3.4751    1.0948    2.9506    0.1447    0.1565    1.4087    0.0366    1.0465    0.0733
-#> 468:    92.1765   -5.8531   -2.1525   -4.2849   -0.9337    0.2255    0.0371    3.4734    1.0952    2.9523    0.1447    0.1563    1.4087    0.0366    1.0465    0.0733
-#> 469:    92.1767   -5.8533   -2.1525   -4.2853   -0.9337    0.2254    0.0372    3.4754    1.0958    2.9540    0.1447    0.1561    1.4090    0.0366    1.0472    0.0733
-#> 470:    92.1767   -5.8536   -2.1525   -4.2858   -0.9338    0.2254    0.0373    3.4780    1.0965    2.9571    0.1448    0.1559    1.4094    0.0366    1.0478    0.0732
-#> 471:    92.1767   -5.8540   -2.1525   -4.2864   -0.9338    0.2254    0.0373    3.4812    1.0970    2.9606    0.1447    0.1558    1.4099    0.0366    1.0482    0.0732
-#> 472:    92.1766   -5.8547   -2.1526   -4.2871   -0.9339    0.2255    0.0373    3.4844    1.0975    2.9645    0.1446    0.1556    1.4101    0.0366    1.0482    0.0732
-#> 473:    92.1764   -5.8549   -2.1527   -4.2875   -0.9339    0.2255    0.0373    3.4848    1.0977    2.9672    0.1446    0.1554    1.4100    0.0366    1.0482    0.0732
-#> 474:    92.1762   -5.8553   -2.1528   -4.2880   -0.9338    0.2256    0.0373    3.4855    1.0979    2.9700    0.1445    0.1552    1.4104    0.0366    1.0484    0.0732
-#> 475:    92.1763   -5.8561   -2.1530   -4.2884   -0.9338    0.2256    0.0374    3.4885    1.0981    2.9726    0.1445    0.1549    1.4103    0.0366    1.0484    0.0731
-#> 476:    92.1763   -5.8564   -2.1530   -4.2885   -0.9339    0.2258    0.0374    3.4914    1.0983    2.9734    0.1444    0.1548    1.4106    0.0366    1.0484    0.0731
-#> 477:    92.1763   -5.8565   -2.1531   -4.2888   -0.9340    0.2259    0.0373    3.4941    1.0985    2.9755    0.1443    0.1546    1.4108    0.0366    1.0487    0.0731
-#> 478:    92.1763   -5.8576   -2.1532   -4.2889   -0.9340    0.2258    0.0373    3.4995    1.0987    2.9772    0.1442    0.1544    1.4111    0.0366    1.0490    0.0731
-#> 479:    92.1765   -5.8593   -2.1533   -4.2890   -0.9342    0.2259    0.0372    3.5086    1.0990    2.9787    0.1442    0.1544    1.4113    0.0366    1.0495    0.0731
-#> 480:    92.1766   -5.8613   -2.1535   -4.2892   -0.9342    0.2260    0.0372    3.5233    1.0991    2.9800    0.1442    0.1543    1.4116    0.0367    1.0496    0.0730
-#> 481:    92.1768   -5.8624   -2.1536   -4.2894   -0.9341    0.2260    0.0371    3.5309    1.0993    2.9820    0.1442    0.1542    1.4117    0.0367    1.0497    0.0730
-#> 482:    92.1766   -5.8634   -2.1537   -4.2896   -0.9341    0.2260    0.0371    3.5393    1.0995    2.9833    0.1443    0.1542    1.4116    0.0367    1.0496    0.0730
-#> 483:    92.1762   -5.8645   -2.1538   -4.2896   -0.9340    0.2260    0.0372    3.5472    1.0997    2.9840    0.1443    0.1542    1.4115    0.0367    1.0498    0.0730
-#> 484:    92.1757   -5.8648   -2.1538   -4.2896   -0.9340    0.2261    0.0373    3.5508    1.0998    2.9843    0.1445    0.1542    1.4115    0.0366    1.0498    0.0730
-#> 485:    92.1752   -5.8648   -2.1539   -4.2896   -0.9340    0.2262    0.0374    3.5516    1.1000    2.9846    0.1445    0.1542    1.4115    0.0366    1.0497    0.0730
-#> 486:    92.1747   -5.8649   -2.1539   -4.2897   -0.9340    0.2262    0.0375    3.5517    1.1003    2.9856    0.1446    0.1541    1.4113    0.0366    1.0498    0.0730
-#> 487:    92.1743   -5.8649   -2.1539   -4.2896   -0.9340    0.2262    0.0376    3.5502    1.1006    2.9856    0.1447    0.1539    1.4110    0.0367    1.0498    0.0730
-#> 488:    92.1739   -5.8645   -2.1540   -4.2893   -0.9340    0.2261    0.0377    3.5475    1.1008    2.9848    0.1447    0.1537    1.4106    0.0367    1.0497    0.0729
-#> 489:    92.1736   -5.8640   -2.1539   -4.2892   -0.9340    0.2260    0.0376    3.5445    1.1011    2.9844    0.1448    0.1536    1.4105    0.0367    1.0496    0.0729
-#> 490:    92.1736   -5.8631   -2.1539   -4.2889   -0.9340    0.2260    0.0376    3.5402    1.1014    2.9835    0.1448    0.1534    1.4103    0.0366    1.0496    0.0729
-#> 491:    92.1735   -5.8617   -2.1539   -4.2887   -0.9339    0.2260    0.0375    3.5343    1.1016    2.9825    0.1449    0.1532    1.4103    0.0366    1.0497    0.0729
-#> 492:    92.1736   -5.8609   -2.1539   -4.2884   -0.9339    0.2259    0.0375    3.5298    1.1017    2.9816    0.1449    0.1530    1.4101    0.0367    1.0499    0.0729
-#> 493:    92.1737   -5.8605   -2.1539   -4.2882   -0.9339    0.2260    0.0375    3.5266    1.1018    2.9807    0.1450    0.1529    1.4098    0.0367    1.0496    0.0729
-#> 494:    92.1739   -5.8609   -2.1539   -4.2881   -0.9340    0.2261    0.0375    3.5273    1.1018    2.9802    0.1450    0.1528    1.4097    0.0367    1.0495    0.0729
-#> 495:    92.1741   -5.8614   -2.1540   -4.2880   -0.9340    0.2262    0.0376    3.5290    1.1019    2.9797    0.1450    0.1526    1.4096    0.0367    1.0492    0.0729
-#> 496:    92.1742   -5.8623   -2.1540   -4.2879   -0.9341    0.2262    0.0376    3.5348    1.1020    2.9791    0.1449    0.1525    1.4096    0.0367    1.0491    0.0729
-#> 497:    92.1742   -5.8634   -2.1541   -4.2879   -0.9341    0.2264    0.0377    3.5402    1.1020    2.9789    0.1449    0.1524    1.4097    0.0367    1.0493    0.0729
-#> 498:    92.1744   -5.8637   -2.1543   -4.2879   -0.9341    0.2266    0.0377    3.5406    1.1019    2.9787    0.1449    0.1524    1.4096    0.0367    1.0496    0.0729
-#> 499:    92.1744   -5.8635   -2.1544   -4.2880   -0.9341    0.2268    0.0376    3.5400    1.1019    2.9789    0.1450    0.1523    1.4095    0.0367    1.0500    0.0728
-#> 500:    92.1744   -5.8628   -2.1545   -4.2882   -0.9341    0.2270    0.0377    3.5381    1.1020    2.9795    0.1450    0.1522    1.4096    0.0367    1.0503    0.0728
-#> Calculating covariance matrix
-#> 
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> Needed Covariates:
-#> [1] "CMT"
-#> Calculating residuals/tables
-#> done
-f_nlmixr_dfop_sfo_focei_obs_tc <- nlmixr(f_mmkin_tc["DFOP-SFO", ], est = "focei",
-  error_model = "obs_tc")
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → calculate jacobian
-#> 
-#> → calculate sensitivities
-#> 
-#> → calculate ∂(f)/∂(η)
-#> 
-#> → calculate ∂(R²)/∂(η)
-#> 
-#> → finding duplicate expressions in inner model...
-#> 
-#> → optimizing duplicate expressions in inner model...
-#> 
-#> → finding duplicate expressions in EBE model...
-#> 
-#> → optimizing duplicate expressions in EBE model...
-#> 
-#> → compiling inner model...
-#>  
-#> ✔ done
-#> → finding duplicate expressions in FD model...
-#> 
-#> → optimizing duplicate expressions in FD model...
-#> 
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> → compiling events FD model...
-#>  
-#> ✔ done
-#> Needed Covariates:
-#> [1] "CMT"
-#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> |    #| Objective Fun |  parent_0 |  log_k_A1 |f_parent_qlogis |    log_k1 |
-#> |.....................|    log_k2 |  g_qlogis |sigma_low_parent |rsd_high_parent |
-#> |.....................|sigma_low_A1 |rsd_high_A1 |        o1 |        o2 |
-#> |.....................|        o3 |        o4 |        o5 |        o6 |
-#> |    1|     495.48573 |     1.000 |    -1.000 |   -0.9104 |   -0.9376 |
-#> |.....................|   -0.9875 |   -0.8823 |   -0.8746 |   -0.8907 |
-#> |.....................|   -0.8746 |   -0.8907 |   -0.8767 |   -0.8731 |
-#> |.....................|   -0.8673 |   -0.8720 |   -0.8739 |   -0.8666 |
-#> |    U|     495.48573 |     91.00 |    -5.200 |   -0.8900 |    -2.200 |
-#> |.....................|    -4.600 |    0.4600 |    0.8300 |   0.05800 |
-#> |.....................|    0.8300 |   0.05800 |    0.7311 |    0.9036 |
-#> |.....................|     1.183 |    0.9554 |    0.8633 |     1.214 |
-#> |    X|     495.48573 |     91.00 |  0.005517 |    0.2911 |    0.1108 |
-#> |.....................|   0.01005 |    0.6130 |    0.8300 |   0.05800 |
-#> |.....................|    0.8300 |   0.05800 |    0.7311 |    0.9036 |
-#> |.....................|     1.183 |    0.9554 |    0.8633 |     1.214 |
-#> |    G|    Gill Diff. |   -0.9648 |     2.223 |   -0.3153 |  -0.01817 |
-#> |.....................|   -0.3350 |    0.6789 |    -23.42 |    -17.64 |
-#> |.....................|    -5.440 |    -1.950 |    0.9642 |     9.851 |
-#> |.....................|    -11.94 |    -1.319 |     8.578 |    -12.45 |
-#> |    2|     481.75012 |     1.026 |    -1.060 |   -0.9019 |   -0.9371 |
-#> |.....................|   -0.9785 |   -0.9007 |   -0.2420 |   -0.4142 |
-#> |.....................|   -0.7277 |   -0.8380 |   -0.9027 |    -1.139 |
-#> |.....................|   -0.5448 |   -0.8364 |    -1.106 |   -0.5303 |
-#> |    U|     481.75012 |     93.37 |    -5.260 |   -0.8824 |    -2.200 |
-#> |.....................|    -4.591 |    0.4516 |     1.093 |   0.07182 |
-#> |.....................|    0.8910 |   0.05953 |    0.7121 |    0.6631 |
-#> |.....................|     1.565 |    0.9895 |    0.6633 |     1.623 |
-#> |    X|     481.75012 |     93.37 |  0.005195 |    0.2927 |    0.1109 |
-#> |.....................|   0.01014 |    0.6110 |     1.093 |   0.07182 |
-#> |.....................|    0.8910 |   0.05953 |    0.7121 |    0.6631 |
-#> |.....................|     1.565 |    0.9895 |    0.6633 |     1.623 |
-#> |    F| Forward Diff. |     152.5 |     1.317 |     3.315 |   -0.1772 |
-#> |.....................|    0.3391 |    0.1426 |    -4.513 |     6.696 |
-#> |.....................|     1.211 |    0.7988 |    0.6299 |    -5.324 |
-#> |.....................|  0.009964 |     3.044 |    -5.727 |    -6.694 |
-#> |    3|     3004.9713 |    0.2745 |    -1.093 |   -0.9147 |   -0.9360 |
-#> |.....................|   -0.9762 |   -0.9095 |   0.05941 |   -0.2377 |
-#> |.....................|   -0.6690 |   -0.8188 |   -0.9174 |    -1.204 |
-#> |.....................|   -0.4027 |   -0.8359 |    -1.205 |   -0.3486 |
-#> |    U|     3004.9713 |     24.98 |    -5.293 |   -0.8938 |    -2.198 |
-#> |.....................|    -4.589 |    0.4475 |     1.218 |   0.07694 |
-#> |.....................|    0.9154 |   0.06008 |    0.7014 |    0.6043 |
-#> |.....................|     1.733 |    0.9899 |    0.5774 |     1.843 |
-#> |    X|     3004.9713 |     24.98 |  0.005026 |    0.2903 |    0.1110 |
-#> |.....................|   0.01017 |    0.6100 |     1.218 |   0.07694 |
-#> |.....................|    0.9154 |   0.06008 |    0.7014 |    0.6043 |
-#> |.....................|     1.733 |    0.9899 |    0.5774 |     1.843 |
-#> |    4|     491.68825 |    0.9393 |    -1.061 |   -0.9038 |   -0.9370 |
-#> |.....................|   -0.9787 |   -0.9008 |   -0.2394 |   -0.4180 |
-#> |.....................|   -0.7284 |   -0.8385 |   -0.9031 |    -1.136 |
-#> |.....................|   -0.5448 |   -0.8381 |    -1.102 |   -0.5265 |
-#> |    U|     491.68825 |     85.47 |    -5.261 |   -0.8841 |    -2.199 |
-#> |.....................|    -4.591 |    0.4515 |     1.094 |   0.07171 |
-#> |.....................|    0.8907 |   0.05951 |    0.7118 |    0.6659 |
-#> |.....................|     1.565 |    0.9878 |    0.6661 |     1.627 |
-#> |    X|     491.68825 |     85.47 |  0.005191 |    0.2923 |    0.1109 |
-#> |.....................|   0.01014 |    0.6110 |     1.094 |   0.07171 |
-#> |.....................|    0.8907 |   0.05951 |    0.7118 |    0.6659 |
-#> |.....................|     1.565 |    0.9878 |    0.6661 |     1.627 |
-#> |    5|     479.72282 |     1.001 |    -1.060 |   -0.9024 |   -0.9371 |
-#> |.....................|   -0.9785 |   -0.9007 |   -0.2413 |   -0.4153 |
-#> |.....................|   -0.7279 |   -0.8381 |   -0.9028 |    -1.138 |
-#> |.....................|   -0.5448 |   -0.8369 |    -1.105 |   -0.5292 |
-#> |    U|     479.72282 |     91.11 |    -5.260 |   -0.8829 |    -2.199 |
-#> |.....................|    -4.591 |    0.4516 |     1.093 |   0.07179 |
-#> |.....................|    0.8909 |   0.05952 |    0.7120 |    0.6639 |
-#> |.....................|     1.565 |    0.9890 |    0.6641 |     1.624 |
-#> |    X|     479.72282 |     91.11 |  0.005194 |    0.2926 |    0.1109 |
-#> |.....................|   0.01014 |    0.6110 |     1.093 |   0.07179 |
-#> |.....................|    0.8909 |   0.05952 |    0.7120 |    0.6639 |
-#> |.....................|     1.565 |    0.9890 |    0.6641 |     1.624 |
-#> |    F| Forward Diff. |     6.589 |     1.222 |    0.9137 |    0.1103 |
-#> |.....................|    0.3993 |    0.5206 |    -3.904 |     6.654 |
-#> |.....................|    0.9090 |     1.134 |    -1.839 |    -6.108 |
-#> |.....................|     1.622 |     4.007 |    -4.921 |    -6.374 |
-#> |    6|     479.56384 |    0.9950 |    -1.061 |   -0.9037 |   -0.9373 |
-#> |.....................|   -0.9792 |   -0.9012 |   -0.2438 |   -0.4298 |
-#> |.....................|   -0.7309 |   -0.8403 |   -0.9001 |    -1.126 |
-#> |.....................|   -0.5509 |   -0.8426 |    -1.095 |   -0.5241 |
-#> |    U|     479.56384 |     90.55 |    -5.261 |   -0.8840 |    -2.200 |
-#> |.....................|    -4.592 |    0.4513 |     1.092 |   0.07137 |
-#> |.....................|    0.8897 |   0.05946 |    0.7140 |    0.6748 |
-#> |.....................|     1.558 |    0.9836 |    0.6729 |     1.630 |
-#> |    X|     479.56384 |     90.55 |  0.005189 |    0.2923 |    0.1108 |
-#> |.....................|   0.01014 |    0.6110 |     1.092 |   0.07137 |
-#> |.....................|    0.8897 |   0.05946 |    0.7140 |    0.6748 |
-#> |.....................|     1.558 |    0.9836 |    0.6729 |     1.630 |
-#> |    F| Forward Diff. |    -31.71 |     1.225 |    0.1963 |    0.1681 |
-#> |.....................|    0.4113 |    0.6853 |    -4.208 |     6.141 |
-#> |.....................|    0.7033 |     1.163 |    -2.029 |    -4.071 |
-#> |.....................|    -1.106 |     3.494 |    -3.921 |    -6.098 |
-#> |    7|     479.23599 |     1.003 |    -1.063 |   -0.9048 |   -0.9375 |
-#> |.....................|   -0.9799 |   -0.9023 |   -0.2352 |   -0.4403 |
-#> |.....................|   -0.7320 |   -0.8422 |   -0.8974 |    -1.117 |
-#> |.....................|   -0.5472 |   -0.8484 |    -1.086 |   -0.5115 |
-#> |    U|     479.23599 |     91.29 |    -5.263 |   -0.8850 |    -2.200 |
-#> |.....................|    -4.592 |    0.4508 |     1.095 |   0.07106 |
-#> |.....................|    0.8892 |   0.05941 |    0.7160 |    0.6828 |
-#> |.....................|     1.562 |    0.9781 |    0.6800 |     1.645 |
-#> |    X|     479.23599 |     91.29 |  0.005177 |    0.2921 |    0.1108 |
-#> |.....................|   0.01013 |    0.6108 |     1.095 |   0.07106 |
-#> |.....................|    0.8892 |   0.05941 |    0.7160 |    0.6828 |
-#> |.....................|     1.562 |    0.9781 |    0.6800 |     1.645 |
-#> |    F| Forward Diff. |     18.36 |     1.286 |    0.8956 |   0.06941 |
-#> |.....................|    0.3942 |    0.6495 |    -3.460 |     6.349 |
-#> |.....................|    0.7828 |    0.9998 |    -1.947 |    -2.931 |
-#> |.....................|    0.1591 |     2.144 |    -3.375 |    -5.909 |
-#> |    8|     479.05200 |    0.9982 |    -1.066 |   -0.9056 |   -0.9376 |
-#> |.....................|   -0.9803 |   -0.9037 |   -0.2181 |   -0.4407 |
-#> |.....................|   -0.7304 |   -0.8427 |   -0.8951 |    -1.119 |
-#> |.....................|   -0.5384 |   -0.8504 |    -1.087 |   -0.4972 |
-#> |    U|       479.052 |     90.84 |    -5.266 |   -0.8857 |    -2.200 |
-#> |.....................|    -4.593 |    0.4502 |     1.102 |   0.07105 |
-#> |.....................|    0.8899 |   0.05939 |    0.7177 |    0.6818 |
-#> |.....................|     1.572 |    0.9761 |    0.6797 |     1.663 |
-#> |    X|       479.052 |     90.84 |  0.005162 |    0.2920 |    0.1108 |
-#> |.....................|   0.01012 |    0.6107 |     1.102 |   0.07105 |
-#> |.....................|    0.8899 |   0.05939 |    0.7177 |    0.6818 |
-#> |.....................|     1.572 |    0.9761 |    0.6797 |     1.663 |
-#> |    9|     478.91507 |    0.9977 |    -1.070 |   -0.9061 |   -0.9377 |
-#> |.....................|   -0.9807 |   -0.9051 |   -0.2002 |   -0.4395 |
-#> |.....................|   -0.7284 |   -0.8431 |   -0.8930 |    -1.121 |
-#> |.....................|   -0.5287 |   -0.8520 |    -1.088 |   -0.4828 |
-#> |    U|     478.91507 |     90.79 |    -5.270 |   -0.8862 |    -2.200 |
-#> |.....................|    -4.593 |    0.4495 |     1.110 |   0.07109 |
-#> |.....................|    0.8907 |   0.05938 |    0.7192 |    0.6799 |
-#> |.....................|     1.584 |    0.9745 |    0.6785 |     1.680 |
-#> |    X|     478.91507 |     90.79 |  0.005146 |    0.2919 |    0.1108 |
-#> |.....................|   0.01012 |    0.6105 |     1.110 |   0.07109 |
-#> |.....................|    0.8907 |   0.05938 |    0.7192 |    0.6799 |
-#> |.....................|     1.584 |    0.9745 |    0.6785 |     1.680 |
-#> |   10|     478.54700 |    0.9959 |    -1.080 |   -0.9081 |   -0.9381 |
-#> |.....................|   -0.9820 |   -0.9099 |   -0.1391 |   -0.4353 |
-#> |.....................|   -0.7215 |   -0.8442 |   -0.8862 |    -1.128 |
-#> |.....................|   -0.4957 |   -0.8577 |    -1.093 |   -0.4342 |
-#> |    U|       478.547 |     90.63 |    -5.280 |   -0.8880 |    -2.200 |
-#> |.....................|    -4.594 |    0.4473 |     1.135 |   0.07121 |
-#> |.....................|    0.8936 |   0.05935 |    0.7242 |    0.6734 |
-#> |.....................|     1.623 |    0.9691 |    0.6746 |     1.739 |
-#> |    X|       478.547 |     90.63 |  0.005094 |    0.2915 |    0.1108 |
-#> |.....................|   0.01011 |    0.6100 |     1.135 |   0.07121 |
-#> |.....................|    0.8936 |   0.05935 |    0.7242 |    0.6734 |
-#> |.....................|     1.623 |    0.9691 |    0.6746 |     1.739 |
-#> |   11|     478.24707 |    0.9926 |    -1.098 |   -0.9118 |   -0.9388 |
-#> |.....................|   -0.9843 |   -0.9186 |  -0.02735 |   -0.4276 |
-#> |.....................|   -0.7088 |   -0.8464 |   -0.8736 |    -1.141 |
-#> |.....................|   -0.4354 |   -0.8680 |    -1.101 |   -0.3451 |
-#> |    U|     478.24707 |     90.33 |    -5.298 |   -0.8913 |    -2.201 |
-#> |.....................|    -4.597 |    0.4433 |     1.182 |   0.07143 |
-#> |.....................|    0.8988 |   0.05929 |    0.7334 |    0.6616 |
-#> |.....................|     1.694 |    0.9593 |    0.6674 |     1.848 |
-#> |    X|     478.24707 |     90.33 |  0.004999 |    0.2909 |    0.1107 |
-#> |.....................|   0.01008 |    0.6090 |     1.182 |   0.07143 |
-#> |.....................|    0.8988 |   0.05929 |    0.7334 |    0.6616 |
-#> |.....................|     1.694 |    0.9593 |    0.6674 |     1.848 |
-#> |    F| Forward Diff. |    -54.86 |     1.159 |   -0.2545 |    0.1198 |
-#> |.....................|    0.4779 |     1.320 |    -1.627 |     7.719 |
-#> |.....................|     1.488 |     1.194 |    -2.008 |    -4.434 |
-#> |.....................|     3.563 |    0.8010 |    -2.393 |    -3.495 |
-#> |   12|     475.90466 |     1.002 |    -1.127 |   -0.9233 |   -0.9398 |
-#> |.....................|   -0.9978 |   -0.9482 |  -0.05448 |   -0.6822 |
-#> |.....................|   -0.7579 |   -0.8801 |   -0.8190 |    -1.095 |
-#> |.....................|   -0.4550 |   -0.8498 |    -1.031 |   -0.2699 |
-#> |    U|     475.90466 |     91.18 |    -5.327 |   -0.9014 |    -2.202 |
-#> |.....................|    -4.610 |    0.4297 |     1.170 |   0.06405 |
-#> |.....................|    0.8785 |   0.05831 |    0.7733 |    0.7032 |
-#> |.....................|     1.671 |    0.9767 |    0.7277 |     1.939 |
-#> |    X|     475.90466 |     91.18 |  0.004860 |    0.2888 |    0.1106 |
-#> |.....................|  0.009950 |    0.6058 |     1.170 |   0.06405 |
-#> |.....................|    0.8785 |   0.05831 |    0.7733 |    0.7032 |
-#> |.....................|     1.671 |    0.9767 |    0.7277 |     1.939 |
-#> |    F| Forward Diff. |    -5.773 |     1.281 |   0.05418 |  -0.06269 |
-#> |.....................|    0.4104 |     1.812 |    -4.981 |     3.640 |
-#> |.....................|  -0.08126 |   0.09477 |    -1.092 |    -2.966 |
-#> |.....................|     5.262 |     2.712 |     3.245 |    -2.012 |
-#> |   13|     477.06760 |     1.030 |    -1.176 |   -0.9281 |   -0.9377 |
-#> |.....................|    -1.013 |    -1.011 |   0.09564 |   -0.8420 |
-#> |.....................|   -0.7668 |   -0.8907 |   -0.7738 |    -1.073 |
-#> |.....................|   -0.5619 |   -0.8693 |    -1.126 |   -0.1773 |
-#> |    U|      477.0676 |     93.71 |    -5.376 |   -0.9057 |    -2.200 |
-#> |.....................|    -4.625 |    0.4008 |     1.233 |   0.05941 |
-#> |.....................|    0.8748 |   0.05800 |    0.8064 |    0.7234 |
-#> |.....................|     1.545 |    0.9581 |    0.6461 |     2.051 |
-#> |    X|      477.0676 |     93.71 |  0.004627 |    0.2879 |    0.1108 |
-#> |.....................|  0.009799 |    0.5989 |     1.233 |   0.05941 |
-#> |.....................|    0.8748 |   0.05800 |    0.8064 |    0.7234 |
-#> |.....................|     1.545 |    0.9581 |    0.6461 |     2.051 |
-#> |   14|     477.20174 |     1.026 |    -1.143 |   -0.9246 |   -0.9391 |
-#> |.....................|    -1.003 |   -0.9695 | -0.001726 |   -0.7335 |
-#> |.....................|   -0.7599 |   -0.8831 |   -0.8043 |    -1.080 |
-#> |.....................|   -0.4976 |   -0.8627 |    -1.065 |   -0.2404 |
-#> |    U|     477.20174 |     93.37 |    -5.343 |   -0.9027 |    -2.201 |
-#> |.....................|    -4.615 |    0.4199 |     1.192 |   0.06256 |
-#> |.....................|    0.8776 |   0.05822 |    0.7840 |    0.7162 |
-#> |.....................|     1.621 |    0.9644 |    0.6988 |     1.975 |
-#> |    X|     477.20174 |     93.37 |  0.004782 |    0.2885 |    0.1106 |
-#> |.....................|  0.009899 |    0.6035 |     1.192 |   0.06256 |
-#> |.....................|    0.8776 |   0.05822 |    0.7840 |    0.7162 |
-#> |.....................|     1.621 |    0.9644 |    0.6988 |     1.975 |
-#> |   15|     476.22973 |     1.014 |    -1.129 |   -0.9234 |   -0.9397 |
-#> |.....................|   -0.9986 |   -0.9521 |  -0.04396 |   -0.6899 |
-#> |.....................|   -0.7577 |   -0.8803 |   -0.8167 |    -1.089 |
-#> |.....................|   -0.4661 |   -0.8555 |    -1.038 |   -0.2656 |
-#> |    U|     476.22973 |     92.29 |    -5.329 |   -0.9015 |    -2.202 |
-#> |.....................|    -4.611 |    0.4279 |     1.175 |   0.06382 |
-#> |.....................|    0.8785 |   0.05830 |    0.7750 |    0.7089 |
-#> |.....................|     1.658 |    0.9712 |    0.7218 |     1.944 |
-#> |    X|     476.22973 |     92.29 |  0.004847 |    0.2887 |    0.1106 |
-#> |.....................|  0.009941 |    0.6054 |     1.175 |   0.06382 |
-#> |.....................|    0.8785 |   0.05830 |    0.7750 |    0.7089 |
-#> |.....................|     1.658 |    0.9712 |    0.7218 |     1.944 |
-#> |   16|     475.87776 |     1.005 |    -1.127 |   -0.9233 |   -0.9398 |
-#> |.....................|   -0.9980 |   -0.9491 |  -0.05201 |   -0.6840 |
-#> |.....................|   -0.7578 |   -0.8802 |   -0.8184 |    -1.093 |
-#> |.....................|   -0.4576 |   -0.8511 |    -1.033 |   -0.2689 |
-#> |    U|     475.87776 |     91.44 |    -5.327 |   -0.9015 |    -2.202 |
-#> |.....................|    -4.610 |    0.4293 |     1.171 |   0.06399 |
-#> |.....................|    0.8785 |   0.05830 |    0.7737 |    0.7045 |
-#> |.....................|     1.668 |    0.9754 |    0.7263 |     1.940 |
-#> |    X|     475.87776 |     91.44 |  0.004857 |    0.2887 |    0.1106 |
-#> |.....................|  0.009948 |    0.6057 |     1.171 |   0.06399 |
-#> |.....................|    0.8785 |   0.05830 |    0.7737 |    0.7045 |
-#> |.....................|     1.668 |    0.9754 |    0.7263 |     1.940 |
-#> |    F| Forward Diff. |     16.12 |     1.298 |    0.4116 |  -0.09723 |
-#> |.....................|    0.4002 |     1.728 |    -4.991 |     3.781 |
-#> |.....................|  -0.06392 |   0.04117 |    -1.251 |   -0.6787 |
-#> |.....................|     5.079 |     2.620 |     3.013 |    -2.074 |
-#> |   17|     475.82399 |     1.002 |    -1.128 |   -0.9234 |   -0.9397 |
-#> |.....................|   -0.9982 |   -0.9501 |  -0.04950 |   -0.6866 |
-#> |.....................|   -0.7580 |   -0.8803 |   -0.8177 |    -1.093 |
-#> |.....................|   -0.4596 |   -0.8518 |    -1.034 |   -0.2675 |
-#> |    U|     475.82399 |     91.17 |    -5.328 |   -0.9016 |    -2.202 |
-#> |.....................|    -4.611 |    0.4288 |     1.172 |   0.06392 |
-#> |.....................|    0.8784 |   0.05830 |    0.7743 |    0.7045 |
-#> |.....................|     1.666 |    0.9748 |    0.7251 |     1.942 |
-#> |    X|     475.82399 |     91.17 |  0.004853 |    0.2887 |    0.1106 |
-#> |.....................|  0.009945 |    0.6056 |     1.172 |   0.06392 |
-#> |.....................|    0.8784 |   0.05830 |    0.7743 |    0.7045 |
-#> |.....................|     1.666 |    0.9748 |    0.7251 |     1.942 |
-#> |    F| Forward Diff. |    -7.267 |     1.279 |  0.007095 |  -0.05940 |
-#> |.....................|    0.4115 |     1.783 |    -5.114 |     3.652 |
-#> |.....................|   -0.1068 |    0.1083 |    -1.295 |   -0.9578 |
-#> |.....................|     2.682 |     2.514 |     3.014 |    -2.035 |
-#> |   18|     475.78862 |     1.005 |    -1.129 |   -0.9235 |   -0.9397 |
-#> |.....................|   -0.9985 |   -0.9512 |  -0.04657 |   -0.6892 |
-#> |.....................|   -0.7580 |   -0.8804 |   -0.8168 |    -1.093 |
-#> |.....................|   -0.4611 |   -0.8527 |    -1.036 |   -0.2661 |
-#> |    U|     475.78862 |     91.41 |    -5.329 |   -0.9016 |    -2.202 |
-#> |.....................|    -4.611 |    0.4283 |     1.174 |   0.06384 |
-#> |.....................|    0.8784 |   0.05830 |    0.7749 |    0.7045 |
-#> |.....................|     1.664 |    0.9739 |    0.7236 |     1.943 |
-#> |    X|     475.78862 |     91.41 |  0.004849 |    0.2887 |    0.1106 |
-#> |.....................|  0.009942 |    0.6055 |     1.174 |   0.06384 |
-#> |.....................|    0.8784 |   0.05830 |    0.7749 |    0.7045 |
-#> |.....................|     1.664 |    0.9739 |    0.7236 |     1.943 |
-#> |    F| Forward Diff. |     13.19 |     1.292 |    0.3498 |  -0.09321 |
-#> |.....................|    0.4023 |     1.703 |    -5.372 |     3.699 |
-#> |.....................|   -0.1234 |   0.05429 |    -1.241 |   -0.7588 |
-#> |.....................|     4.815 |     2.436 |     2.783 |    -2.083 |
-#> |   19|     475.73531 |     1.002 |    -1.130 |   -0.9236 |   -0.9397 |
-#> |.....................|   -0.9987 |   -0.9524 |  -0.04361 |   -0.6921 |
-#> |.....................|   -0.7582 |   -0.8806 |   -0.8159 |    -1.094 |
-#> |.....................|   -0.4630 |   -0.8531 |    -1.037 |   -0.2646 |
-#> |    U|     475.73531 |     91.21 |    -5.330 |   -0.9018 |    -2.202 |
-#> |.....................|    -4.611 |    0.4278 |     1.175 |   0.06376 |
-#> |.....................|    0.8783 |   0.05829 |    0.7756 |    0.7041 |
-#> |.....................|     1.662 |    0.9735 |    0.7222 |     1.945 |
-#> |    X|     475.73531 |     91.21 |  0.004845 |    0.2887 |    0.1106 |
-#> |.....................|  0.009940 |    0.6053 |     1.175 |   0.06376 |
-#> |.....................|    0.8783 |   0.05829 |    0.7756 |    0.7041 |
-#> |.....................|     1.662 |    0.9735 |    0.7222 |     1.945 |
-#> |    F| Forward Diff. |    -3.312 |     1.277 |   0.06663 |  -0.06695 |
-#> |.....................|    0.4102 |     1.736 |    -5.095 |     3.555 |
-#> |.....................|  -0.08175 |   0.08515 |    -1.253 |   -0.9364 |
-#> |.....................|     4.836 |     2.452 |     2.739 |    -2.058 |
-#> |   20|     475.69941 |     1.004 |    -1.131 |   -0.9237 |   -0.9396 |
-#> |.....................|   -0.9990 |   -0.9534 |  -0.04063 |   -0.6942 |
-#> |.....................|   -0.7581 |   -0.8807 |   -0.8151 |    -1.093 |
-#> |.....................|   -0.4658 |   -0.8545 |    -1.039 |   -0.2634 |
-#> |    U|     475.69941 |     91.39 |    -5.331 |   -0.9018 |    -2.202 |
-#> |.....................|    -4.611 |    0.4273 |     1.176 |   0.06370 |
-#> |.....................|    0.8783 |   0.05829 |    0.7761 |    0.7046 |
-#> |.....................|     1.658 |    0.9722 |    0.7208 |     1.947 |
-#> |    X|     475.69941 |     91.39 |  0.004841 |    0.2887 |    0.1106 |
-#> |.....................|  0.009937 |    0.6052 |     1.176 |   0.06370 |
-#> |.....................|    0.8783 |   0.05829 |    0.7761 |    0.7046 |
-#> |.....................|     1.658 |    0.9722 |    0.7208 |     1.947 |
-#> |    F| Forward Diff. |     11.57 |     1.287 |    0.3079 |  -0.08979 |
-#> |.....................|    0.4039 |     1.674 |    -5.153 |     3.653 |
-#> |.....................|  -0.06063 |   0.04440 |    -1.200 |   -0.7646 |
-#> |.....................|     2.452 |     2.339 |     2.552 |    -2.095 |
-#> |   21|     475.66307 |     1.001 |    -1.131 |   -0.9238 |   -0.9396 |
-#> |.....................|   -0.9992 |   -0.9545 |  -0.03780 |   -0.6969 |
-#> |.....................|   -0.7583 |   -0.8808 |   -0.8143 |    -1.094 |
-#> |.....................|   -0.4671 |   -0.8550 |    -1.041 |   -0.2620 |
-#> |    U|     475.66307 |     91.11 |    -5.331 |   -0.9019 |    -2.202 |
-#> |.....................|    -4.612 |    0.4268 |     1.177 |   0.06362 |
-#> |.....................|    0.8783 |   0.05829 |    0.7767 |    0.7044 |
-#> |.....................|     1.657 |    0.9717 |    0.7195 |     1.948 |
-#> |    X|     475.66307 |     91.11 |  0.004837 |    0.2887 |    0.1106 |
-#> |.....................|  0.009935 |    0.6051 |     1.177 |   0.06362 |
-#> |.....................|    0.8783 |   0.05829 |    0.7767 |    0.7044 |
-#> |.....................|     1.657 |    0.9717 |    0.7195 |     1.948 |
-#> |    F| Forward Diff. |    -12.57 |     1.267 |  -0.09715 |  -0.05310 |
-#> |.....................|    0.4138 |     1.728 |    -5.558 |     3.438 |
-#> |.....................|   -0.1081 |    0.1203 |    -1.232 |    -1.053 |
-#> |.....................|     2.344 |     2.291 |     2.543 |    -2.059 |
-#> |   22|     475.61346 |     1.003 |    -1.132 |   -0.9238 |   -0.9395 |
-#> |.....................|   -0.9995 |   -0.9557 |  -0.03467 |   -0.6999 |
-#> |.....................|   -0.7585 |   -0.8810 |   -0.8134 |    -1.094 |
-#> |.....................|   -0.4680 |   -0.8550 |    -1.042 |   -0.2607 |
-#> |    U|     475.61346 |     91.32 |    -5.332 |   -0.9020 |    -2.202 |
-#> |.....................|    -4.612 |    0.4262 |     1.179 |   0.06353 |
-#> |.....................|    0.8782 |   0.05828 |    0.7774 |    0.7040 |
-#> |.....................|     1.656 |    0.9717 |    0.7181 |     1.950 |
-#> |    X|     475.61346 |     91.32 |  0.004833 |    0.2886 |    0.1106 |
-#> |.....................|  0.009932 |    0.6050 |     1.179 |   0.06353 |
-#> |.....................|    0.8782 |   0.05828 |    0.7774 |    0.7040 |
-#> |.....................|     1.656 |    0.9717 |    0.7181 |     1.950 |
-#> |    F| Forward Diff. |     5.192 |     1.277 |    0.1967 |  -0.08157 |
-#> |.....................|    0.4060 |     1.656 |    -5.231 |     3.627 |
-#> |.....................|   -0.1038 |   0.05786 |    -1.199 |   -0.8859 |
-#> |.....................|     2.283 |     2.293 |     2.331 |    -2.101 |
-#> |   23|     475.58436 |     1.001 |    -1.133 |   -0.9239 |   -0.9395 |
-#> |.....................|   -0.9998 |   -0.9568 |  -0.03140 |   -0.7025 |
-#> |.....................|   -0.7585 |   -0.8810 |   -0.8126 |    -1.094 |
-#> |.....................|   -0.4692 |   -0.8560 |    -1.044 |   -0.2594 |
-#> |    U|     475.58436 |     91.09 |    -5.333 |   -0.9021 |    -2.202 |
-#> |.....................|    -4.612 |    0.4257 |     1.180 |   0.06346 |
-#> |.....................|    0.8782 |   0.05828 |    0.7780 |    0.7043 |
-#> |.....................|     1.654 |    0.9707 |    0.7167 |     1.952 |
-#> |    X|     475.58436 |     91.09 |  0.004829 |    0.2886 |    0.1106 |
-#> |.....................|  0.009929 |    0.6049 |     1.180 |   0.06346 |
-#> |.....................|    0.8782 |   0.05828 |    0.7780 |    0.7043 |
-#> |.....................|     1.654 |    0.9707 |    0.7167 |     1.952 |
-#> |    F| Forward Diff. |    -14.46 |     1.261 |   -0.1306 |  -0.05131 |
-#> |.....................|    0.4140 |     1.696 |    -5.518 |     3.404 |
-#> |.....................|   -0.1407 |    0.1181 |    -1.199 |    -1.071 |
-#> |.....................|     2.272 |     2.212 |     2.296 |    -2.075 |
-#> |   24|     475.53229 |     1.003 |    -1.134 |   -0.9240 |   -0.9394 |
-#> |.....................|    -1.000 |   -0.9581 |  -0.02828 |   -0.7055 |
-#> |.....................|   -0.7587 |   -0.8812 |   -0.8117 |    -1.094 |
-#> |.....................|   -0.4701 |   -0.8560 |    -1.045 |   -0.2580 |
-#> |    U|     475.53229 |     91.31 |    -5.334 |   -0.9021 |    -2.202 |
-#> |.....................|    -4.613 |    0.4251 |     1.181 |   0.06337 |
-#> |.....................|    0.8781 |   0.05828 |    0.7786 |    0.7039 |
-#> |.....................|     1.653 |    0.9708 |    0.7153 |     1.953 |
-#> |    X|     475.53229 |     91.31 |  0.004824 |    0.2886 |    0.1106 |
-#> |.....................|  0.009926 |    0.6047 |     1.181 |   0.06337 |
-#> |.....................|    0.8781 |   0.05828 |    0.7786 |    0.7039 |
-#> |.....................|     1.653 |    0.9708 |    0.7153 |     1.953 |
-#> |    F| Forward Diff. |     4.355 |     1.271 |    0.1786 |  -0.08149 |
-#> |.....................|    0.4055 |     1.621 |    -5.117 |     3.557 |
-#> |.....................|   -0.1060 |   0.04285 |   -0.9518 |    -2.902 |
-#> |.....................|     4.469 |     2.204 |     2.093 |    -2.115 |
-#> |   25|     475.50379 |     1.001 |    -1.135 |   -0.9241 |   -0.9394 |
-#> |.....................|    -1.000 |   -0.9591 |  -0.02533 |   -0.7076 |
-#> |.....................|   -0.7587 |   -0.8812 |   -0.8111 |    -1.093 |
-#> |.....................|   -0.4726 |   -0.8571 |    -1.047 |   -0.2568 |
-#> |    U|     475.50379 |     91.10 |    -5.335 |   -0.9022 |    -2.202 |
-#> |.....................|    -4.613 |    0.4247 |     1.182 |   0.06331 |
-#> |.....................|    0.8781 |   0.05828 |    0.7790 |    0.7053 |
-#> |.....................|     1.650 |    0.9697 |    0.7143 |     1.955 |
-#> |    X|     475.50379 |     91.10 |  0.004820 |    0.2886 |    0.1106 |
-#> |.....................|  0.009924 |    0.6046 |     1.182 |   0.06331 |
-#> |.....................|    0.8781 |   0.05828 |    0.7790 |    0.7053 |
-#> |.....................|     1.650 |    0.9697 |    0.7143 |     1.955 |
-#> |    F| Forward Diff. |    -13.73 |     1.259 |   -0.1294 |  -0.05234 |
-#> |.....................|    0.4131 |     1.659 |    -5.626 |     3.356 |
-#> |.....................|   -0.1179 |    0.1182 |    -1.163 |   -0.9759 |
-#> |.....................|     2.282 |     2.162 |     2.085 |    -2.085 |
-#> |   26|     475.45890 |     1.004 |    -1.136 |   -0.9240 |   -0.9393 |
-#> |.....................|    -1.001 |   -0.9602 |  -0.02221 |   -0.7103 |
-#> |.....................|   -0.7588 |   -0.8813 |   -0.8104 |    -1.092 |
-#> |.....................|   -0.4738 |   -0.8571 |    -1.048 |   -0.2555 |
-#> |    U|      475.4589 |     91.37 |    -5.336 |   -0.9021 |    -2.202 |
-#> |.....................|    -4.613 |    0.4242 |     1.184 |   0.06323 |
-#> |.....................|    0.8781 |   0.05827 |    0.7796 |    0.7056 |
-#> |.....................|     1.649 |    0.9697 |    0.7132 |     1.956 |
-#> |    X|      475.4589 |     91.37 |  0.004816 |    0.2886 |    0.1106 |
-#> |.....................|  0.009921 |    0.6045 |     1.184 |   0.06323 |
-#> |.....................|    0.8781 |   0.05827 |    0.7796 |    0.7056 |
-#> |.....................|     1.649 |    0.9697 |    0.7132 |     1.956 |
-#> |    F| Forward Diff. |     9.388 |     1.275 |    0.2447 |  -0.08891 |
-#> |.....................|    0.4027 |     1.576 |    -4.598 |     3.539 |
-#> |.....................|  -0.08390 |   0.04261 |   -0.9004 |    -2.725 |
-#> |.....................|     4.305 |     2.111 |     1.882 |    -2.135 |
-#> |   27|     475.41657 |     1.002 |    -1.137 |   -0.9241 |   -0.9392 |
-#> |.....................|    -1.001 |   -0.9615 |  -0.01910 |   -0.7133 |
-#> |.....................|   -0.7590 |   -0.8814 |   -0.8097 |    -1.092 |
-#> |.....................|   -0.4754 |   -0.8571 |    -1.049 |   -0.2540 |
-#> |    U|     475.41657 |     91.17 |    -5.337 |   -0.9022 |    -2.202 |
-#> |.....................|    -4.613 |    0.4236 |     1.185 |   0.06314 |
-#> |.....................|    0.8780 |   0.05827 |    0.7801 |    0.7060 |
-#> |.....................|     1.647 |    0.9697 |    0.7121 |     1.958 |
-#> |    X|     475.41657 |     91.17 |  0.004811 |    0.2886 |    0.1106 |
-#> |.....................|  0.009918 |    0.6043 |     1.185 |   0.06314 |
-#> |.....................|    0.8780 |   0.05827 |    0.7801 |    0.7060 |
-#> |.....................|     1.647 |    0.9697 |    0.7121 |     1.958 |
-#> |    F| Forward Diff. |    -7.291 |     1.263 |  -0.02799 |  -0.06240 |
-#> |.....................|    0.4098 |     1.607 |    -5.561 |     3.409 |
-#> |.....................|   -0.1363 |   0.09124 |    -1.126 |   -0.9025 |
-#> |.....................|     4.264 |     2.123 |     1.858 |    -2.103 |
-#> |   28|     475.37603 |     1.004 |    -1.138 |   -0.9241 |   -0.9392 |
-#> |.....................|    -1.001 |   -0.9626 |  -0.01569 |   -0.7160 |
-#> |.....................|   -0.7590 |   -0.8815 |   -0.8090 |    -1.092 |
-#> |.....................|   -0.4775 |   -0.8574 |    -1.050 |   -0.2525 |
-#> |    U|     475.37603 |     91.35 |    -5.338 |   -0.9022 |    -2.202 |
-#> |.....................|    -4.614 |    0.4231 |     1.186 |   0.06307 |
-#> |.....................|    0.8780 |   0.05827 |    0.7806 |    0.7060 |
-#> |.....................|     1.645 |    0.9695 |    0.7112 |     1.960 |
-#> |    X|     475.37603 |     91.35 |  0.004807 |    0.2886 |    0.1106 |
-#> |.....................|  0.009915 |    0.6042 |     1.186 |   0.06307 |
-#> |.....................|    0.8780 |   0.05827 |    0.7806 |    0.7060 |
-#> |.....................|     1.645 |    0.9695 |    0.7112 |     1.960 |
-#> |    F| Forward Diff. |     7.976 |     1.271 |    0.2167 |  -0.08766 |
-#> |.....................|    0.4024 |     1.550 |    -5.132 |     3.516 |
-#> |.....................|  -0.09627 |   0.04106 |    -1.088 |   -0.7404 |
-#> |.....................|     4.103 |     2.126 |     1.707 |    -2.133 |
-#> |   29|     475.34297 |     1.001 |    -1.139 |   -0.9242 |   -0.9391 |
-#> |.....................|    -1.002 |   -0.9636 |  -0.01242 |   -0.7185 |
-#> |.....................|   -0.7591 |   -0.8816 |   -0.8082 |    -1.092 |
-#> |.....................|   -0.4796 |   -0.8578 |    -1.051 |   -0.2511 |
-#> |    U|     475.34297 |     91.13 |    -5.339 |   -0.9023 |    -2.201 |
-#> |.....................|    -4.614 |    0.4226 |     1.188 |   0.06299 |
-#> |.....................|    0.8779 |   0.05826 |    0.7812 |    0.7056 |
-#> |.....................|     1.642 |    0.9691 |    0.7103 |     1.962 |
-#> |    X|     475.34297 |     91.13 |  0.004803 |    0.2886 |    0.1106 |
-#> |.....................|  0.009912 |    0.6041 |     1.188 |   0.06299 |
-#> |.....................|    0.8779 |   0.05826 |    0.7812 |    0.7056 |
-#> |.....................|     1.642 |    0.9691 |    0.7103 |     1.962 |
-#> |    F| Forward Diff. |    -11.69 |     1.251 |  -0.09758 |  -0.05188 |
-#> |.....................|    0.4100 |     1.596 |    -5.544 |     3.338 |
-#> |.....................|   -0.1288 |   0.09302 |    -1.103 |   -0.9943 |
-#> |.....................|     4.044 |     2.113 |     1.726 |    -2.096 |
-#> |   30|     475.29763 |     1.004 |    -1.140 |   -0.9242 |   -0.9391 |
-#> |.....................|    -1.002 |   -0.9647 | -0.009016 |   -0.7212 |
-#> |.....................|   -0.7592 |   -0.8817 |   -0.8074 |    -1.093 |
-#> |.....................|   -0.4815 |   -0.8578 |    -1.052 |   -0.2496 |
-#> |    U|     475.29763 |     91.33 |    -5.340 |   -0.9023 |    -2.201 |
-#> |.....................|    -4.614 |    0.4221 |     1.189 |   0.06292 |
-#> |.....................|    0.8779 |   0.05826 |    0.7818 |    0.7049 |
-#> |.....................|     1.640 |    0.9691 |    0.7096 |     1.964 |
-#> |    X|     475.29763 |     91.33 |  0.004798 |    0.2886 |    0.1106 |
-#> |.....................|  0.009909 |    0.6040 |     1.189 |   0.06292 |
-#> |.....................|    0.8779 |   0.05826 |    0.7818 |    0.7049 |
-#> |.....................|     1.640 |    0.9691 |    0.7096 |     1.964 |
-#> |    F| Forward Diff. |     5.626 |     1.261 |    0.1834 |  -0.08674 |
-#> |.....................|    0.4019 |     1.535 |    -5.612 |     3.466 |
-#> |.....................|   -0.1091 |   0.03444 |    -1.082 |   -0.8814 |
-#> |.....................|     3.882 |     2.084 |     1.576 |    -2.128 |
-#> |   31|     475.26968 |     1.001 |    -1.140 |   -0.9243 |   -0.9390 |
-#> |.....................|    -1.002 |   -0.9656 | -0.005554 |   -0.7235 |
-#> |.....................|   -0.7592 |   -0.8818 |   -0.8067 |    -1.093 |
-#> |.....................|   -0.4837 |   -0.8585 |    -1.053 |   -0.2482 |
-#> |    U|     475.26968 |     91.11 |    -5.340 |   -0.9024 |    -2.201 |
-#> |.....................|    -4.615 |    0.4217 |     1.191 |   0.06285 |
-#> |.....................|    0.8779 |   0.05826 |    0.7823 |    0.7049 |
-#> |.....................|     1.637 |    0.9684 |    0.7088 |     1.965 |
-#> |    X|     475.26968 |     91.11 |  0.004794 |    0.2886 |    0.1106 |
-#> |.....................|  0.009907 |    0.6039 |     1.191 |   0.06285 |
-#> |.....................|    0.8779 |   0.05826 |    0.7823 |    0.7049 |
-#> |.....................|     1.637 |    0.9684 |    0.7088 |     1.965 |
-#> |    F| Forward Diff. |    -13.71 |     1.246 |   -0.1255 |  -0.05322 |
-#> |.....................|    0.4099 |     1.581 |    -5.546 |     3.317 |
-#> |.....................|   -0.1509 |    0.1096 |   -0.8594 |    -3.000 |
-#> |.....................|     3.990 |     2.056 |     1.604 |    -2.087 |
-#> |   32|     475.22190 |     1.004 |    -1.141 |   -0.9243 |   -0.9390 |
-#> |.....................|    -1.002 |   -0.9667 | -0.002058 |   -0.7261 |
-#> |.....................|   -0.7593 |   -0.8819 |   -0.8061 |    -1.093 |
-#> |.....................|   -0.4854 |   -0.8583 |    -1.054 |   -0.2469 |
-#> |    U|      475.2219 |     91.33 |    -5.341 |   -0.9024 |    -2.201 |
-#> |.....................|    -4.615 |    0.4212 |     1.192 |   0.06277 |
-#> |.....................|    0.8778 |   0.05826 |    0.7828 |    0.7049 |
-#> |.....................|     1.635 |    0.9686 |    0.7081 |     1.967 |
-#> |    X|      475.2219 |     91.33 |  0.004790 |    0.2886 |    0.1107 |
-#> |.....................|  0.009904 |    0.6038 |     1.192 |   0.06277 |
-#> |.....................|    0.8778 |   0.05826 |    0.7828 |    0.7049 |
-#> |.....................|     1.635 |    0.9686 |    0.7081 |     1.967 |
-#> |    F| Forward Diff. |     5.841 |     1.258 |    0.1840 |  -0.08823 |
-#> |.....................|    0.4011 |     1.514 |    -4.992 |     3.441 |
-#> |.....................|   -0.1080 |   0.03852 |    -1.043 |   -0.8514 |
-#> |.....................|     3.826 |     2.019 |     1.451 |    -2.125 |
-#> |   33|     475.19540 |     1.001 |    -1.142 |   -0.9244 |   -0.9389 |
-#> |.....................|    -1.003 |   -0.9677 |  0.001228 |   -0.7286 |
-#> |.....................|   -0.7593 |   -0.8819 |   -0.8054 |    -1.093 |
-#> |.....................|   -0.4876 |   -0.8589 |    -1.055 |   -0.2455 |
-#> |    U|      475.1954 |     91.10 |    -5.342 |   -0.9025 |    -2.201 |
-#> |.....................|    -4.615 |    0.4207 |     1.193 |   0.06270 |
-#> |.....................|    0.8778 |   0.05825 |    0.7833 |    0.7050 |
-#> |.....................|     1.633 |    0.9680 |    0.7073 |     1.969 |
-#> |    X|      475.1954 |     91.10 |  0.004786 |    0.2885 |    0.1107 |
-#> |.....................|  0.009901 |    0.6037 |     1.193 |   0.06270 |
-#> |.....................|    0.8778 |   0.05825 |    0.7833 |    0.7050 |
-#> |.....................|     1.633 |    0.9680 |    0.7073 |     1.969 |
-#> |    F| Forward Diff. |    -14.17 |     1.239 |   -0.1323 |  -0.05443 |
-#> |.....................|    0.4093 |     1.561 |    -5.475 |     3.262 |
-#> |.....................|   -0.1301 |   0.09817 |    -1.038 |    -1.045 |
-#> |.....................|     3.818 |     2.054 |     1.474 |    -2.085 |
-#> |   34|     475.14668 |     1.003 |    -1.143 |   -0.9244 |   -0.9388 |
-#> |.....................|    -1.003 |   -0.9688 |  0.004635 |   -0.7312 |
-#> |.....................|   -0.7595 |   -0.8820 |   -0.8046 |    -1.094 |
-#> |.....................|   -0.4894 |   -0.8588 |    -1.055 |   -0.2440 |
-#> |    U|     475.14668 |     91.31 |    -5.343 |   -0.9025 |    -2.201 |
-#> |.....................|    -4.615 |    0.4202 |     1.195 |   0.06262 |
-#> |.....................|    0.8778 |   0.05825 |    0.7838 |    0.7043 |
-#> |.....................|     1.631 |    0.9681 |    0.7066 |     1.970 |
-#> |    X|     475.14668 |     91.31 |  0.004781 |    0.2885 |    0.1107 |
-#> |.....................|  0.009898 |    0.6035 |     1.195 |   0.06262 |
-#> |.....................|    0.8778 |   0.05825 |    0.7838 |    0.7043 |
-#> |.....................|     1.631 |    0.9681 |    0.7066 |     1.970 |
-#> |    F| Forward Diff. |     3.838 |     1.251 |    0.1547 |  -0.08725 |
-#> |.....................|    0.4006 |     1.498 |    -4.927 |     3.416 |
-#> |.....................|   -0.1219 |   0.06473 |    -1.010 |    -2.917 |
-#> |.....................|     3.712 |     2.020 |     1.337 |    -2.117 |
-#> |   35|     475.12366 |     1.001 |    -1.144 |   -0.9245 |   -0.9388 |
-#> |.....................|    -1.003 |   -0.9698 |  0.007665 |   -0.7333 |
-#> |.....................|   -0.7594 |   -0.8821 |   -0.8040 |    -1.092 |
-#> |.....................|   -0.4916 |   -0.8600 |    -1.056 |   -0.2427 |
-#> |    U|     475.12366 |     91.10 |    -5.344 |   -0.9025 |    -2.201 |
-#> |.....................|    -4.616 |    0.4198 |     1.196 |   0.06256 |
-#> |.....................|    0.8778 |   0.05825 |    0.7843 |    0.7059 |
-#> |.....................|     1.628 |    0.9669 |    0.7059 |     1.972 |
-#> |    X|     475.12366 |     91.10 |  0.004777 |    0.2885 |    0.1107 |
-#> |.....................|  0.009896 |    0.6034 |     1.196 |   0.06256 |
-#> |.....................|    0.8778 |   0.05825 |    0.7843 |    0.7059 |
-#> |.....................|     1.628 |    0.9669 |    0.7059 |     1.972 |
-#> |    F| Forward Diff. |    -14.75 |     1.239 |   -0.1466 |  -0.05465 |
-#> |.....................|    0.4082 |     1.541 |    -5.471 |     3.270 |
-#> |.....................|   -0.1342 |   0.09829 |    -1.014 |    -1.026 |
-#> |.....................|     3.624 |     1.932 |     1.359 |    -2.081 |
-#> |   36|     475.07465 |     1.004 |    -1.145 |   -0.9245 |   -0.9387 |
-#> |.....................|    -1.003 |   -0.9709 |   0.01108 |   -0.7360 |
-#> |.....................|   -0.7595 |   -0.8821 |   -0.8033 |    -1.092 |
-#> |.....................|   -0.4933 |   -0.8597 |    -1.057 |   -0.2414 |
-#> |    U|     475.07465 |     91.33 |    -5.345 |   -0.9025 |    -2.201 |
-#> |.....................|    -4.616 |    0.4193 |     1.198 |   0.06248 |
-#> |.....................|    0.8778 |   0.05825 |    0.7848 |    0.7058 |
-#> |.....................|     1.626 |    0.9672 |    0.7053 |     1.974 |
-#> |    X|     475.07465 |     91.33 |  0.004773 |    0.2885 |    0.1107 |
-#> |.....................|  0.009893 |    0.6033 |     1.198 |   0.06248 |
-#> |.....................|    0.8778 |   0.05825 |    0.7848 |    0.7058 |
-#> |.....................|     1.626 |    0.9672 |    0.7053 |     1.974 |
-#> |    F| Forward Diff. |     5.021 |     1.249 |    0.1599 |  -0.08992 |
-#> |.....................|    0.3985 |     1.471 |    -4.995 |     3.410 |
-#> |.....................|   -0.1196 |   0.03779 |   -0.9990 |    -2.873 |
-#> |.....................|     3.497 |     1.906 |     1.211 |    -2.119 |
-#> |   37|     475.04940 |     1.001 |    -1.146 |   -0.9245 |   -0.9386 |
-#> |.....................|    -1.004 |   -0.9719 |   0.01438 |   -0.7384 |
-#> |.....................|   -0.7594 |   -0.8822 |   -0.8026 |    -1.091 |
-#> |.....................|   -0.4953 |   -0.8604 |    -1.058 |   -0.2400 |
-#> |    U|      475.0494 |     91.11 |    -5.346 |   -0.9026 |    -2.201 |
-#> |.....................|    -4.616 |    0.4188 |     1.199 |   0.06242 |
-#> |.....................|    0.8778 |   0.05825 |    0.7853 |    0.7070 |
-#> |.....................|     1.623 |    0.9666 |    0.7046 |     1.975 |
-#> |    X|      475.0494 |     91.11 |  0.004769 |    0.2885 |    0.1107 |
-#> |.....................|  0.009890 |    0.6032 |     1.199 |   0.06242 |
-#> |.....................|    0.8778 |   0.05825 |    0.7853 |    0.7070 |
-#> |.....................|     1.623 |    0.9666 |    0.7046 |     1.975 |
-#> |    F| Forward Diff. |    -14.15 |     1.235 |   -0.1370 |  -0.05688 |
-#> |.....................|    0.4085 |     1.517 |    -5.494 |     3.160 |
-#> |.....................|   -0.1583 |    0.1112 |   -0.7821 |    -2.927 |
-#> |.....................|     3.432 |     1.909 |     1.245 |    -2.084 |
-#> |   38|     475.00092 |     1.004 |    -1.147 |   -0.9245 |   -0.9386 |
-#> |.....................|    -1.004 |   -0.9731 |   0.01792 |   -0.7411 |
-#> |.....................|   -0.7595 |   -0.8822 |   -0.8020 |    -1.090 |
-#> |.....................|   -0.4968 |   -0.8598 |    -1.059 |   -0.2387 |
-#> |    U|     475.00092 |     91.32 |    -5.347 |   -0.9025 |    -2.201 |
-#> |.....................|    -4.617 |    0.4182 |     1.200 |   0.06234 |
-#> |.....................|    0.8778 |   0.05825 |    0.7857 |    0.7077 |
-#> |.....................|     1.622 |    0.9671 |    0.7039 |     1.977 |
-#> |    X|     475.00092 |     91.32 |  0.004764 |    0.2885 |    0.1107 |
-#> |.....................|  0.009887 |    0.6031 |     1.200 |   0.06234 |
-#> |.....................|    0.8778 |   0.05825 |    0.7857 |    0.7077 |
-#> |.....................|     1.622 |    0.9671 |    0.7039 |     1.977 |
-#> |    F| Forward Diff. |     4.379 |     1.249 |    0.1419 |  -0.08698 |
-#> |.....................|    0.3989 |     1.449 |    -4.966 |     3.395 |
-#> |.....................|   -0.1055 |   0.03295 |   -0.9696 |   -0.7580 |
-#> |.....................|     3.283 |     1.918 |     1.096 |    -2.115 |
-#> |   39|     474.98492 |     1.001 |    -1.147 |   -0.9246 |   -0.9385 |
-#> |.....................|    -1.004 |   -0.9740 |   0.02115 |   -0.7433 |
-#> |.....................|   -0.7595 |   -0.8822 |   -0.8014 |    -1.089 |
-#> |.....................|   -0.4989 |   -0.8610 |    -1.059 |   -0.2373 |
-#> |    U|     474.98492 |     91.07 |    -5.347 |   -0.9026 |    -2.201 |
-#> |.....................|    -4.617 |    0.4178 |     1.202 |   0.06227 |
-#> |.....................|    0.8778 |   0.05825 |    0.7862 |    0.7081 |
-#> |.....................|     1.619 |    0.9660 |    0.7033 |     1.978 |
-#> |    X|     474.98492 |     91.07 |  0.004760 |    0.2885 |    0.1107 |
-#> |.....................|  0.009884 |    0.6030 |     1.202 |   0.06227 |
-#> |.....................|    0.8778 |   0.05825 |    0.7862 |    0.7081 |
-#> |.....................|     1.619 |    0.9660 |    0.7033 |     1.978 |
-#> |    F| Forward Diff. |    -17.65 |     1.231 |   -0.1920 |  -0.05242 |
-#> |.....................|    0.4084 |     1.504 |    -5.397 |     3.171 |
-#> |.....................|   -0.1354 |    0.1061 |   -0.9468 |   -0.9144 |
-#> |.....................|     1.271 |     1.859 |     1.156 |    -2.067 |
-#> |   40|     474.93249 |     1.004 |    -1.148 |   -0.9245 |   -0.9384 |
-#> |.....................|    -1.005 |   -0.9752 |   0.02452 |   -0.7460 |
-#> |.....................|   -0.7596 |   -0.8823 |   -0.8007 |    -1.090 |
-#> |.....................|   -0.5000 |   -0.8607 |    -1.060 |   -0.2361 |
-#> |    U|     474.93249 |     91.32 |    -5.348 |   -0.9026 |    -2.201 |
-#> |.....................|    -4.617 |    0.4173 |     1.203 |   0.06220 |
-#> |.....................|    0.8778 |   0.05824 |    0.7867 |    0.7073 |
-#> |.....................|     1.618 |    0.9663 |    0.7027 |     1.980 |
-#> |    X|     474.93249 |     91.32 |  0.004755 |    0.2885 |    0.1107 |
-#> |.....................|  0.009881 |    0.6028 |     1.203 |   0.06220 |
-#> |.....................|    0.8778 |   0.05824 |    0.7867 |    0.7073 |
-#> |.....................|     1.618 |    0.9663 |    0.7027 |     1.980 |
-#> |    F| Forward Diff. |     4.492 |     1.243 |    0.1448 |  -0.09052 |
-#> |.....................|    0.3963 |     1.427 |    -4.973 |     3.376 |
-#> |.....................|  -0.06414 |   0.02300 |   -0.7344 |    -2.787 |
-#> |.....................|     3.083 |     1.834 |    0.9813 |    -2.110 |
-#> |   41|     474.90355 |     1.001 |    -1.149 |   -0.9246 |   -0.9383 |
-#> |.....................|    -1.005 |   -0.9763 |   0.02806 |   -0.7486 |
-#> |.....................|   -0.7596 |   -0.8823 |   -0.8002 |    -1.089 |
-#> |.....................|   -0.5018 |   -0.8611 |    -1.061 |   -0.2347 |
-#> |    U|     474.90355 |     91.13 |    -5.349 |   -0.9026 |    -2.201 |
-#> |.....................|    -4.617 |    0.4168 |     1.205 |   0.06212 |
-#> |.....................|    0.8777 |   0.05824 |    0.7870 |    0.7084 |
-#> |.....................|     1.616 |    0.9659 |    0.7020 |     1.982 |
-#> |    X|     474.90355 |     91.13 |  0.004751 |    0.2885 |    0.1107 |
-#> |.....................|  0.009878 |    0.6027 |     1.205 |   0.06212 |
-#> |.....................|    0.8777 |   0.05824 |    0.7870 |    0.7084 |
-#> |.....................|     1.616 |    0.9659 |    0.7020 |     1.982 |
-#> |    F| Forward Diff. |    -12.15 |     1.229 |   -0.1075 |  -0.06320 |
-#> |.....................|    0.4033 |     1.463 |    -5.606 |     3.135 |
-#> |.....................|   -0.1416 |   0.07801 |   -0.9461 |    -2.867 |
-#> |.....................|     3.063 |     1.817 |     1.008 |    -2.075 |
-#> |   42|     474.85832 |     1.003 |    -1.150 |   -0.9245 |   -0.9383 |
-#> |.....................|    -1.005 |   -0.9775 |   0.03184 |   -0.7513 |
-#> |.....................|   -0.7597 |   -0.8823 |   -0.7996 |    -1.089 |
-#> |.....................|   -0.5032 |   -0.8605 |    -1.061 |   -0.2334 |
-#> |    U|     474.85832 |     91.32 |    -5.350 |   -0.9026 |    -2.201 |
-#> |.....................|    -4.618 |    0.4162 |     1.206 |   0.06204 |
-#> |.....................|    0.8777 |   0.05824 |    0.7875 |    0.7089 |
-#> |.....................|     1.614 |    0.9665 |    0.7015 |     1.983 |
-#> |    X|     474.85832 |     91.32 |  0.004746 |    0.2885 |    0.1107 |
-#> |.....................|  0.009875 |    0.6026 |     1.206 |   0.06204 |
-#> |.....................|    0.8777 |   0.05824 |    0.7875 |    0.7089 |
-#> |.....................|     1.614 |    0.9665 |    0.7015 |     1.983 |
-#> |    F| Forward Diff. |     3.689 |     1.242 |    0.1265 |  -0.09001 |
-#> |.....................|    0.3949 |     1.405 |    -5.495 |     3.344 |
-#> |.....................|   -0.1166 |   0.02645 |   -0.9105 |   -0.7126 |
-#> |.....................|     2.952 |     1.861 |    0.8779 |    -2.102 |
-#> |   43|     474.83791 |     1.001 |    -1.151 |   -0.9246 |   -0.9382 |
-#> |.....................|    -1.006 |   -0.9784 |   0.03545 |   -0.7535 |
-#> |.....................|   -0.7596 |   -0.8823 |   -0.7990 |    -1.088 |
-#> |.....................|   -0.5052 |   -0.8617 |    -1.062 |   -0.2320 |
-#> |    U|     474.83791 |     91.10 |    -5.351 |   -0.9027 |    -2.201 |
-#> |.....................|    -4.618 |    0.4158 |     1.208 |   0.06198 |
-#> |.....................|    0.8777 |   0.05824 |    0.7879 |    0.7094 |
-#> |.....................|     1.612 |    0.9653 |    0.7010 |     1.985 |
-#> |    X|     474.83791 |     91.10 |  0.004742 |    0.2885 |    0.1107 |
-#> |.....................|  0.009872 |    0.6025 |     1.208 |   0.06198 |
-#> |.....................|    0.8777 |   0.05824 |    0.7879 |    0.7094 |
-#> |.....................|     1.612 |    0.9653 |    0.7010 |     1.985 |
-#> |    F| Forward Diff. |    -15.77 |     1.225 |   -0.1616 |  -0.05944 |
-#> |.....................|    0.4032 |     1.455 |    -5.461 |     3.071 |
-#> |.....................|   -0.1419 |   0.08593 |   -0.9091 |   -0.8855 |
-#> |.....................|     2.951 |     1.791 |    0.9091 |    -2.062 |
-#> |   44|     474.78971 |     1.004 |    -1.152 |   -0.9246 |   -0.9381 |
-#> |.....................|    -1.006 |   -0.9794 |   0.03911 |   -0.7559 |
-#> |.....................|   -0.7597 |   -0.8824 |   -0.7984 |    -1.089 |
-#> |.....................|   -0.5068 |   -0.8614 |    -1.062 |   -0.2307 |
-#> |    U|     474.78971 |     91.33 |    -5.352 |   -0.9026 |    -2.200 |
-#> |.....................|    -4.618 |    0.4153 |     1.209 |   0.06191 |
-#> |.....................|    0.8777 |   0.05824 |    0.7883 |    0.7086 |
-#> |.....................|     1.610 |    0.9656 |    0.7006 |     1.986 |
-#> |    X|     474.78971 |     91.33 |  0.004738 |    0.2885 |    0.1107 |
-#> |.....................|  0.009869 |    0.6024 |     1.209 |   0.06191 |
-#> |.....................|    0.8777 |   0.05824 |    0.7883 |    0.7086 |
-#> |.....................|     1.610 |    0.9656 |    0.7006 |     1.986 |
-#> |    F| Forward Diff. |     4.398 |     1.237 |    0.1402 |  -0.09195 |
-#> |.....................|    0.3940 |     1.388 |    -4.885 |     3.322 |
-#> |.....................|   -0.1374 |   0.01792 |   -0.6865 |    -2.709 |
-#> |.....................|     2.810 |     1.778 |    0.8100 |    -2.095 |
-#> |   45|     474.76763 |     1.001 |    -1.153 |   -0.9247 |   -0.9380 |
-#> |.....................|    -1.006 |   -0.9804 |   0.04256 |   -0.7584 |
-#> |.....................|   -0.7597 |   -0.8824 |   -0.7979 |    -1.088 |
-#> |.....................|   -0.5086 |   -0.8621 |    -1.063 |   -0.2293 |
-#> |    U|     474.76763 |     91.11 |    -5.353 |   -0.9027 |    -2.200 |
-#> |.....................|    -4.619 |    0.4149 |     1.211 |   0.06184 |
-#> |.....................|    0.8777 |   0.05824 |    0.7887 |    0.7097 |
-#> |.....................|     1.608 |    0.9650 |    0.7001 |     1.988 |
-#> |    X|     474.76763 |     91.11 |  0.004734 |    0.2885 |    0.1108 |
-#> |.....................|  0.009867 |    0.6023 |     1.211 |   0.06184 |
-#> |.....................|    0.8777 |   0.05824 |    0.7887 |    0.7097 |
-#> |.....................|     1.608 |    0.9650 |    0.7001 |     1.988 |
-#> |    F| Forward Diff. |    -14.92 |     1.222 |   -0.1466 |  -0.06186 |
-#> |.....................|    0.4014 |     1.433 |    -4.989 |     3.157 |
-#> |.....................|   -0.1326 |   0.08284 |   -0.6789 |    -2.803 |
-#> |.....................|     2.814 |     1.775 |    0.8327 |    -2.053 |
-#> |   46|     474.71973 |     1.004 |    -1.154 |   -0.9246 |   -0.9379 |
-#> |.....................|    -1.006 |   -0.9816 |   0.04617 |   -0.7611 |
-#> |.....................|   -0.7597 |   -0.8824 |   -0.7975 |    -1.087 |
-#> |.....................|   -0.5100 |   -0.8614 |    -1.064 |   -0.2281 |
-#> |    U|     474.71973 |     91.32 |    -5.354 |   -0.9026 |    -2.200 |
-#> |.....................|    -4.619 |    0.4143 |     1.212 |   0.06176 |
-#> |.....................|    0.8777 |   0.05824 |    0.7890 |    0.7100 |
-#> |.....................|     1.606 |    0.9656 |    0.6996 |     1.990 |
-#> |    X|     474.71973 |     91.32 |  0.004729 |    0.2885 |    0.1108 |
-#> |.....................|  0.009863 |    0.6021 |     1.212 |   0.06176 |
-#> |.....................|    0.8777 |   0.05824 |    0.7890 |    0.7100 |
-#> |.....................|     1.606 |    0.9656 |    0.6996 |     1.990 |
-#> |    F| Forward Diff. |     4.021 |     1.236 |    0.1299 |  -0.09158 |
-#> |.....................|    0.3929 |     1.368 |    -4.925 |     3.331 |
-#> |.....................|  -0.07142 |   0.08893 |   -0.6522 |    -2.634 |
-#> |.....................|     2.639 |     1.780 |    0.7273 |    -2.085 |
-#> |   47|     474.70040 |     1.001 |    -1.155 |   -0.9247 |   -0.9379 |
-#> |.....................|    -1.007 |   -0.9826 |   0.04954 |   -0.7634 |
-#> |.....................|   -0.7597 |   -0.8825 |   -0.7971 |    -1.086 |
-#> |.....................|   -0.5117 |   -0.8624 |    -1.064 |   -0.2267 |
-#> |    U|      474.7004 |     91.10 |    -5.355 |   -0.9027 |    -2.200 |
-#> |.....................|    -4.619 |    0.4139 |     1.214 |   0.06169 |
-#> |.....................|    0.8777 |   0.05824 |    0.7893 |    0.7114 |
-#> |.....................|     1.604 |    0.9647 |    0.6992 |     1.991 |
-#> |    X|      474.7004 |     91.10 |  0.004724 |    0.2885 |    0.1108 |
-#> |.....................|  0.009861 |    0.6020 |     1.214 |   0.06169 |
-#> |.....................|    0.8777 |   0.05824 |    0.7893 |    0.7114 |
-#> |.....................|     1.604 |    0.9647 |    0.6992 |     1.991 |
-#> |    F| Forward Diff. |    -15.76 |     1.220 |   -0.1617 |  -0.06091 |
-#> |.....................|    0.4007 |     1.415 |    -5.116 |     3.166 |
-#> |.....................|   -0.1298 |   0.07714 |   -0.6701 |    -2.700 |
-#> |.....................|     2.670 |     1.748 |    0.7590 |    -2.043 |
-#> |   48|     474.65116 |     1.003 |    -1.156 |   -0.9246 |   -0.9378 |
-#> |.....................|    -1.007 |   -0.9837 |   0.05321 |   -0.7662 |
-#> |.....................|   -0.7598 |   -0.8825 |   -0.7967 |    -1.086 |
-#> |.....................|   -0.5130 |   -0.8617 |    -1.065 |   -0.2255 |
-#> |    U|     474.65116 |     91.32 |    -5.356 |   -0.9026 |    -2.200 |
-#> |.....................|    -4.620 |    0.4134 |     1.215 |   0.06161 |
-#> |.....................|    0.8777 |   0.05824 |    0.7896 |    0.7116 |
-#> |.....................|     1.603 |    0.9653 |    0.6987 |     1.993 |
-#> |    X|     474.65116 |     91.32 |  0.004720 |    0.2885 |    0.1108 |
-#> |.....................|  0.009857 |    0.6019 |     1.215 |   0.06161 |
-#> |.....................|    0.8777 |   0.05824 |    0.7896 |    0.7116 |
-#> |.....................|     1.603 |    0.9653 |    0.6987 |     1.993 |
-#> |    F| Forward Diff. |     3.462 |     1.239 |    0.1107 |  -0.09136 |
-#> |.....................|    0.3915 |     1.348 |    -5.441 |     3.268 |
-#> |.....................|   -0.1113 |   0.02510 |   -0.6252 |    -2.485 |
-#> |.....................|     2.647 |     1.796 |    0.6587 |    -2.076 |
-#> |   49|     474.63065 |     1.001 |    -1.157 |   -0.9247 |   -0.9377 |
-#> |.....................|    -1.007 |   -0.9846 |   0.05678 |   -0.7683 |
-#> |.....................|   -0.7597 |   -0.8825 |   -0.7963 |    -1.084 |
-#> |.....................|   -0.5148 |   -0.8629 |    -1.065 |   -0.2241 |
-#> |    U|     474.63065 |     91.11 |    -5.357 |   -0.9027 |    -2.200 |
-#> |.....................|    -4.620 |    0.4129 |     1.217 |   0.06155 |
-#> |.....................|    0.8777 |   0.05824 |    0.7899 |    0.7131 |
-#> |.....................|     1.600 |    0.9642 |    0.6984 |     1.994 |
-#> |    X|     474.63065 |     91.11 |  0.004716 |    0.2885 |    0.1108 |
-#> |.....................|  0.009855 |    0.6018 |     1.217 |   0.06155 |
-#> |.....................|    0.8777 |   0.05824 |    0.7899 |    0.7131 |
-#> |.....................|     1.600 |    0.9642 |    0.6984 |     1.994 |
-#> |    F| Forward Diff. |    -14.93 |     1.220 |   -0.1531 |  -0.06288 |
-#> |.....................|    0.3983 |     1.394 |    -5.436 |     3.113 |
-#> |.....................|   -0.1458 |   0.07621 |   -0.8397 |   -0.6848 |
-#> |.....................|     2.501 |     1.690 |    0.6891 |    -2.034 |
-#> |   50|     474.58497 |     1.004 |    -1.158 |   -0.9246 |   -0.9376 |
-#> |.....................|    -1.008 |   -0.9857 |   0.06060 |   -0.7708 |
-#> |.....................|   -0.7598 |   -0.8826 |   -0.7958 |    -1.084 |
-#> |.....................|   -0.5162 |   -0.8624 |    -1.065 |   -0.2230 |
-#> |    U|     474.58497 |     91.34 |    -5.358 |   -0.9027 |    -2.200 |
-#> |.....................|    -4.620 |    0.4125 |     1.218 |   0.06148 |
-#> |.....................|    0.8777 |   0.05824 |    0.7902 |    0.7126 |
-#> |.....................|     1.599 |    0.9647 |    0.6980 |     1.996 |
-#> |    X|     474.58497 |     91.34 |  0.004711 |    0.2885 |    0.1108 |
-#> |.....................|  0.009852 |    0.6017 |     1.218 |   0.06148 |
-#> |.....................|    0.8777 |   0.05824 |    0.7902 |    0.7126 |
-#> |.....................|     1.599 |    0.9647 |    0.6980 |     1.996 |
-#> |    F| Forward Diff. |     5.248 |     1.234 |    0.1371 |  -0.09456 |
-#> |.....................|    0.3896 |     1.328 |    -5.011 |     3.180 |
-#> |.....................|   -0.1110 |  0.004022 |   -0.8103 |   -0.4964 |
-#> |.....................|     2.349 |     1.713 |    0.5705 |    -2.061 |
-#> |   51|     474.55760 |     1.002 |    -1.159 |   -0.9247 |   -0.9376 |
-#> |.....................|    -1.008 |   -0.9867 |   0.06444 |   -0.7734 |
-#> |.....................|   -0.7598 |   -0.8826 |   -0.7952 |    -1.085 |
-#> |.....................|   -0.5178 |   -0.8626 |    -1.066 |   -0.2215 |
-#> |    U|      474.5576 |     91.15 |    -5.359 |   -0.9027 |    -2.200 |
-#> |.....................|    -4.620 |    0.4120 |     1.220 |   0.06140 |
-#> |.....................|    0.8777 |   0.05824 |    0.7907 |    0.7122 |
-#> |.....................|     1.597 |    0.9645 |    0.6977 |     1.998 |
-#> |    X|      474.5576 |     91.15 |  0.004706 |    0.2885 |    0.1108 |
-#> |.....................|  0.009849 |    0.6016 |     1.220 |   0.06140 |
-#> |.....................|    0.8777 |   0.05824 |    0.7907 |    0.7122 |
-#> |.....................|     1.597 |    0.9645 |    0.6977 |     1.998 |
-#> |    F| Forward Diff. |    -11.86 |     1.219 |   -0.1003 |  -0.07615 |
-#> |.....................|    0.3954 |     1.369 |    -4.929 |     3.171 |
-#> |.....................|   -0.1229 |   0.06540 |   -0.8183 |   -0.7141 |
-#> |.....................|     2.360 |     1.696 |    0.6359 |    -2.032 |
-#> |   52|     474.51619 |     1.004 |    -1.160 |   -0.9246 |   -0.9375 |
-#> |.....................|    -1.008 |   -0.9878 |   0.06816 |   -0.7761 |
-#> |.....................|   -0.7599 |   -0.8826 |   -0.7946 |    -1.086 |
-#> |.....................|   -0.5193 |   -0.8622 |    -1.066 |   -0.2202 |
-#> |    U|     474.51619 |     91.33 |    -5.360 |   -0.9027 |    -2.200 |
-#> |.....................|    -4.621 |    0.4115 |     1.221 |   0.06132 |
-#> |.....................|    0.8776 |   0.05823 |    0.7911 |    0.7113 |
-#> |.....................|     1.595 |    0.9648 |    0.6972 |     1.999 |
-#> |    X|     474.51619 |     91.33 |  0.004702 |    0.2885 |    0.1108 |
-#> |.....................|  0.009846 |    0.6014 |     1.221 |   0.06132 |
-#> |.....................|    0.8776 |   0.05823 |    0.7911 |    0.7113 |
-#> |.....................|     1.595 |    0.9648 |    0.6972 |     1.999 |
-#> |    F| Forward Diff. |     4.413 |     1.225 |    0.1371 |  -0.09620 |
-#> |.....................|    0.3880 |     1.314 |    -5.554 |     3.197 |
-#> |.....................|  -0.07604 |  0.008867 |   -0.7931 |   -0.6282 |
-#> |.....................|     2.148 |     1.715 |    0.5273 |    -2.052 |
-#> |   53|     474.48673 |     1.002 |    -1.161 |   -0.9247 |   -0.9374 |
-#> |.....................|    -1.009 |   -0.9889 |   0.07224 |   -0.7786 |
-#> |.....................|   -0.7599 |   -0.8826 |   -0.7941 |    -1.086 |
-#> |.....................|   -0.5208 |   -0.8625 |    -1.067 |   -0.2188 |
-#> |    U|     474.48673 |     91.17 |    -5.361 |   -0.9027 |    -2.200 |
-#> |.....................|    -4.621 |    0.4110 |     1.223 |   0.06125 |
-#> |.....................|    0.8776 |   0.05823 |    0.7915 |    0.7110 |
-#> |.....................|     1.593 |    0.9645 |    0.6969 |     2.001 |
-#> |    X|     474.48673 |     91.17 |  0.004697 |    0.2885 |    0.1108 |
-#> |.....................|  0.009843 |    0.6013 |     1.223 |   0.06125 |
-#> |.....................|    0.8776 |   0.05823 |    0.7915 |    0.7110 |
-#> |.....................|     1.593 |    0.9645 |    0.6969 |     2.001 |
-#> |    F| Forward Diff. |    -10.51 |     1.211 |  -0.06554 |  -0.07429 |
-#> |.....................|    0.3932 |     1.350 |    -4.456 |     3.182 |
-#> |.....................|  -0.08901 |   0.05354 |   -0.5957 |    -2.739 |
-#> |.....................|     2.160 |     1.696 |    0.5687 |    -2.022 |
-#> |   54|     474.45218 |     1.004 |    -1.162 |   -0.9246 |   -0.9373 |
-#> |.....................|    -1.009 |   -0.9900 |   0.07590 |   -0.7814 |
-#> |.....................|   -0.7601 |   -0.8826 |   -0.7937 |    -1.086 |
-#> |.....................|   -0.5220 |   -0.8620 |    -1.067 |   -0.2177 |
-#> |    U|     474.45218 |     91.40 |    -5.362 |   -0.9027 |    -2.200 |
-#> |.....................|    -4.621 |    0.4105 |     1.224 |   0.06117 |
-#> |.....................|    0.8776 |   0.05823 |    0.7918 |    0.7111 |
-#> |.....................|     1.592 |    0.9650 |    0.6965 |     2.002 |
-#> |    X|     474.45218 |     91.40 |  0.004692 |    0.2885 |    0.1108 |
-#> |.....................|  0.009840 |    0.6012 |     1.224 |   0.06117 |
-#> |.....................|    0.8776 |   0.05823 |    0.7918 |    0.7111 |
-#> |.....................|     1.592 |    0.9650 |    0.6965 |     2.002 |
-#> |    F| Forward Diff. |     9.724 |     1.224 |    0.2009 |   -0.1069 |
-#> |.....................|    0.3834 |     1.279 |    -5.556 |     3.324 |
-#> |.....................|   -0.1101 |  -0.01912 |   -0.5638 |    -2.553 |
-#> |.....................|     2.043 |     1.731 |    0.4140 |    -2.044 |
-#> |   55|     474.41257 |     1.003 |    -1.163 |   -0.9246 |   -0.9371 |
-#> |.....................|    -1.009 |   -0.9913 |   0.07979 |   -0.7844 |
-#> |.....................|   -0.7601 |   -0.8825 |   -0.7935 |    -1.085 |
-#> |.....................|   -0.5231 |   -0.8612 |    -1.068 |   -0.2167 |
-#> |    U|     474.41257 |     91.25 |    -5.363 |   -0.9026 |    -2.199 |
-#> |.....................|    -4.622 |    0.4099 |     1.226 |   0.06108 |
-#> |.....................|    0.8775 |   0.05824 |    0.7919 |    0.7118 |
-#> |.....................|     1.591 |    0.9658 |    0.6961 |     2.004 |
-#> |    X|     474.41257 |     91.25 |  0.004687 |    0.2885 |    0.1109 |
-#> |.....................|  0.009836 |    0.6011 |     1.226 |   0.06108 |
-#> |.....................|    0.8775 |   0.05824 |    0.7919 |    0.7118 |
-#> |.....................|     1.591 |    0.9658 |    0.6961 |     2.004 |
-#> |    F| Forward Diff. |    -3.208 |     1.213 |   0.03978 |  -0.08693 |
-#> |.....................|    0.3876 |     1.303 |    -5.023 |     3.218 |
-#> |.....................|   -0.1347 |   0.02311 |   -0.7771 |   -0.6556 |
-#> |.....................|     2.056 |     1.822 |    0.4520 |    -2.025 |
-#> |   56|     474.39271 |     1.005 |    -1.164 |   -0.9246 |   -0.9371 |
-#> |.....................|    -1.010 |   -0.9922 |   0.08348 |   -0.7867 |
-#> |.....................|   -0.7600 |   -0.8825 |   -0.7930 |    -1.085 |
-#> |.....................|   -0.5246 |   -0.8625 |    -1.068 |   -0.2152 |
-#> |    U|     474.39271 |     91.47 |    -5.364 |   -0.9027 |    -2.199 |
-#> |.....................|    -4.622 |    0.4094 |     1.228 |   0.06101 |
-#> |.....................|    0.8776 |   0.05824 |    0.7923 |    0.7123 |
-#> |.....................|     1.589 |    0.9645 |    0.6958 |     2.005 |
-#> |    X|     474.39271 |     91.47 |  0.004683 |    0.2885 |    0.1109 |
-#> |.....................|  0.009833 |    0.6010 |     1.228 |   0.06101 |
-#> |.....................|    0.8776 |   0.05824 |    0.7923 |    0.7123 |
-#> |.....................|     1.589 |    0.9645 |    0.6958 |     2.005 |
-#> |    F| Forward Diff. |     15.86 |     1.227 |    0.2807 |   -0.1163 |
-#> |.....................|    0.3793 |     1.243 |    -5.494 |     3.329 |
-#> |.....................|  -0.09368 |   0.01293 |   -0.5149 |    -2.407 |
-#> |.....................|     1.979 |     1.686 |    0.3308 |    -2.044 |
-#> |   57|     474.34538 |     1.003 |    -1.165 |   -0.9247 |   -0.9369 |
-#> |.....................|    -1.010 |   -0.9934 |   0.08718 |   -0.7897 |
-#> |.....................|   -0.7601 |   -0.8825 |   -0.7926 |    -1.086 |
-#> |.....................|   -0.5258 |   -0.8620 |    -1.068 |   -0.2141 |
-#> |    U|     474.34538 |     91.27 |    -5.365 |   -0.9027 |    -2.199 |
-#> |.....................|    -4.622 |    0.4089 |     1.229 |   0.06093 |
-#> |.....................|    0.8775 |   0.05824 |    0.7926 |    0.7117 |
-#> |.....................|     1.587 |    0.9650 |    0.6954 |     2.007 |
-#> |    X|     474.34538 |     91.27 |  0.004677 |    0.2885 |    0.1109 |
-#> |.....................|  0.009830 |    0.6008 |     1.229 |   0.06093 |
-#> |.....................|    0.8775 |   0.05824 |    0.7926 |    0.7117 |
-#> |.....................|     1.587 |    0.9650 |    0.6954 |     2.007 |
-#> |    F| Forward Diff. |    -2.345 |     1.210 |   0.04189 |  -0.08986 |
-#> |.....................|    0.3855 |     1.284 |    -5.145 |     3.218 |
-#> |.....................|   -0.1284 |   0.01309 |   -0.7466 |   -0.6536 |
-#> |.....................|     1.964 |     1.743 |    0.3816 |    -2.008 |
-#> |   58|     474.31834 |     1.005 |    -1.166 |   -0.9247 |   -0.9369 |
-#> |.....................|    -1.010 |   -0.9944 |   0.09109 |   -0.7921 |
-#> |.....................|   -0.7600 |   -0.8825 |   -0.7920 |    -1.085 |
-#> |.....................|   -0.5273 |   -0.8633 |    -1.069 |   -0.2126 |
-#> |    U|     474.31834 |     91.43 |    -5.366 |   -0.9027 |    -2.199 |
-#> |.....................|    -4.623 |    0.4085 |     1.231 |   0.06086 |
-#> |.....................|    0.8776 |   0.05824 |    0.7930 |    0.7121 |
-#> |.....................|     1.586 |    0.9638 |    0.6952 |     2.008 |
-#> |    X|     474.31834 |     91.43 |  0.004673 |    0.2885 |    0.1109 |
-#> |.....................|  0.009827 |    0.6007 |     1.231 |   0.06086 |
-#> |.....................|    0.8776 |   0.05824 |    0.7930 |    0.7121 |
-#> |.....................|     1.586 |    0.9638 |    0.6952 |     2.008 |
-#> |    F| Forward Diff. |     12.13 |     1.219 |    0.2312 |   -0.1125 |
-#> |.....................|    0.3787 |     1.238 |    -5.317 |     3.196 |
-#> |.....................|  -0.08361 |  -0.02599 |   -0.7000 |   -0.4940 |
-#> |.....................|     1.837 |     1.637 |    0.3211 |    -2.028 |
-#> |   59|     474.27833 |     1.003 |    -1.167 |   -0.9247 |   -0.9368 |
-#> |.....................|    -1.010 |   -0.9955 |   0.09487 |   -0.7949 |
-#> |.....................|   -0.7601 |   -0.8825 |   -0.7915 |    -1.086 |
-#> |.....................|   -0.5286 |   -0.8630 |    -1.069 |   -0.2114 |
-#> |    U|     474.27833 |     91.25 |    -5.367 |   -0.9028 |    -2.199 |
-#> |.....................|    -4.623 |    0.4080 |     1.232 |   0.06078 |
-#> |.....................|    0.8775 |   0.05824 |    0.7934 |    0.7111 |
-#> |.....................|     1.584 |    0.9640 |    0.6948 |     2.010 |
-#> |    X|     474.27833 |     91.25 |  0.004668 |    0.2885 |    0.1109 |
-#> |.....................|  0.009824 |    0.6006 |     1.232 |   0.06078 |
-#> |.....................|    0.8775 |   0.05824 |    0.7934 |    0.7111 |
-#> |.....................|     1.584 |    0.9640 |    0.6948 |     2.010 |
-#> |    F| Forward Diff. |    -4.145 |     1.202 |   0.02355 |  -0.08919 |
-#> |.....................|    0.3842 |     1.275 |    -5.102 |     3.189 |
-#> |.....................|   -0.1071 |   0.01700 |   -0.7283 |   -0.7209 |
-#> |.....................|     1.776 |     1.686 |    0.3249 |    -1.982 |
-#> |   60|     474.25305 |     1.005 |    -1.168 |   -0.9247 |   -0.9367 |
-#> |.....................|    -1.011 |   -0.9965 |   0.09878 |   -0.7975 |
-#> |.....................|   -0.7601 |   -0.8825 |   -0.7909 |    -1.086 |
-#> |.....................|   -0.5300 |   -0.8636 |    -1.069 |   -0.2100 |
-#> |    U|     474.25305 |     91.44 |    -5.368 |   -0.9028 |    -2.199 |
-#> |.....................|    -4.623 |    0.4075 |     1.234 |   0.06070 |
-#> |.....................|    0.8775 |   0.05824 |    0.7938 |    0.7109 |
-#> |.....................|     1.583 |    0.9635 |    0.6946 |     2.012 |
-#> |    X|     474.25305 |     91.44 |  0.004663 |    0.2885 |    0.1109 |
-#> |.....................|  0.009821 |    0.6005 |     1.234 |   0.06070 |
-#> |.....................|    0.8775 |   0.05824 |    0.7938 |    0.7109 |
-#> |.....................|     1.583 |    0.9635 |    0.6946 |     2.012 |
-#> |    F| Forward Diff. |     13.11 |     1.213 |    0.2527 |   -0.1161 |
-#> |.....................|    0.3767 |     1.219 |    -5.003 |     3.213 |
-#> |.....................|  -0.09270 |  -0.04298 |   -0.4814 |    -2.533 |
-#> |.....................|     1.730 |     1.613 |    0.2495 |    -2.014 |
-#> |   61|     474.21254 |     1.003 |    -1.169 |   -0.9248 |   -0.9365 |
-#> |.....................|    -1.011 |   -0.9977 |    0.1025 |   -0.8005 |
-#> |.....................|   -0.7602 |   -0.8824 |   -0.7906 |    -1.087 |
-#> |.....................|   -0.5311 |   -0.8630 |    -1.070 |   -0.2089 |
-#> |    U|     474.21254 |     91.24 |    -5.369 |   -0.9028 |    -2.199 |
-#> |.....................|    -4.624 |    0.4069 |     1.236 |   0.06062 |
-#> |.....................|    0.8775 |   0.05824 |    0.7941 |    0.7105 |
-#> |.....................|     1.581 |    0.9641 |    0.6942 |     2.013 |
-#> |    X|     474.21254 |     91.24 |  0.004658 |    0.2885 |    0.1109 |
-#> |.....................|  0.009817 |    0.6003 |     1.236 |   0.06062 |
-#> |.....................|    0.8775 |   0.05824 |    0.7941 |    0.7105 |
-#> |.....................|     1.581 |    0.9641 |    0.6942 |     2.013 |
-#> |    F| Forward Diff. |    -5.267 |     1.195 |   0.01760 |  -0.08987 |
-#> |.....................|    0.3825 |     1.260 |    -5.272 |     3.141 |
-#> |.....................|   -0.1336 |  0.009843 |   -0.5186 |    -2.706 |
-#> |.....................|     1.727 |     1.652 |    0.2904 |    -1.976 |
-#> |   62|     474.18171 |     1.004 |    -1.170 |   -0.9247 |   -0.9364 |
-#> |.....................|    -1.011 |   -0.9989 |    0.1065 |   -0.8033 |
-#> |.....................|   -0.7602 |   -0.8823 |   -0.7904 |    -1.086 |
-#> |.....................|   -0.5322 |   -0.8627 |    -1.070 |   -0.2078 |
-#> |    U|     474.18171 |     91.41 |    -5.370 |   -0.9028 |    -2.199 |
-#> |.....................|    -4.624 |    0.4064 |     1.237 |   0.06054 |
-#> |.....................|    0.8775 |   0.05824 |    0.7942 |    0.7112 |
-#> |.....................|     1.580 |    0.9644 |    0.6939 |     2.014 |
-#> |    X|     474.18171 |     91.41 |  0.004653 |    0.2885 |    0.1109 |
-#> |.....................|  0.009814 |    0.6002 |     1.237 |   0.06054 |
-#> |.....................|    0.8775 |   0.05824 |    0.7942 |    0.7112 |
-#> |.....................|     1.580 |    0.9644 |    0.6939 |     2.014 |
-#> |    F| Forward Diff. |     9.716 |     1.206 |    0.2113 |   -0.1128 |
-#> |.....................|    0.3755 |     1.207 |    -5.399 |     3.226 |
-#> |.....................|  -0.09670 |  -0.03459 |   -0.6713 |   -0.5638 |
-#> |.....................|     1.619 |     1.687 |    0.2005 |    -1.998 |
-#> |   63|     474.14509 |     1.003 |    -1.171 |   -0.9248 |   -0.9363 |
-#> |.....................|    -1.012 |    -1.000 |    0.1105 |   -0.8061 |
-#> |.....................|   -0.7602 |   -0.8822 |   -0.7900 |    -1.087 |
-#> |.....................|   -0.5333 |   -0.8621 |    -1.071 |   -0.2068 |
-#> |    U|     474.14509 |     91.25 |    -5.371 |   -0.9028 |    -2.199 |
-#> |.....................|    -4.624 |    0.4059 |     1.239 |   0.06045 |
-#> |.....................|    0.8775 |   0.05825 |    0.7945 |    0.7106 |
-#> |.....................|     1.579 |    0.9649 |    0.6936 |     2.015 |
-#> |    X|     474.14509 |     91.25 |  0.004648 |    0.2885 |    0.1110 |
-#> |.....................|  0.009811 |    0.6001 |     1.239 |   0.06045 |
-#> |.....................|    0.8775 |   0.05825 |    0.7945 |    0.7106 |
-#> |.....................|     1.579 |    0.9649 |    0.6936 |     2.015 |
-#> |    F| Forward Diff. |    -5.280 |     1.192 |   0.02321 |  -0.09129 |
-#> |.....................|    0.3799 |     1.239 |    -5.339 |     3.156 |
-#> |.....................|   -0.1074 |   0.06181 |   -0.4875 |    -2.680 |
-#> |.....................|     1.648 |     1.743 |    0.2195 |    -1.955 |
-#> |   64|     474.11542 |     1.005 |    -1.172 |   -0.9248 |   -0.9361 |
-#> |.....................|    -1.012 |    -1.001 |    0.1146 |   -0.8089 |
-#> |.....................|   -0.7603 |   -0.8821 |   -0.7897 |    -1.086 |
-#> |.....................|   -0.5344 |   -0.8621 |    -1.071 |   -0.2057 |
-#> |    U|     474.11542 |     91.42 |    -5.372 |   -0.9028 |    -2.199 |
-#> |.....................|    -4.625 |    0.4054 |     1.241 |   0.06037 |
-#> |.....................|    0.8774 |   0.05825 |    0.7947 |    0.7110 |
-#> |.....................|     1.577 |    0.9649 |    0.6934 |     2.017 |
-#> |    X|     474.11542 |     91.42 |  0.004643 |    0.2885 |    0.1110 |
-#> |.....................|  0.009807 |    0.6000 |     1.241 |   0.06037 |
-#> |.....................|    0.8774 |   0.05825 |    0.7947 |    0.7110 |
-#> |.....................|     1.577 |    0.9649 |    0.6934 |     2.017 |
-#> |    F| Forward Diff. |     10.52 |     1.202 |    0.2258 |   -0.1162 |
-#> |.....................|    0.3725 |     1.186 |    -5.381 |     3.222 |
-#> |.....................|   -0.1104 |  -0.04157 |   -0.6550 |   -0.5841 |
-#> |.....................|     1.505 |     1.701 |    0.1753 |    -1.993 |
-#> |   65|     474.07794 |     1.003 |    -1.173 |   -0.9248 |   -0.9360 |
-#> |.....................|    -1.012 |    -1.002 |    0.1187 |   -0.8117 |
-#> |.....................|   -0.7604 |   -0.8821 |   -0.7895 |    -1.087 |
-#> |.....................|   -0.5355 |   -0.8615 |    -1.071 |   -0.2048 |
-#> |    U|     474.07794 |     91.25 |    -5.373 |   -0.9028 |    -2.198 |
-#> |.....................|    -4.625 |    0.4048 |     1.242 |   0.06029 |
-#> |.....................|    0.8774 |   0.05825 |    0.7949 |    0.7104 |
-#> |.....................|     1.576 |    0.9655 |    0.6932 |     2.018 |
-#> |    X|     474.07794 |     91.25 |  0.004638 |    0.2885 |    0.1110 |
-#> |.....................|  0.009804 |    0.5999 |     1.242 |   0.06029 |
-#> |.....................|    0.8774 |   0.05825 |    0.7949 |    0.7104 |
-#> |.....................|     1.576 |    0.9655 |    0.6932 |     2.018 |
-#> |    F| Forward Diff. |    -4.801 |     1.188 |   0.03689 |  -0.09236 |
-#> |.....................|    0.3785 |     1.221 |    -5.368 |     3.104 |
-#> |.....................|   -0.1066 |  0.003449 |   -0.6711 |   -0.7398 |
-#> |.....................|     1.563 |     1.803 |    0.1884 |    -1.939 |
-#> |   66|     474.04951 |     1.005 |    -1.175 |   -0.9248 |   -0.9359 |
-#> |.....................|    -1.013 |    -1.003 |    0.1228 |   -0.8144 |
-#> |.....................|   -0.7604 |   -0.8820 |   -0.7890 |    -1.087 |
-#> |.....................|   -0.5367 |   -0.8618 |    -1.071 |   -0.2036 |
-#> |    U|     474.04951 |     91.43 |    -5.375 |   -0.9028 |    -2.198 |
-#> |.....................|    -4.625 |    0.4044 |     1.244 |   0.06021 |
-#> |.....................|    0.8774 |   0.05825 |    0.7952 |    0.7100 |
-#> |.....................|     1.575 |    0.9652 |    0.6930 |     2.019 |
-#> |    X|     474.04951 |     91.43 |  0.004633 |    0.2885 |    0.1110 |
-#> |.....................|  0.009801 |    0.5997 |     1.244 |   0.06021 |
-#> |.....................|    0.8774 |   0.05825 |    0.7952 |    0.7100 |
-#> |.....................|     1.575 |    0.9652 |    0.6930 |     2.019 |
-#> |    F| Forward Diff. |     10.86 |     1.196 |    0.2377 |   -0.1190 |
-#> |.....................|    0.3700 |     1.169 |    -5.399 |     3.259 |
-#> |.....................|  -0.09645 |  -0.03914 |   -0.4400 |    -2.610 |
-#> |.....................|     1.421 |     1.705 |    0.1351 |    -1.978 |
-#> |   67|     474.01246 |     1.003 |    -1.176 |   -0.9249 |   -0.9357 |
-#> |.....................|    -1.013 |    -1.004 |    0.1268 |   -0.8173 |
-#> |.....................|   -0.7606 |   -0.8819 |   -0.7888 |    -1.088 |
-#> |.....................|   -0.5377 |   -0.8613 |    -1.072 |   -0.2028 |
-#> |    U|     474.01246 |     91.25 |    -5.376 |   -0.9029 |    -2.198 |
-#> |.....................|    -4.626 |    0.4039 |     1.246 |   0.06013 |
-#> |.....................|    0.8773 |   0.05825 |    0.7954 |    0.7098 |
-#> |.....................|     1.573 |    0.9657 |    0.6927 |     2.020 |
-#> |    X|     474.01246 |     91.25 |  0.004628 |    0.2885 |    0.1110 |
-#> |.....................|  0.009798 |    0.5996 |     1.246 |   0.06013 |
-#> |.....................|    0.8773 |   0.05825 |    0.7954 |    0.7098 |
-#> |.....................|     1.573 |    0.9657 |    0.6927 |     2.020 |
-#> |    F| Forward Diff. |    -5.724 |     1.179 |   0.03043 |  -0.09493 |
-#> |.....................|    0.3750 |     1.206 |    -5.283 |     3.092 |
-#> |.....................|  -0.09863 |  -0.01543 |   -0.6573 |   -0.7980 |
-#> |.....................|     1.377 |     1.778 |    0.1578 |    -1.944 |
-#> |   68|     473.98155 |     1.005 |    -1.177 |   -0.9249 |   -0.9356 |
-#> |.....................|    -1.013 |    -1.005 |    0.1310 |   -0.8202 |
-#> |.....................|   -0.7607 |   -0.8818 |   -0.7885 |    -1.088 |
-#> |.....................|   -0.5387 |   -0.8611 |    -1.072 |   -0.2018 |
-#> |    U|     473.98155 |     91.42 |    -5.377 |   -0.9029 |    -2.198 |
-#> |.....................|    -4.626 |    0.4034 |     1.247 |   0.06004 |
-#> |.....................|    0.8773 |   0.05826 |    0.7956 |    0.7095 |
-#> |.....................|     1.572 |    0.9659 |    0.6925 |     2.022 |
-#> |    X|     473.98155 |     91.42 |  0.004623 |    0.2885 |    0.1110 |
-#> |.....................|  0.009794 |    0.5995 |     1.247 |   0.06004 |
-#> |.....................|    0.8773 |   0.05826 |    0.7956 |    0.7095 |
-#> |.....................|     1.572 |    0.9659 |    0.6925 |     2.022 |
-#> |    F| Forward Diff. |     9.125 |     1.189 |    0.2215 |   -0.1183 |
-#> |.....................|    0.3680 |     1.157 |    -5.346 |     3.214 |
-#> |.....................|  -0.06695 |  -0.05805 |   -0.6245 |   -0.6678 |
-#> |.....................|     1.365 |     1.770 |   0.07348 |    -1.960 |
-#> |   69|     473.94647 |     1.003 |    -1.178 |   -0.9250 |   -0.9354 |
-#> |.....................|    -1.014 |    -1.007 |    0.1350 |   -0.8231 |
-#> |.....................|   -0.7608 |   -0.8817 |   -0.7881 |    -1.089 |
-#> |.....................|   -0.5397 |   -0.8608 |    -1.072 |   -0.2009 |
-#> |    U|     473.94647 |     91.26 |    -5.378 |   -0.9030 |    -2.198 |
-#> |.....................|    -4.626 |    0.4029 |     1.249 |   0.05996 |
-#> |.....................|    0.8772 |   0.05826 |    0.7959 |    0.7086 |
-#> |.....................|     1.571 |    0.9661 |    0.6923 |     2.023 |
-#> |    X|     473.94647 |     91.26 |  0.004618 |    0.2884 |    0.1110 |
-#> |.....................|  0.009791 |    0.5994 |     1.249 |   0.05996 |
-#> |.....................|    0.8772 |   0.05826 |    0.7959 |    0.7086 |
-#> |.....................|     1.571 |    0.9661 |    0.6923 |     2.023 |
-#> |    F| Forward Diff. |    -5.271 |     1.174 |   0.04603 |  -0.09766 |
-#> |.....................|    0.3725 |     1.188 |    -5.320 |     3.084 |
-#> |.....................|  -0.09768 |  -0.01918 |   -0.6378 |   -0.8469 |
-#> |.....................|     1.360 |     1.825 |   0.08453 |    -1.920 |
-#> |   70|     473.91708 |     1.005 |    -1.179 |   -0.9250 |   -0.9353 |
-#> |.....................|    -1.014 |    -1.008 |    0.1391 |   -0.8259 |
-#> |.....................|   -0.7609 |   -0.8816 |   -0.7877 |    -1.089 |
-#> |.....................|   -0.5408 |   -0.8610 |    -1.072 |   -0.1999 |
-#> |    U|     473.91708 |     91.43 |    -5.379 |   -0.9030 |    -2.198 |
-#> |.....................|    -4.627 |    0.4024 |     1.251 |   0.05988 |
-#> |.....................|    0.8772 |   0.05826 |    0.7962 |    0.7081 |
-#> |.....................|     1.570 |    0.9660 |    0.6921 |     2.024 |
-#> |    X|     473.91708 |     91.43 |  0.004613 |    0.2884 |    0.1111 |
-#> |.....................|  0.009788 |    0.5993 |     1.251 |   0.05988 |
-#> |.....................|    0.8772 |   0.05826 |    0.7962 |    0.7081 |
-#> |.....................|     1.570 |    0.9660 |    0.6921 |     2.024 |
-#> |    F| Forward Diff. |     9.919 |     1.183 |    0.2388 |   -0.1221 |
-#> |.....................|    0.3649 |     1.138 |    -5.295 |     3.201 |
-#> |.....................|  -0.05759 |  -0.06746 |   -0.6018 |   -0.7458 |
-#> |.....................|     1.218 |     1.797 |   0.02666 |    -1.950 |
-#> |   71|     473.88166 |     1.003 |    -1.180 |   -0.9251 |   -0.9351 |
-#> |.....................|    -1.014 |    -1.009 |    0.1432 |   -0.8289 |
-#> |.....................|   -0.7611 |   -0.8814 |   -0.7874 |    -1.090 |
-#> |.....................|   -0.5418 |   -0.8607 |    -1.072 |   -0.1991 |
-#> |    U|     473.88166 |     91.26 |    -5.380 |   -0.9031 |    -2.198 |
-#> |.....................|    -4.627 |    0.4019 |     1.252 |   0.05979 |
-#> |.....................|    0.8771 |   0.05827 |    0.7964 |    0.7073 |
-#> |.....................|     1.568 |    0.9662 |    0.6919 |     2.025 |
-#> |    X|     473.88166 |     91.26 |  0.004608 |    0.2884 |    0.1111 |
-#> |.....................|  0.009785 |    0.5991 |     1.252 |   0.05979 |
-#> |.....................|    0.8771 |   0.05827 |    0.7964 |    0.7073 |
-#> |.....................|     1.568 |    0.9662 |    0.6919 |     2.025 |
-#> |    F| Forward Diff. |    -5.370 |     1.167 |   0.05346 |  -0.09978 |
-#> |.....................|    0.3701 |     1.174 |    -5.172 |     3.105 |
-#> |.....................|  -0.07011 |  -0.02516 |   -0.4239 |    -2.943 |
-#> |.....................|     1.187 |     1.854 |   0.07395 |    -1.907 |
-#> |   72|     473.85215 |     1.005 |    -1.181 |   -0.9251 |   -0.9350 |
-#> |.....................|    -1.015 |    -1.010 |    0.1472 |   -0.8318 |
-#> |.....................|   -0.7612 |   -0.8813 |   -0.7872 |    -1.090 |
-#> |.....................|   -0.5427 |   -0.8608 |    -1.073 |   -0.1983 |
-#> |    U|     473.85215 |     91.44 |    -5.381 |   -0.9031 |    -2.197 |
-#> |.....................|    -4.627 |    0.4014 |     1.254 |   0.05971 |
-#> |.....................|    0.8771 |   0.05827 |    0.7965 |    0.7078 |
-#> |.....................|     1.567 |    0.9662 |    0.6918 |     2.026 |
-#> |    X|     473.85215 |     91.44 |  0.004603 |    0.2884 |    0.1111 |
-#> |.....................|  0.009781 |    0.5990 |     1.254 |   0.05971 |
-#> |.....................|    0.8771 |   0.05827 |    0.7965 |    0.7078 |
-#> |.....................|     1.567 |    0.9662 |    0.6918 |     2.026 |
-#> |    F| Forward Diff. |     10.42 |     1.179 |    0.2474 |   -0.1240 |
-#> |.....................|    0.3627 |     1.120 |    -5.345 |     3.221 |
-#> |.....................|  -0.07960 |  -0.04998 |   -0.3836 |    -2.755 |
-#> |.....................|     1.094 |     1.797 |  -0.01014 |    -1.939 |
-#> |   73|     473.81514 |     1.003 |    -1.182 |   -0.9251 |   -0.9348 |
-#> |.....................|    -1.015 |    -1.011 |    0.1513 |   -0.8349 |
-#> |.....................|   -0.7614 |   -0.8810 |   -0.7873 |    -1.089 |
-#> |.....................|   -0.5432 |   -0.8601 |    -1.073 |   -0.1979 |
-#> |    U|     473.81514 |     91.27 |    -5.382 |   -0.9031 |    -2.197 |
-#> |.....................|    -4.628 |    0.4008 |     1.256 |   0.05962 |
-#> |.....................|    0.8770 |   0.05828 |    0.7964 |    0.7084 |
-#> |.....................|     1.567 |    0.9669 |    0.6916 |     2.026 |
-#> |    X|     473.81514 |     91.27 |  0.004598 |    0.2884 |    0.1111 |
-#> |.....................|  0.009778 |    0.5989 |     1.256 |   0.05962 |
-#> |.....................|    0.8770 |   0.05828 |    0.7964 |    0.7084 |
-#> |.....................|     1.567 |    0.9669 |    0.6916 |     2.026 |
-#> |    F| Forward Diff. |    -4.811 |     1.166 |   0.05684 |   -0.1019 |
-#> |.....................|    0.3663 |     1.150 |    -5.276 |     3.057 |
-#> |.....................|  -0.06818 |  -0.03474 |   -0.4125 |    -2.836 |
-#> |.....................|     1.158 |     1.851 |   0.03258 |    -1.914 |
-#> |   74|     473.78884 |     1.005 |    -1.183 |   -0.9252 |   -0.9346 |
-#> |.....................|    -1.015 |    -1.012 |    0.1554 |   -0.8377 |
-#> |.....................|   -0.7615 |   -0.8808 |   -0.7873 |    -1.088 |
-#> |.....................|   -0.5439 |   -0.8602 |    -1.073 |   -0.1971 |
-#> |    U|     473.78884 |     91.46 |    -5.383 |   -0.9031 |    -2.197 |
-#> |.....................|    -4.628 |    0.4003 |     1.257 |   0.05954 |
-#> |.....................|    0.8770 |   0.05829 |    0.7965 |    0.7095 |
-#> |.....................|     1.566 |    0.9667 |    0.6915 |     2.027 |
-#> |    X|     473.78884 |     91.46 |  0.004593 |    0.2884 |    0.1111 |
-#> |.....................|  0.009775 |    0.5988 |     1.257 |   0.05954 |
-#> |.....................|    0.8770 |   0.05829 |    0.7965 |    0.7095 |
-#> |.....................|     1.566 |    0.9667 |    0.6915 |     2.027 |
-#> |    F| Forward Diff. |     12.26 |     1.178 |    0.2628 |   -0.1282 |
-#> |.....................|    0.3579 |     1.094 |    -5.180 |     3.234 |
-#> |.....................|  -0.08932 |  -0.09780 |   -0.5652 |   -0.6340 |
-#> |.....................|     1.031 |     1.841 |  -0.06209 |    -1.938 |
-#> |   75|     473.75065 |     1.003 |    -1.184 |   -0.9252 |   -0.9344 |
-#> |.....................|    -1.016 |    -1.013 |    0.1594 |   -0.8407 |
-#> |.....................|   -0.7617 |   -0.8806 |   -0.7872 |    -1.088 |
-#> |.....................|   -0.5446 |   -0.8597 |    -1.073 |   -0.1966 |
-#> |    U|     473.75065 |     91.27 |    -5.384 |   -0.9032 |    -2.197 |
-#> |.....................|    -4.628 |    0.3998 |     1.259 |   0.05945 |
-#> |.....................|    0.8769 |   0.05829 |    0.7965 |    0.7092 |
-#> |.....................|     1.565 |    0.9672 |    0.6914 |     2.028 |
-#> |    X|     473.75065 |     91.27 |  0.004588 |    0.2884 |    0.1112 |
-#> |.....................|  0.009772 |    0.5986 |     1.259 |   0.05945 |
-#> |.....................|    0.8769 |   0.05829 |    0.7965 |    0.7092 |
-#> |.....................|     1.565 |    0.9672 |    0.6914 |     2.028 |
-#> |    F| Forward Diff. |    -5.250 |     1.164 |   0.05078 |   -0.1019 |
-#> |.....................|    0.3635 |     1.132 |    -5.308 |     3.057 |
-#> |.....................|  -0.09569 |  -0.05602 |   -0.5891 |   -0.8121 |
-#> |.....................|     1.074 |     1.883 |  0.002586 |    -1.906 |
-#> |   76|     473.72028 |     1.005 |    -1.185 |   -0.9252 |   -0.9343 |
-#> |.....................|    -1.016 |    -1.014 |    0.1635 |   -0.8437 |
-#> |.....................|   -0.7618 |   -0.8804 |   -0.7870 |    -1.089 |
-#> |.....................|   -0.5455 |   -0.8599 |    -1.073 |   -0.1958 |
-#> |    U|     473.72028 |     91.43 |    -5.385 |   -0.9032 |    -2.197 |
-#> |.....................|    -4.629 |    0.3993 |     1.261 |   0.05936 |
-#> |.....................|    0.8768 |   0.05830 |    0.7967 |    0.7088 |
-#> |.....................|     1.564 |    0.9671 |    0.6912 |     2.029 |
-#> |    X|     473.72028 |     91.43 |  0.004583 |    0.2884 |    0.1112 |
-#> |.....................|  0.009768 |    0.5985 |     1.261 |   0.05936 |
-#> |.....................|    0.8768 |   0.05830 |    0.7967 |    0.7088 |
-#> |.....................|     1.564 |    0.9671 |    0.6912 |     2.029 |
-#> |    F| Forward Diff. |     8.975 |     1.171 |    0.2290 |   -0.1246 |
-#> |.....................|    0.3563 |     1.085 |    -5.320 |     3.173 |
-#> |.....................|  -0.08707 |   -0.1016 |   -0.5561 |   -0.7117 |
-#> |.....................|    0.9536 |     1.850 |  -0.07963 |    -1.922 |
-#> |   77|     473.68600 |     1.003 |    -1.186 |   -0.9253 |   -0.9341 |
-#> |.....................|    -1.016 |    -1.015 |    0.1676 |   -0.8467 |
-#> |.....................|   -0.7620 |   -0.8801 |   -0.7868 |    -1.089 |
-#> |.....................|   -0.5463 |   -0.8596 |    -1.073 |   -0.1952 |
-#> |    U|       473.686 |     91.28 |    -5.386 |   -0.9033 |    -2.196 |
-#> |.....................|    -4.629 |    0.3989 |     1.263 |   0.05928 |
-#> |.....................|    0.8768 |   0.05831 |    0.7968 |    0.7081 |
-#> |.....................|     1.563 |    0.9673 |    0.6911 |     2.030 |
-#> |    X|       473.686 |     91.28 |  0.004578 |    0.2884 |    0.1112 |
-#> |.....................|  0.009765 |    0.5984 |     1.263 |   0.05928 |
-#> |.....................|    0.8768 |   0.05831 |    0.7968 |    0.7081 |
-#> |.....................|     1.563 |    0.9673 |    0.6911 |     2.030 |
-#> |    F| Forward Diff. |    -5.608 |     1.155 |   0.05506 |   -0.1036 |
-#> |.....................|    0.3607 |     1.118 |    -5.212 |     3.031 |
-#> |.....................|  -0.08611 |  -0.04336 |   -0.3798 |    -2.808 |
-#> |.....................|     1.093 |     1.880 |  -0.02731 |    -1.896 |
-#> |   78|     473.65599 |     1.005 |    -1.188 |   -0.9253 |   -0.9339 |
-#> |.....................|    -1.017 |    -1.016 |    0.1718 |   -0.8497 |
-#> |.....................|   -0.7621 |   -0.8799 |   -0.7868 |    -1.089 |
-#> |.....................|   -0.5471 |   -0.8595 |    -1.074 |   -0.1946 |
-#> |    U|     473.65599 |     91.44 |    -5.388 |   -0.9033 |    -2.196 |
-#> |.....................|    -4.629 |    0.3984 |     1.264 |   0.05919 |
-#> |.....................|    0.8767 |   0.05831 |    0.7968 |    0.7087 |
-#> |.....................|     1.562 |    0.9674 |    0.6910 |     2.030 |
-#> |    X|     473.65599 |     91.44 |  0.004573 |    0.2884 |    0.1112 |
-#> |.....................|  0.009762 |    0.5983 |     1.264 |   0.05919 |
-#> |.....................|    0.8767 |   0.05831 |    0.7968 |    0.7087 |
-#> |.....................|     1.562 |    0.9674 |    0.6910 |     2.030 |
-#> |    F| Forward Diff. |     9.720 |     1.170 |    0.2444 |   -0.1229 |
-#> |.....................|    0.3557 |     1.067 |    -5.275 |     3.173 |
-#> |.....................|  -0.07850 |   -0.1042 |   -0.5348 |   -0.6844 |
-#> |.....................|    0.9479 |     1.915 |   -0.1018 |    -1.917 |
-#> |   79|     473.62083 |     1.003 |    -1.189 |   -0.9254 |   -0.9337 |
-#> |.....................|    -1.017 |    -1.017 |    0.1759 |   -0.8528 |
-#> |.....................|   -0.7623 |   -0.8795 |   -0.7869 |    -1.089 |
-#> |.....................|   -0.5477 |   -0.8591 |    -1.074 |   -0.1942 |
-#> |    U|     473.62083 |     91.28 |    -5.389 |   -0.9033 |    -2.196 |
-#> |.....................|    -4.630 |    0.3979 |     1.266 |   0.05910 |
-#> |.....................|    0.8766 |   0.05832 |    0.7968 |    0.7085 |
-#> |.....................|     1.562 |    0.9678 |    0.6909 |     2.031 |
-#> |    X|     473.62083 |     91.28 |  0.004568 |    0.2884 |    0.1112 |
-#> |.....................|  0.009758 |    0.5982 |     1.266 |   0.05910 |
-#> |.....................|    0.8766 |   0.05832 |    0.7968 |    0.7085 |
-#> |.....................|     1.562 |    0.9678 |    0.6909 |     2.031 |
-#> |    F| Forward Diff. |    -5.323 |     1.153 |   0.05982 |   -0.1053 |
-#> |.....................|    0.3572 |     1.098 |    -4.702 |     3.058 |
-#> |.....................|   -0.1117 |  -0.04281 |   -0.5573 |   -0.7999 |
-#> |.....................|     1.039 |     1.912 |  -0.05974 |    -1.890 |
-#> |   80|     473.59326 |     1.005 |    -1.190 |   -0.9254 |   -0.9335 |
-#> |.....................|    -1.018 |    -1.019 |    0.1798 |   -0.8560 |
-#> |.....................|   -0.7624 |   -0.8793 |   -0.7867 |    -1.090 |
-#> |.....................|   -0.5486 |   -0.8595 |    -1.074 |   -0.1934 |
-#> |    U|     473.59326 |     91.46 |    -5.390 |   -0.9034 |    -2.196 |
-#> |.....................|    -4.630 |    0.3974 |     1.268 |   0.05901 |
-#> |.....................|    0.8766 |   0.05833 |    0.7969 |    0.7081 |
-#> |.....................|     1.560 |    0.9674 |    0.6908 |     2.032 |
-#> |    X|     473.59326 |     91.46 |  0.004562 |    0.2884 |    0.1113 |
-#> |.....................|  0.009755 |    0.5981 |     1.268 |   0.05901 |
-#> |.....................|    0.8766 |   0.05833 |    0.7969 |    0.7081 |
-#> |.....................|     1.560 |    0.9674 |    0.6908 |     2.032 |
-#> |    F| Forward Diff. |     11.25 |     1.162 |    0.2586 |   -0.1299 |
-#> |.....................|    0.3499 |     1.048 |    -5.229 |     3.126 |
-#> |.....................|  -0.05642 |  -0.09930 |   -0.3252 |    -2.718 |
-#> |.....................|    0.8202 |     1.876 |   -0.1477 |    -1.910 |
-#> |   81|     473.55541 |     1.003 |    -1.191 |   -0.9255 |   -0.9333 |
-#> |.....................|    -1.018 |    -1.020 |    0.1836 |   -0.8595 |
-#> |.....................|   -0.7626 |   -0.8789 |   -0.7868 |    -1.090 |
-#> |.....................|   -0.5492 |   -0.8592 |    -1.074 |   -0.1932 |
-#> |    U|     473.55541 |     91.31 |    -5.391 |   -0.9034 |    -2.196 |
-#> |.....................|    -4.630 |    0.3968 |     1.269 |   0.05891 |
-#> |.....................|    0.8765 |   0.05834 |    0.7968 |    0.7080 |
-#> |.....................|     1.560 |    0.9677 |    0.6906 |     2.032 |
-#> |    X|     473.55541 |     91.31 |  0.004557 |    0.2883 |    0.1113 |
-#> |.....................|  0.009751 |    0.5979 |     1.269 |   0.05891 |
-#> |.....................|    0.8765 |   0.05834 |    0.7968 |    0.7080 |
-#> |.....................|     1.560 |    0.9677 |    0.6906 |     2.032 |
-#> |    F| Forward Diff. |    -3.062 |     1.149 |   0.09224 |   -0.1103 |
-#> |.....................|    0.3525 |     1.070 |    -5.098 |     2.994 |
-#> |.....................|   -0.1095 |  -0.04877 |   -0.3504 |    -2.828 |
-#> |.....................|    0.8255 |     1.898 |   -0.1147 |    -1.889 |
-#> |   82|     473.53708 |     1.006 |    -1.192 |   -0.9256 |   -0.9332 |
-#> |.....................|    -1.018 |    -1.021 |    0.1873 |   -0.8616 |
-#> |.....................|   -0.7625 |   -0.8789 |   -0.7866 |    -1.087 |
-#> |.....................|   -0.5498 |   -0.8606 |    -1.074 |   -0.1918 |
-#> |    U|     473.53708 |     91.52 |    -5.392 |   -0.9035 |    -2.196 |
-#> |.....................|    -4.631 |    0.3964 |     1.271 |   0.05884 |
-#> |.....................|    0.8765 |   0.05834 |    0.7970 |    0.7099 |
-#> |.....................|     1.559 |    0.9664 |    0.6907 |     2.034 |
-#> |    X|     473.53708 |     91.52 |  0.004553 |    0.2883 |    0.1113 |
-#> |.....................|  0.009749 |    0.5978 |     1.271 |   0.05884 |
-#> |.....................|    0.8765 |   0.05834 |    0.7970 |    0.7099 |
-#> |.....................|     1.559 |    0.9664 |    0.6907 |     2.034 |
-#> |    F| Forward Diff. |     16.25 |     1.165 |    0.3077 |   -0.1378 |
-#> |.....................|    0.3448 |     1.019 |    -5.264 |     3.150 |
-#> |.....................|  -0.09278 |   -0.1366 |   -0.2969 |    -2.557 |
-#> |.....................|    0.7485 |     1.781 |   -0.1828 |    -1.909 |
-#> |   83|     473.49312 |     1.003 |    -1.193 |   -0.9256 |   -0.9329 |
-#> |.....................|    -1.018 |    -1.022 |    0.1912 |   -0.8647 |
-#> |.....................|   -0.7626 |   -0.8785 |   -0.7869 |    -1.087 |
-#> |.....................|   -0.5501 |   -0.8598 |    -1.074 |   -0.1918 |
-#> |    U|     473.49312 |     91.32 |    -5.393 |   -0.9035 |    -2.195 |
-#> |.....................|    -4.631 |    0.3959 |     1.272 |   0.05875 |
-#> |.....................|    0.8765 |   0.05835 |    0.7967 |    0.7106 |
-#> |.....................|     1.559 |    0.9671 |    0.6906 |     2.034 |
-#> |    X|     473.49312 |     91.32 |  0.004547 |    0.2883 |    0.1113 |
-#> |.....................|  0.009745 |    0.5977 |     1.272 |   0.05875 |
-#> |.....................|    0.8765 |   0.05835 |    0.7967 |    0.7106 |
-#> |.....................|     1.559 |    0.9671 |    0.6906 |     2.034 |
-#> |    F| Forward Diff. |    -2.793 |     1.150 |   0.08391 |   -0.1095 |
-#> |.....................|    0.3500 |     1.057 |    -5.154 |     2.847 |
-#> |.....................|  -0.07414 |  -0.06025 |   -0.5244 |   -0.6779 |
-#> |.....................|    0.8291 |     1.867 |   -0.1201 |    -1.880 |
-#> |   84|     473.47390 |     1.006 |    -1.194 |   -0.9256 |   -0.9329 |
-#> |.....................|    -1.019 |    -1.022 |    0.1953 |   -0.8670 |
-#> |.....................|   -0.7626 |   -0.8785 |   -0.7865 |    -1.086 |
-#> |.....................|   -0.5507 |   -0.8613 |    -1.074 |   -0.1903 |
-#> |    U|      473.4739 |     91.52 |    -5.394 |   -0.9036 |    -2.195 |
-#> |.....................|    -4.631 |    0.3955 |     1.274 |   0.05869 |
-#> |.....................|    0.8765 |   0.05835 |    0.7970 |    0.7110 |
-#> |.....................|     1.558 |    0.9657 |    0.6907 |     2.036 |
-#> |    X|      473.4739 |     91.52 |  0.004543 |    0.2883 |    0.1113 |
-#> |.....................|  0.009743 |    0.5976 |     1.274 |   0.05869 |
-#> |.....................|    0.8765 |   0.05835 |    0.7970 |    0.7110 |
-#> |.....................|     1.558 |    0.9657 |    0.6907 |     2.036 |
-#> |    F| Forward Diff. |     15.82 |     1.163 |    0.3026 |   -0.1376 |
-#> |.....................|    0.3423 |     1.007 |    -4.821 |     3.176 |
-#> |.....................|  -0.06207 |   -0.1161 |   -0.4712 |   -0.4774 |
-#> |.....................|    0.7015 |     1.725 |   -0.1877 |    -1.896 |
-#> |   85|     473.43080 |     1.003 |    -1.195 |   -0.9257 |   -0.9326 |
-#> |.....................|    -1.019 |    -1.024 |    0.1991 |   -0.8700 |
-#> |.....................|   -0.7628 |   -0.8781 |   -0.7866 |    -1.087 |
-#> |.....................|   -0.5513 |   -0.8608 |    -1.074 |   -0.1899 |
-#> |    U|      473.4308 |     91.31 |    -5.395 |   -0.9036 |    -2.195 |
-#> |.....................|    -4.632 |    0.3950 |     1.276 |   0.05860 |
-#> |.....................|    0.8764 |   0.05836 |    0.7970 |    0.7105 |
-#> |.....................|     1.557 |    0.9662 |    0.6906 |     2.036 |
-#> |    X|      473.4308 |     91.31 |  0.004538 |    0.2883 |    0.1114 |
-#> |.....................|  0.009739 |    0.5975 |     1.276 |   0.05860 |
-#> |.....................|    0.8764 |   0.05836 |    0.7970 |    0.7105 |
-#> |.....................|     1.557 |    0.9662 |    0.6906 |     2.036 |
-#> |    F| Forward Diff. |    -3.611 |     1.145 |   0.07564 |   -0.1091 |
-#> |.....................|    0.3478 |     1.048 |    -5.196 |     2.853 |
-#> |.....................|  -0.07176 |  -0.06153 |   -0.5100 |   -0.6862 |
-#> |.....................|    0.7701 |     1.783 |   -0.1204 |    -1.866 |
-#> |   86|     473.40390 |     1.005 |    -1.196 |   -0.9258 |   -0.9324 |
-#> |.....................|    -1.019 |    -1.025 |    0.2034 |   -0.8728 |
-#> |.....................|   -0.7629 |   -0.8779 |   -0.7864 |    -1.087 |
-#> |.....................|   -0.5520 |   -0.8612 |    -1.074 |   -0.1890 |
-#> |    U|      473.4039 |     91.48 |    -5.396 |   -0.9037 |    -2.195 |
-#> |.....................|    -4.632 |    0.3946 |     1.277 |   0.05852 |
-#> |.....................|    0.8764 |   0.05837 |    0.7971 |    0.7105 |
-#> |.....................|     1.556 |    0.9658 |    0.6906 |     2.037 |
-#> |    X|      473.4039 |     91.48 |  0.004533 |    0.2883 |    0.1114 |
-#> |.....................|  0.009736 |    0.5974 |     1.277 |   0.05852 |
-#> |.....................|    0.8764 |   0.05837 |    0.7971 |    0.7105 |
-#> |.....................|     1.556 |    0.9658 |    0.6906 |     2.037 |
-#> |    F| Forward Diff. |     11.82 |     1.154 |    0.2542 |   -0.1321 |
-#> |.....................|    0.3410 |     1.002 |    -5.150 |     3.097 |
-#> |.....................|  -0.04820 |   -0.1059 |   -0.4698 |   -0.5387 |
-#> |.....................|    0.6891 |     1.733 |   -0.1906 |    -1.879 |
-#> |   87|     473.36686 |     1.003 |    -1.198 |   -0.9258 |   -0.9322 |
-#> |.....................|    -1.020 |    -1.026 |    0.2076 |   -0.8758 |
-#> |.....................|   -0.7631 |   -0.8776 |   -0.7865 |    -1.087 |
-#> |.....................|   -0.5525 |   -0.8606 |    -1.074 |   -0.1886 |
-#> |    U|     473.36686 |     91.32 |    -5.398 |   -0.9037 |    -2.195 |
-#> |.....................|    -4.632 |    0.3941 |     1.279 |   0.05843 |
-#> |.....................|    0.8763 |   0.05838 |    0.7970 |    0.7100 |
-#> |.....................|     1.556 |    0.9664 |    0.6905 |     2.038 |
-#> |    X|     473.36686 |     91.32 |  0.004527 |    0.2883 |    0.1114 |
-#> |.....................|  0.009733 |    0.5973 |     1.279 |   0.05843 |
-#> |.....................|    0.8763 |   0.05838 |    0.7970 |    0.7100 |
-#> |.....................|     1.556 |    0.9664 |    0.6905 |     2.038 |
-#> |    F| Forward Diff. |    -3.686 |     1.139 |   0.08028 |   -0.1103 |
-#> |.....................|    0.3450 |     1.034 |    -5.059 |     2.983 |
-#> |.....................|  -0.07022 |  -0.06541 |   -0.4954 |   -0.7148 |
-#> |.....................|    0.6839 |     1.782 |   -0.1353 |    -1.853 |
-#> |   88|     473.34117 |     1.005 |    -1.199 |   -0.9259 |   -0.9321 |
-#> |.....................|    -1.020 |    -1.027 |    0.2118 |   -0.8787 |
-#> |.....................|   -0.7632 |   -0.8774 |   -0.7864 |    -1.087 |
-#> |.....................|   -0.5531 |   -0.8611 |    -1.074 |   -0.1877 |
-#> |    U|     473.34117 |     91.49 |    -5.399 |   -0.9038 |    -2.194 |
-#> |.....................|    -4.633 |    0.3936 |     1.281 |   0.05835 |
-#> |.....................|    0.8763 |   0.05838 |    0.7971 |    0.7100 |
-#> |.....................|     1.555 |    0.9659 |    0.6904 |     2.039 |
-#> |    X|     473.34117 |     91.49 |  0.004522 |    0.2883 |    0.1114 |
-#> |.....................|  0.009730 |    0.5972 |     1.281 |   0.05835 |
-#> |.....................|    0.8763 |   0.05838 |    0.7971 |    0.7100 |
-#> |.....................|     1.555 |    0.9659 |    0.6904 |     2.039 |
-#> |    F| Forward Diff. |     12.62 |     1.149 |    0.2679 |   -0.1346 |
-#> |.....................|    0.3379 |    0.9875 |    -5.147 |     2.965 |
-#> |.....................|  -0.07400 |   -0.1145 |   -0.4542 |   -0.5455 |
-#> |.....................|    0.6283 |     1.734 |   -0.2097 |    -1.869 |
-#> |   89|     473.30326 |     1.004 |    -1.200 |   -0.9259 |   -0.9318 |
-#> |.....................|    -1.020 |    -1.028 |    0.2159 |   -0.8818 |
-#> |.....................|   -0.7634 |   -0.8771 |   -0.7865 |    -1.088 |
-#> |.....................|   -0.5535 |   -0.8604 |    -1.074 |   -0.1874 |
-#> |    U|     473.30326 |     91.32 |    -5.400 |   -0.9038 |    -2.194 |
-#> |.....................|    -4.633 |    0.3932 |     1.283 |   0.05826 |
-#> |.....................|    0.8762 |   0.05839 |    0.7970 |    0.7096 |
-#> |.....................|     1.555 |    0.9665 |    0.6903 |     2.039 |
-#> |    X|     473.30326 |     91.32 |  0.004517 |    0.2883 |    0.1114 |
-#> |.....................|  0.009726 |    0.5970 |     1.283 |   0.05826 |
-#> |.....................|    0.8762 |   0.05839 |    0.7970 |    0.7096 |
-#> |.....................|     1.555 |    0.9665 |    0.6903 |     2.039 |
-#> |    F| Forward Diff. |    -3.609 |     1.134 |   0.08636 |   -0.1114 |
-#> |.....................|    0.3423 |     1.018 |    -5.228 |     2.880 |
-#> |.....................|   -0.1079 |  -0.06580 |   -0.2896 |    -2.686 |
-#> |.....................|    0.6917 |     1.801 |   -0.1599 |    -1.842 |
-#> |   90|     473.27616 |     1.005 |    -1.201 |   -0.9260 |   -0.9316 |
-#> |.....................|    -1.021 |    -1.029 |    0.2202 |   -0.8845 |
-#> |.....................|   -0.7634 |   -0.8768 |   -0.7866 |    -1.087 |
-#> |.....................|   -0.5540 |   -0.8607 |    -1.074 |   -0.1867 |
-#> |    U|     473.27616 |     91.48 |    -5.401 |   -0.9039 |    -2.194 |
-#> |.....................|    -4.633 |    0.3927 |     1.284 |   0.05818 |
-#> |.....................|    0.8762 |   0.05840 |    0.7970 |    0.7107 |
-#> |.....................|     1.554 |    0.9663 |    0.6904 |     2.040 |
-#> |    X|     473.27616 |     91.48 |  0.004512 |    0.2883 |    0.1115 |
-#> |.....................|  0.009723 |    0.5969 |     1.284 |   0.05818 |
-#> |.....................|    0.8762 |   0.05840 |    0.7970 |    0.7107 |
-#> |.....................|     1.554 |    0.9663 |    0.6904 |     2.040 |
-#> |    F| Forward Diff. |     11.44 |     1.145 |    0.2516 |   -0.1333 |
-#> |.....................|    0.3351 |    0.9744 |    -4.753 |     3.090 |
-#> |.....................|  -0.05028 |   -0.1148 |   -0.4450 |   -0.5198 |
-#> |.....................|    0.5573 |     1.743 |   -0.2240 |    -1.858 |
-#> |   91|     473.24283 |     1.003 |    -1.202 |   -0.9260 |   -0.9314 |
-#> |.....................|    -1.021 |    -1.030 |    0.2240 |   -0.8877 |
-#> |.....................|   -0.7636 |   -0.8764 |   -0.7870 |    -1.087 |
-#> |.....................|   -0.5543 |   -0.8601 |    -1.074 |   -0.1866 |
-#> |    U|     473.24283 |     91.29 |    -5.402 |   -0.9039 |    -2.194 |
-#> |.....................|    -4.634 |    0.3922 |     1.286 |   0.05809 |
-#> |.....................|    0.8761 |   0.05841 |    0.7967 |    0.7107 |
-#> |.....................|     1.554 |    0.9668 |    0.6903 |     2.040 |
-#> |    X|     473.24283 |     91.29 |  0.004506 |    0.2882 |    0.1115 |
-#> |.....................|  0.009720 |    0.5968 |     1.286 |   0.05809 |
-#> |.....................|    0.8761 |   0.05841 |    0.7967 |    0.7107 |
-#> |.....................|     1.554 |    0.9668 |    0.6903 |     2.040 |
-#> |    F| Forward Diff. |    -7.383 |     1.129 |   0.03939 |   -0.1057 |
-#> |.....................|    0.3410 |     1.013 |    -4.733 |     2.907 |
-#> |.....................|  -0.07460 |  -0.06623 |   -0.4732 |   -0.6761 |
-#> |.....................|    0.6495 |     1.823 |   -0.1637 |    -1.832 |
-#> |   92|     473.20973 |     1.005 |    -1.204 |   -0.9260 |   -0.9311 |
-#> |.....................|    -1.021 |    -1.031 |    0.2279 |   -0.8912 |
-#> |.....................|   -0.7638 |   -0.8760 |   -0.7872 |    -1.087 |
-#> |.....................|   -0.5548 |   -0.8600 |    -1.075 |   -0.1862 |
-#> |    U|     473.20973 |     91.43 |    -5.404 |   -0.9039 |    -2.193 |
-#> |.....................|    -4.634 |    0.3917 |     1.288 |   0.05799 |
-#> |.....................|    0.8760 |   0.05843 |    0.7966 |    0.7102 |
-#> |.....................|     1.553 |    0.9669 |    0.6900 |     2.040 |
-#> |    X|     473.20973 |     91.43 |  0.004500 |    0.2882 |    0.1115 |
-#> |.....................|  0.009716 |    0.5967 |     1.288 |   0.05799 |
-#> |.....................|    0.8760 |   0.05843 |    0.7966 |    0.7102 |
-#> |.....................|     1.553 |    0.9669 |    0.6900 |     2.040 |
-#> |   93|     473.17178 |     1.005 |    -1.205 |   -0.9261 |   -0.9307 |
-#> |.....................|    -1.022 |    -1.032 |    0.2326 |   -0.8959 |
-#> |.....................|   -0.7641 |   -0.8754 |   -0.7876 |    -1.088 |
-#> |.....................|   -0.5554 |   -0.8593 |    -1.075 |   -0.1863 |
-#> |    U|     473.17178 |     91.43 |    -5.405 |   -0.9040 |    -2.193 |
-#> |.....................|    -4.634 |    0.3910 |     1.289 |   0.05785 |
-#> |.....................|    0.8759 |   0.05844 |    0.7963 |    0.7092 |
-#> |.....................|     1.552 |    0.9676 |    0.6896 |     2.040 |
-#> |    X|     473.17178 |     91.43 |  0.004492 |    0.2882 |    0.1116 |
-#> |.....................|  0.009711 |    0.5965 |     1.289 |   0.05785 |
-#> |.....................|    0.8759 |   0.05844 |    0.7963 |    0.7092 |
-#> |.....................|     1.552 |    0.9676 |    0.6896 |     2.040 |
-#> |   94|     472.97479 |     1.005 |    -1.215 |   -0.9262 |   -0.9287 |
-#> |.....................|    -1.025 |    -1.041 |    0.2575 |   -0.9212 |
-#> |.....................|   -0.7657 |   -0.8720 |   -0.7899 |    -1.094 |
-#> |.....................|   -0.5585 |   -0.8552 |    -1.078 |   -0.1866 |
-#> |    U|     472.97479 |     91.45 |    -5.415 |   -0.9041 |    -2.191 |
-#> |.....................|    -4.637 |    0.3872 |     1.300 |   0.05712 |
-#> |.....................|    0.8752 |   0.05854 |    0.7946 |    0.7037 |
-#> |.....................|     1.549 |    0.9715 |    0.6874 |     2.040 |
-#> |    X|     472.97479 |     91.45 |  0.004449 |    0.2882 |    0.1118 |
-#> |.....................|  0.009685 |    0.5956 |     1.300 |   0.05712 |
-#> |.....................|    0.8752 |   0.05854 |    0.7946 |    0.7037 |
-#> |.....................|     1.549 |    0.9715 |    0.6874 |     2.040 |
-#> |   95|     472.26932 |     1.006 |    -1.253 |   -0.9268 |   -0.9205 |
-#> |.....................|    -1.035 |    -1.074 |    0.3572 |    -1.022 |
-#> |.....................|   -0.7723 |   -0.8583 |   -0.7991 |    -1.118 |
-#> |.....................|   -0.5709 |   -0.8392 |    -1.088 |   -0.1877 |
-#> |    U|     472.26932 |     91.55 |    -5.453 |   -0.9046 |    -2.183 |
-#> |.....................|    -4.648 |    0.3719 |     1.341 |   0.05419 |
-#> |.....................|    0.8725 |   0.05894 |    0.7878 |    0.6819 |
-#> |.....................|     1.534 |    0.9868 |    0.6787 |     2.039 |
-#> |    X|     472.26932 |     91.55 |  0.004282 |    0.2881 |    0.1127 |
-#> |.....................|  0.009582 |    0.5919 |     1.341 |   0.05419 |
-#> |.....................|    0.8725 |   0.05894 |    0.7878 |    0.6819 |
-#> |.....................|     1.534 |    0.9868 |    0.6787 |     2.039 |
-#> |   96|     470.90347 |     1.012 |    -1.408 |   -0.9286 |   -0.8872 |
-#> |.....................|    -1.078 |    -1.207 |    0.7550 |    -1.427 |
-#> |.....................|   -0.7985 |   -0.8024 |   -0.8343 |    -1.204 |
-#> |.....................|   -0.6170 |   -0.7722 |    -1.128 |   -0.1957 |
-#> |    U|     470.90347 |     92.06 |    -5.608 |   -0.9062 |    -2.150 |
-#> |.....................|    -4.691 |    0.3105 |     1.506 |   0.04245 |
-#> |.....................|    0.8616 |   0.06056 |    0.7621 |    0.6043 |
-#> |.....................|     1.480 |     1.051 |    0.6438 |     2.029 |
-#> |    X|     470.90347 |     92.06 |  0.003670 |    0.2878 |    0.1165 |
-#> |.....................|  0.009180 |    0.5770 |     1.506 |   0.04245 |
-#> |.....................|    0.8616 |   0.06056 |    0.7621 |    0.6043 |
-#> |.....................|     1.480 |     1.051 |    0.6438 |     2.029 |
-#> |    F| Forward Diff. |     16.46 |    0.7178 |     1.137 |   -0.2842 |
-#> |.....................|   0.06515 |    -1.058 |    -6.810 |    -2.325 |
-#> |.....................|   -0.1903 |   -0.6630 |     1.424 |    -9.046 |
-#> |.....................|    -1.659 |     8.235 |    -7.307 |    -1.506 |
-#> |   97|     469.55066 |     1.016 |    -1.623 |   -0.9529 |   -0.8214 |
-#> |.....................|    -1.136 |    -1.353 |     1.295 |    -1.874 |
-#> |.....................|   -0.8595 |   -0.6716 |   -0.9513 |    -1.204 |
-#> |.....................|   -0.7087 |   -0.8316 |   -0.9499 |   -0.4083 |
-#> |    U|     469.55066 |     92.47 |    -5.823 |   -0.9279 |    -2.084 |
-#> |.....................|    -4.749 |    0.2437 |     1.731 |   0.02949 |
-#> |.....................|    0.8363 |   0.06435 |    0.6766 |    0.6043 |
-#> |.....................|     1.371 |    0.9940 |    0.7978 |     1.771 |
-#> |    X|     469.55066 |     92.47 |  0.002960 |    0.2834 |    0.1245 |
-#> |.....................|  0.008661 |    0.5606 |     1.731 |   0.02949 |
-#> |.....................|    0.8363 |   0.06435 |    0.6766 |    0.6043 |
-#> |.....................|     1.371 |    0.9940 |    0.7978 |     1.771 |
-#> |    F| Forward Diff. |    -5.003 |    0.4823 |    0.6025 |   -0.2481 |
-#> |.....................|    -1.135 |    0.1015 |    -5.875 |    -8.309 |
-#> |.....................|   -0.8363 |   -0.7839 |     1.711 |    -6.097 |
-#> |.....................|    -4.755 |     1.794 |     4.040 |   -0.5408 |
-#> |   98|     471.32255 |     1.022 |    -1.880 |    -1.043 |   -0.7426 |
-#> |.....................|    -1.107 |    -1.512 |     1.956 |    -1.964 |
-#> |.....................|   -0.9773 |   -0.5429 |    -1.097 |    -1.122 |
-#> |.....................|   -0.6469 |   -0.5662 |   -0.9027 |   -0.4752 |
-#> |    U|     471.32255 |     93.00 |    -6.080 |    -1.008 |    -2.005 |
-#> |.....................|    -4.719 |    0.1705 |     2.005 |   0.02687 |
-#> |.....................|    0.7874 |   0.06809 |    0.5704 |    0.6787 |
-#> |.....................|     1.444 |     1.248 |    0.8385 |     1.690 |
-#> |    X|     471.32255 |     93.00 |  0.002289 |    0.2674 |    0.1347 |
-#> |.....................|  0.008922 |    0.5425 |     2.005 |   0.02687 |
-#> |.....................|    0.7874 |   0.06809 |    0.5704 |    0.6787 |
-#> |.....................|     1.444 |     1.248 |    0.8385 |     1.690 |
-#> |   99|     468.82475 |     1.022 |    -1.709 |   -0.9836 |   -0.7948 |
-#> |.....................|    -1.126 |    -1.406 |     1.521 |    -1.898 |
-#> |.....................|   -0.8984 |   -0.6279 |    -1.001 |    -1.172 |
-#> |.....................|   -0.6845 |   -0.7440 |   -0.9371 |   -0.4303 |
-#> |    U|     468.82475 |     92.98 |    -5.909 |   -0.9551 |    -2.057 |
-#> |.....................|    -4.738 |    0.2191 |     1.824 |   0.02879 |
-#> |.....................|    0.8201 |   0.06562 |    0.6400 |    0.6333 |
-#> |.....................|     1.400 |     1.078 |    0.8088 |     1.744 |
-#> |    X|     468.82475 |     92.98 |  0.002714 |    0.2779 |    0.1278 |
-#> |.....................|  0.008755 |    0.5546 |     1.824 |   0.02879 |
-#> |.....................|    0.8201 |   0.06562 |    0.6400 |    0.6333 |
-#> |.....................|     1.400 |     1.078 |    0.8088 |     1.744 |
-#> |    F| Forward Diff. |     40.86 |    0.3767 |  -0.09575 |   -0.1893 |
-#> |.....................|    -1.313 |   -0.2132 |    -3.864 |    -4.927 |
-#> |.....................|    -1.292 |    -1.079 |   -0.1017 |    -3.329 |
-#> |.....................|    -4.248 |     8.116 |     3.916 |   -0.3530 |
-#> |  100|     467.75171 |     1.017 |    -1.816 |   -0.9824 |   -0.7623 |
-#> |.....................|    -1.067 |    -1.470 |     1.678 |    -1.962 |
-#> |.....................|   -0.9501 |   -0.5667 |   -0.9995 |    -1.140 |
-#> |.....................|   -0.5909 |   -0.8204 |    -1.012 |   -0.4878 |
-#> |    U|     467.75171 |     92.51 |    -6.016 |   -0.9541 |    -2.025 |
-#> |.....................|    -4.679 |    0.1896 |     1.889 |   0.02693 |
-#> |.....................|    0.7987 |   0.06740 |    0.6413 |    0.6622 |
-#> |.....................|     1.510 |     1.005 |    0.7438 |     1.674 |
-#> |    X|     467.75171 |     92.51 |  0.002440 |    0.2781 |    0.1320 |
-#> |.....................|  0.009285 |    0.5473 |     1.889 |   0.02693 |
-#> |.....................|    0.7987 |   0.06740 |    0.6413 |    0.6622 |
-#> |.....................|     1.510 |     1.005 |    0.7438 |     1.674 |
-#> |    F| Forward Diff. |    -11.72 |    0.1617 |   -0.2966 |    0.1391 |
-#> |.....................|   -0.7722 |   -0.6625 |    -3.136 |    -6.222 |
-#> |.....................|    -1.617 |   -0.9189 |   -0.2811 |    -3.105 |
-#> |.....................|   0.05355 |     2.320 |    -3.473 |    -2.160 |
-#> |  101|     467.28745 |     1.018 |    -1.902 |   -0.9107 |   -0.7577 |
-#> |.....................|   -0.9795 |    -1.517 |     1.777 |    -1.860 |
-#> |.....................|   -0.8874 |   -0.4787 |   -0.8826 |    -1.170 |
-#> |.....................|   -0.6199 |   -0.8544 |   -0.9952 |   -0.3962 |
-#> |    U|     467.28745 |     92.66 |    -6.102 |   -0.8902 |    -2.020 |
-#> |.....................|    -4.592 |    0.1682 |     1.931 |   0.02990 |
-#> |.....................|    0.8247 |   0.06995 |    0.7268 |    0.6357 |
-#> |.....................|     1.476 |    0.9723 |    0.7587 |     1.785 |
-#> |    X|     467.28745 |     92.66 |  0.002239 |    0.2911 |    0.1327 |
-#> |.....................|   0.01013 |    0.5420 |     1.931 |   0.02990 |
-#> |.....................|    0.8247 |   0.06995 |    0.7268 |    0.6357 |
-#> |.....................|     1.476 |    0.9723 |    0.7587 |     1.785 |
-#> |    F| Forward Diff. |     21.75 |    0.1003 |     2.571 |    0.1450 |
-#> |.....................|   -0.5415 |    -1.471 |    -1.062 |    -1.774 |
-#> |.....................|     1.363 |    0.7539 |     2.182 |    -3.357 |
-#> |.....................|    -1.337 |    0.2346 |    -1.234 |   -0.8531 |
-#> |  102|     469.68385 |    0.9954 |    -1.950 |    -1.032 |   -0.7900 |
-#> |.....................|   -0.8810 |    -1.433 |     1.783 |    -1.785 |
-#> |.....................|   -0.9418 |   -0.5114 |   -0.9107 |    -1.204 |
-#> |.....................|   -0.6798 |   -0.8966 |    -1.014 |   -0.2565 |
-#> |    U|     469.68385 |     90.58 |    -6.150 |   -0.9984 |    -2.052 |
-#> |.....................|    -4.493 |    0.2066 |     1.933 |   0.03207 |
-#> |.....................|    0.8021 |   0.06900 |    0.7062 |    0.6043 |
-#> |.....................|     1.405 |    0.9320 |    0.7422 |     1.955 |
-#> |    X|     469.68385 |     90.58 |  0.002133 |    0.2693 |    0.1284 |
-#> |.....................|   0.01118 |    0.5515 |     1.933 |   0.03207 |
-#> |.....................|    0.8021 |   0.06900 |    0.7062 |    0.6043 |
-#> |.....................|     1.405 |    0.9320 |    0.7422 |     1.955 |
-#> |  103|     467.87907 |     1.005 |    -1.909 |   -0.9308 |   -0.7628 |
-#> |.....................|   -0.9639 |    -1.503 |     1.779 |    -1.847 |
-#> |.....................|   -0.8965 |   -0.4841 |   -0.8880 |    -1.173 |
-#> |.....................|   -0.6287 |   -0.8610 |   -0.9975 |   -0.3740 |
-#> |    U|     467.87907 |     91.48 |    -6.109 |   -0.9081 |    -2.025 |
-#> |.....................|    -4.576 |    0.1745 |     1.931 |   0.03026 |
-#> |.....................|    0.8209 |   0.06979 |    0.7229 |    0.6325 |
-#> |.....................|     1.466 |    0.9660 |    0.7566 |     1.812 |
-#> |    X|     467.87907 |     91.48 |  0.002222 |    0.2874 |    0.1320 |
-#> |.....................|   0.01029 |    0.5435 |     1.931 |   0.03026 |
-#> |.....................|    0.8209 |   0.06979 |    0.7229 |    0.6325 |
-#> |.....................|     1.466 |    0.9660 |    0.7566 |     1.812 |
-#> |  104|     467.53566 |     1.009 |    -1.902 |   -0.9117 |   -0.7577 |
-#> |.....................|   -0.9793 |    -1.516 |     1.778 |    -1.859 |
-#> |.....................|   -0.8880 |   -0.4790 |   -0.8835 |    -1.168 |
-#> |.....................|   -0.6194 |   -0.8545 |   -0.9947 |   -0.3959 |
-#> |    U|     467.53566 |     91.86 |    -6.102 |   -0.8912 |    -2.020 |
-#> |.....................|    -4.592 |    0.1685 |     1.931 |   0.02992 |
-#> |.....................|    0.8245 |   0.06994 |    0.7261 |    0.6369 |
-#> |.....................|     1.477 |    0.9722 |    0.7591 |     1.786 |
-#> |    X|     467.53566 |     91.86 |  0.002239 |    0.2909 |    0.1326 |
-#> |.....................|   0.01013 |    0.5420 |     1.931 |   0.02992 |
-#> |.....................|    0.8245 |   0.06994 |    0.7261 |    0.6369 |
-#> |.....................|     1.477 |    0.9722 |    0.7591 |     1.786 |
-#> |  105|     467.26444 |     1.016 |    -1.902 |   -0.9109 |   -0.7577 |
-#> |.....................|   -0.9795 |    -1.516 |     1.777 |    -1.860 |
-#> |.....................|   -0.8875 |   -0.4788 |   -0.8828 |    -1.169 |
-#> |.....................|   -0.6198 |   -0.8544 |   -0.9951 |   -0.3961 |
-#> |    U|     467.26444 |     92.48 |    -6.102 |   -0.8905 |    -2.020 |
-#> |.....................|    -4.592 |    0.1683 |     1.931 |   0.02990 |
-#> |.....................|    0.8246 |   0.06995 |    0.7266 |    0.6360 |
-#> |.....................|     1.476 |    0.9723 |    0.7588 |     1.786 |
-#> |    X|     467.26444 |     92.48 |  0.002239 |    0.2910 |    0.1326 |
-#> |.....................|   0.01013 |    0.5420 |     1.931 |   0.02990 |
-#> |.....................|    0.8246 |   0.06995 |    0.7266 |    0.6360 |
-#> |.....................|     1.476 |    0.9723 |    0.7588 |     1.786 |
-#> |    F| Forward Diff. |    -1.458 |   0.09189 |     2.450 |    0.1713 |
-#> |.....................|   -0.5320 |    -1.492 |    -1.346 |    -2.030 |
-#> |.....................|     1.374 |    0.8089 |     1.804 |    -5.854 |
-#> |.....................|    -1.303 |    0.2787 |    -1.170 |   -0.8602 |
-#> |  106|     467.25360 |     1.017 |    -1.902 |   -0.9116 |   -0.7577 |
-#> |.....................|   -0.9793 |    -1.516 |     1.778 |    -1.859 |
-#> |.....................|   -0.8879 |   -0.4790 |   -0.8833 |    -1.168 |
-#> |.....................|   -0.6195 |   -0.8545 |   -0.9948 |   -0.3959 |
-#> |    U|      467.2536 |     92.51 |    -6.102 |   -0.8910 |    -2.020 |
-#> |.....................|    -4.592 |    0.1685 |     1.931 |   0.02992 |
-#> |.....................|    0.8245 |   0.06994 |    0.7263 |    0.6374 |
-#> |.....................|     1.477 |    0.9722 |    0.7590 |     1.786 |
-#> |    X|      467.2536 |     92.51 |  0.002239 |    0.2909 |    0.1326 |
-#> |.....................|   0.01013 |    0.5420 |     1.931 |   0.02992 |
-#> |.....................|    0.8245 |   0.06994 |    0.7263 |    0.6374 |
-#> |.....................|     1.477 |    0.9722 |    0.7590 |     1.786 |
-#> |    F| Forward Diff. |     3.196 |   0.08873 |     2.446 |    0.1672 |
-#> |.....................|   -0.5342 |    -1.484 |    -1.056 |    -1.956 |
-#> |.....................|     1.373 |    0.7965 |     2.077 |    -5.722 |
-#> |.....................|    -1.292 |    0.2471 |    -1.040 |   -0.8496 |
-#> |  107|     467.24389 |     1.015 |    -1.902 |   -0.9128 |   -0.7578 |
-#> |.....................|   -0.9790 |    -1.515 |     1.778 |    -1.858 |
-#> |.....................|   -0.8886 |   -0.4794 |   -0.8844 |    -1.165 |
-#> |.....................|   -0.6188 |   -0.8546 |   -0.9942 |   -0.3955 |
-#> |    U|     467.24389 |     92.37 |    -6.102 |   -0.8922 |    -2.020 |
-#> |.....................|    -4.592 |    0.1688 |     1.931 |   0.02995 |
-#> |.....................|    0.8242 |   0.06993 |    0.7255 |    0.6400 |
-#> |.....................|     1.477 |    0.9721 |    0.7595 |     1.786 |
-#> |    X|     467.24389 |     92.37 |  0.002239 |    0.2907 |    0.1326 |
-#> |.....................|   0.01014 |    0.5421 |     1.931 |   0.02995 |
-#> |.....................|    0.8242 |   0.06993 |    0.7255 |    0.6400 |
-#> |.....................|     1.477 |    0.9721 |    0.7595 |     1.786 |
-#> |    F| Forward Diff. |    -15.43 |   0.07336 |     2.305 |    0.1893 |
-#> |.....................|   -0.5256 |    -1.495 |    -1.329 |    -2.142 |
-#> |.....................|     1.357 |    0.9382 |     1.940 |    -3.165 |
-#> |.....................|    -1.157 |    0.2760 |   -0.9277 |   -0.8566 |
-#> |  108|     467.22397 |     1.017 |    -1.902 |   -0.9138 |   -0.7581 |
-#> |.....................|   -0.9782 |    -1.514 |     1.778 |    -1.857 |
-#> |.....................|   -0.8889 |   -0.4797 |   -0.8863 |    -1.164 |
-#> |.....................|   -0.6190 |   -0.8552 |   -0.9945 |   -0.3935 |
-#> |    U|     467.22397 |     92.56 |    -6.102 |   -0.8930 |    -2.020 |
-#> |.....................|    -4.591 |    0.1692 |     1.931 |   0.02998 |
-#> |.....................|    0.8241 |   0.06992 |    0.7241 |    0.6409 |
-#> |.....................|     1.477 |    0.9715 |    0.7593 |     1.789 |
-#> |    X|     467.22397 |     92.56 |  0.002238 |    0.2905 |    0.1326 |
-#> |.....................|   0.01015 |    0.5422 |     1.931 |   0.02998 |
-#> |.....................|    0.8241 |   0.06992 |    0.7241 |    0.6409 |
-#> |.....................|     1.477 |    0.9715 |    0.7593 |     1.789 |
-#> |    F| Forward Diff. |     8.612 |   0.07601 |     2.377 |    0.1597 |
-#> |.....................|   -0.5308 |    -1.476 |    -1.038 |    -1.834 |
-#> |.....................|     1.332 |    0.7679 |     2.039 |    -3.039 |
-#> |.....................|    -1.288 |    0.2037 |    -1.093 |   -0.8313 |
-#> |  109|     467.20858 |     1.016 |    -1.903 |   -0.9153 |   -0.7584 |
-#> |.....................|   -0.9772 |    -1.513 |     1.777 |    -1.856 |
-#> |.....................|   -0.8896 |   -0.4802 |   -0.8882 |    -1.164 |
-#> |.....................|   -0.6194 |   -0.8560 |   -0.9946 |   -0.3915 |
-#> |    U|     467.20858 |     92.46 |    -6.103 |   -0.8944 |    -2.021 |
-#> |.....................|    -4.590 |    0.1698 |     1.931 |   0.03001 |
-#> |.....................|    0.8238 |   0.06990 |    0.7227 |    0.6411 |
-#> |.....................|     1.477 |    0.9707 |    0.7591 |     1.791 |
-#> |    X|     467.20858 |     92.46 |  0.002236 |    0.2902 |    0.1325 |
-#> |.....................|   0.01016 |    0.5423 |     1.931 |   0.03001 |
-#> |.....................|    0.8238 |   0.06990 |    0.7227 |    0.6411 |
-#> |.....................|     1.477 |    0.9707 |    0.7591 |     1.791 |
-#> |    F| Forward Diff. |    -3.651 |   0.07137 |     2.259 |    0.1744 |
-#> |.....................|   -0.5171 |    -1.486 |    -1.304 |    -1.934 |
-#> |.....................|     1.324 |    0.7910 |     1.690 |    -3.053 |
-#> |.....................|    -1.233 |    0.1999 |    -1.046 |   -0.8164 |
-#> |  110|     467.19548 |     1.017 |    -1.903 |   -0.9170 |   -0.7588 |
-#> |.....................|   -0.9762 |    -1.512 |     1.778 |    -1.855 |
-#> |.....................|   -0.8906 |   -0.4808 |   -0.8898 |    -1.163 |
-#> |.....................|   -0.6195 |   -0.8567 |   -0.9946 |   -0.3897 |
-#> |    U|     467.19548 |     92.56 |    -6.103 |   -0.8959 |    -2.021 |
-#> |.....................|    -4.589 |    0.1705 |     1.931 |   0.03005 |
-#> |.....................|    0.8234 |   0.06989 |    0.7215 |    0.6417 |
-#> |.....................|     1.477 |    0.9701 |    0.7592 |     1.793 |
-#> |    X|     467.19548 |     92.56 |  0.002235 |    0.2899 |    0.1325 |
-#> |.....................|   0.01017 |    0.5425 |     1.931 |   0.03005 |
-#> |.....................|    0.8234 |   0.06989 |    0.7215 |    0.6417 |
-#> |.....................|     1.477 |    0.9701 |    0.7592 |     1.793 |
-#> |    F| Forward Diff. |     9.695 |   0.07360 |     2.256 |    0.1610 |
-#> |.....................|   -0.5147 |    -1.467 |    -1.275 |    -1.734 |
-#> |.....................|     1.307 |    0.8740 |     2.039 |    -5.568 |
-#> |.....................|    -1.898 |   -0.2550 |    -1.273 |   -0.7762 |
-#> |  111|     467.17845 |     1.016 |    -1.904 |   -0.9175 |   -0.7593 |
-#> |.....................|   -0.9751 |    -1.510 |     1.777 |    -1.854 |
-#> |.....................|   -0.8907 |   -0.4813 |   -0.8918 |    -1.161 |
-#> |.....................|   -0.6194 |   -0.8571 |   -0.9949 |   -0.3876 |
-#> |    U|     467.17845 |     92.50 |    -6.104 |   -0.8963 |    -2.022 |
-#> |.....................|    -4.588 |    0.1711 |     1.930 |   0.03007 |
-#> |.....................|    0.8234 |   0.06987 |    0.7201 |    0.6433 |
-#> |.....................|     1.477 |    0.9697 |    0.7589 |     1.796 |
-#> |    X|     467.17845 |     92.50 |  0.002234 |    0.2898 |    0.1324 |
-#> |.....................|   0.01018 |    0.5427 |     1.930 |   0.03007 |
-#> |.....................|    0.8234 |   0.06987 |    0.7201 |    0.6433 |
-#> |.....................|     1.477 |    0.9697 |    0.7589 |     1.796 |
-#> |    F| Forward Diff. |     2.021 |   0.06308 |     2.194 |    0.1658 |
-#> |.....................|   -0.5050 |    -1.471 |    -1.283 |    -1.811 |
-#> |.....................|     1.304 |    0.7659 |     1.629 |    -2.860 |
-#> |.....................|    -1.234 |    0.1434 |    -1.025 |   -0.7796 |
-#> |  112|     467.16518 |     1.015 |    -1.904 |   -0.9192 |   -0.7596 |
-#> |.....................|   -0.9742 |    -1.509 |     1.777 |    -1.853 |
-#> |.....................|   -0.8917 |   -0.4819 |   -0.8931 |    -1.160 |
-#> |.....................|   -0.6190 |   -0.8574 |   -0.9946 |   -0.3864 |
-#> |    U|     467.16518 |     92.39 |    -6.104 |   -0.8978 |    -2.022 |
-#> |.....................|    -4.587 |    0.1719 |     1.931 |   0.03011 |
-#> |.....................|    0.8229 |   0.06985 |    0.7191 |    0.6447 |
-#> |.....................|     1.477 |    0.9694 |    0.7592 |     1.797 |
-#> |    X|     467.16518 |     92.39 |  0.002234 |    0.2895 |    0.1324 |
-#> |.....................|   0.01019 |    0.5429 |     1.931 |   0.03011 |
-#> |.....................|    0.8229 |   0.06985 |    0.7191 |    0.6447 |
-#> |.....................|     1.477 |    0.9694 |    0.7592 |     1.797 |
-#> |    F| Forward Diff. |    -11.15 |   0.05292 |     2.063 |    0.1800 |
-#> |.....................|   -0.4962 |    -1.473 |   -0.9311 |    -1.912 |
-#> |.....................|     1.287 |    0.8965 |     1.659 |    -5.399 |
-#> |.....................|    -1.766 |   -0.2649 |    -1.228 |   -0.7899 |
-#> |  113|     467.14275 |     1.016 |    -1.904 |   -0.9201 |   -0.7599 |
-#> |.....................|   -0.9736 |    -1.507 |     1.777 |    -1.851 |
-#> |.....................|   -0.8922 |   -0.4826 |   -0.8948 |    -1.157 |
-#> |.....................|   -0.6182 |   -0.8576 |   -0.9943 |   -0.3850 |
-#> |    U|     467.14275 |     92.43 |    -6.104 |   -0.8986 |    -2.022 |
-#> |.....................|    -4.586 |    0.1725 |     1.931 |   0.03014 |
-#> |.....................|    0.8227 |   0.06984 |    0.7179 |    0.6470 |
-#> |.....................|     1.478 |    0.9693 |    0.7594 |     1.799 |
-#> |    X|     467.14275 |     92.43 |  0.002233 |    0.2893 |    0.1324 |
-#> |.....................|   0.01019 |    0.5430 |     1.931 |   0.03014 |
-#> |.....................|    0.8227 |   0.06984 |    0.7179 |    0.6470 |
-#> |.....................|     1.478 |    0.9693 |    0.7594 |     1.799 |
-#> |    F| Forward Diff. |    -6.177 |   0.04590 |     2.051 |    0.1758 |
-#> |.....................|   -0.4936 |    -1.461 |   -0.9893 |    -1.828 |
-#> |.....................|     1.266 |    0.7615 |     1.545 |    -5.206 |
-#> |.....................|    -1.792 |   -0.2512 |    -1.220 |   -0.7551 |
-#> |  114|     467.10820 |     1.017 |    -1.905 |   -0.9220 |   -0.7605 |
-#> |.....................|   -0.9724 |    -1.505 |     1.777 |    -1.849 |
-#> |.....................|   -0.8932 |   -0.4835 |   -0.8976 |    -1.151 |
-#> |.....................|   -0.6164 |   -0.8576 |   -0.9935 |   -0.3828 |
-#> |    U|      467.1082 |     92.55 |    -6.105 |   -0.9003 |    -2.023 |
-#> |.....................|    -4.585 |    0.1737 |     1.930 |   0.03020 |
-#> |.....................|    0.8223 |   0.06981 |    0.7158 |    0.6522 |
-#> |.....................|     1.480 |    0.9692 |    0.7601 |     1.802 |
-#> |    X|      467.1082 |     92.55 |  0.002232 |    0.2890 |    0.1323 |
-#> |.....................|   0.01020 |    0.5433 |     1.930 |   0.03020 |
-#> |.....................|    0.8223 |   0.06981 |    0.7158 |    0.6522 |
-#> |.....................|     1.480 |    0.9692 |    0.7601 |     1.802 |
-#> |    F| Forward Diff. |     8.449 |   0.03092 |     2.044 |    0.1611 |
-#> |.....................|   -0.4934 |    -1.430 |    -1.221 |    -1.596 |
-#> |.....................|     1.229 |    0.8691 |     1.875 |    -2.123 |
-#> |.....................|    -1.605 |   -0.2558 |    -1.009 |   -0.7122 |
-#> |  115|     467.10106 |     1.014 |    -1.905 |   -0.9236 |   -0.7611 |
-#> |.....................|   -0.9712 |    -1.502 |     1.777 |    -1.847 |
-#> |.....................|   -0.8940 |   -0.4849 |   -0.9012 |    -1.147 |
-#> |.....................|   -0.6148 |   -0.8578 |   -0.9928 |   -0.3803 |
-#> |    U|     467.10106 |     92.28 |    -6.105 |   -0.9017 |    -2.023 |
-#> |.....................|    -4.584 |    0.1749 |     1.930 |   0.03026 |
-#> |.....................|    0.8220 |   0.06977 |    0.7132 |    0.6562 |
-#> |.....................|     1.482 |    0.9690 |    0.7607 |     1.805 |
-#> |    X|     467.10106 |     92.28 |  0.002232 |    0.2887 |    0.1322 |
-#> |.....................|   0.01022 |    0.5436 |     1.930 |   0.03026 |
-#> |.....................|    0.8220 |   0.06977 |    0.7132 |    0.6562 |
-#> |.....................|     1.482 |    0.9690 |    0.7607 |     1.805 |
-#> |    F| Forward Diff. |    -24.17 |  0.001665 |     1.814 |    0.1960 |
-#> |.....................|   -0.4738 |    -1.444 |   -0.8955 |    -1.908 |
-#> |.....................|     1.221 |    0.7910 |     1.755 |    -3.560 |
-#> |.....................|    -2.244 |   -0.2675 |   -0.8607 |   -0.7175 |
-#> |  116|     467.04630 |     1.016 |    -1.905 |   -0.9246 |   -0.7619 |
-#> |.....................|   -0.9696 |    -1.499 |     1.777 |    -1.845 |
-#> |.....................|   -0.8944 |   -0.4866 |   -0.9055 |    -1.143 |
-#> |.....................|   -0.6133 |   -0.8582 |   -0.9923 |   -0.3775 |
-#> |    U|      467.0463 |     92.45 |    -6.105 |   -0.9026 |    -2.024 |
-#> |.....................|    -4.582 |    0.1762 |     1.930 |   0.03032 |
-#> |.....................|    0.8218 |   0.06972 |    0.7101 |    0.6601 |
-#> |.....................|     1.484 |    0.9686 |    0.7611 |     1.808 |
-#> |    X|      467.0463 |     92.45 |  0.002231 |    0.2885 |    0.1321 |
-#> |.....................|   0.01023 |    0.5439 |     1.930 |   0.03032 |
-#> |.....................|    0.8218 |   0.06972 |    0.7101 |    0.6601 |
-#> |.....................|     1.484 |    0.9686 |    0.7611 |     1.808 |
-#> |    F| Forward Diff. |    -2.647 | -0.007887 |     1.876 |    0.1719 |
-#> |.....................|   -0.4730 |    -1.410 |   -0.8701 |    -1.589 |
-#> |.....................|     1.184 |    0.7244 |     1.544 |    -4.110 |
-#> |.....................|    -1.544 |   -0.3120 |   -0.9430 |   -0.6527 |
-#> |  117|     467.02543 |     1.017 |    -1.906 |   -0.9263 |   -0.7625 |
-#> |.....................|   -0.9684 |    -1.497 |     1.777 |    -1.843 |
-#> |.....................|   -0.8954 |   -0.4879 |   -0.9089 |    -1.137 |
-#> |.....................|   -0.6116 |   -0.8583 |   -0.9915 |   -0.3753 |
-#> |    U|     467.02543 |     92.58 |    -6.106 |   -0.9041 |    -2.025 |
-#> |.....................|    -4.581 |    0.1775 |     1.930 |   0.03038 |
-#> |.....................|    0.8214 |   0.06968 |    0.7076 |    0.6649 |
-#> |.....................|     1.486 |    0.9686 |    0.7618 |     1.811 |
-#> |    X|     467.02543 |     92.58 |  0.002230 |    0.2882 |    0.1320 |
-#> |.....................|   0.01025 |    0.5443 |     1.930 |   0.03038 |
-#> |.....................|    0.8214 |   0.06968 |    0.7076 |    0.6649 |
-#> |.....................|     1.486 |    0.9686 |    0.7618 |     1.811 |
-#> |    F| Forward Diff. |     12.94 |  -0.02385 |     1.879 |    0.1542 |
-#> |.....................|   -0.4735 |    -1.378 |   -0.8918 |    -1.355 |
-#> |.....................|     1.131 |    0.6590 |     1.631 |    -3.618 |
-#> |.....................|    -1.430 |   -0.2321 |   -0.8462 |   -0.6495 |
-#> |  118|     466.99646 |     1.016 |    -1.906 |   -0.9273 |   -0.7632 |
-#> |.....................|   -0.9670 |    -1.494 |     1.776 |    -1.841 |
-#> |.....................|   -0.8958 |   -0.4892 |   -0.9132 |    -1.133 |
-#> |.....................|   -0.6101 |   -0.8587 |   -0.9911 |   -0.3725 |
-#> |    U|     466.99646 |     92.42 |    -6.106 |   -0.9050 |    -2.026 |
-#> |.....................|    -4.579 |    0.1788 |     1.930 |   0.03043 |
-#> |.....................|    0.8212 |   0.06964 |    0.7044 |    0.6690 |
-#> |.....................|     1.488 |    0.9682 |    0.7622 |     1.814 |
-#> |    X|     466.99646 |     92.42 |  0.002230 |    0.2880 |    0.1319 |
-#> |.....................|   0.01026 |    0.5446 |     1.930 |   0.03043 |
-#> |.....................|    0.8212 |   0.06964 |    0.7044 |    0.6690 |
-#> |.....................|     1.488 |    0.9682 |    0.7622 |     1.814 |
-#> |    F| Forward Diff. |    -5.590 |  -0.05004 |     1.738 |    0.1737 |
-#> |.....................|   -0.4573 |    -1.378 |   -0.8791 |    -1.534 |
-#> |.....................|     1.117 |    0.8064 |     1.528 |    -3.141 |
-#> |.....................|   -0.8220 |    0.1296 |   -0.3838 |   -0.6246 |
-#> |  119|     466.97639 |     1.017 |    -1.906 |   -0.9282 |   -0.7640 |
-#> |.....................|   -0.9655 |    -1.490 |     1.776 |    -1.839 |
-#> |.....................|   -0.8964 |   -0.4910 |   -0.9175 |    -1.129 |
-#> |.....................|   -0.6092 |   -0.8593 |   -0.9910 |   -0.3693 |
-#> |    U|     466.97639 |     92.52 |    -6.106 |   -0.9059 |    -2.026 |
-#> |.....................|    -4.578 |    0.1803 |     1.930 |   0.03049 |
-#> |.....................|    0.8210 |   0.06959 |    0.7013 |    0.6726 |
-#> |.....................|     1.489 |    0.9676 |    0.7623 |     1.818 |
-#> |    X|     466.97639 |     92.52 |  0.002230 |    0.2878 |    0.1318 |
-#> |.....................|   0.01028 |    0.5450 |     1.930 |   0.03049 |
-#> |.....................|    0.8210 |   0.06959 |    0.7013 |    0.6726 |
-#> |.....................|     1.489 |    0.9676 |    0.7623 |     1.818 |
-#> |    F| Forward Diff. |     7.027 |  -0.06281 |     1.755 |    0.1604 |
-#> |.....................|   -0.4507 |    -1.349 |   -0.8053 |    -1.299 |
-#> |.....................|     1.095 |    0.6623 |     1.032 |    -2.794 |
-#> |.....................|   -0.8171 |   0.07286 |   -0.3538 |   -0.5889 |
-#> |  120|     466.96001 |     1.015 |    -1.906 |   -0.9299 |   -0.7649 |
-#> |.....................|   -0.9637 |    -1.486 |     1.775 |    -1.837 |
-#> |.....................|   -0.8976 |   -0.4931 |   -0.9192 |    -1.125 |
-#> |.....................|   -0.6091 |   -0.8600 |   -0.9916 |   -0.3657 |
-#> |    U|     466.96001 |     92.40 |    -6.106 |   -0.9074 |    -2.027 |
-#> |.....................|    -4.576 |    0.1824 |     1.930 |   0.03055 |
-#> |.....................|    0.8205 |   0.06953 |    0.7000 |    0.6758 |
-#> |.....................|     1.489 |    0.9669 |    0.7618 |     1.823 |
-#> |    X|     466.96001 |     92.40 |  0.002230 |    0.2875 |    0.1317 |
-#> |.....................|   0.01029 |    0.5455 |     1.930 |   0.03055 |
-#> |.....................|    0.8205 |   0.06953 |    0.7000 |    0.6758 |
-#> |.....................|     1.489 |    0.9669 |    0.7618 |     1.823 |
-#> |    F| Forward Diff. |    -7.315 |  -0.08361 |     1.595 |    0.1755 |
-#> |.....................|   -0.4289 |    -1.331 |   -0.8104 |    -1.428 |
-#> |.....................|     1.055 |    0.7710 |     1.242 |    -2.826 |
-#> |.....................|    -1.346 |   -0.3282 |   -0.6399 |   -0.5709 |
-#> |  121|     466.94053 |     1.016 |    -1.905 |   -0.9315 |   -0.7662 |
-#> |.....................|   -0.9617 |    -1.480 |     1.774 |    -1.835 |
-#> |.....................|   -0.8987 |   -0.4954 |   -0.9193 |    -1.121 |
-#> |.....................|   -0.6079 |   -0.8601 |   -0.9919 |   -0.3632 |
-#> |    U|     466.94053 |     92.48 |    -6.105 |   -0.9088 |    -2.029 |
-#> |.....................|    -4.574 |    0.1849 |     1.929 |   0.03061 |
-#> |.....................|    0.8200 |   0.06946 |    0.6999 |    0.6792 |
-#> |.....................|     1.490 |    0.9668 |    0.7615 |     1.826 |
-#> |    X|     466.94053 |     92.48 |  0.002231 |    0.2873 |    0.1315 |
-#> |.....................|   0.01031 |    0.5461 |     1.929 |   0.03061 |
-#> |.....................|    0.8200 |   0.06946 |    0.6999 |    0.6792 |
-#> |.....................|     1.490 |    0.9668 |    0.7615 |     1.826 |
-#> |    F| Forward Diff. |     2.448 |  -0.09452 |     1.578 |    0.1631 |
-#> |.....................|   -0.4178 |    -1.275 |   -0.7880 |    -1.291 |
-#> |.....................|     1.013 |    0.7275 |     1.336 |   -0.1176 |
-#> |.....................|    -1.297 |   -0.2757 |   -0.6338 |   -0.5586 |
-#> |  122|     466.92529 |     1.015 |    -1.905 |   -0.9321 |   -0.7676 |
-#> |.....................|   -0.9593 |    -1.476 |     1.775 |    -1.833 |
-#> |.....................|   -0.8992 |   -0.4984 |   -0.9232 |    -1.122 |
-#> |.....................|   -0.6063 |   -0.8604 |   -0.9916 |   -0.3612 |
-#> |    U|     466.92529 |     92.34 |    -6.105 |   -0.9093 |    -2.030 |
-#> |.....................|    -4.572 |    0.1871 |     1.930 |   0.03066 |
-#> |.....................|    0.8198 |   0.06938 |    0.6971 |    0.6791 |
-#> |.....................|     1.492 |    0.9666 |    0.7618 |     1.828 |
-#> |    X|     466.92529 |     92.34 |  0.002233 |    0.2871 |    0.1313 |
-#> |.....................|   0.01034 |    0.5466 |     1.930 |   0.03066 |
-#> |.....................|    0.8198 |   0.06938 |    0.6971 |    0.6791 |
-#> |.....................|     1.492 |    0.9666 |    0.7618 |     1.828 |
-#> |    F| Forward Diff. |    -12.72 |  -0.09950 |     1.479 |    0.1754 |
-#> |.....................|   -0.4012 |    -1.242 |   -0.7866 |    -1.413 |
-#> |.....................|    0.9668 |    0.6187 |    0.9349 |    -2.630 |
-#> |.....................|    -1.260 |   -0.3489 |   -0.4063 |   -0.5476 |
-#> |  123|     466.89942 |     1.016 |    -1.904 |   -0.9326 |   -0.7693 |
-#> |.....................|   -0.9564 |    -1.470 |     1.775 |    -1.832 |
-#> |.....................|   -0.8995 |   -0.5006 |   -0.9260 |    -1.122 |
-#> |.....................|   -0.6055 |   -0.8609 |   -0.9921 |   -0.3587 |
-#> |    U|     466.89942 |     92.48 |    -6.104 |   -0.9097 |    -2.032 |
-#> |.....................|    -4.569 |    0.1897 |     1.929 |   0.03069 |
-#> |.....................|    0.8197 |   0.06931 |    0.6950 |    0.6788 |
-#> |.....................|     1.493 |    0.9661 |    0.7614 |     1.831 |
-#> |    X|     466.89942 |     92.48 |  0.002235 |    0.2871 |    0.1311 |
-#> |.....................|   0.01037 |    0.5473 |     1.929 |   0.03069 |
-#> |.....................|    0.8197 |   0.06931 |    0.6950 |    0.6788 |
-#> |.....................|     1.493 |    0.9661 |    0.7614 |     1.831 |
-#> |    F| Forward Diff. |     3.439 |  -0.09008 |     1.544 |    0.1555 |
-#> |.....................|   -0.3845 |    -1.174 |   -0.7709 |    -1.201 |
-#> |.....................|    0.9305 |    0.6799 |     1.153 |    -2.871 |
-#> |.....................|    -1.766 |   -0.2963 |   -0.5389 |   -0.5305 |
-#> |  124|     466.87885 |     1.016 |    -1.902 |   -0.9335 |   -0.7713 |
-#> |.....................|   -0.9544 |    -1.465 |     1.775 |    -1.831 |
-#> |.....................|   -0.8988 |   -0.5028 |   -0.9291 |    -1.120 |
-#> |.....................|   -0.6025 |   -0.8609 |   -0.9918 |   -0.3573 |
-#> |    U|     466.87885 |     92.42 |    -6.102 |   -0.9106 |    -2.034 |
-#> |.....................|    -4.567 |    0.1922 |     1.930 |   0.03072 |
-#> |.....................|    0.8200 |   0.06925 |    0.6928 |    0.6803 |
-#> |.....................|     1.497 |    0.9661 |    0.7616 |     1.833 |
-#> |    X|     466.87885 |     92.42 |  0.002239 |    0.2869 |    0.1309 |
-#> |.....................|   0.01039 |    0.5479 |     1.930 |   0.03072 |
-#> |.....................|    0.8200 |   0.06925 |    0.6928 |    0.6803 |
-#> |.....................|     1.497 |    0.9661 |    0.7616 |     1.833 |
-#> |    F| Forward Diff. |    -3.274 |  -0.09794 |     1.477 |    0.1445 |
-#> |.....................|   -0.3711 |    -1.126 |   -0.7697 |    -1.253 |
-#> |.....................|    0.9213 |    0.5797 |    0.6929 |    -2.254 |
-#> |.....................|   -0.4364 |   0.05549 |  -0.07007 |   -0.5105 |
-#> |  125|     466.87374 |     1.017 |    -1.901 |   -0.9363 |   -0.7725 |
-#> |.....................|   -0.9523 |    -1.459 |     1.775 |    -1.829 |
-#> |.....................|   -0.9004 |   -0.5050 |   -0.9284 |    -1.119 |
-#> |.....................|   -0.6029 |   -0.8616 |   -0.9930 |   -0.3542 |
-#> |    U|     466.87374 |     92.57 |    -6.101 |   -0.9131 |    -2.035 |
-#> |.....................|    -4.565 |    0.1945 |     1.929 |   0.03078 |
-#> |.....................|    0.8193 |   0.06919 |    0.6933 |    0.6817 |
-#> |.....................|     1.496 |    0.9655 |    0.7605 |     1.836 |
-#> |    X|     466.87374 |     92.57 |  0.002241 |    0.2864 |    0.1307 |
-#> |.....................|   0.01041 |    0.5485 |     1.929 |   0.03078 |
-#> |.....................|    0.8193 |   0.06919 |    0.6933 |    0.6817 |
-#> |.....................|     1.496 |    0.9655 |    0.7605 |     1.836 |
-#> |    F| Forward Diff. |     13.60 |  -0.09484 |     1.445 |    0.1251 |
-#> |.....................|   -0.3584 |    -1.070 |   -0.7354 |    -1.048 |
-#> |.....................|    0.8551 |    0.6144 |    0.8824 | -0.009520 |
-#> |.....................|   -0.4410 |   0.04024 |   -0.2274 |   -0.5153 |
-#> |  126|     466.85547 |     1.016 |    -1.900 |   -0.9388 |   -0.7737 |
-#> |.....................|   -0.9500 |    -1.454 |     1.774 |    -1.828 |
-#> |.....................|   -0.9020 |   -0.5070 |   -0.9271 |    -1.119 |
-#> |.....................|   -0.6040 |   -0.8622 |   -0.9946 |   -0.3509 |
-#> |    U|     466.85547 |     92.42 |    -6.100 |   -0.9152 |    -2.036 |
-#> |.....................|    -4.562 |    0.1970 |     1.929 |   0.03083 |
-#> |.....................|    0.8186 |   0.06913 |    0.6942 |    0.6818 |
-#> |.....................|     1.495 |    0.9648 |    0.7592 |     1.841 |
-#> |    X|     466.85547 |     92.42 |  0.002243 |    0.2859 |    0.1305 |
-#> |.....................|   0.01044 |    0.5491 |     1.929 |   0.03083 |
-#> |.....................|    0.8186 |   0.06913 |    0.6942 |    0.6818 |
-#> |.....................|     1.495 |    0.9648 |    0.7592 |     1.841 |
-#> |    F| Forward Diff. |    -2.539 |  -0.09755 |     1.262 |    0.1433 |
-#> |.....................|   -0.3291 |    -1.038 |   -0.7482 |    -1.225 |
-#> |.....................|    0.8087 |    0.5023 |    0.8171 | -0.005344 |
-#> |.....................|   -0.4685 |   0.01356 |   -0.1499 |   -0.5112 |
-#> |  127|     466.84409 |     1.016 |    -1.899 |   -0.9408 |   -0.7751 |
-#> |.....................|   -0.9477 |    -1.449 |     1.774 |    -1.826 |
-#> |.....................|   -0.9037 |   -0.5088 |   -0.9269 |    -1.119 |
-#> |.....................|   -0.6048 |   -0.8630 |   -0.9960 |   -0.3473 |
-#> |    U|     466.84409 |     92.47 |    -6.099 |   -0.9171 |    -2.037 |
-#> |.....................|    -4.560 |    0.1996 |     1.929 |   0.03088 |
-#> |.....................|    0.8179 |   0.06907 |    0.6944 |    0.6816 |
-#> |.....................|     1.494 |    0.9641 |    0.7580 |     1.845 |
-#> |    X|     466.84409 |     92.47 |  0.002245 |    0.2856 |    0.1304 |
-#> |.....................|   0.01046 |    0.5497 |     1.929 |   0.03088 |
-#> |.....................|    0.8179 |   0.06907 |    0.6944 |    0.6816 |
-#> |.....................|     1.494 |    0.9641 |    0.7580 |     1.845 |
-#> |    F| Forward Diff. |     3.205 |  -0.09489 |     1.201 |    0.1289 |
-#> |.....................|   -0.3142 |   -0.9889 |   -0.7667 |    -1.156 |
-#> |.....................|    0.7401 |    0.5570 |     1.301 |    -1.479 |
-#> |.....................|    -1.860 |   -0.4540 |   -0.5722 |   -0.5005 |
-#> |  128|     466.83069 |     1.016 |    -1.897 |   -0.9405 |   -0.7762 |
-#> |.....................|   -0.9462 |    -1.443 |     1.775 |    -1.825 |
-#> |.....................|   -0.9047 |   -0.5101 |   -0.9307 |    -1.119 |
-#> |.....................|   -0.6046 |   -0.8636 |   -0.9969 |   -0.3435 |
-#> |    U|     466.83069 |     92.41 |    -6.097 |   -0.9168 |    -2.039 |
-#> |.....................|    -4.559 |    0.2019 |     1.929 |   0.03091 |
-#> |.....................|    0.8175 |   0.06904 |    0.6917 |    0.6819 |
-#> |.....................|     1.494 |    0.9635 |    0.7572 |     1.850 |
-#> |    X|     466.83069 |     92.41 |  0.002250 |    0.2856 |    0.1302 |
-#> |.....................|   0.01048 |    0.5503 |     1.929 |   0.03091 |
-#> |.....................|    0.8175 |   0.06904 |    0.6917 |    0.6819 |
-#> |.....................|     1.494 |    0.9635 |    0.7572 |     1.850 |
-#> |  129|     466.81923 |     1.016 |    -1.894 |   -0.9398 |   -0.7773 |
-#> |.....................|   -0.9447 |    -1.438 |     1.775 |    -1.824 |
-#> |.....................|   -0.9056 |   -0.5113 |   -0.9343 |    -1.119 |
-#> |.....................|   -0.6049 |   -0.8643 |   -0.9979 |   -0.3395 |
-#> |    U|     466.81923 |     92.43 |    -6.094 |   -0.9162 |    -2.040 |
-#> |.....................|    -4.557 |    0.2043 |     1.930 |   0.03094 |
-#> |.....................|    0.8171 |   0.06900 |    0.6890 |    0.6818 |
-#> |.....................|     1.494 |    0.9628 |    0.7563 |     1.854 |
-#> |    X|     466.81923 |     92.43 |  0.002255 |    0.2857 |    0.1301 |
-#> |.....................|   0.01049 |    0.5509 |     1.930 |   0.03094 |
-#> |.....................|    0.8171 |   0.06900 |    0.6890 |    0.6818 |
-#> |.....................|     1.494 |    0.9628 |    0.7563 |     1.854 |
-#> |  130|     466.78977 |     1.016 |    -1.887 |   -0.9376 |   -0.7810 |
-#> |.....................|   -0.9400 |    -1.422 |     1.776 |    -1.820 |
-#> |.....................|   -0.9086 |   -0.5153 |   -0.9461 |    -1.119 |
-#> |.....................|   -0.6057 |   -0.8666 |    -1.001 |   -0.3266 |
-#> |    U|     466.78977 |     92.47 |    -6.087 |   -0.9142 |    -2.043 |
-#> |.....................|    -4.552 |    0.2120 |     1.930 |   0.03105 |
-#> |.....................|    0.8159 |   0.06889 |    0.6804 |    0.6815 |
-#> |.....................|     1.493 |    0.9606 |    0.7533 |     1.870 |
-#> |    X|     466.78977 |     92.47 |  0.002272 |    0.2861 |    0.1296 |
-#> |.....................|   0.01054 |    0.5528 |     1.930 |   0.03105 |
-#> |.....................|    0.8159 |   0.06889 |    0.6804 |    0.6815 |
-#> |.....................|     1.493 |    0.9606 |    0.7533 |     1.870 |
-#> |  131|     466.76586 |     1.017 |    -1.875 |   -0.9340 |   -0.7871 |
-#> |.....................|   -0.9321 |    -1.394 |     1.779 |    -1.814 |
-#> |.....................|   -0.9134 |   -0.5218 |   -0.9656 |    -1.119 |
-#> |.....................|   -0.6071 |   -0.8705 |    -1.007 |   -0.3052 |
-#> |    U|     466.76586 |     92.53 |    -6.075 |   -0.9110 |    -2.049 |
-#> |.....................|    -4.545 |    0.2247 |     1.931 |   0.03121 |
-#> |.....................|    0.8139 |   0.06870 |    0.6661 |    0.6811 |
-#> |.....................|     1.491 |    0.9569 |    0.7485 |     1.896 |
-#> |    X|     466.76586 |     92.53 |  0.002300 |    0.2868 |    0.1288 |
-#> |.....................|   0.01062 |    0.5559 |     1.931 |   0.03121 |
-#> |.....................|    0.8139 |   0.06870 |    0.6661 |    0.6811 |
-#> |.....................|     1.491 |    0.9569 |    0.7485 |     1.896 |
-#> |    F| Forward Diff. |     10.71 |  -0.05605 |     1.440 |   0.09508 |
-#> |.....................|   -0.1459 |   -0.5070 |   -0.9907 |   -0.8007 |
-#> |.....................|    0.4069 |    0.2923 |   0.01818 |    -1.553 |
-#> |.....................|    -1.109 |   -0.3306 |   -0.3991 |   -0.2309 |
-#> |  132|     466.72646 |     1.014 |    -1.848 |   -0.9815 |   -0.8092 |
-#> |.....................|   -0.9160 |    -1.342 |     1.783 |    -1.808 |
-#> |.....................|   -0.9032 |   -0.5322 |   -0.9570 |    -1.117 |
-#> |.....................|   -0.6032 |   -0.8748 |    -1.022 |   -0.2748 |
-#> |    U|     466.72646 |     92.30 |    -6.048 |   -0.9533 |    -2.072 |
-#> |.....................|    -4.528 |    0.2483 |     1.933 |   0.03140 |
-#> |.....................|    0.8182 |   0.06840 |    0.6724 |    0.6828 |
-#> |.....................|     1.496 |    0.9528 |    0.7357 |     1.933 |
-#> |    X|     466.72646 |     92.30 |  0.002362 |    0.2782 |    0.1260 |
-#> |.....................|   0.01080 |    0.5618 |     1.933 |   0.03140 |
-#> |.....................|    0.8182 |   0.06840 |    0.6724 |    0.6828 |
-#> |.....................|     1.496 |    0.9528 |    0.7357 |     1.933 |
-#> |    F| Forward Diff. |    -13.11 |  -0.01237 |   -0.5306 |  0.001870 |
-#> |.....................|   0.01074 | -0.001553 |   -0.5011 |    -1.124 |
-#> |.....................|    0.5240 |    0.3999 |    0.1337 |    0.6209 |
-#> |.....................|   -0.3667 |   -0.5464 |   -0.9326 |   -0.1861 |
-#> |  133|     466.72714 |     1.014 |    -1.830 |   -0.9704 |   -0.8250 |
-#> |.....................|   -0.9153 |    -1.342 |     1.791 |    -1.785 |
-#> |.....................|   -0.9449 |   -0.5943 |   -0.9266 |    -1.116 |
-#> |.....................|   -0.5962 |   -0.8737 |    -1.020 |   -0.2698 |
-#> |    U|     466.72714 |     92.32 |    -6.030 |   -0.9434 |    -2.087 |
-#> |.....................|    -4.528 |    0.2486 |     1.936 |   0.03205 |
-#> |.....................|    0.8009 |   0.06660 |    0.6946 |    0.6846 |
-#> |.....................|     1.504 |    0.9539 |    0.7372 |     1.939 |
-#> |    X|     466.72714 |     92.32 |  0.002405 |    0.2802 |    0.1240 |
-#> |.....................|   0.01081 |    0.5618 |     1.936 |   0.03205 |
-#> |.....................|    0.8009 |   0.06660 |    0.6946 |    0.6846 |
-#> |.....................|     1.504 |    0.9539 |    0.7372 |     1.939 |
-#> |  134|     466.69721 |     1.015 |    -1.839 |   -0.9760 |   -0.8170 |
-#> |.....................|   -0.9156 |    -1.342 |     1.787 |    -1.797 |
-#> |.....................|   -0.9238 |   -0.5630 |   -0.9420 |    -1.117 |
-#> |.....................|   -0.5997 |   -0.8742 |    -1.021 |   -0.2723 |
-#> |    U|     466.69721 |     92.41 |    -6.039 |   -0.9484 |    -2.079 |
-#> |.....................|    -4.528 |    0.2485 |     1.935 |   0.03173 |
-#> |.....................|    0.8096 |   0.06750 |    0.6834 |    0.6836 |
-#> |.....................|     1.500 |    0.9534 |    0.7365 |     1.936 |
-#> |    X|     466.69721 |     92.41 |  0.002383 |    0.2792 |    0.1250 |
-#> |.....................|   0.01080 |    0.5618 |     1.935 |   0.03173 |
-#> |.....................|    0.8096 |   0.06750 |    0.6834 |    0.6836 |
-#> |.....................|     1.500 |    0.9534 |    0.7365 |     1.936 |
-#> |    F| Forward Diff. |    0.5723 |  0.006769 |   -0.2879 |  -0.06332 |
-#> |.....................|   0.01114 |  -0.03155 |   -0.3915 |   -0.7923 |
-#> |.....................|   -0.3201 |   -0.2330 |    0.8086 |    -1.424 |
-#> |.....................|   -0.3663 |   -0.4815 |   -0.7933 |   -0.2384 |
-#> |  135|     466.73286 |     1.017 |    -1.834 |   -0.9731 |   -0.8131 |
-#> |.....................|   -0.9227 |    -1.351 |     1.796 |    -1.779 |
-#> |.....................|   -0.9201 |   -0.5595 |   -0.9572 |    -1.109 |
-#> |.....................|   -0.6142 |   -0.8686 |    -1.016 |   -0.2440 |
-#> |    U|     466.73286 |     92.54 |    -6.034 |   -0.9458 |    -2.075 |
-#> |.....................|    -4.535 |    0.2444 |     1.938 |   0.03223 |
-#> |.....................|    0.8111 |   0.06760 |    0.6723 |    0.6901 |
-#> |.....................|     1.483 |    0.9587 |    0.7409 |     1.970 |
-#> |    X|     466.73286 |     92.54 |  0.002396 |    0.2797 |    0.1255 |
-#> |.....................|   0.01072 |    0.5608 |     1.938 |   0.03223 |
-#> |.....................|    0.8111 |   0.06760 |    0.6723 |    0.6901 |
-#> |.....................|     1.483 |    0.9587 |    0.7409 |     1.970 |
-#> |  136|     466.69733 |     1.015 |    -1.838 |   -0.9750 |   -0.8159 |
-#> |.....................|   -0.9176 |    -1.345 |     1.790 |    -1.791 |
-#> |.....................|   -0.9226 |   -0.5619 |   -0.9467 |    -1.114 |
-#> |.....................|   -0.6033 |   -0.8723 |    -1.019 |   -0.2644 |
-#> |    U|     466.69733 |     92.40 |    -6.038 |   -0.9475 |    -2.078 |
-#> |.....................|    -4.530 |    0.2474 |     1.936 |   0.03188 |
-#> |.....................|    0.8101 |   0.06754 |    0.6799 |    0.6863 |
-#> |.....................|     1.496 |    0.9552 |    0.7382 |     1.945 |
-#> |    X|     466.69733 |     92.40 |  0.002386 |    0.2794 |    0.1251 |
-#> |.....................|   0.01078 |    0.5615 |     1.936 |   0.03188 |
-#> |.....................|    0.8101 |   0.06754 |    0.6799 |    0.6863 |
-#> |.....................|     1.496 |    0.9552 |    0.7382 |     1.945 |
-#> |  137|     466.69584 |     1.015 |    -1.839 |   -0.9754 |   -0.8165 |
-#> |.....................|   -0.9164 |    -1.343 |     1.788 |    -1.794 |
-#> |.....................|   -0.9231 |   -0.5623 |   -0.9445 |    -1.114 |
-#> |.....................|   -0.6009 |   -0.8731 |    -1.020 |   -0.2689 |
-#> |    U|     466.69584 |     92.37 |    -6.039 |   -0.9478 |    -2.079 |
-#> |.....................|    -4.529 |    0.2480 |     1.935 |   0.03180 |
-#> |.....................|    0.8099 |   0.06752 |    0.6815 |    0.6857 |
-#> |.....................|     1.499 |    0.9544 |    0.7377 |     1.940 |
-#> |    X|     466.69584 |     92.37 |  0.002384 |    0.2793 |    0.1251 |
-#> |.....................|   0.01079 |    0.5617 |     1.935 |   0.03180 |
-#> |.....................|    0.8099 |   0.06752 |    0.6815 |    0.6857 |
-#> |.....................|     1.499 |    0.9544 |    0.7377 |     1.940 |
-#> |    F| Forward Diff. |    -3.069 | -0.001275 |   -0.2861 |  -0.04975 |
-#> |.....................|   0.01387 |  -0.05203 |   -0.3437 |   -0.7173 |
-#> |.....................|   -0.2694 |   -0.1778 |    0.5026 |    0.8511 |
-#> |.....................|   -0.9213 |   -0.7376 |   -0.9765 |   -0.1682 |
-#> |  138|     466.68962 |     1.016 |    -1.839 |   -0.9764 |   -0.8159 |
-#> |.....................|   -0.9167 |    -1.342 |     1.790 |    -1.793 |
-#> |.....................|   -0.9191 |   -0.5597 |   -0.9461 |    -1.115 |
-#> |.....................|   -0.6002 |   -0.8712 |    -1.018 |   -0.2680 |
-#> |    U|     466.68962 |     92.46 |    -6.039 |   -0.9488 |    -2.078 |
-#> |.....................|    -4.529 |    0.2485 |     1.936 |   0.03184 |
-#> |.....................|    0.8115 |   0.06760 |    0.6803 |    0.6854 |
-#> |.....................|     1.499 |    0.9562 |    0.7392 |     1.941 |
-#> |    X|     466.68962 |     92.46 |  0.002385 |    0.2791 |    0.1251 |
-#> |.....................|   0.01079 |    0.5618 |     1.936 |   0.03184 |
-#> |.....................|    0.8115 |   0.06760 |    0.6803 |    0.6854 |
-#> |.....................|     1.499 |    0.9562 |    0.7392 |     1.941 |
-#> |    F| Forward Diff. |     6.342 |  0.001592 |   -0.2787 |  -0.05882 |
-#> |.....................|  0.004933 |  -0.02534 |   -0.4440 |   -0.5467 |
-#> |.....................|   -0.1484 |  -0.03146 |    0.4648 |    -1.264 |
-#> |.....................|   -0.3607 |   -0.2274 |   -0.5157 |   -0.1312 |
-#> |  139|     466.68314 |     1.015 |    -1.839 |   -0.9751 |   -0.8151 |
-#> |.....................|   -0.9166 |    -1.339 |     1.792 |    -1.792 |
-#> |.....................|   -0.9160 |   -0.5585 |   -0.9470 |    -1.115 |
-#> |.....................|   -0.5998 |   -0.8691 |    -1.016 |   -0.2676 |
-#> |    U|     466.68314 |     92.36 |    -6.039 |   -0.9476 |    -2.077 |
-#> |.....................|    -4.529 |    0.2501 |     1.937 |   0.03187 |
-#> |.....................|    0.8128 |   0.06763 |    0.6797 |    0.6853 |
-#> |.....................|     1.500 |    0.9582 |    0.7404 |     1.942 |
-#> |    X|     466.68314 |     92.36 |  0.002385 |    0.2794 |    0.1252 |
-#> |.....................|   0.01079 |    0.5622 |     1.937 |   0.03187 |
-#> |.....................|    0.8128 |   0.06763 |    0.6797 |    0.6853 |
-#> |.....................|     1.500 |    0.9582 |    0.7404 |     1.942 |
-#> |    F| Forward Diff. |    -4.258 |-0.0003497 |   -0.2788 |  -0.03383 |
-#> |.....................|   0.01408 |   0.02647 |   -0.2857 |   -0.5956 |
-#> |.....................|  -0.05089 |   0.05050 |    0.4395 |    0.8187 |
-#> |.....................|   -0.2669 |  -0.06868 |   -0.3694 |   -0.1159 |
-#> |  140|     466.67997 |     1.015 |    -1.839 |   -0.9739 |   -0.8142 |
-#> |.....................|   -0.9180 |    -1.339 |     1.794 |    -1.790 |
-#> |.....................|   -0.9137 |   -0.5623 |   -0.9494 |    -1.116 |
-#> |.....................|   -0.6002 |   -0.8690 |    -1.016 |   -0.2664 |
-#> |    U|     466.67997 |     92.38 |    -6.039 |   -0.9465 |    -2.077 |
-#> |.....................|    -4.531 |    0.2499 |     1.938 |   0.03191 |
-#> |.....................|    0.8138 |   0.06752 |    0.6779 |    0.6846 |
-#> |.....................|     1.499 |    0.9583 |    0.7410 |     1.943 |
-#> |    X|     466.67997 |     92.38 |  0.002385 |    0.2796 |    0.1254 |
-#> |.....................|   0.01078 |    0.5622 |     1.938 |   0.03191 |
-#> |.....................|    0.8138 |   0.06752 |    0.6779 |    0.6846 |
-#> |.....................|     1.499 |    0.9583 |    0.7410 |     1.943 |
-#> |    M|   Mixed Diff. |    -1.882 |-7.391e+04 |   -0.2259 |  -0.03295 |
-#> |.....................|  0.005718 |   0.01130 |   -0.3842 |   -0.4930 |
-#> |.....................|  -0.04972 |  -0.05953 |    0.5251 |    -1.398 |
-#> |.....................|   -0.3564 |  -0.08212 |   -0.3242 |   -0.1008 |
-#> |  141|     466.67997 |     1.015 |    -1.839 |   -0.9739 |   -0.8142 |
-#> |.....................|   -0.9180 |    -1.339 |     1.794 |    -1.790 |
-#> |.....................|   -0.9137 |   -0.5623 |   -0.9494 |    -1.116 |
-#> |.....................|   -0.6002 |   -0.8690 |    -1.016 |   -0.2664 |
-#> |    U|     466.67997 |     92.38 |    -6.039 |   -0.9465 |    -2.077 |
-#> |.....................|    -4.531 |    0.2499 |     1.938 |   0.03191 |
-#> |.....................|    0.8138 |   0.06752 |    0.6779 |    0.6846 |
-#> |.....................|     1.499 |    0.9583 |    0.7410 |     1.943 |
-#> |    X|     466.67997 |     92.38 |  0.002385 |    0.2796 |    0.1254 |
-#> |.....................|   0.01078 |    0.5622 |     1.938 |   0.03191 |
-#> |.....................|    0.8138 |   0.06752 |    0.6779 |    0.6846 |
-#> |.....................|     1.499 |    0.9583 |    0.7410 |     1.943 |
-#> calculating covariance matrix
-#> done
-#> Calculating residuals/tables
-#> done
-
-AIC(
-  f_nlmixr_sfo_sfo_focei_const$nm,
-  f_nlmixr_fomc_sfo_focei_const$nm,
-  f_nlmixr_dfop_sfo_focei_const$nm,
-  f_nlmixr_fomc_sfo_saem_obs$nm,
-  f_nlmixr_fomc_sfo_focei_obs$nm,
-  f_nlmixr_dfop_sfo_saem_obs$nm,
-  f_nlmixr_dfop_sfo_focei_obs$nm,
-  f_nlmixr_fomc_sfo_focei_tc$nm,
-  f_nlmixr_dfop_sfo_focei_tc$nm,
-  f_nlmixr_fomc_sfo_saem_obs_tc$nm,
-  f_nlmixr_fomc_sfo_focei_obs_tc$nm,
-  f_nlmixr_dfop_sfo_saem_obs_tc$nm,
-  f_nlmixr_dfop_sfo_focei_obs_tc$nm
-)
-#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
-#> 
-#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
-#> 
-#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
-#> 
-#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
-#> 
-#>                                   df       AIC
-#> f_nlmixr_sfo_sfo_focei_const$nm    9 1082.4605
-#> f_nlmixr_fomc_sfo_focei_const$nm  11  814.4261
-#> f_nlmixr_dfop_sfo_focei_const$nm  13  870.2659
-#> f_nlmixr_fomc_sfo_saem_obs$nm     12  788.8373
-#> f_nlmixr_fomc_sfo_focei_obs$nm    12  794.5194
-#> f_nlmixr_dfop_sfo_saem_obs$nm     14  815.0797
-#> f_nlmixr_dfop_sfo_focei_obs$nm    14  834.8474
-#> f_nlmixr_fomc_sfo_focei_tc$nm     12  812.3296
-#> f_nlmixr_dfop_sfo_focei_tc$nm     14  819.4103
-#> f_nlmixr_fomc_sfo_saem_obs_tc$nm  14  814.4248
-#> f_nlmixr_fomc_sfo_focei_obs_tc$nm 14  787.4355
-#> f_nlmixr_dfop_sfo_saem_obs_tc$nm  16  828.5143
-#> f_nlmixr_dfop_sfo_focei_obs_tc$nm 16  811.1191
-# Currently, FOMC-SFO with two-component error by variable fitted by focei gives the
-# lowest AIC
-plot(f_nlmixr_fomc_sfo_focei_obs_tc)
-
-summary(f_nlmixr_fomc_sfo_focei_obs_tc)
-#> nlmixr version used for fitting:    2.0.6 
-#> mkin version used for pre-fitting:  1.1.0 
-#> R version used for fitting:         4.1.2 
-#> Date of fit:     Mon Feb 28 14:50:18 2022 
-#> Date of summary: Mon Feb 28 14:51:57 2022 
-#> 
-#> Equations:
-#> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
-#> d_A1/dt = + f_parent_to_A1 * (alpha/beta) * 1/((time/beta) + 1) *
-#>            parent - k_A1 * A1
-#> 
-#> Data:
-#> 170 observations of 2 variable(s) grouped in 5 datasets
-#> 
-#> Degradation model predictions using RxODE
-#> 
-#> Fitted in 18.08 s
-#> 
-#> Variance model: Two-component variance unique to each observed variable 
-#> 
-#> Mean of starting values for individual parameters:
-#>        parent_0        log_k_A1 f_parent_qlogis       log_alpha        log_beta 
-#>         93.1168         -5.3034         -0.9442         -0.1065          2.2909 
-#> 
-#> Mean of starting values for error model parameters:
-#> sigma_low_parent  rsd_high_parent     sigma_low_A1      rsd_high_A1 
-#>          1.15958          0.03005          1.15958          0.03005 
-#> 
-#> Fixed degradation parameter values:
-#> None
-#> 
-#> Results:
-#> 
-#> Likelihood calculated by focei  
-#>     AIC   BIC logLik
-#>   787.4 831.3 -379.7
-#> 
-#> Optimised parameters:
-#>                    est.   lower   upper
-#> parent_0        93.6717 91.2552 96.0882
-#> log_k_A1        -6.3199 -8.4468 -4.1930
-#> f_parent_qlogis -1.0089 -1.3823 -0.6356
-#> log_alpha       -0.1616 -0.6624  0.3392
-#> log_beta         2.2088  1.6800  2.7376
-#> 
-#> Correlation: 
-#>                 prnt_0 lg__A1 f_prn_ lg_lph
-#> log_k_A1         0.372                     
-#> f_parent_qlogis -0.786 -0.409              
-#> log_alpha        0.336  0.942 -0.306       
-#> log_beta        -0.399 -0.759  0.248 -0.555
-#> 
-#> Random effects (omega):
-#>                     eta.parent_0 eta.log_k_A1 eta.f_parent_qlogis eta.log_alpha
-#> eta.parent_0               4.391        0.000              0.0000        0.0000
-#> eta.log_k_A1               0.000        6.402              0.0000        0.0000
-#> eta.f_parent_qlogis        0.000        0.000              0.1584        0.0000
-#> eta.log_alpha              0.000        0.000              0.0000        0.3381
-#> eta.log_beta               0.000        0.000              0.0000        0.0000
-#>                     eta.log_beta
-#> eta.parent_0               0.000
-#> eta.log_k_A1               0.000
-#> eta.f_parent_qlogis        0.000
-#> eta.log_alpha              0.000
-#> eta.log_beta               0.358
-#> 
-#> Variance model:
-#> sigma_low_parent  rsd_high_parent     sigma_low_A1      rsd_high_A1 
-#>          2.35616          0.00153          0.63564          0.08639 
-#> 
-#> Backtransformed parameters:
-#>                   est.     lower   upper
-#> parent_0       93.6717 9.126e+01 96.0882
-#> k_A1            0.0018 2.146e-04  0.0151
-#> f_parent_to_A1  0.2672 2.006e-01  0.3462
-#> alpha           0.8508 5.156e-01  1.4038
-#> beta            9.1049 5.366e+00 15.4499
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_A1   0.2672
-#> parent_sink 0.7328
-#> 
-#> Estimated disappearance times:
-#>          DT50   DT90 DT50back
-#> parent  11.46  127.3    38.31
-#> A1     385.05 1279.1       NA
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.2.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/nobs.mkinfit.html b/docs/dev/reference/nobs.mkinfit.html
deleted file mode 100644
index 10f6550b..00000000
--- a/docs/dev/reference/nobs.mkinfit.html
+++ /dev/null
@@ -1,157 +0,0 @@
-
-Number of observations on which an mkinfit object was fitted — nobs.mkinfit • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Number of observations on which an mkinfit object was fitted
      
-    Source: R/nobs.mkinfit.R
-    
-    
      
-
-    
      
-    
      Number of observations on which an mkinfit object was fitted
      
-    
      
-
-    
      
-    
      # S3 method for mkinfit
-nobs(object, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      An mkinfit object
      
-
-
-
      ...
      
-
      For compatibility with the generic method
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The number of rows in the data included in the mkinfit object
      
-    
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/parhist.html b/docs/dev/reference/parhist.html
deleted file mode 100644
index 27fc116f..00000000
--- a/docs/dev/reference/parhist.html
+++ /dev/null
@@ -1,169 +0,0 @@
-
-Plot parameter distributions from multistart objects — parhist • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Plot parameter distributions from multistart objects
      
-    Source: R/parhist.R
-    
-    
      
-
-    
      
-    
      Produces a boxplot with all parameters from the multiple runs, scaled
-either by the parameters of the run with the highest likelihood,
-or by their medians as proposed in the paper by Duchesne et al. (2021).
      
-    
      
-
-    
      
-    
      parhist(
-  object,
-  llmin = -Inf,
-  scale = c("best", "median"),
-  lpos = "bottomleft",
-  main = "",
-  ...
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      The multistart object
      
-
-
-
      llmin
      
-
      The minimum likelihood of objects to be shown
      
-
-
-
      scale
      
-
      By default, scale parameters using the best available fit.
-If 'median', parameters are scaled using the median parameters from all fits.
      
-
-
-
      lpos
      
-
      Positioning of the legend.
      
-
-
-
      main
      
-
      Title of the plot
      
-
-
-
      ...
      
-
      Passed to boxplot
      
-
-
      
-    
      
-    
      References
      
-    
      Duchesne R, Guillemin A, Gandrillon O, Crauste F. Practical
-identifiability in the frame of nonlinear mixed effects models: the example
-of the in vitro erythropoiesis. BMC Bioinformatics. 2021 Oct 4;22(1):478.
-doi: 10.1186/s12859-021-04373-4.
      
-    
      
-    
      
-    
      See also
      
-    
      multistart
      
-    
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.6.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/parms.html b/docs/dev/reference/parms.html
deleted file mode 100644
index d4175d41..00000000
--- a/docs/dev/reference/parms.html
+++ /dev/null
@@ -1,296 +0,0 @@
-
-Extract model parameters — parms • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Extract model parameters
      
-    Source: R/parms.R, R/saem.R
-    
-    
      
-
-    
      
-    
      This function returns degradation model parameters as well as error
-model parameters per default, in order to avoid working with a fitted model
-without considering the error structure that was assumed for the fit.
      
-    
      
-
-    
      
-    
      parms(object, ...)
-
-# S3 method for mkinfit
-parms(object, transformed = FALSE, errparms = TRUE, ...)
-
-# S3 method for mmkin
-parms(object, transformed = FALSE, errparms = TRUE, ...)
-
-# S3 method for multistart
-parms(object, exclude_failed = TRUE, ...)
-
-# S3 method for saem.mmkin
-parms(object, ci = FALSE, covariates = NULL, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      A fitted model object.
      
-
-
-
      ...
      
-
      Not used
      
-
-
-
      transformed
      
-
      Should the parameters be returned as used internally
-during the optimisation?
      
-
-
-
      errparms
      
-
      Should the error model parameters be returned
-in addition to the degradation parameters?
      
-
-
-
      exclude_failed
      
-
      For multistart objects, should rows for failed fits
-be removed from the returned parameter matrix?
      
-
-
-
      ci
      
-
      Should a matrix with estimates and confidence interval boundaries
-be returned? If FALSE (default), a vector of estimates is returned if no
-covariates are given, otherwise a matrix of estimates is returned, with
-each column corresponding to a row of the data frame holding the covariates
      
-
-
-
      covariates
      
-
      A data frame holding covariate values for which to
-return parameter values. Only has an effect if 'ci' is FALSE.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      Depending on the object, a numeric vector of fitted model parameters,
-a matrix (e.g. for mmkin row objects), or a list of matrices (e.g. for
-mmkin objects with more than one row).
      
-    
      
-    
      
-    
      See also
      
-    
      saem, multistart
      
-    
      
-
-    
      
-    
      Examples
      
-    
      # mkinfit objects
-fit <- mkinfit("SFO", FOCUS_2006_C, quiet = TRUE)
-parms(fit)
-#>   parent_0   k_parent      sigma 
-#> 82.4921598  0.3060633  4.6730124 
-parms(fit, transformed = TRUE)
-#>     parent_0 log_k_parent        sigma 
-#>    82.492160    -1.183963     4.673012 
-
-# mmkin objects
-ds <- lapply(experimental_data_for_UBA_2019[6:10],
- function(x) subset(x$data[c("name", "time", "value")]))
-names(ds) <- paste("Dataset", 6:10)
-# \dontrun{
-fits <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE, cores = 1)
-parms(fits["SFO", ])
-#>            Dataset 6    Dataset 7  Dataset 8  Dataset 9  Dataset 10
-#> parent_0 88.52275400 82.666781678 86.8547308 91.7779306 82.14809450
-#> k_parent  0.05794659  0.009647805  0.2102974  0.1232258  0.00720421
-#> sigma     5.15274487  7.040168584  3.6769645  6.4669234  6.50457673
-parms(fits[, 2])
-#> $SFO
-#>             Dataset 7
-#> parent_0 82.666781678
-#> k_parent  0.009647805
-#> sigma     7.040168584
-#> 
-#> $FOMC
-#>           Dataset 7
-#> parent_0 92.6837649
-#> alpha     0.4967832
-#> beta     14.1451255
-#> sigma     1.9167519
-#> 
-#> $DFOP
-#>             Dataset 7
-#> parent_0 91.058971589
-#> k1        0.044946770
-#> k2        0.002868336
-#> g         0.526942415
-#> sigma     2.221302196
-#> 
-parms(fits)
-#> $SFO
-#>            Dataset 6    Dataset 7  Dataset 8  Dataset 9  Dataset 10
-#> parent_0 88.52275400 82.666781678 86.8547308 91.7779306 82.14809450
-#> k_parent  0.05794659  0.009647805  0.2102974  0.1232258  0.00720421
-#> sigma     5.15274487  7.040168584  3.6769645  6.4669234  6.50457673
-#> 
-#> $FOMC
-#>          Dataset 6  Dataset 7 Dataset 8 Dataset 9 Dataset 10
-#> parent_0 95.558575 92.6837649 90.719787 98.383939 94.8481459
-#> alpha     1.338667  0.4967832  1.639099  1.074460  0.2805272
-#> beta     13.033315 14.1451255  5.007077  4.397126  6.9052224
-#> sigma     1.847671  1.9167519  1.066063  3.146056  1.6222778
-#> 
-#> $DFOP
-#>            Dataset 6    Dataset 7   Dataset 8   Dataset 9   Dataset 10
-#> parent_0 96.55213663 91.058971589 90.34509493 98.14858820 94.311323734
-#> k1        0.21954588  0.044946770  0.41232288  0.31697588  0.080663857
-#> k2        0.02957934  0.002868336  0.07581766  0.03260384  0.003425417
-#> g         0.44845068  0.526942415  0.66091967  0.65322767  0.342652880
-#> sigma     1.35690468  2.221302196  1.34169076  2.87159846  1.942067831
-#> 
-parms(fits, transformed = TRUE)
-#> $SFO
-#>              Dataset 6 Dataset 7 Dataset 8 Dataset 9 Dataset 10
-#> parent_0     88.522754 82.666782 86.854731 91.777931  82.148094
-#> log_k_parent -2.848234 -4.641025 -1.559232 -2.093737  -4.933090
-#> sigma         5.152745  7.040169  3.676964  6.466923   6.504577
-#> 
-#> $FOMC
-#>            Dataset 6  Dataset 7  Dataset 8   Dataset 9 Dataset 10
-#> parent_0  95.5585751 92.6837649 90.7197870 98.38393897  94.848146
-#> log_alpha  0.2916741 -0.6996015  0.4941466  0.07181816  -1.271085
-#> log_beta   2.5675088  2.6493701  1.6108523  1.48095106   1.932278
-#> sigma      1.8476712  1.9167519  1.0660627  3.14605557   1.622278
-#> 
-#> $DFOP
-#>           Dataset 6  Dataset 7  Dataset 8  Dataset 9 Dataset 10
-#> parent_0 96.5521366 91.0589716 90.3450949 98.1485882 94.3113237
-#> log_k1   -1.5161940 -3.1022764 -0.8859486 -1.1489296 -2.5174647
-#> log_k2   -3.5206791 -5.8540232 -2.5794240 -3.4233253 -5.6765322
-#> g_qlogis -0.2069326  0.1078741  0.6673953  0.6332573 -0.6514943
-#> sigma     1.3569047  2.2213022  1.3416908  2.8715985  1.9420678
-#> 
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/parplot.html b/docs/dev/reference/parplot.html
deleted file mode 100644
index ee2ec7b2..00000000
--- a/docs/dev/reference/parplot.html
+++ /dev/null
@@ -1,205 +0,0 @@
-
-Plot parameter variability of multistart objects — parplot • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Plot parameter variability of multistart objects
      
-    Source: R/parplot.R
-    
-    
      
-
-    
      
-    
      Produces a boxplot with all parameters from the multiple runs, scaled
-either by the parameters of the run with the highest likelihood,
-or by their medians as proposed in the paper by Duchesne et al. (2021).
      
-    
      
-
-    
      
-    
      parplot(object, ...)
-
-# S3 method for multistart.saem.mmkin
-parplot(
-  object,
-  llmin = -Inf,
-  llquant = NA,
-  scale = c("best", "median"),
-  lpos = "bottomleft",
-  main = "",
-  ...
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      The multistart object
      
-
-
-
      ...
      
-
      Passed to boxplot
      
-
-
-
      llmin
      
-
      The minimum likelihood of objects to be shown
      
-
-
-
      llquant
      
-
      Fractional value for selecting only the fits with higher
-likelihoods. Overrides 'llmin'.
      
-
-
-
      scale
      
-
      By default, scale parameters using the best
-available fit.
-If 'median', parameters are scaled using the median parameters from all fits.
      
-
-
-
      lpos
      
-
      Positioning of the legend.
      
-
-
-
      main
      
-
      Title of the plot
      
-
-
      
-    
      
-    
      Details
      
-    
      Starting values of degradation model parameters and error model parameters
-are shown as green circles. The results obtained in the original run
-are shown as red circles.
      
-    
      
-    
      
-    
      References
      
-    
      Duchesne R, Guillemin A, Gandrillon O, Crauste F. Practical
-identifiability in the frame of nonlinear mixed effects models: the example
-of the in vitro erythropoiesis. BMC Bioinformatics. 2021 Oct 4;22(1):478.
-doi: 10.1186/s12859-021-04373-4.
      
-    
      
-    
      
-    
      See also
      
-    
      multistart
      
-    
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
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      Site built with pkgdown 2.0.7.
      
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-
-Plot predictions from a fitted nonlinear mixed model obtained via an mmkin row object — plot.mixed.mmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Plot predictions from a fitted nonlinear mixed model obtained via an mmkin row object
      
-    Source: R/plot.mixed.mmkin.R
-    
-    
      
-
-    
      
-    
      Plot predictions from a fitted nonlinear mixed model obtained via an mmkin row object
      
-    
      
-
-    
      
-    
      # S3 method for mixed.mmkin
-plot(
-  x,
-  i = 1:ncol(x$mmkin),
-  obs_vars = names(x$mkinmod$map),
-  standardized = TRUE,
-  covariates = NULL,
-  covariate_quantiles = c(0.5, 0.05, 0.95),
-  xlab = "Time",
-  xlim = range(x$data$time),
-  resplot = c("predicted", "time"),
-  pop_curves = "auto",
-  pred_over = NULL,
-  test_log_parms = FALSE,
-  conf.level = 0.6,
-  default_log_parms = NA,
-  ymax = "auto",
-  maxabs = "auto",
-  ncol.legend = ifelse(length(i) <= 3, length(i) + 1, ifelse(length(i) <= 8, 3, 4)),
-  nrow.legend = ceiling((length(i) + 1)/ncol.legend),
-  rel.height.legend = 0.02 + 0.07 * nrow.legend,
-  rel.height.bottom = 1.1,
-  pch_ds = 1:length(i),
-  col_ds = pch_ds + 1,
-  lty_ds = col_ds,
-  frame = TRUE,
-  ...
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      x
      
-
      An object of class mixed.mmkin, saem.mmkin or nlme.mmkin
      
-
-
-
      i
      
-
      A numeric index to select datasets for which to plot the individual predictions,
-in case plots get too large
      
-
-
-
      obs_vars
      
-
      A character vector of names of the observed variables for
-which the data and the model should be plotted. Defauls to all observed
-variables in the model.
      
-
-
-
      standardized
      
-
      Should the residuals be standardized? Only takes effect if
-resplot = "time".
      
-
-
-
      covariates
      
-
      Data frame with covariate values for all variables in
-any covariate models in the object. If given, it overrides 'covariate_quantiles'.
-Each line in the data frame will result in a line drawn for the population.
-Rownames are used in the legend to label the lines.
      
-
-
-
      covariate_quantiles
      
-
      This argument only has an effect if the fitted
-object has covariate models. If so, the default is to show three population
-curves, for the 5th percentile, the 50th percentile and the 95th percentile
-of the covariate values used for fitting the model.
      
-
-
-
      xlab
      
-
      Label for the x axis.
      
-
-
-
      xlim
      
-
      Plot range in x direction.
      
-
-
-
      resplot
      
-
      Should the residuals plotted against time or against
-predicted values?
      
-
-
-
      pop_curves
      
-
      Per default, one population curve is drawn in case
-population parameters are fitted by the model, e.g. for saem objects.
-In case there is a covariate model, the behaviour depends on the value
-of 'covariates'
      
-
-
-
      pred_over
      
-
      Named list of alternative predictions as obtained
-from mkinpredict with a compatible mkinmod.
      
-
-
-
      test_log_parms
      
-
      Passed to mean_degparms in the case of an
-mixed.mmkin object
      
-
-
-
      conf.level
      
-
      Passed to mean_degparms in the case of an
-mixed.mmkin object
      
-
-
-
      default_log_parms
      
-
      Passed to mean_degparms in the case of an
-mixed.mmkin object
      
-
-
-
      ymax
      
-
      Vector of maximum y axis values
      
-
-
-
      maxabs
      
-
      Maximum absolute value of the residuals. This is used for the
-scaling of the y axis and defaults to "auto".
      
-
-
-
      ncol.legend
      
-
      Number of columns to use in the legend
      
-
-
-
      nrow.legend
      
-
      Number of rows to use in the legend
      
-
-
-
      rel.height.legend
      
-
      The relative height of the legend shown on top
      
-
-
-
      rel.height.bottom
      
-
      The relative height of the bottom plot row
      
-
-
-
      pch_ds
      
-
      Symbols to be used for plotting the data.
      
-
-
-
      col_ds
      
-
      Colors used for plotting the observed data and the
-corresponding model prediction lines for the different datasets.
      
-
-
-
      lty_ds
      
-
      Line types to be used for the model predictions.
      
-
-
-
      frame
      
-
      Should a frame be drawn around the plots?
      
-
-
-
      ...
      
-
      Further arguments passed to plot.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The function is called for its side effect.
      
-    
      
-    
      
-    
      Note
      
-    
      Covariate models are currently only supported for saem.mmkin objects.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      ds <- lapply(experimental_data_for_UBA_2019[6:10],
- function(x) x$data[c("name", "time", "value")])
-names(ds) <- paste0("ds ", 6:10)
-dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
-  A1 = mkinsub("SFO"), quiet = TRUE)
-# \dontrun{
-f <- mmkin(list("DFOP-SFO" = dfop_sfo), ds, quiet = TRUE)
-plot(f[, 3:4], standardized = TRUE)
-
-
-# For this fit we need to increase pnlsMaxiter, and we increase the
-# tolerance in order to speed up the fit for this example evaluation
-# It still takes 20 seconds to run
-f_nlme <- nlme(f, control = list(pnlsMaxIter = 120, tolerance = 1e-3))
-plot(f_nlme)
-
-
-f_saem <- saem(f, transformations = "saemix")
-plot(f_saem)
-
-
-f_obs <- mmkin(list("DFOP-SFO" = dfop_sfo), ds, quiet = TRUE, error_model = "obs")
-f_nlmix <- nlmix(f_obs)
-#> Error in nlmix(f_obs): could not find function "nlmix"
-plot(f_nlmix)
-#> Error in plot(f_nlmix): object 'f_nlmix' not found
-
-# We can overlay the two variants if we generate predictions
-pred_nlme <- mkinpredict(dfop_sfo,
-  f_nlme$bparms.optim[-1],
-  c(parent = f_nlme$bparms.optim[[1]], A1 = 0),
-  seq(0, 180, by = 0.2))
-plot(f_saem, pred_over = list(nlme = pred_nlme))
-
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
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-
-Plot the observed data and the fitted model of an mkinfit object — plot.mkinfit • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Plot the observed data and the fitted model of an mkinfit object
      
-    Source: R/plot.mkinfit.R
-    
-    
      
-
-    
      
-    
      Solves the differential equations with the optimised and fixed parameters
-from a previous successful call to mkinfit and plots the
-observed data together with the solution of the fitted model.
      
-    
      
-
-    
      
-    
      # S3 method for mkinfit
-plot(
-  x,
-  fit = x,
-  obs_vars = names(fit$mkinmod$map),
-  xlab = "Time",
-  ylab = "Residue",
-  xlim = range(fit$data$time),
-  ylim = "default",
-  col_obs = 1:length(obs_vars),
-  pch_obs = col_obs,
-  lty_obs = rep(1, length(obs_vars)),
-  add = FALSE,
-  legend = !add,
-  show_residuals = FALSE,
-  show_errplot = FALSE,
-  maxabs = "auto",
-  sep_obs = FALSE,
-  rel.height.middle = 0.9,
-  row_layout = FALSE,
-  lpos = "topright",
-  inset = c(0.05, 0.05),
-  show_errmin = FALSE,
-  errmin_digits = 3,
-  frame = TRUE,
-  ...
-)
-
-plot_sep(
-  fit,
-  show_errmin = TRUE,
-  show_residuals = ifelse(identical(fit$err_mod, "const"), TRUE, "standardized"),
-  ...
-)
-
-plot_res(
-  fit,
-  sep_obs = FALSE,
-  show_errmin = sep_obs,
-  standardized = ifelse(identical(fit$err_mod, "const"), FALSE, TRUE),
-  ...
-)
-
-plot_err(fit, sep_obs = FALSE, show_errmin = sep_obs, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      x
      
-
      Alias for fit introduced for compatibility with the generic S3
-method.
      
-
-
-
      fit
      
-
      An object of class mkinfit.
      
-
-
-
      obs_vars
      
-
      A character vector of names of the observed variables for
-which the data and the model should be plotted. Defauls to all observed
-variables in the model.
      
-
-
-
      xlab
      
-
      Label for the x axis.
      
-
-
-
      ylab
      
-
      Label for the y axis.
      
-
-
-
      xlim
      
-
      Plot range in x direction.
      
-
-
-
      ylim
      
-
      Plot range in y direction. If given as a list, plot ranges
-for the different plot rows can be given for row layout.
      
-
-
-
      col_obs
      
-
      Colors used for plotting the observed data and the
-corresponding model prediction lines.
      
-
-
-
      pch_obs
      
-
      Symbols to be used for plotting the data.
      
-
-
-
      lty_obs
      
-
      Line types to be used for the model predictions.
      
-
-
-
      add
      
-
      Should the plot be added to an existing plot?
      
-
-
-
      legend
      
-
      Should a legend be added to the plot?
      
-
-
-
      show_residuals
      
-
      Should residuals be shown? If only one plot of the
-fits is shown, the residual plot is in the lower third of the plot.
-Otherwise, i.e. if "sep_obs" is given, the residual plots will be located
-to the right of the plots of the fitted curves. If this is set to
-'standardized', a plot of the residuals divided by the standard deviation
-given by the fitted error model will be shown.
      
-
-
-
      show_errplot
      
-
      Should squared residuals and the error model be shown?
-If only one plot of the fits is shown, this plot is in the lower third of
-the plot.  Otherwise, i.e. if "sep_obs" is given, the residual plots will
-be located to the right of the plots of the fitted curves.
      
-
-
-
      maxabs
      
-
      Maximum absolute value of the residuals. This is used for the
-scaling of the y axis and defaults to "auto".
      
-
-
-
      sep_obs
      
-
      Should the observed variables be shown in separate subplots?
-If yes, residual plots requested by "show_residuals" will be shown next
-to, not below the plot of the fits.
      
-
-
-
      rel.height.middle
      
-
      The relative height of the middle plot, if more
-than two rows of plots are shown.
      
-
-
-
      row_layout
      
-
      Should we use a row layout where the residual plot or the
-error model plot is shown to the right?
      
-
-
-
      lpos
      
-
      Position(s) of the legend(s). Passed to legend as
-the first argument.  If not length one, this should be of the same length
-as the obs_var argument.
      
-
-
-
      inset
      
-
      Passed to legend if applicable.
      
-
-
-
      show_errmin
      
-
      Should the FOCUS chi2 error value be shown in the upper
-margin of the plot?
      
-
-
-
      errmin_digits
      
-
      The number of significant digits for rounding the FOCUS
-chi2 error percentage.
      
-
-
-
      frame
      
-
      Should a frame be drawn around the plots?
      
-
-
-
      ...
      
-
      Further arguments passed to plot.
      
-
-
-
      standardized
      
-
      When calling 'plot_res', should the residuals be
-standardized in the residual plot?
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The function is called for its side effect.
      
-    
      
-    
      
-    
      Details
      
-    
      If the current plot device is a tikz device, then
-latex is being used for the formatting of the chi2 error level, if
-show_errmin = TRUE.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-# One parent compound, one metabolite, both single first order, path from
-# parent to sink included
-# \dontrun{
-SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1", full = "Parent"),
-                   m1 = mkinsub("SFO", full = "Metabolite M1" ))
-#> Temporary DLL for differentials generated and loaded
-fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
-#> Warning: Observations with value of zero were removed from the data
-fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE, error_model = "tc")
-#> Warning: Observations with value of zero were removed from the data
-plot(fit)
-
-plot_res(fit)
-
-plot_res(fit, standardized = FALSE)
-
-plot_err(fit)
-
-
-# Show the observed variables separately, with residuals
-plot(fit, sep_obs = TRUE, show_residuals = TRUE, lpos = c("topright", "bottomright"),
-     show_errmin = TRUE)
-
-
-# The same can be obtained with less typing, using the convenience function plot_sep
-plot_sep(fit, lpos = c("topright", "bottomright"))
-
-
-# Show the observed variables separately, with the error model
-plot(fit, sep_obs = TRUE, show_errplot = TRUE, lpos = c("topright", "bottomright"),
-     show_errmin = TRUE)
-
-# }
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
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-
-Plot model fits (observed and fitted) and the residuals for a row or column
-of an mmkin object — plot.mmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Plot model fits (observed and fitted) and the residuals for a row or column
-of an mmkin object
      
-    Source: R/plot.mmkin.R
-    
-    
      
-
-    
      
-    
      When x is a row selected from an mmkin object ([.mmkin), the
-same model fitted for at least one dataset is shown. When it is a column,
-the fit of at least one model to the same dataset is shown.
      
-    
      
-
-    
      
-    
      # S3 method for mmkin
-plot(
-  x,
-  main = "auto",
-  legends = 1,
-  resplot = c("time", "errmod"),
-  ylab = "Residue",
-  standardized = FALSE,
-  show_errmin = TRUE,
-  errmin_var = "All data",
-  errmin_digits = 3,
-  cex = 0.7,
-  rel.height.middle = 0.9,
-  ymax = "auto",
-  ...
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      x
      
-
      An object of class mmkin, with either one row or one
-column.
      
-
-
-
      main
      
-
      The main title placed on the outer margin of the plot.
      
-
-
-
      legends
      
-
      An index for the fits for which legends should be shown.
      
-
-
-
      resplot
      
-
      Should the residuals plotted against time, using
-mkinresplot, or as squared residuals against predicted
-values, with the error model, using mkinerrplot.
      
-
-
-
      ylab
      
-
      Label for the y axis.
      
-
-
-
      standardized
      
-
      Should the residuals be standardized? This option
-is passed to mkinresplot, it only takes effect if
-resplot = "time".
      
-
-
-
      show_errmin
      
-
      Should the chi2 error level be shown on top of the plots
-to the left?
      
-
-
-
      errmin_var
      
-
      The variable for which the FOCUS chi2 error value should
-be shown.
      
-
-
-
      errmin_digits
      
-
      The number of significant digits for rounding the FOCUS
-chi2 error percentage.
      
-
-
-
      cex
      
-
      Passed to the plot functions and mtext.
      
-
-
-
      rel.height.middle
      
-
      The relative height of the middle plot, if more
-than two rows of plots are shown.
      
-
-
-
      ymax
      
-
      Maximum y axis value for plot.mkinfit.
      
-
-
-
      ...
      
-
      Further arguments passed to plot.mkinfit and
-mkinresplot.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The function is called for its side effect.
      
-    
      
-    
      
-    
      Details
      
-    
      If the current plot device is a tikz device, then
-latex is being used for the formatting of the chi2 error level.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-  # \dontrun{
-  # Only use one core not to offend CRAN checks
-  fits <- mmkin(c("FOMC", "HS"),
-                list("FOCUS B" = FOCUS_2006_B, "FOCUS C" = FOCUS_2006_C), # named list for titles
-                cores = 1, quiet = TRUE, error_model = "tc")
-#> Warning: Optimisation did not converge:
-#> iteration limit reached without convergence (10)
-  plot(fits[, "FOCUS C"])
-
-  plot(fits["FOMC", ])
-
-  plot(fits["FOMC", ], show_errmin = FALSE)
-
-
-  # We can also plot a single fit, if we like the way plot.mmkin works, but then the plot
-  # height should be smaller than the plot width (this is not possible for the html pages
-  # generated by pkgdown, as far as I know).
-  plot(fits["FOMC", "FOCUS C"]) # same as plot(fits[1, 2])
-
-
-  # Show the error models
-  plot(fits["FOMC", ], resplot = "errmod")
-
-  # }
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/plot.nafta.html b/docs/dev/reference/plot.nafta.html
deleted file mode 100644
index 8acaa8b3..00000000
--- a/docs/dev/reference/plot.nafta.html
+++ /dev/null
@@ -1,175 +0,0 @@
-
-Plot the results of the three models used in the NAFTA scheme. — plot.nafta • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Plot the results of the three models used in the NAFTA scheme.
      
-    Source: R/nafta.R
-    
-    
      
-
-    
      
-    
      The plots are ordered with increasing complexity of the model in this
-function (SFO, then IORE, then DFOP).
      
-    
      
-
-    
      
-    
      # S3 method for nafta
-plot(x, legend = FALSE, main = "auto", ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      x
      
-
      An object of class nafta.
      
-
-
-
      legend
      
-
      Should a legend be added?
      
-
-
-
      main
      
-
      Possibility to override the main title of the plot.
      
-
-
-
      ...
      
-
      Further arguments passed to plot.mmkin.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The function is called for its side effect.
      
-    
      
-    
      
-    
      Details
      
-    
      Calls plot.mmkin.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/print.mmkin.html b/docs/dev/reference/print.mmkin.html
deleted file mode 100644
index 12c67d86..00000000
--- a/docs/dev/reference/print.mmkin.html
+++ /dev/null
@@ -1,194 +0,0 @@
-
-
-
-  
-  
-
-
-
-Print method for mmkin objects — print.mmkin • mkin
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-  
-
-  
-    
      
-      
      
-      
-
-      
-
-      
      
-
-
      
-  
      
-    
      
-    
      Print method for mmkin objects
      
-    Source: R/mmkin.R
-    
-    
      
-
-    
      
-    
      Print method for mmkin objects
      
-    
      
-
-    
      # S3 method for mmkin
-print(x, ...)
      
-
-    
      Arguments
      
-    
-    
-    
-      
-      
-    
-    
-      
-      
-    
-    
      x
      An mmkin object.
      ...
      Not used.
      
-
-
-  
      
-  
-
      
-
-
-      
      
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 1.6.1.
      
-
      
-
-      
      
-   
      
-
-  
-
-
-  
-
-
-
diff --git a/docs/dev/reference/read_spreadsheet.html b/docs/dev/reference/read_spreadsheet.html
deleted file mode 100644
index 6e7203f4..00000000
--- a/docs/dev/reference/read_spreadsheet.html
+++ /dev/null
@@ -1,196 +0,0 @@
-
-Read datasets and relevant meta information from a spreadsheet file — read_spreadsheet • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Read datasets and relevant meta information from a spreadsheet file
      
-    Source: R/read_spreadsheet.R
-    
-    
      
-
-    
      
-    
      This function imports one dataset from each sheet of a spreadsheet file.
-These sheets are selected based on the contents of a sheet 'Datasets', with
-a column called 'Dataset Number', containing numbers identifying the dataset
-sheets to be read in. In the second column there must be a grouping
-variable, which will often be named 'Soil'. Optionally, time normalization
-factors can be given in columns named 'Temperature' and 'Moisture'.
      
-    
      
-
-    
      
-    
      read_spreadsheet(
-  path,
-  valid_datasets = "all",
-  parent_only = FALSE,
-  normalize = TRUE
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      path
      
-
      Absolute or relative path to the spreadsheet file
      
-
-
-
      valid_datasets
      
-
      Optional numeric index of the valid datasets, default is
-to use all datasets
      
-
-
-
      parent_only
      
-
      Should only the parent data be used?
      
-
-
-
      normalize
      
-
      Should the time scale be normalized using temperature
-and moisture normalisation factors in the sheet 'Datasets'?
      
-
-
      
-    
      
-    
      Details
      
-    
      There must be a sheet 'Compounds', with columns 'Name' and 'Acronym'.
-The first row read after the header read in from this sheet is assumed
-to contain name and acronym of the parent compound.
      
-
      The dataset sheets should be named using the dataset numbers read in from
-the 'Datasets' sheet, i.e. '1', '2', ... . In each dataset sheet, name
-of the observed variable (e.g. the acronym of the parent compound or
-one of its transformation products) should be in the first column,
-the time values should be in the second colum, and the observed value
-in the third column.
      
-
      In case relevant covariate data are available, they should be given
-in a sheet 'Covariates', containing one line for each value of the grouping
-variable specified in 'Datasets'. These values should be in the first
-column and the column must have the same name as the second column in
-'Datasets'. Covariates will be read in from columns four and higher.
-Their names should preferably not contain special characters like spaces,
-so they can be easily used for specifying covariate models.
      
-
      An similar data structure is defined as the R6 class mkindsg, but
-is probably more complicated to use.
      
-    
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/reexports.html b/docs/dev/reference/reexports.html
deleted file mode 100644
index ee1148da..00000000
--- a/docs/dev/reference/reexports.html
+++ /dev/null
@@ -1,157 +0,0 @@
-
-Objects exported from other packages — reexports • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Objects exported from other packages
      
-    Source: R/intervals.R, R/lrtest.mkinfit.R, R/nlme.mmkin.R
-    
-    
      
-
-    
      
-    
      These objects are imported from other packages. Follow the links
-below to see their documentation.
      
-
      lmtest
      
-
      lrtest
      
-
-
-  
      nlme
      
-
      intervals, nlme
      
-
-
-
      
-
-
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/residuals.mkinfit.html b/docs/dev/reference/residuals.mkinfit.html
deleted file mode 100644
index 578b5066..00000000
--- a/docs/dev/reference/residuals.mkinfit.html
+++ /dev/null
@@ -1,167 +0,0 @@
-
-Extract residuals from an mkinfit model — residuals.mkinfit • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Extract residuals from an mkinfit model
      
-    Source: R/residuals.mkinfit.R
-    
-    
      
-
-    
      
-    
      Extract residuals from an mkinfit model
      
-    
      
-
-    
      
-    
      # S3 method for mkinfit
-residuals(object, standardized = FALSE, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      A mkinfit object
      
-
-
-
      standardized
      
-
      Should the residuals be standardized by dividing by the
-standard deviation obtained from the fitted error model?
      
-
-
-
      ...
      
-
      Not used
      
-
-
      
-
-    
      
-    
      Examples
      
-    
      f <- mkinfit("DFOP", FOCUS_2006_C, quiet = TRUE)
-residuals(f)
-#> [1]  0.09726374 -0.13912142 -0.15351210  0.73388322 -0.08657004 -0.93204702
-#> [7] -0.03269080  1.45347823 -0.88423697
-residuals(f, standardized = TRUE)
-#> [1]  0.13969917 -0.19981904 -0.22048826  1.05407091 -0.12433989 -1.33869208
-#> [7] -0.04695355  2.08761977 -1.27002287
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/saem-1.png b/docs/dev/reference/saem-1.png
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diff --git a/docs/dev/reference/saem.html b/docs/dev/reference/saem.html
deleted file mode 100644
index 9b9a911d..00000000
--- a/docs/dev/reference/saem.html
+++ /dev/null
@@ -1,779 +0,0 @@
-
-Fit nonlinear mixed models with SAEM — saem • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Fit nonlinear mixed models with SAEM
      
-    Source: R/saem.R
-    
-    
      
-
-    
      
-    
      This function uses saemix::saemix() as a backend for fitting nonlinear mixed
-effects models created from mmkin row objects using the Stochastic Approximation
-Expectation Maximisation algorithm (SAEM).
      
-    
      
-
-    
      
-    
      saem(object, ...)
-
-# S3 method for mmkin
-saem(
-  object,
-  transformations = c("mkin", "saemix"),
-  error_model = "auto",
-  degparms_start = numeric(),
-  test_log_parms = TRUE,
-  conf.level = 0.6,
-  solution_type = "auto",
-  covariance.model = "auto",
-  omega.init = "auto",
-  covariates = NULL,
-  covariate_models = NULL,
-  no_random_effect = NULL,
-  error.init = c(1, 1),
-  nbiter.saemix = c(300, 100),
-  control = list(displayProgress = FALSE, print = FALSE, nbiter.saemix = nbiter.saemix,
-    save = FALSE, save.graphs = FALSE),
-  verbose = FALSE,
-  quiet = FALSE,
-  ...
-)
-
-# S3 method for saem.mmkin
-print(x, digits = max(3, getOption("digits") - 3), ...)
-
-saemix_model(
-  object,
-  solution_type = "auto",
-  transformations = c("mkin", "saemix"),
-  error_model = "auto",
-  degparms_start = numeric(),
-  covariance.model = "auto",
-  no_random_effect = NULL,
-  omega.init = "auto",
-  covariates = NULL,
-  covariate_models = NULL,
-  error.init = numeric(),
-  test_log_parms = FALSE,
-  conf.level = 0.6,
-  verbose = FALSE,
-  ...
-)
-
-saemix_data(object, covariates = NULL, verbose = FALSE, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      An mmkin row object containing several fits of the same
-mkinmod model to different datasets
      
-
-
-
      ...
      
-
      Further parameters passed to saemix::saemixModel.
      
-
-
-
      transformations
      
-
      Per default, all parameter transformations are done
-in mkin. If this argument is set to 'saemix', parameter transformations
-are done in 'saemix' for the supported cases, i.e. (as of version 1.1.2)
-SFO, FOMC, DFOP and HS without fixing parent_0, and SFO or DFOP with
-one SFO metabolite.
      
-
-
-
      error_model
      
-
      Possibility to override the error model used in the mmkin object
      
-
-
-
      degparms_start
      
-
      Parameter values given as a named numeric vector will
-be used to override the starting values obtained from the 'mmkin' object.
      
-
-
-
      test_log_parms
      
-
      If TRUE, an attempt is made to use more robust starting
-values for population parameters fitted as log parameters in mkin (like
-rate constants) by only considering rate constants that pass the t-test
-when calculating mean degradation parameters using mean_degparms.
      
-
-
-
      conf.level
      
-
      Possibility to adjust the required confidence level
-for parameter that are tested if requested by 'test_log_parms'.
      
-
-
-
      solution_type
      
-
      Possibility to specify the solution type in case the
-automatic choice is not desired
      
-
-
-
      covariance.model
      
-
      Will be passed to saemix::saemixModel(). Per
-default, uncorrelated random effects are specified for all degradation
-parameters.
      
-
-
-
      omega.init
      
-
      Will be passed to saemix::saemixModel(). If using
-mkin transformations and the default covariance model with optionally
-excluded random effects, the variances of the degradation parameters
-are estimated using mean_degparms, with testing of untransformed
-log parameters for significant difference from zero. If not using
-mkin transformations or a custom covariance model, the default
-initialisation of saemix::saemixModel is used for omega.init.
      
-
-
-
      covariates
      
-
      A data frame with covariate data for use in
-'covariate_models', with dataset names as row names.
      
-
-
-
      covariate_models
      
-
      A list containing linear model formulas with one explanatory
-variable, i.e. of the type 'parameter ~ covariate'. Covariates must be available
-in the 'covariates' data frame.
      
-
-
-
      no_random_effect
      
-
      Character vector of degradation parameters for
-which there should be no variability over the groups. Only used
-if the covariance model is not explicitly specified.
      
-
-
-
      error.init
      
-
      Will be passed to saemix::saemixModel().
      
-
-
-
      nbiter.saemix
      
-
      Convenience option to increase the number of
-iterations
      
-
-
-
      control
      
-
      Passed to saemix::saemix.
      
-
-
-
      verbose
      
-
      Should we print information about created objects of
-type saemix::SaemixModel and saemix::SaemixData?
      
-
-
-
      quiet
      
-
      Should we suppress the messages saemix prints at the beginning
-and the end of the optimisation process?
      
-
-
-
      x
      
-
      An saem.mmkin object to print
      
-
-
-
      digits
      
-
      Number of digits to use for printing
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      An S3 object of class 'saem.mmkin', containing the fitted
-saemix::SaemixObject as a list component named 'so'. The
-object also inherits from 'mixed.mmkin'.
      
-
-
-
      An saemix::SaemixModel object.
      
-
-
-
      An saemix::SaemixData object.
      
-    
      
-    
      
-    
      Details
      
-    
      An mmkin row object is essentially a list of mkinfit objects that have been
-obtained by fitting the same model to a list of datasets using mkinfit.
      
-
      Starting values for the fixed effects (population mean parameters, argument
-psi0 of saemix::saemixModel() are the mean values of the parameters found
-using mmkin.
      
-    
      
-    
-
-    
      
-    
      Examples
      
-    
      # \dontrun{
-ds <- lapply(experimental_data_for_UBA_2019[6:10],
- function(x) subset(x$data[c("name", "time", "value")]))
-names(ds) <- paste("Dataset", 6:10)
-f_mmkin_parent_p0_fixed <- mmkin("FOMC", ds,
-  state.ini = c(parent = 100), fixed_initials = "parent", quiet = TRUE)
-f_saem_p0_fixed <- saem(f_mmkin_parent_p0_fixed)
-
-f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE)
-f_saem_sfo <- saem(f_mmkin_parent["SFO", ])
-f_saem_fomc <- saem(f_mmkin_parent["FOMC", ])
-f_saem_dfop <- saem(f_mmkin_parent["DFOP", ])
-anova(f_saem_sfo, f_saem_fomc, f_saem_dfop)
-#> Data: 90 observations of 1 variable(s) grouped in 5 datasets
-#> 
-#>             npar    AIC    BIC     Lik
-#> f_saem_sfo     5 624.33 622.38 -307.17
-#> f_saem_fomc    7 467.85 465.11 -226.92
-#> f_saem_dfop    9 493.76 490.24 -237.88
-anova(f_saem_sfo, f_saem_dfop, test = TRUE)
-#> Data: 90 observations of 1 variable(s) grouped in 5 datasets
-#> 
-#>             npar    AIC    BIC     Lik  Chisq Df Pr(>Chisq)    
-#> f_saem_sfo     5 624.33 622.38 -307.17                         
-#> f_saem_dfop    9 493.76 490.24 -237.88 138.57  4  < 2.2e-16 ***
-#> ---
-#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
-illparms(f_saem_dfop)
-#> [1] "sd(g_qlogis)"
-f_saem_dfop_red <- update(f_saem_dfop, no_random_effect = "g_qlogis")
-anova(f_saem_dfop, f_saem_dfop_red, test = TRUE)
-#> Data: 90 observations of 1 variable(s) grouped in 5 datasets
-#> 
-#>                 npar    AIC    BIC     Lik Chisq Df Pr(>Chisq)
-#> f_saem_dfop_red    8 488.68 485.55 -236.34                    
-#> f_saem_dfop        9 493.76 490.24 -237.88     0  1          1
-
-anova(f_saem_sfo, f_saem_fomc, f_saem_dfop)
-#> Data: 90 observations of 1 variable(s) grouped in 5 datasets
-#> 
-#>             npar    AIC    BIC     Lik
-#> f_saem_sfo     5 624.33 622.38 -307.17
-#> f_saem_fomc    7 467.85 465.11 -226.92
-#> f_saem_dfop    9 493.76 490.24 -237.88
-# The returned saem.mmkin object contains an SaemixObject, therefore we can use
-# functions from saemix
-library(saemix)
-#> Loading required package: npde
-#> Package saemix, version 3.2
-#>   please direct bugs, questions and feedback to emmanuelle.comets@inserm.fr
-#> 
-#> Attaching package: ‘saemix’
-#> The following objects are masked from ‘package:npde’:
-#> 
-#>     kurtosis, skewness
-compare.saemix(f_saem_sfo$so, f_saem_fomc$so, f_saem_dfop$so)
-#> Likelihoods calculated by importance sampling
-#>        AIC      BIC
-#> 1 624.3316 622.3788
-#> 2 467.8472 465.1132
-#> 3 493.7592 490.2441
-plot(f_saem_fomc$so, plot.type = "convergence")
-
-plot(f_saem_fomc$so, plot.type = "individual.fit")
-
-plot(f_saem_fomc$so, plot.type = "npde")
-#> Simulating data using nsim = 1000 simulated datasets
-#> Computing WRES and npde .
-#> Please use npdeSaemix to obtain VPC and npde
-plot(f_saem_fomc$so, plot.type = "vpc")
-
-
-f_mmkin_parent_tc <- update(f_mmkin_parent, error_model = "tc")
-f_saem_fomc_tc <- saem(f_mmkin_parent_tc["FOMC", ])
-anova(f_saem_fomc, f_saem_fomc_tc, test = TRUE)
-#> Data: 90 observations of 1 variable(s) grouped in 5 datasets
-#> 
-#>                npar    AIC    BIC     Lik Chisq Df Pr(>Chisq)
-#> f_saem_fomc       7 467.85 465.11 -226.92                    
-#> f_saem_fomc_tc    8 469.83 466.71 -226.92 0.015  1     0.9027
-
-sfo_sfo <- mkinmod(parent = mkinsub("SFO", "A1"),
-  A1 = mkinsub("SFO"))
-#> Temporary DLL for differentials generated and loaded
-fomc_sfo <- mkinmod(parent = mkinsub("FOMC", "A1"),
-  A1 = mkinsub("SFO"))
-#> Temporary DLL for differentials generated and loaded
-dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
-  A1 = mkinsub("SFO"))
-#> Temporary DLL for differentials generated and loaded
-# The following fit uses analytical solutions for SFO-SFO and DFOP-SFO,
-# and compiled ODEs for FOMC that are much slower
-f_mmkin <- mmkin(list(
-    "SFO-SFO" = sfo_sfo, "FOMC-SFO" = fomc_sfo, "DFOP-SFO" = dfop_sfo),
-  ds, quiet = TRUE)
-# saem fits of SFO-SFO and DFOP-SFO to these data take about five seconds
-# each on this system, as we use analytical solutions written for saemix.
-# When using the analytical solutions written for mkin this took around
-# four minutes
-f_saem_sfo_sfo <- saem(f_mmkin["SFO-SFO", ])
-f_saem_dfop_sfo <- saem(f_mmkin["DFOP-SFO", ])
-# We can use print, plot and summary methods to check the results
-print(f_saem_dfop_sfo)
-#> Kinetic nonlinear mixed-effects model fit by SAEM
-#> Structural model:
-#> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-#>            time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-#>            * parent
-#> d_A1/dt = + f_parent_to_A1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)
-#>            * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-#>            exp(-k2 * time))) * parent - k_A1 * A1
-#> 
-#> Data:
-#> 170 observations of 2 variable(s) grouped in 5 datasets
-#> 
-#> Likelihood computed by importance sampling
-#>     AIC   BIC logLik
-#>   839.2 834.1 -406.6
-#> 
-#> Fitted parameters:
-#>                    estimate    lower   upper
-#> parent_0           93.70402 91.04104 96.3670
-#> log_k_A1           -5.83760 -7.66452 -4.0107
-#> f_parent_qlogis    -0.95718 -1.35955 -0.5548
-#> log_k1             -2.35514 -3.39402 -1.3163
-#> log_k2             -3.79634 -5.64009 -1.9526
-#> g_qlogis           -0.02108 -0.66463  0.6225
-#> a.1                 1.88191  1.66491  2.0989
-#> SD.parent_0         2.81628  0.78922  4.8433
-#> SD.log_k_A1         1.78751  0.42105  3.1540
-#> SD.f_parent_qlogis  0.45016  0.16116  0.7391
-#> SD.log_k1           1.06923  0.31676  1.8217
-#> SD.log_k2           2.03768  0.70938  3.3660
-#> SD.g_qlogis         0.44024 -0.09262  0.9731
-plot(f_saem_dfop_sfo)
-
-summary(f_saem_dfop_sfo, data = TRUE)
-#> saemix version used for fitting:      3.2 
-#> mkin version used for pre-fitting:  1.2.3 
-#> R version used for fitting:         4.2.3 
-#> Date of fit:     Sun Apr 16 08:32:32 2023 
-#> Date of summary: Sun Apr 16 08:32:32 2023 
-#> 
-#> Equations:
-#> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-#>            time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-#>            * parent
-#> d_A1/dt = + f_parent_to_A1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)
-#>            * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-#>            exp(-k2 * time))) * parent - k_A1 * A1
-#> 
-#> Data:
-#> 170 observations of 2 variable(s) grouped in 5 datasets
-#> 
-#> Model predictions using solution type analytical 
-#> 
-#> Fitted in 4.145 s
-#> Using 300, 100 iterations and 10 chains
-#> 
-#> Variance model: Constant variance 
-#> 
-#> Starting values for degradation parameters:
-#>        parent_0        log_k_A1 f_parent_qlogis          log_k1          log_k2 
-#>         93.8102         -5.3734         -0.9711         -1.8799         -4.2708 
-#>        g_qlogis 
-#>          0.1356 
-#> 
-#> Fixed degradation parameter values:
-#> None
-#> 
-#> Starting values for random effects (square root of initial entries in omega):
-#>                 parent_0 log_k_A1 f_parent_qlogis log_k1 log_k2 g_qlogis
-#> parent_0           4.941    0.000          0.0000  0.000  0.000   0.0000
-#> log_k_A1           0.000    2.551          0.0000  0.000  0.000   0.0000
-#> f_parent_qlogis    0.000    0.000          0.7251  0.000  0.000   0.0000
-#> log_k1             0.000    0.000          0.0000  1.449  0.000   0.0000
-#> log_k2             0.000    0.000          0.0000  0.000  2.228   0.0000
-#> g_qlogis           0.000    0.000          0.0000  0.000  0.000   0.7814
-#> 
-#> Starting values for error model parameters:
-#> a.1 
-#>   1 
-#> 
-#> Results:
-#> 
-#> Likelihood computed by importance sampling
-#>     AIC   BIC logLik
-#>   839.2 834.1 -406.6
-#> 
-#> Optimised parameters:
-#>                        est.    lower   upper
-#> parent_0           93.70402 91.04104 96.3670
-#> log_k_A1           -5.83760 -7.66452 -4.0107
-#> f_parent_qlogis    -0.95718 -1.35955 -0.5548
-#> log_k1             -2.35514 -3.39402 -1.3163
-#> log_k2             -3.79634 -5.64009 -1.9526
-#> g_qlogis           -0.02108 -0.66463  0.6225
-#> a.1                 1.88191  1.66491  2.0989
-#> SD.parent_0         2.81628  0.78922  4.8433
-#> SD.log_k_A1         1.78751  0.42105  3.1540
-#> SD.f_parent_qlogis  0.45016  0.16116  0.7391
-#> SD.log_k1           1.06923  0.31676  1.8217
-#> SD.log_k2           2.03768  0.70938  3.3660
-#> SD.g_qlogis         0.44024 -0.09262  0.9731
-#> 
-#> Correlation: 
-#>                 parnt_0 lg_k_A1 f_prnt_ log_k1  log_k2 
-#> log_k_A1        -0.0147                                
-#> f_parent_qlogis -0.0269  0.0573                        
-#> log_k1           0.0263 -0.0011 -0.0040                
-#> log_k2           0.0020  0.0065 -0.0002 -0.0776        
-#> g_qlogis        -0.0248 -0.0180 -0.0004 -0.0903 -0.0603
-#> 
-#> Random effects:
-#>                      est.    lower  upper
-#> SD.parent_0        2.8163  0.78922 4.8433
-#> SD.log_k_A1        1.7875  0.42105 3.1540
-#> SD.f_parent_qlogis 0.4502  0.16116 0.7391
-#> SD.log_k1          1.0692  0.31676 1.8217
-#> SD.log_k2          2.0377  0.70938 3.3660
-#> SD.g_qlogis        0.4402 -0.09262 0.9731
-#> 
-#> Variance model:
-#>      est. lower upper
-#> a.1 1.882 1.665 2.099
-#> 
-#> Backtransformed parameters:
-#>                     est.     lower    upper
-#> parent_0       93.704015 9.104e+01 96.36699
-#> k_A1            0.002916 4.692e-04  0.01812
-#> f_parent_to_A1  0.277443 2.043e-01  0.36475
-#> k1              0.094880 3.357e-02  0.26813
-#> k2              0.022453 3.553e-03  0.14191
-#> g               0.494731 3.397e-01  0.65078
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_A1   0.2774
-#> parent_sink 0.7226
-#> 
-#> Estimated disappearance times:
-#>         DT50   DT90 DT50back DT50_k1 DT50_k2
-#> parent  14.0  72.38    21.79   7.306   30.87
-#> A1     237.7 789.68       NA      NA      NA
-#> 
-#> Data:
-#>          ds   name time observed predicted residual   std standardized
-#>   Dataset 6 parent    0     97.2  95.70025  1.49975 1.882      0.79693
-#>   Dataset 6 parent    0     96.4  95.70025  0.69975 1.882      0.37183
-#>   Dataset 6 parent    3     71.1  71.44670 -0.34670 1.882     -0.18423
-#>   Dataset 6 parent    3     69.2  71.44670 -2.24670 1.882     -1.19384
-#>   Dataset 6 parent    6     58.1  56.59283  1.50717 1.882      0.80087
-#>   Dataset 6 parent    6     56.6  56.59283  0.00717 1.882      0.00381
-#>   Dataset 6 parent   10     44.4  44.56648 -0.16648 1.882     -0.08847
-#>   Dataset 6 parent   10     43.4  44.56648 -1.16648 1.882     -0.61984
-#>   Dataset 6 parent   20     33.3  29.76020  3.53980 1.882      1.88096
-#>   Dataset 6 parent   20     29.2  29.76020 -0.56020 1.882     -0.29767
-#>   Dataset 6 parent   34     17.6  19.39208 -1.79208 1.882     -0.95226
-#>   Dataset 6 parent   34     18.0  19.39208 -1.39208 1.882     -0.73971
-#>   Dataset 6 parent   55     10.5  10.55761 -0.05761 1.882     -0.03061
-#>   Dataset 6 parent   55      9.3  10.55761 -1.25761 1.882     -0.66826
-#>   Dataset 6 parent   90      4.5   3.84742  0.65258 1.882      0.34676
-#>   Dataset 6 parent   90      4.7   3.84742  0.85258 1.882      0.45304
-#>   Dataset 6 parent  112      3.0   2.03997  0.96003 1.882      0.51013
-#>   Dataset 6 parent  112      3.4   2.03997  1.36003 1.882      0.72268
-#>   Dataset 6 parent  132      2.3   1.14585  1.15415 1.882      0.61328
-#>   Dataset 6 parent  132      2.7   1.14585  1.55415 1.882      0.82583
-#>   Dataset 6     A1    3      4.3   4.86054 -0.56054 1.882     -0.29786
-#>   Dataset 6     A1    3      4.6   4.86054 -0.26054 1.882     -0.13844
-#>   Dataset 6     A1    6      7.0   7.74179 -0.74179 1.882     -0.39417
-#>   Dataset 6     A1    6      7.2   7.74179 -0.54179 1.882     -0.28789
-#>   Dataset 6     A1   10      8.2   9.94048 -1.74048 1.882     -0.92485
-#>   Dataset 6     A1   10      8.0   9.94048 -1.94048 1.882     -1.03112
-#>   Dataset 6     A1   20     11.0  12.19109 -1.19109 1.882     -0.63291
-#>   Dataset 6     A1   20     13.7  12.19109  1.50891 1.882      0.80180
-#>   Dataset 6     A1   34     11.5  13.10706 -1.60706 1.882     -0.85395
-#>   Dataset 6     A1   34     12.7  13.10706 -0.40706 1.882     -0.21630
-#>   Dataset 6     A1   55     14.9  13.06131  1.83869 1.882      0.97703
-#>   Dataset 6     A1   55     14.5  13.06131  1.43869 1.882      0.76448
-#>   Dataset 6     A1   90     12.1  11.54495  0.55505 1.882      0.29494
-#>   Dataset 6     A1   90     12.3  11.54495  0.75505 1.882      0.40122
-#>   Dataset 6     A1  112      9.9  10.31533 -0.41533 1.882     -0.22070
-#>   Dataset 6     A1  112     10.2  10.31533 -0.11533 1.882     -0.06128
-#>   Dataset 6     A1  132      8.8   9.20222 -0.40222 1.882     -0.21373
-#>   Dataset 6     A1  132      7.8   9.20222 -1.40222 1.882     -0.74510
-#>   Dataset 7 parent    0     93.6  90.82357  2.77643 1.882      1.47532
-#>   Dataset 7 parent    0     92.3  90.82357  1.47643 1.882      0.78453
-#>   Dataset 7 parent    3     87.0  84.73448  2.26552 1.882      1.20384
-#>   Dataset 7 parent    3     82.2  84.73448 -2.53448 1.882     -1.34675
-#>   Dataset 7 parent    7     74.0  77.65013 -3.65013 1.882     -1.93958
-#>   Dataset 7 parent    7     73.9  77.65013 -3.75013 1.882     -1.99272
-#>   Dataset 7 parent   14     64.2  67.60639 -3.40639 1.882     -1.81007
-#>   Dataset 7 parent   14     69.5  67.60639  1.89361 1.882      1.00621
-#>   Dataset 7 parent   30     54.0  52.53663  1.46337 1.882      0.77760
-#>   Dataset 7 parent   30     54.6  52.53663  2.06337 1.882      1.09642
-#>   Dataset 7 parent   60     41.1  39.42728  1.67272 1.882      0.88884
-#>   Dataset 7 parent   60     38.4  39.42728 -1.02728 1.882     -0.54587
-#>   Dataset 7 parent   90     32.5  33.76360 -1.26360 1.882     -0.67144
-#>   Dataset 7 parent   90     35.5  33.76360  1.73640 1.882      0.92268
-#>   Dataset 7 parent  120     28.1  30.39975 -2.29975 1.882     -1.22203
-#>   Dataset 7 parent  120     29.0  30.39975 -1.39975 1.882     -0.74379
-#>   Dataset 7 parent  180     26.5  25.62379  0.87621 1.882      0.46559
-#>   Dataset 7 parent  180     27.6  25.62379  1.97621 1.882      1.05010
-#>   Dataset 7     A1    3      3.9   2.70005  1.19995 1.882      0.63762
-#>   Dataset 7     A1    3      3.1   2.70005  0.39995 1.882      0.21252
-#>   Dataset 7     A1    7      6.9   5.83475  1.06525 1.882      0.56605
-#>   Dataset 7     A1    7      6.6   5.83475  0.76525 1.882      0.40663
-#>   Dataset 7     A1   14     10.4  10.26142  0.13858 1.882      0.07364
-#>   Dataset 7     A1   14      8.3  10.26142 -1.96142 1.882     -1.04225
-#>   Dataset 7     A1   30     14.4  16.82999 -2.42999 1.882     -1.29123
-#>   Dataset 7     A1   30     13.7  16.82999 -3.12999 1.882     -1.66319
-#>   Dataset 7     A1   60     22.1  22.32486 -0.22486 1.882     -0.11949
-#>   Dataset 7     A1   60     22.3  22.32486 -0.02486 1.882     -0.01321
-#>   Dataset 7     A1   90     27.5  24.45927  3.04073 1.882      1.61576
-#>   Dataset 7     A1   90     25.4  24.45927  0.94073 1.882      0.49988
-#>   Dataset 7     A1  120     28.0  25.54862  2.45138 1.882      1.30260
-#>   Dataset 7     A1  120     26.6  25.54862  1.05138 1.882      0.55868
-#>   Dataset 7     A1  180     25.8  26.82277 -1.02277 1.882     -0.54347
-#>   Dataset 7     A1  180     25.3  26.82277 -1.52277 1.882     -0.80916
-#>   Dataset 8 parent    0     91.9  91.16791  0.73209 1.882      0.38901
-#>   Dataset 8 parent    0     90.8  91.16791 -0.36791 1.882     -0.19550
-#>   Dataset 8 parent    1     64.9  67.58358 -2.68358 1.882     -1.42598
-#>   Dataset 8 parent    1     66.2  67.58358 -1.38358 1.882     -0.73520
-#>   Dataset 8 parent    3     43.5  41.62086  1.87914 1.882      0.99853
-#>   Dataset 8 parent    3     44.1  41.62086  2.47914 1.882      1.31735
-#>   Dataset 8 parent    8     18.3  19.60116 -1.30116 1.882     -0.69140
-#>   Dataset 8 parent    8     18.1  19.60116 -1.50116 1.882     -0.79768
-#>   Dataset 8 parent   14     10.2  10.63101 -0.43101 1.882     -0.22903
-#>   Dataset 8 parent   14     10.8  10.63101  0.16899 1.882      0.08980
-#>   Dataset 8 parent   27      4.9   3.12435  1.77565 1.882      0.94354
-#>   Dataset 8 parent   27      3.3   3.12435  0.17565 1.882      0.09334
-#>   Dataset 8 parent   48      1.6   0.43578  1.16422 1.882      0.61864
-#>   Dataset 8 parent   48      1.5   0.43578  1.06422 1.882      0.56550
-#>   Dataset 8 parent   70      1.1   0.05534  1.04466 1.882      0.55510
-#>   Dataset 8 parent   70      0.9   0.05534  0.84466 1.882      0.44883
-#>   Dataset 8     A1    1      9.6   7.63450  1.96550 1.882      1.04442
-#>   Dataset 8     A1    1      7.7   7.63450  0.06550 1.882      0.03481
-#>   Dataset 8     A1    3     15.0  15.52593 -0.52593 1.882     -0.27947
-#>   Dataset 8     A1    3     15.1  15.52593 -0.42593 1.882     -0.22633
-#>   Dataset 8     A1    8     21.2  20.32192  0.87808 1.882      0.46659
-#>   Dataset 8     A1    8     21.1  20.32192  0.77808 1.882      0.41345
-#>   Dataset 8     A1   14     19.7  20.09721 -0.39721 1.882     -0.21107
-#>   Dataset 8     A1   14     18.9  20.09721 -1.19721 1.882     -0.63617
-#>   Dataset 8     A1   27     17.5  16.37477  1.12523 1.882      0.59792
-#>   Dataset 8     A1   27     15.9  16.37477 -0.47477 1.882     -0.25228
-#>   Dataset 8     A1   48      9.5  10.13141 -0.63141 1.882     -0.33551
-#>   Dataset 8     A1   48      9.8  10.13141 -0.33141 1.882     -0.17610
-#>   Dataset 8     A1   70      6.2   5.81827  0.38173 1.882      0.20284
-#>   Dataset 8     A1   70      6.1   5.81827  0.28173 1.882      0.14970
-#>   Dataset 9 parent    0     99.8  97.48728  2.31272 1.882      1.22892
-#>   Dataset 9 parent    0     98.3  97.48728  0.81272 1.882      0.43186
-#>   Dataset 9 parent    1     77.1  79.29476 -2.19476 1.882     -1.16624
-#>   Dataset 9 parent    1     77.2  79.29476 -2.09476 1.882     -1.11310
-#>   Dataset 9 parent    3     59.0  55.67060  3.32940 1.882      1.76915
-#>   Dataset 9 parent    3     58.1  55.67060  2.42940 1.882      1.29092
-#>   Dataset 9 parent    8     27.4  31.57871 -4.17871 1.882     -2.22046
-#>   Dataset 9 parent    8     29.2  31.57871 -2.37871 1.882     -1.26398
-#>   Dataset 9 parent   14     19.1  22.51546 -3.41546 1.882     -1.81489
-#>   Dataset 9 parent   14     29.6  22.51546  7.08454 1.882      3.76454
-#>   Dataset 9 parent   27     10.1  14.09074 -3.99074 1.882     -2.12057
-#>   Dataset 9 parent   27     18.2  14.09074  4.10926 1.882      2.18355
-#>   Dataset 9 parent   48      4.5   6.95747 -2.45747 1.882     -1.30584
-#>   Dataset 9 parent   48      9.1   6.95747  2.14253 1.882      1.13848
-#>   Dataset 9 parent   70      2.3   3.32472 -1.02472 1.882     -0.54451
-#>   Dataset 9 parent   70      2.9   3.32472 -0.42472 1.882     -0.22569
-#>   Dataset 9 parent   91      2.0   1.64300  0.35700 1.882      0.18970
-#>   Dataset 9 parent   91      1.8   1.64300  0.15700 1.882      0.08343
-#>   Dataset 9 parent  120      2.0   0.62073  1.37927 1.882      0.73291
-#>   Dataset 9 parent  120      2.2   0.62073  1.57927 1.882      0.83918
-#>   Dataset 9     A1    1      4.2   3.64568  0.55432 1.882      0.29455
-#>   Dataset 9     A1    1      3.9   3.64568  0.25432 1.882      0.13514
-#>   Dataset 9     A1    3      7.4   8.30173 -0.90173 1.882     -0.47916
-#>   Dataset 9     A1    3      7.9   8.30173 -0.40173 1.882     -0.21347
-#>   Dataset 9     A1    8     14.5  12.71589  1.78411 1.882      0.94803
-#>   Dataset 9     A1    8     13.7  12.71589  0.98411 1.882      0.52293
-#>   Dataset 9     A1   14     14.2  13.90452  0.29548 1.882      0.15701
-#>   Dataset 9     A1   14     12.2  13.90452 -1.70452 1.882     -0.90574
-#>   Dataset 9     A1   27     13.7  14.15523 -0.45523 1.882     -0.24190
-#>   Dataset 9     A1   27     13.2  14.15523 -0.95523 1.882     -0.50759
-#>   Dataset 9     A1   48     13.6  13.31038  0.28962 1.882      0.15389
-#>   Dataset 9     A1   48     15.4  13.31038  2.08962 1.882      1.11037
-#>   Dataset 9     A1   70     10.4  11.85965 -1.45965 1.882     -0.77562
-#>   Dataset 9     A1   70     11.6  11.85965 -0.25965 1.882     -0.13797
-#>   Dataset 9     A1   91     10.0  10.36294 -0.36294 1.882     -0.19286
-#>   Dataset 9     A1   91      9.5  10.36294 -0.86294 1.882     -0.45855
-#>   Dataset 9     A1  120      9.1   8.43003  0.66997 1.882      0.35601
-#>   Dataset 9     A1  120      9.0   8.43003  0.56997 1.882      0.30287
-#>  Dataset 10 parent    0     96.1  93.95603  2.14397 1.882      1.13925
-#>  Dataset 10 parent    0     94.3  93.95603  0.34397 1.882      0.18278
-#>  Dataset 10 parent    8     73.9  77.70592 -3.80592 1.882     -2.02237
-#>  Dataset 10 parent    8     73.9  77.70592 -3.80592 1.882     -2.02237
-#>  Dataset 10 parent   14     69.4  70.04570 -0.64570 1.882     -0.34311
-#>  Dataset 10 parent   14     73.1  70.04570  3.05430 1.882      1.62298
-#>  Dataset 10 parent   21     65.6  64.01710  1.58290 1.882      0.84111
-#>  Dataset 10 parent   21     65.3  64.01710  1.28290 1.882      0.68170
-#>  Dataset 10 parent   41     55.9  54.98434  0.91566 1.882      0.48656
-#>  Dataset 10 parent   41     54.4  54.98434 -0.58434 1.882     -0.31050
-#>  Dataset 10 parent   63     47.0  49.87137 -2.87137 1.882     -1.52577
-#>  Dataset 10 parent   63     49.3  49.87137 -0.57137 1.882     -0.30361
-#>  Dataset 10 parent   91     44.7  45.06727 -0.36727 1.882     -0.19516
-#>  Dataset 10 parent   91     46.7  45.06727  1.63273 1.882      0.86759
-#>  Dataset 10 parent  120     42.1  40.76402  1.33598 1.882      0.70991
-#>  Dataset 10 parent  120     41.3  40.76402  0.53598 1.882      0.28481
-#>  Dataset 10     A1    8      3.3   4.14599 -0.84599 1.882     -0.44954
-#>  Dataset 10     A1    8      3.4   4.14599 -0.74599 1.882     -0.39640
-#>  Dataset 10     A1   14      3.9   6.08478 -2.18478 1.882     -1.16093
-#>  Dataset 10     A1   14      2.9   6.08478 -3.18478 1.882     -1.69231
-#>  Dataset 10     A1   21      6.4   7.59411 -1.19411 1.882     -0.63452
-#>  Dataset 10     A1   21      7.2   7.59411 -0.39411 1.882     -0.20942
-#>  Dataset 10     A1   41      9.1   9.78292 -0.68292 1.882     -0.36289
-#>  Dataset 10     A1   41      8.5   9.78292 -1.28292 1.882     -0.68171
-#>  Dataset 10     A1   63     11.7  10.93274  0.76726 1.882      0.40770
-#>  Dataset 10     A1   63     12.0  10.93274  1.06726 1.882      0.56711
-#>  Dataset 10     A1   91     13.3  11.93986  1.36014 1.882      0.72274
-#>  Dataset 10     A1   91     13.2  11.93986  1.26014 1.882      0.66961
-#>  Dataset 10     A1  120     14.3  12.79238  1.50762 1.882      0.80111
-#>  Dataset 10     A1  120     12.1  12.79238 -0.69238 1.882     -0.36791
-
-# The following takes about 6 minutes
-f_saem_dfop_sfo_deSolve <- saem(f_mmkin["DFOP-SFO", ], solution_type = "deSolve",
-  nbiter.saemix = c(200, 80))
-#> DINTDY-  T (=R1) illegal      
-#> In above message, R1 = 70
-#>  
-#>       T not in interval TCUR - HU (= R1) to TCUR (=R2)      
-#> In above message, R1 = 53.1122, R2 = 56.6407
-#>  
-#> DINTDY-  T (=R1) illegal      
-#> In above message, R1 = 91
-#>  
-#>       T not in interval TCUR - HU (= R1) to TCUR (=R2)      
-#> In above message, R1 = 53.1122, R2 = 56.6407
-#>  
-#> DLSODA-  Trouble in DINTDY.  ITASK = I1, TOUT = R1
-#> In above message, I1 = 1
-#>  
-#> In above message, R1 = 91
-#>  
-#> Error in deSolve::lsoda(y = odeini, times = outtimes, func = lsoda_func,  : 
-#>   illegal input detected before taking any integration steps - see written message
-
-#anova(
-#  f_saem_dfop_sfo,
-#  f_saem_dfop_sfo_deSolve))
-
-# If the model supports it, we can also use eigenvalue based solutions, which
-# take a similar amount of time
-#f_saem_sfo_sfo_eigen <- saem(f_mmkin["SFO-SFO", ], solution_type = "eigen",
-#  control = list(nbiter.saemix = c(200, 80), nbdisplay = 10))
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
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-  
      Site built with pkgdown 2.0.7.
      
-
      
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-  
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diff --git a/docs/dev/reference/schaefer07_complex_case-1.png b/docs/dev/reference/schaefer07_complex_case-1.png
deleted file mode 100644
index 7622ae7f..00000000
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diff --git a/docs/dev/reference/schaefer07_complex_case.html b/docs/dev/reference/schaefer07_complex_case.html
deleted file mode 100644
index 880e5ac0..00000000
--- a/docs/dev/reference/schaefer07_complex_case.html
+++ /dev/null
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-
-Metabolism data set used for checking the software quality of KinGUI — schaefer07_complex_case • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Metabolism data set used for checking the software quality of KinGUI
      
-    
-    
-    
      
-
-    
      
-    
      This dataset was used for a comparison of KinGUI and ModelMaker to check the
-  software quality of KinGUI in the original publication (Schäfer et al., 2007).
-  The results from the fitting are also included.
      
-    
      
-
-    
      
-    
      schaefer07_complex_case
      
-    
      
-
-    
      
-    
      Format
      
-    
      The data set is a data frame with 8 observations on the following 6 variables.
      time
      
-
      a numeric vector
      
-
-    
      parent
      
-
      a numeric vector
      
-
-    
      A1
      
-
      a numeric vector
      
-
-    
      B1
      
-
      a numeric vector
      
-
-    
      C1
      
-
      a numeric vector
      
-
-    
      A2
      
-
      a numeric vector
      
-
-  
-
      The results are a data frame with 14 results for different parameter values
      
-    
      
-    
      
-    
      References
      
-    
      Schäfer D, Mikolasch B, Rainbird P and Harvey B (2007). KinGUI: a new kinetic
-  software tool for evaluations according to FOCUS degradation kinetics. In: Del
-  Re AAM, Capri E, Fragoulis G and Trevisan M (Eds.). Proceedings of the XIII
-  Symposium Pesticide Chemistry, Piacenza, 2007, p. 916-923.
      
-    
      
-
-    
      
-    
      Examples
      
-    
      data <- mkin_wide_to_long(schaefer07_complex_case, time = "time")
-model <- mkinmod(
-  parent = list(type = "SFO", to = c("A1", "B1", "C1"), sink = FALSE),
-  A1 = list(type = "SFO", to = "A2"),
-  B1 = list(type = "SFO"),
-  C1 = list(type = "SFO"),
-  A2 = list(type = "SFO"), use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-  # \dontrun{
-    fit <- mkinfit(model, data, quiet = TRUE)
-    plot(fit)
-
-    endpoints(fit)
-#> $ff
-#>   parent_A1   parent_B1   parent_C1 parent_sink       A1_A2     A1_sink 
-#>   0.3809620   0.1954667   0.4235713   0.0000000   0.4479619   0.5520381 
-#> 
-#> $distimes
-#>            DT50      DT90
-#> parent 13.95078  46.34350
-#> A1     49.75342 165.27728
-#> B1     37.26908 123.80520
-#> C1     11.23131  37.30961
-#> A2     28.50624  94.69567
-#> 
-  # }
- # Compare with the results obtained in the original publication
- print(schaefer07_complex_results)
-#>         compound          parameter  KinGUI ModelMaker deviation
-#> 1         parent   degradation rate  0.0496     0.0506       2.0
-#> 2         parent               DT50 13.9900    13.6900       2.2
-#> 3  metabolite A1 formation fraction  0.3803     0.3696       2.9
-#> 4  metabolite A1   degradation rate  0.0139     0.0136       2.2
-#> 5  metabolite A1               DT50 49.9600    50.8900       1.8
-#> 6  metabolite B1 formation fraction  0.1866     0.1818       2.6
-#> 7  metabolite B1   degradation rate  0.0175     0.0172       1.7
-#> 8  metabolite B1               DT50 39.6100    40.2400       1.6
-#> 9  metabolite C1 formation fraction  0.4331     0.4486       3.5
-#> 10 metabolite C1   degradation rate  0.0638     0.0700       8.9
-#> 11 metabolite C1               DT50 10.8700     9.9000       9.8
-#> 12 metabolite A2 formation fraction  0.4529     0.4559       0.7
-#> 13 metabolite A2   degradation rate  0.0245     0.0244       0.4
-#> 14 metabolite A2               DT50 28.2400    28.4500       0.7
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
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-  
-
-  
-
diff --git a/docs/dev/reference/set_nd_nq.html b/docs/dev/reference/set_nd_nq.html
deleted file mode 100644
index 6f4ae169..00000000
--- a/docs/dev/reference/set_nd_nq.html
+++ /dev/null
@@ -1,278 +0,0 @@
-
-Set non-detects and unquantified values in residue series without replicates — set_nd_nq • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Set non-detects and unquantified values in residue series without replicates
      
-    Source: R/set_nd_nq.R
-    
-    
      
-
-    
      
-    
      This function automates replacing unquantified values in residue time and
-depth series. For time series, the function performs part of the residue
-processing proposed in the FOCUS kinetics guidance for parent compounds
-and metabolites. For two-dimensional residue series over time and depth,
-it automates the proposal of Boesten et al (2015).
      
-    
      
-
-    
      
-    
      set_nd_nq(res_raw, lod, loq = NA, time_zero_presence = FALSE)
-
-set_nd_nq_focus(
-  res_raw,
-  lod,
-  loq = NA,
-  set_first_sample_nd = TRUE,
-  first_sample_nd_value = 0,
-  ignore_below_loq_after_first_nd = TRUE
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      res_raw
      
-
      Character vector of a residue time series, or matrix of
-residue values with rows representing depth profiles for a specific sampling
-time, and columns representing time series of residues at the same depth.
-Values below the limit of detection (lod) have to be coded as "nd", values
-between the limit of detection and the limit of quantification, if any, have
-to be coded as "nq". Samples not analysed have to be coded as "na". All
-values that are not "na", "nd" or "nq" have to be coercible to numeric
      
-
-
-
      lod
      
-
      Limit of detection (numeric)
      
-
-
-
      loq
      
-
      Limit of quantification(numeric). Must be specified if the FOCUS rule to
-stop after the first non-detection is to be applied
      
-
-
-
      time_zero_presence
      
-
      Do we assume that residues occur at time zero?
-This only affects samples from the first sampling time that have been
-reported as "nd" (not detected).
      
-
-
-
      set_first_sample_nd
      
-
      Should the first sample be set to "first_sample_nd_value"
-in case it is a non-detection?
      
-
-
-
      first_sample_nd_value
      
-
      Value to be used for the first sample if it is a non-detection
      
-
-
-
      ignore_below_loq_after_first_nd
      
-
      Should we ignore values below the LOQ after the first
-non-detection that occurs after the quantified values?
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      A numeric vector, if a vector was supplied, or a numeric matrix otherwise
      
-    
      
-    
      
-    
      Functions
      
-    
-
      • set_nd_nq_focus(): Set non-detects in residue time series according to FOCUS rules
        • 
-
      
-    
      
-    
      References
      
-    
      Boesten, J. J. T. I., van der Linden, A. M. A., Beltman, W. H.
-J. and Pol, J. W. (2015). Leaching of plant protection products and their
-transformation products; Proposals for improving the assessment of leaching
-to groundwater in the Netherlands — Version 2. Alterra report 2630, Alterra
-Wageningen UR (University & Research centre)
      
-
      FOCUS (2014) Generic Guidance for Estimating Persistence and Degradation
-Kinetics from Environmental Fate Studies on Pesticides in EU Registration, Version 1.1,
-18 December 2014, p. 251
      
-    
      
-
-    
      
-    
      Examples
      
-    
      # FOCUS (2014) p. 75/76 and 131/132
-parent_1 <- c(.12, .09, .05, .03, "nd", "nd", "nd", "nd", "nd", "nd")
-set_nd_nq(parent_1, 0.02)
-#>  [1] 0.12 0.09 0.05 0.03 0.01   NA   NA   NA   NA   NA
-parent_2 <- c(.12, .09, .05, .03, "nd", "nd", .03, "nd", "nd", "nd")
-set_nd_nq(parent_2, 0.02)
-#>  [1] 0.12 0.09 0.05 0.03 0.01 0.01 0.03 0.01   NA   NA
-set_nd_nq_focus(parent_2, 0.02, loq = 0.05)
-#>  [1] 0.12 0.09 0.05 0.03 0.01   NA   NA   NA   NA   NA
-parent_3 <- c(.12, .09, .05, .03, "nd", "nd", .06, "nd", "nd", "nd")
-set_nd_nq(parent_3, 0.02)
-#>  [1] 0.12 0.09 0.05 0.03 0.01 0.01 0.06 0.01   NA   NA
-set_nd_nq_focus(parent_3, 0.02, loq = 0.05)
-#>  [1] 0.12 0.09 0.05 0.03 0.01 0.01 0.06 0.01   NA   NA
-metabolite <- c("nd", "nd", "nd", 0.03, 0.06, 0.10, 0.11, 0.10, 0.09, 0.05, 0.03, "nd", "nd")
-set_nd_nq(metabolite, 0.02)
-#>  [1]   NA   NA 0.01 0.03 0.06 0.10 0.11 0.10 0.09 0.05 0.03 0.01   NA
-set_nd_nq_focus(metabolite, 0.02, 0.05)
-#>  [1] 0.00   NA 0.01 0.03 0.06 0.10 0.11 0.10 0.09 0.05 0.03 0.01   NA
-#
-# Boesten et al. (2015), p. 57/58
-table_8 <- matrix(
-  c(10, 10, rep("nd", 4),
-    10, 10, rep("nq", 2), rep("nd", 2),
-    10, 10, 10, "nq", "nd", "nd",
-    "nq", 10, "nq", rep("nd", 3),
-    "nd", "nq", "nq", rep("nd", 3),
-    rep("nd", 6), rep("nd", 6)),
-  ncol = 6, byrow = TRUE)
-set_nd_nq(table_8, 0.5, 1.5, time_zero_presence = TRUE)
-#>       [,1]  [,2]  [,3] [,4] [,5] [,6]
-#> [1,] 10.00 10.00  0.25 0.25   NA   NA
-#> [2,] 10.00 10.00  1.00 1.00 0.25   NA
-#> [3,] 10.00 10.00 10.00 1.00 0.25   NA
-#> [4,]  1.00 10.00  1.00 0.25   NA   NA
-#> [5,]  0.25  1.00  1.00 0.25   NA   NA
-#> [6,]    NA  0.25  0.25   NA   NA   NA
-#> [7,]    NA    NA    NA   NA   NA   NA
-table_10 <- matrix(
-  c(10, 10, rep("nd", 4),
-    10, 10, rep("nd", 4),
-    10, 10, 10, rep("nd", 3),
-    "nd", 10, rep("nd", 4),
-    rep("nd", 18)),
-  ncol = 6, byrow = TRUE)
-set_nd_nq(table_10, 0.5, time_zero_presence = TRUE)
-#>       [,1]  [,2]  [,3] [,4] [,5] [,6]
-#> [1,] 10.00 10.00  0.25   NA   NA   NA
-#> [2,] 10.00 10.00  0.25   NA   NA   NA
-#> [3,] 10.00 10.00 10.00 0.25   NA   NA
-#> [4,]  0.25 10.00  0.25   NA   NA   NA
-#> [5,]    NA  0.25    NA   NA   NA   NA
-#> [6,]    NA    NA    NA   NA   NA   NA
-#> [7,]    NA    NA    NA   NA   NA   NA
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/sigma_twocomp-1.png b/docs/dev/reference/sigma_twocomp-1.png
deleted file mode 100644
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diff --git a/docs/dev/reference/sigma_twocomp.html b/docs/dev/reference/sigma_twocomp.html
deleted file mode 100644
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-
-Two-component error model — sigma_twocomp • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Two-component error model
      
-    Source: R/sigma_twocomp.R
-    
-    
      
-
-    
      
-    
      Function describing the standard deviation of the measurement error in
-dependence of the measured value \(y\):
      
-    
      
-
-    
      
-    
      sigma_twocomp(y, sigma_low, rsd_high)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      y
      
-
      The magnitude of the observed value
      
-
-
-
      sigma_low
      
-
      The asymptotic minimum of the standard deviation for low
-observed values
      
-
-
-
      rsd_high
      
-
      The coefficient describing the increase of the standard
-deviation with the magnitude of the observed value
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The standard deviation of the response variable.
      
-    
      
-    
      
-    
      Details
      
-    
      $$\sigma = \sqrt{ \sigma_{low}^2 + y^2 * {rsd}_{high}^2}$$ sigma =
-sqrt(sigma_low^2 + y^2 * rsd_high^2)
      
-
      This is the error model used for example by Werner et al. (1978). The model
-proposed by Rocke and Lorenzato (1995) can be written in this form as well,
-but assumes approximate lognormal distribution of errors for high values of
-y.
      
-    
      
-    
      
-    
      References
      
-    
      Werner, Mario, Brooks, Samuel H., and Knott, Lancaster B. (1978)
-Additive, Multiplicative, and Mixed Analytical Errors. Clinical Chemistry
-24(11), 1895-1898.
      
-
      Rocke, David M. and Lorenzato, Stefan (1995) A two-component model for
-measurement error in analytical chemistry. Technometrics 37(2), 176-184.
      
-
      Ranke J and Meinecke S (2019) Error Models for the Kinetic Evaluation of Chemical
-Degradation Data. Environments 6(12) 124
-doi:10.3390/environments6120124
-.
      
-    
      
-
-    
      
-    
      Examples
      
-    
      times <- c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-d_pred <- data.frame(time = times, parent = 100 * exp(- 0.03 * times))
-set.seed(123456)
-d_syn <- add_err(d_pred, function(y) sigma_twocomp(y, 1, 0.07),
-  reps = 2, n = 1)[[1]]
-f_nls <- nls(value ~ SSasymp(time, 0, parent_0, lrc), data = d_syn,
- start = list(parent_0 = 100, lrc = -3))
-library(nlme)
-f_gnls <- gnls(value ~ SSasymp(time, 0, parent_0, lrc),
-  data = d_syn, na.action = na.omit,
-  start = list(parent_0 = 100, lrc = -3))
-if (length(findFunction("varConstProp")) > 0) {
-  f_gnls_tc <- update(f_gnls, weights = varConstProp())
-  f_gnls_tc_sf <- update(f_gnls_tc, control = list(sigma = 1))
-}
-f_mkin <- mkinfit("SFO", d_syn, error_model = "const", quiet = TRUE)
-f_mkin_tc <- mkinfit("SFO", d_syn, error_model = "tc", quiet = TRUE)
-plot_res(f_mkin_tc, standardized = TRUE)
-
-AIC(f_nls, f_gnls, f_gnls_tc, f_gnls_tc_sf, f_mkin, f_mkin_tc)
-#>              df      AIC
-#> f_nls         3 114.4817
-#> f_gnls        3 114.4817
-#> f_gnls_tc     5 103.6447
-#> f_gnls_tc_sf  4 101.6447
-#> f_mkin        3 114.4817
-#> f_mkin_tc     4 101.6446
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
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-  
-
diff --git a/docs/dev/reference/status.html b/docs/dev/reference/status.html
deleted file mode 100644
index df3e3a44..00000000
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+++ /dev/null
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-
-Method to get status information for fit array objects — status • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Method to get status information for fit array objects
      
-    Source: R/status.R
-    
-    
      
-
-    
      
-    
      Method to get status information for fit array objects
      
-    
      
-
-    
      
-    
      status(object, ...)
-
-# S3 method for mmkin
-status(object, ...)
-
-# S3 method for status.mmkin
-print(x, ...)
-
-# S3 method for mhmkin
-status(object, ...)
-
-# S3 method for status.mhmkin
-print(x, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      The object to investigate
      
-
-
-
      ...
      
-
      For potential future extensions
      
-
-
-
      x
      
-
      The object to be printed
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      An object with the same dimensions as the fit array
-suitable printing method.
      
-    
      
-
-    
      
-    
      Examples
      
-    
      # \dontrun{
-fits <- mmkin(
-  c("SFO", "FOMC"),
-  list("FOCUS A" = FOCUS_2006_A,
-       "FOCUS B" = FOCUS_2006_C),
-  quiet = TRUE)
-status(fits)
-#>       dataset
-#> model  FOCUS A FOCUS B
-#>   SFO  OK      OK     
-#>   FOMC OK      OK     
-#> 
-#> OK: No warnings
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/summary.mkinfit.html b/docs/dev/reference/summary.mkinfit.html
deleted file mode 100644
index f627c2f6..00000000
--- a/docs/dev/reference/summary.mkinfit.html
+++ /dev/null
@@ -1,334 +0,0 @@
-
-Summary method for class "mkinfit" — summary.mkinfit • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Summary method for class "mkinfit"
      
-    Source: R/summary.mkinfit.R
-    
-    
      
-
-    
      
-    
      Lists model equations, initial parameter values, optimised parameters with
-some uncertainty statistics, the chi2 error levels calculated according to
-FOCUS guidance (2006) as defined therein, formation fractions, DT50 values
-and optionally the data, consisting of observed, predicted and residual
-values.
      
-    
      
-
-    
      
-    
      # S3 method for mkinfit
-summary(object, data = TRUE, distimes = TRUE, alpha = 0.05, ...)
-
-# S3 method for summary.mkinfit
-print(x, digits = max(3, getOption("digits") - 3), ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      an object of class mkinfit.
      
-
-
-
      data
      
-
      logical, indicating whether the data should be included in the
-summary.
      
-
-
-
      distimes
      
-
      logical, indicating whether DT50 and DT90 values should be
-included.
      
-
-
-
      alpha
      
-
      error level for confidence interval estimation from t
-distribution
      
-
-
-
      ...
      
-
      optional arguments passed to methods like print.
      
-
-
-
      x
      
-
      an object of class summary.mkinfit.
      
-
-
-
      digits
      
-
      Number of digits to use for printing
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The summary function returns a list with components, among others
      
-
      version, Rversion
      
-
      The mkin and R versions used
      
-
-
      date.fit, date.summary
      
-
      The dates where the fit and the summary were
-produced
      
-
-
      diffs
      
-
      The differential equations used in the model
      
-
-
      use_of_ff
      
-
      Was maximum or minimum use made of formation fractions
      
-
-
      bpar
      
-
      Optimised and backtransformed
-parameters
      
-
-
      data
      
-
      The data (see Description above).
      
-
-
      start
      
-
      The starting values and bounds, if applicable, for optimised
-parameters.
      
-
-
      fixed
      
-
      The values of fixed parameters.
      
-
-
      errmin 
      
-
      The chi2 error levels for
-each observed variable.
      
-
-
      bparms.ode
      
-
      All backtransformed ODE
-parameters, for use as starting parameters for related models.
      
-
-
      errparms
      
-
      Error model parameters.
      
-
-
      ff
      
-
      The estimated formation fractions derived from the fitted
-model.
      
-
-
      distimes
      
-
      The DT50 and DT90 values for each observed variable.
      
-
-
      SFORB
      
-
      If applicable, eigenvalues and fractional eigenvector component
-g of SFORB systems in the model.
      
-
-
      The print method is called for its side effect, i.e. printing the summary.
      
-    
      
-    
      
-    
      References
      
-    
      FOCUS (2006) “Guidance Document on Estimating Persistence
-and Degradation Kinetics from Environmental Fate Studies on Pesticides in
-EU Registration” Report of the FOCUS Work Group on Degradation Kinetics,
-EC Document Reference Sanco/10058/2005 version 2.0, 434 pp,
-http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-  summary(mkinfit("SFO", FOCUS_2006_A, quiet = TRUE))
-#> mkin version used for fitting:    1.2.3 
-#> R version used for fitting:       4.2.3 
-#> Date of fit:     Sun Apr 16 08:34:39 2023 
-#> Date of summary: Sun Apr 16 08:34:39 2023 
-#> 
-#> Equations:
-#> d_parent/dt = - k_parent * parent
-#> 
-#> Model predictions using solution type analytical 
-#> 
-#> Fitted using 131 model solutions performed in 0.009 s
-#> 
-#> Error model: Constant variance 
-#> 
-#> Error model algorithm: OLS 
-#> 
-#> Starting values for parameters to be optimised:
-#>           value   type
-#> parent_0 101.24  state
-#> k_parent   0.10 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                   value lower upper
-#> parent_0     101.240000  -Inf   Inf
-#> log_k_parent  -2.302585  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#> None
-#> 
-#> Results:
-#> 
-#>        AIC     BIC    logLik
-#>   55.28197 55.5203 -24.64099
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>              Estimate Std. Error  Lower   Upper
-#> parent_0      109.200    3.70400 99.630 118.700
-#> log_k_parent   -3.291    0.09176 -3.527  -3.055
-#> sigma           5.266    1.31600  1.882   8.649
-#> 
-#> Parameter correlation:
-#>               parent_0 log_k_parent     sigma
-#> parent_0     1.000e+00    5.428e-01 1.642e-07
-#> log_k_parent 5.428e-01    1.000e+00 2.507e-07
-#> sigma        1.642e-07    2.507e-07 1.000e+00
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>           Estimate t value    Pr(>t)   Lower     Upper
-#> parent_0 109.20000   29.47 4.218e-07 99.6300 118.70000
-#> k_parent   0.03722   10.90 5.650e-05  0.0294   0.04712
-#> sigma      5.26600    4.00 5.162e-03  1.8820   8.64900
-#> 
-#> FOCUS Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   8.385       2  6
-#> parent     8.385       2  6
-#> 
-#> Estimated disappearance times:
-#>         DT50  DT90
-#> parent 18.62 61.87
-#> 
-#> Data:
-#>  time variable observed predicted residual
-#>     0   parent   101.24   109.153  -7.9132
-#>     3   parent    99.27    97.622   1.6484
-#>     7   parent    90.11    84.119   5.9913
-#>    14   parent    72.19    64.826   7.3641
-#>    30   parent    29.71    35.738  -6.0283
-#>    62   parent     5.98    10.862  -4.8818
-#>    90   parent     1.54     3.831  -2.2911
-#>   118   parent     0.39     1.351  -0.9613
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/summary.mmkin.html b/docs/dev/reference/summary.mmkin.html
deleted file mode 100644
index c27f1634..00000000
--- a/docs/dev/reference/summary.mmkin.html
+++ /dev/null
@@ -1,196 +0,0 @@
-
-Summary method for class "mmkin" — summary.mmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Summary method for class "mmkin"
      
-    Source: R/summary.mmkin.R
-    
-    
      
-
-    
      
-    
      Shows status information on the mkinfit objects contained in the object
-and gives an overview of ill-defined parameters calculated by illparms.
      
-    
      
-
-    
      
-    
      # S3 method for mmkin
-summary(object, conf.level = 0.95, ...)
-
-# S3 method for summary.mmkin
-print(x, digits = max(3, getOption("digits") - 3), ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      an object of class mmkin
      
-
-
-
      conf.level
      
-
      confidence level for testing parameters
      
-
-
-
      ...
      
-
      optional arguments passed to methods like print.
      
-
-
-
      x
      
-
      an object of class summary.mmkin.
      
-
-
-
      digits
      
-
      number of digits to use for printing
      
-
-
      
-
-    
      
-    
      Examples
      
-    
      
-fits <- mmkin(
-  c("SFO", "FOMC"),
-  list("FOCUS A" = FOCUS_2006_A,
-       "FOCUS C" = FOCUS_2006_C),
-  quiet = TRUE, cores = 1)
-  summary(fits)
-#> Error model: Constant variance 
-#> Fitted in 0.509 s
-#> 
-#> Status:
-#>       dataset
-#> model  FOCUS A FOCUS C
-#>   SFO  OK      OK     
-#>   FOMC OK      OK     
-#> 
-#> OK: No warnings
-#> 
-#> Ill-defined parameters:
-#>       dataset
-#> model  FOCUS A                      FOCUS C
-#>   SFO                                      
-#>   FOMC parent_0, alpha, beta, sigma        
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/summary.nlme.mmkin.html b/docs/dev/reference/summary.nlme.mmkin.html
deleted file mode 100644
index cb2c20bd..00000000
--- a/docs/dev/reference/summary.nlme.mmkin.html
+++ /dev/null
@@ -1,435 +0,0 @@
-
-Summary method for class "nlme.mmkin" — summary.nlme.mmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Summary method for class "nlme.mmkin"
      
-    Source: R/summary.nlme.mmkin.R
-    
-    
      
-
-    
      
-    
      Lists model equations, initial parameter values, optimised parameters
-for fixed effects (population), random effects (deviations from the
-population mean) and residual error model, as well as the resulting
-endpoints such as formation fractions and DT50 values. Optionally
-(default is FALSE), the data are listed in full.
      
-    
      
-
-    
      
-    
      # S3 method for nlme.mmkin
-summary(
-  object,
-  data = FALSE,
-  verbose = FALSE,
-  distimes = TRUE,
-  alpha = 0.05,
-  ...
-)
-
-# S3 method for summary.nlme.mmkin
-print(x, digits = max(3, getOption("digits") - 3), verbose = x$verbose, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      an object of class nlme.mmkin
      
-
-
-
      data
      
-
      logical, indicating whether the full data should be included in
-the summary.
      
-
-
-
      verbose
      
-
      Should the summary be verbose?
      
-
-
-
      distimes
      
-
      logical, indicating whether DT50 and DT90 values should be
-included.
      
-
-
-
      alpha
      
-
      error level for confidence interval estimation from the t
-distribution
      
-
-
-
      ...
      
-
      optional arguments passed to methods like print.
      
-
-
-
      x
      
-
      an object of class summary.nlme.mmkin
      
-
-
-
      digits
      
-
      Number of digits to use for printing
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The summary function returns a list based on the nlme object
-obtained in the fit, with at least the following additional components
      
-
      nlmeversion, mkinversion, Rversion
      
-
      The nlme, mkin and R versions used
      
-
-
      date.fit, date.summary
      
-
      The dates where the fit and the summary were
-produced
      
-
-
      diffs
      
-
      The differential equations used in the degradation model
      
-
-
      use_of_ff
      
-
      Was maximum or minimum use made of formation fractions
      
-
-
      data
      
-
      The data
      
-
-
      confint_trans
      
-
      Transformed parameters as used in the optimisation, with confidence intervals
      
-
-
      confint_back
      
-
      Backtransformed parameters, with confidence intervals if available
      
-
-
      ff
      
-
      The estimated formation fractions derived from the fitted
-model.
      
-
-
      distimes
      
-
      The DT50 and DT90 values for each observed variable.
      
-
-
      SFORB
      
-
      If applicable, eigenvalues of SFORB components of the model.
      
-
-
      The print method is called for its side effect, i.e. printing the summary.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke for the mkin specific parts
-José Pinheiro and Douglas Bates for the components inherited from nlme
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-# Generate five datasets following SFO kinetics
-sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-dt50_sfo_in_pop <- 50
-k_in_pop <- log(2) / dt50_sfo_in_pop
-set.seed(1234)
-k_in <- rlnorm(5, log(k_in_pop), 0.5)
-SFO <- mkinmod(parent = mkinsub("SFO"))
-
-pred_sfo <- function(k) {
-  mkinpredict(SFO,
-    c(k_parent = k),
-    c(parent = 100),
-    sampling_times)
-}
-
-ds_sfo_mean <- lapply(k_in, pred_sfo)
-names(ds_sfo_mean) <- paste("ds", 1:5)
-
-set.seed(12345)
-ds_sfo_syn <- lapply(ds_sfo_mean, function(ds) {
-  add_err(ds,
-    sdfunc = function(value) sqrt(1^2 + value^2 * 0.07^2),
-    n = 1)[[1]]
-})
-
-# \dontrun{
-# Evaluate using mmkin and nlme
-library(nlme)
-f_mmkin <- mmkin("SFO", ds_sfo_syn, quiet = TRUE, error_model = "tc", cores = 1)
-#> Warning: Optimisation did not converge:
-#> iteration limit reached without convergence (10)
-f_nlme <- nlme(f_mmkin)
-summary(f_nlme, data = TRUE)
-#> nlme version used for fitting:      3.1.162 
-#> mkin version used for pre-fitting:  1.2.3 
-#> R version used for fitting:         4.2.3 
-#> Date of fit:     Sun Apr 16 08:34:41 2023 
-#> Date of summary: Sun Apr 16 08:34:41 2023 
-#> 
-#> Equations:
-#> d_parent/dt = - k_parent * parent
-#> 
-#> Data:
-#> 90 observations of 1 variable(s) grouped in 5 datasets
-#> 
-#> Model predictions using solution type analytical 
-#> 
-#> Fitted in 0.194 s using 4 iterations
-#> 
-#> Variance model: Two-component variance function 
-#> 
-#> Mean of starting values for individual parameters:
-#>     parent_0 log_k_parent 
-#>      101.569       -4.454 
-#> 
-#> Fixed degradation parameter values:
-#> None
-#> 
-#> Results:
-#> 
-#>     AIC   BIC logLik
-#>   584.5 599.5 -286.2
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>               lower    est.   upper
-#> parent_0     99.371 101.592 103.814
-#> log_k_parent -4.973  -4.449  -3.926
-#> 
-#> Correlation: 
-#>              parnt_0
-#> log_k_parent 0.0507 
-#> 
-#> Random effects:
-#>  Formula: list(parent_0 ~ 1, log_k_parent ~ 1)
-#>  Level: ds
-#>  Structure: Diagonal
-#>         parent_0 log_k_parent Residual
-#> StdDev: 6.92e-05       0.5863        1
-#> 
-#> Variance function:
-#>  Structure: Constant plus proportion of variance covariate
-#>  Formula: ~fitted(.) 
-#>  Parameter estimates:
-#>        const         prop 
-#> 0.0001208154 0.0789968021 
-#> 
-#> Backtransformed parameters with asymmetric confidence intervals:
-#>              lower      est.     upper
-#> parent_0 99.370882 101.59243 103.81398
-#> k_parent  0.006923   0.01168   0.01972
-#> 
-#> Estimated disappearance times:
-#>         DT50  DT90
-#> parent 59.32 197.1
-#> 
-#> Data:
-#>    ds   name time observed predicted  residual    std standardized
-#>  ds 1 parent    0    104.1   101.592   2.50757 8.0255     0.312451
-#>  ds 1 parent    0    105.0   101.592   3.40757 8.0255     0.424594
-#>  ds 1 parent    1     98.5   100.796  -2.29571 7.9625    -0.288313
-#>  ds 1 parent    1     96.1   100.796  -4.69571 7.9625    -0.589725
-#>  ds 1 parent    3    101.9    99.221   2.67904 7.8381     0.341796
-#>  ds 1 parent    3     85.2    99.221 -14.02096 7.8381    -1.788812
-#>  ds 1 parent    7     99.1    96.145   2.95512 7.5951     0.389081
-#>  ds 1 parent    7     93.0    96.145  -3.14488 7.5951    -0.414065
-#>  ds 1 parent   14     88.1    90.989  -2.88944 7.1879    -0.401987
-#>  ds 1 parent   14     84.1    90.989  -6.88944 7.1879    -0.958480
-#>  ds 1 parent   28     80.2    81.493  -1.29305 6.4377    -0.200857
-#>  ds 1 parent   28     91.3    81.493   9.80695 6.4377     1.523364
-#>  ds 1 parent   60     65.1    63.344   1.75642 5.0039     0.351008
-#>  ds 1 parent   60     65.8    63.344   2.45642 5.0039     0.490898
-#>  ds 1 parent   90     47.8    50.018  -2.21764 3.9512    -0.561252
-#>  ds 1 parent   90     53.5    50.018   3.48236 3.9512     0.881335
-#>  ds 1 parent  120     37.6    39.495  -1.89515 3.1200    -0.607423
-#>  ds 1 parent  120     39.3    39.495  -0.19515 3.1200    -0.062549
-#>  ds 2 parent    0    107.9   101.592   6.30757 8.0255     0.785943
-#>  ds 2 parent    0    102.1   101.592   0.50757 8.0255     0.063245
-#>  ds 2 parent    1    103.8   100.058   3.74159 7.9043     0.473361
-#>  ds 2 parent    1    108.6   100.058   8.54159 7.9043     1.080626
-#>  ds 2 parent    3     91.0    97.060  -6.05952 7.6674    -0.790297
-#>  ds 2 parent    3     84.9    97.060 -12.15952 7.6674    -1.585874
-#>  ds 2 parent    7     79.3    91.329 -12.02867 7.2147    -1.667251
-#>  ds 2 parent    7    100.9    91.329   9.57133 7.2147     1.326647
-#>  ds 2 parent   14     77.3    82.102  -4.80185 6.4858    -0.740366
-#>  ds 2 parent   14     83.5    82.102   1.39815 6.4858     0.215571
-#>  ds 2 parent   28     66.8    66.351   0.44945 5.2415     0.085748
-#>  ds 2 parent   28     63.3    66.351  -3.05055 5.2415    -0.582002
-#>  ds 2 parent   60     40.8    40.775   0.02474 3.2211     0.007679
-#>  ds 2 parent   60     44.8    40.775   4.02474 3.2211     1.249485
-#>  ds 2 parent   90     27.8    25.832   1.96762 2.0407     0.964198
-#>  ds 2 parent   90     27.0    25.832   1.16762 2.0407     0.572171
-#>  ds 2 parent  120     15.2    16.366  -1.16561 1.2928    -0.901595
-#>  ds 2 parent  120     15.5    16.366  -0.86561 1.2928    -0.669547
-#>  ds 3 parent    0     97.7   101.592  -3.89243 8.0255    -0.485009
-#>  ds 3 parent    0     88.2   101.592 -13.39243 8.0255    -1.668739
-#>  ds 3 parent    1    109.9    99.218  10.68196 7.8379     1.362858
-#>  ds 3 parent    1     97.8    99.218  -1.41804 7.8379    -0.180921
-#>  ds 3 parent    3    100.5    94.634   5.86555 7.4758     0.784603
-#>  ds 3 parent    3     77.4    94.634 -17.23445 7.4758    -2.305360
-#>  ds 3 parent    7     78.3    86.093  -7.79273 6.8011    -1.145813
-#>  ds 3 parent    7     90.3    86.093   4.20727 6.8011     0.618620
-#>  ds 3 parent   14     76.0    72.958   3.04222 5.7634     0.527848
-#>  ds 3 parent   14     79.1    72.958   6.14222 5.7634     1.065722
-#>  ds 3 parent   28     46.0    52.394  -6.39404 4.1390    -1.544842
-#>  ds 3 parent   28     53.4    52.394   1.00596 4.1390     0.243046
-#>  ds 3 parent   60     25.1    24.582   0.51786 1.9419     0.266676
-#>  ds 3 parent   60     21.4    24.582  -3.18214 1.9419    -1.638664
-#>  ds 3 parent   90     11.0    12.092  -1.09202 0.9552    -1.143199
-#>  ds 3 parent   90     14.2    12.092   2.10798 0.9552     2.206776
-#>  ds 3 parent  120      5.8     5.948  -0.14810 0.4699    -0.315178
-#>  ds 3 parent  120      6.1     5.948   0.15190 0.4699     0.323282
-#>  ds 4 parent    0     95.3   101.592  -6.29243 8.0255    -0.784057
-#>  ds 4 parent    0    102.0   101.592   0.40757 8.0255     0.050784
-#>  ds 4 parent    1    104.4   101.125   3.27549 7.9885     0.410025
-#>  ds 4 parent    1    105.4   101.125   4.27549 7.9885     0.535205
-#>  ds 4 parent    3    113.7   100.195  13.50487 7.9151     1.706218
-#>  ds 4 parent    3     82.3   100.195 -17.89513 7.9151    -2.260886
-#>  ds 4 parent    7     98.1    98.362  -0.26190 7.7703    -0.033706
-#>  ds 4 parent    7     87.8    98.362 -10.56190 7.7703    -1.359270
-#>  ds 4 parent   14     97.9    95.234   2.66590 7.5232     0.354357
-#>  ds 4 parent   14    104.8    95.234   9.56590 7.5232     1.271521
-#>  ds 4 parent   28     85.0    89.274  -4.27372 7.0523    -0.606001
-#>  ds 4 parent   28     77.2    89.274 -12.07372 7.0523    -1.712017
-#>  ds 4 parent   60     82.2    77.013   5.18660 6.0838     0.852526
-#>  ds 4 parent   60     86.1    77.013   9.08660 6.0838     1.493571
-#>  ds 4 parent   90     70.5    67.053   3.44692 5.2970     0.650733
-#>  ds 4 parent   90     61.7    67.053  -5.35308 5.2970    -1.010591
-#>  ds 4 parent  120     60.0    58.381   1.61905 4.6119     0.351058
-#>  ds 4 parent  120     56.4    58.381  -1.98095 4.6119    -0.429530
-#>  ds 5 parent    0     92.6   101.592  -8.99243 8.0255    -1.120485
-#>  ds 5 parent    0    116.5   101.592  14.90757 8.0255     1.857531
-#>  ds 5 parent    1    108.0    99.914   8.08560 7.8929     1.024413
-#>  ds 5 parent    1    104.9    99.914   4.98560 7.8929     0.631655
-#>  ds 5 parent    3    100.5    96.641   3.85898 7.6343     0.505477
-#>  ds 5 parent    3     89.5    96.641  -7.14102 7.6343    -0.935383
-#>  ds 5 parent    7     91.7    90.412   1.28752 7.1423     0.180267
-#>  ds 5 parent    7     95.1    90.412   4.68752 7.1423     0.656304
-#>  ds 5 parent   14     82.2    80.463   1.73715 6.3563     0.273295
-#>  ds 5 parent   14     84.5    80.463   4.03715 6.3563     0.635141
-#>  ds 5 parent   28     60.5    63.728  -3.22788 5.0343    -0.641178
-#>  ds 5 parent   28     72.8    63.728   9.07212 5.0343     1.802062
-#>  ds 5 parent   60     38.3    37.399   0.90061 2.9544     0.304835
-#>  ds 5 parent   60     40.7    37.399   3.30061 2.9544     1.117174
-#>  ds 5 parent   90     22.5    22.692  -0.19165 1.7926    -0.106913
-#>  ds 5 parent   90     20.8    22.692  -1.89165 1.7926    -1.055273
-#>  ds 5 parent  120     13.4    13.768  -0.36790 1.0876    -0.338259
-#>  ds 5 parent  120     13.8    13.768   0.03210 1.0876     0.029517
-# }
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/summary.nlmixr.mmkin.html b/docs/dev/reference/summary.nlmixr.mmkin.html
deleted file mode 100644
index 31f68f3f..00000000
--- a/docs/dev/reference/summary.nlmixr.mmkin.html
+++ /dev/null
@@ -1,2914 +0,0 @@
-
-Summary method for class "nlmixr.mmkin" — summary.nlmixr.mmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Summary method for class "nlmixr.mmkin"
      
-    Source: R/summary.nlmixr.mmkin.R
-    
-    
      
-
-    
      
-    
      Lists model equations, initial parameter values, optimised parameters
-for fixed effects (population), random effects (deviations from the
-population mean) and residual error model, as well as the resulting
-endpoints such as formation fractions and DT50 values. Optionally
-(default is FALSE), the data are listed in full.
      
-    
      
-
-    
      
-    
      # S3 method for nlmixr.mmkin
-summary(object, data = FALSE, verbose = FALSE, distimes = TRUE, ...)
-
-# S3 method for summary.nlmixr.mmkin
-print(x, digits = max(3, getOption("digits") - 3), verbose = x$verbose, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      an object of class nlmixr.mmkin
      
-
      data
      
-
      logical, indicating whether the full data should be included in
-the summary.
      
-
      verbose
      
-
      Should the summary be verbose?
      
-
      distimes
      
-
      logical, indicating whether DT50 and DT90 values should be
-included.
      
-
      ...
      
-
      optional arguments passed to methods like print.
      
-
      x
      
-
      an object of class summary.nlmixr.mmkin
      
-
      digits
      
-
      Number of digits to use for printing
      
-
      
-    
      
-    
      Value
      
-    
      The summary function returns a list obtained in the fit, with at
-least the following additional components
      
-
      nlmixrversion, mkinversion, Rversion
      
-
      The nlmixr, mkin and R versions used
      
-
      date.fit, date.summary
      
-
      The dates where the fit and the summary were
-produced
      
-
      diffs
      
-
      The differential equations used in the degradation model
      
-
      use_of_ff
      
-
      Was maximum or minimum use made of formation fractions
      
-
      data
      
-
      The data
      
-
      confint_back
      
-
      Backtransformed parameters, with confidence intervals if available
      
-
      ff
      
-
      The estimated formation fractions derived from the fitted
-model.
      
-
      distimes
      
-
      The DT50 and DT90 values for each observed variable.
      
-
      SFORB
      
-
      If applicable, eigenvalues of SFORB components of the model.
      
-
      The print method is called for its side effect, i.e. printing the summary.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke for the mkin specific parts
-nlmixr authors for the parts inherited from nlmixr.
      
-    
      
-
-    
      
-    
      Examples
      
-    
      # Generate five datasets following DFOP-SFO kinetics
-sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "m1"),
- m1 = mkinsub("SFO"), quiet = TRUE)
-set.seed(1234)
-k1_in <- rlnorm(5, log(0.1), 0.3)
-k2_in <- rlnorm(5, log(0.02), 0.3)
-g_in <- plogis(rnorm(5, qlogis(0.5), 0.3))
-f_parent_to_m1_in <- plogis(rnorm(5, qlogis(0.3), 0.3))
-k_m1_in <- rlnorm(5, log(0.02), 0.3)
-
-pred_dfop_sfo <- function(k1, k2, g, f_parent_to_m1, k_m1) {
-  mkinpredict(dfop_sfo,
-    c(k1 = k1, k2 = k2, g = g, f_parent_to_m1 = f_parent_to_m1, k_m1 = k_m1),
-    c(parent = 100, m1 = 0),
-    sampling_times)
-}
-
-ds_mean_dfop_sfo <- lapply(1:5, function(i) {
-  mkinpredict(dfop_sfo,
-    c(k1 = k1_in[i], k2 = k2_in[i], g = g_in[i],
-      f_parent_to_m1 = f_parent_to_m1_in[i], k_m1 = k_m1_in[i]),
-    c(parent = 100, m1 = 0),
-    sampling_times)
-})
-names(ds_mean_dfop_sfo) <- paste("ds", 1:5)
-
-ds_syn_dfop_sfo <- lapply(ds_mean_dfop_sfo, function(ds) {
-  add_err(ds,
-    sdfunc = function(value) sqrt(1^2 + value^2 * 0.07^2),
-    n = 1)[[1]]
-})
-
-# \dontrun{
-# Evaluate using mmkin and nlmixr
-f_mmkin_dfop_sfo <- mmkin(list(dfop_sfo), ds_syn_dfop_sfo,
-  quiet = TRUE, error_model = "tc", cores = 5)
-f_saemix_dfop_sfo <- mkin::saem(f_mmkin_dfop_sfo)
-f_nlme_dfop_sfo <- mkin::nlme(f_mmkin_dfop_sfo)
-f_nlmixr_dfop_sfo_saem <- nlmixr(f_mmkin_dfop_sfo, est = "saem")
-#> With est = 'saem', a different error model is required for each observed variableChanging the error model to 'obs_tc' (Two-component error for each observed variable)
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#>  
-#> → generate SAEM model
-#> ✔ done
-#> 1:    99.5921   -3.9040   -2.1350   -3.7103   -2.0097    0.3217    6.6502    0.1520    0.5415    0.1995    0.3705    0.5588    7.9084    0.0824    7.5666    0.1777
-#> 2:    99.9835   -3.8650   -2.3586   -4.0306   -1.6536    0.0696    6.3177    0.1590    0.5144    0.1895    0.3520    0.5308    4.7746    0.0649    4.5667    0.0865
-#> 3:    1.0014e+02  -4.0173e+00  -2.3869e+00  -4.0840e+00  -1.2338e+00   3.4899e-02   6.0018e+00   1.5109e-01   4.8870e-01   1.8005e-01   3.3438e-01   5.0428e-01   2.8890e+00   7.0377e-02   2.9045e+00   9.5437e-02
-#> 4:    1.0024e+02  -4.1414e+00  -2.4972e+00  -4.1082e+00  -1.0291e+00  -1.0684e-02   5.7017e+00   1.4354e-01   4.6427e-01   1.7105e-01   3.1766e-01   4.7907e-01   2.1715e+00   8.9921e-02   1.8765e+00   1.0403e-01
-#> 5:    1.0068e+02  -4.1132e+00  -2.4776e+00  -4.0576e+00  -1.0391e+00  -8.8738e-02   5.8192e+00   1.3636e-01   4.4106e-01   1.6249e-01   3.0177e-01   4.5512e-01   1.6349e+00   8.3197e-02   1.4947e+00   1.0221e-01
-#> 6:    1.0044e+02  -4.0883e+00  -2.3931e+00  -4.1068e+00  -9.5058e-01  -1.2696e-01   5.5283e+00   1.2954e-01   4.1900e-01   1.5437e-01   2.8669e-01   4.5581e-01   1.4126e+00   8.1219e-02   1.2286e+00   1.0043e-01
-#> 7:    1.0103e+02  -4.0833e+00  -2.4194e+00  -4.0894e+00  -9.8547e-01   5.2360e-03   9.8755e+00   1.2306e-01   3.9805e-01   1.4665e-01   2.7235e-01   5.3394e-01   1.3620e+00   7.9842e-02   1.0649e+00   1.0298e-01
-#> 8:    1.0106e+02  -4.0535e+00  -2.3489e+00  -4.0682e+00  -9.4455e-01  -9.4310e-02   9.3818e+00   1.1691e-01   3.7815e-01   1.3932e-01   2.5873e-01   5.0724e-01   1.2163e+00   7.0820e-02   1.0147e+00   9.2362e-02
-#> 9:    1.0150e+02  -4.0498e+00  -2.4037e+00  -4.0719e+00  -9.3384e-01  -1.2384e-01   8.9127e+00   1.1107e-01   3.5924e-01   1.3235e-01   2.4580e-01   5.3463e-01   1.0849e+00   7.7513e-02   9.8295e-01   8.5927e-02
-#> 10:    1.0089e+02  -4.0313e+00  -2.3670e+00  -4.0573e+00  -9.0269e-01  -1.6427e-01   8.4670e+00   1.0551e-01   3.4128e-01   1.2573e-01   2.3351e-01   5.4980e-01   1.1274e+00   7.6000e-02   9.8582e-01   8.9740e-02
-#> 11:    1.0089e+02  -4.0664e+00  -2.3547e+00  -4.0554e+00  -9.3659e-01  -1.6900e-01   8.0437e+00   1.0024e-01   3.2422e-01   1.1945e-01   2.2183e-01   5.2231e-01   1.1513e+00   7.5801e-02   9.7638e-01   8.5324e-02
-#> 12:    1.0067e+02  -4.0427e+00  -2.3729e+00  -4.0413e+00  -9.2169e-01  -2.0927e-01   8.6156e+00   9.5225e-02   3.0801e-01   1.1348e-01   2.1074e-01   6.0288e-01   1.1918e+00   7.4830e-02   9.1899e-01   8.7983e-02
-#> 13:    1.0042e+02  -4.0387e+00  -2.3650e+00  -4.0623e+00  -9.3973e-01  -2.2277e-01   8.1848e+00   9.0463e-02   2.9260e-01   1.0780e-01   2.0020e-01   5.7274e-01   1.1022e+00   7.3652e-02   9.1657e-01   8.7973e-02
-#> 14:    1.0020e+02  -4.0227e+00  -2.3586e+00  -4.0333e+00  -9.4451e-01  -1.8020e-01   7.7756e+00   8.5940e-02   2.7797e-01   1.0241e-01   1.9019e-01   5.4410e-01   1.0728e+00   8.0169e-02   7.8974e-01   9.0162e-02
-#> 15:    1.0045e+02  -4.0209e+00  -2.3544e+00  -4.0187e+00  -8.9758e-01  -2.4348e-01   7.3868e+00   8.1643e-02   2.6408e-01   9.7291e-02   1.8068e-01   6.4534e-01   1.0287e+00   7.9387e-02   7.3357e-01   9.0858e-02
-#> 16:    1.0061e+02  -4.0195e+00  -2.3678e+00  -4.0419e+00  -8.9130e-01  -2.4248e-01   7.0175e+00   7.7561e-02   2.5087e-01   9.2427e-02   1.7165e-01   6.7145e-01   1.0440e+00   7.9292e-02   8.4681e-01   8.5285e-02
-#> 17:    1.0034e+02  -4.0298e+00  -2.3685e+00  -4.0637e+00  -8.9550e-01  -1.0712e-01   6.6666e+00   7.3683e-02   2.3833e-01   8.7805e-02   1.6307e-01   6.3788e-01   1.0827e+00   7.1441e-02   8.5278e-01   8.8090e-02
-#> 18:    99.8774   -4.0600   -2.3805   -4.0726   -0.9545   -0.1196    6.3333    0.0700    0.2264    0.0834    0.1549    0.6060    1.0056    0.0751    0.8017    0.0877
-#> 19:    1.0055e+02  -4.0731e+00  -2.2711e+00  -4.0824e+00  -9.5827e-01  -5.9764e-02   6.0166e+00   6.6499e-02   2.1509e-01   7.9244e-02   1.4717e-01   5.7835e-01   9.3185e-01   7.9396e-02   8.2332e-01   9.1277e-02
-#> 20:    1.0060e+02  -4.1023e+00  -2.2841e+00  -4.0757e+00  -9.7931e-01  -1.0440e-01   5.7158e+00   6.3174e-02   2.0434e-01   7.5282e-02   1.3981e-01   6.4675e-01   1.0006e+00   7.7840e-02   8.7958e-01   9.1512e-02
-#> 21:    1.0095e+02  -4.0955e+00  -2.3274e+00  -4.1038e+00  -9.5611e-01  -5.2481e-02   5.8063e+00   6.0015e-02   1.9412e-01   7.1518e-02   1.3282e-01   6.4943e-01   1.0926e+00   7.2665e-02   9.0450e-01   8.6278e-02
-#> 22:    1.0083e+02  -4.0789e+00  -2.3108e+00  -4.1074e+00  -9.6548e-01  -4.9665e-02   5.5160e+00   5.7014e-02   1.8441e-01   6.7942e-02   1.2618e-01   6.7304e-01   9.3297e-01   8.1042e-02   8.9206e-01   9.2336e-02
-#> 23:    1.0114e+02  -4.0924e+00  -2.4027e+00  -4.0947e+00  -9.7291e-01  -5.0773e-02   5.2567e+00   5.4164e-02   1.7519e-01   6.5747e-02   1.1987e-01   7.3402e-01   9.7858e-01   8.2133e-02   8.4928e-01   8.8254e-02
-#> 24:    1.0151e+02  -4.0787e+00  -2.3696e+00  -4.0712e+00  -9.5647e-01  -5.4136e-02   4.9938e+00   5.1456e-02   1.6643e-01   6.2460e-02   1.1388e-01   7.1847e-01   9.7548e-01   7.7691e-02   9.0418e-01   8.9115e-02
-#> 25:    1.0158e+02  -4.0830e+00  -2.3384e+00  -4.0705e+00  -9.5727e-01  -8.4974e-02   4.7442e+00   4.8883e-02   1.5811e-01   5.9337e-02   1.0818e-01   6.8255e-01   1.0340e+00   7.4497e-02   9.0691e-01   9.0886e-02
-#> 26:    1.0156e+02  -4.0784e+00  -2.3030e+00  -4.1027e+00  -9.5638e-01  -4.9456e-03   4.5069e+00   4.6439e-02   1.5021e-01   5.6370e-02   1.1189e-01   6.4842e-01   1.0537e+00   7.7612e-02   9.6725e-01   8.7824e-02
-#> 27:    1.0198e+02  -4.0828e+00  -2.3006e+00  -4.0803e+00  -9.9402e-01  -8.3280e-02   4.2816e+00   4.4117e-02   1.4270e-01   5.3552e-02   1.3300e-01   6.1600e-01   9.1051e-01   7.7677e-02   9.5949e-01   8.6552e-02
-#> 28:    1.0183e+02  -4.0871e+00  -2.2822e+00  -4.0596e+00  -9.9920e-01  -1.1469e-01   4.0675e+00   4.1911e-02   1.3556e-01   5.0874e-02   1.4021e-01   5.8520e-01   1.0294e+00   7.0917e-02   8.6440e-01   9.0301e-02
-#> 29:    1.0171e+02  -4.0838e+00  -2.2606e+00  -4.0885e+00  -9.8937e-01  -6.6488e-02   4.3393e+00   3.9815e-02   1.2878e-01   4.8330e-02   1.3320e-01   5.5594e-01   1.0042e+00   8.1585e-02   8.5434e-01   8.6032e-02
-#> 30:    1.0177e+02  -4.0861e+00  -2.2615e+00  -4.0670e+00  -9.9119e-01  -1.1322e-01   6.3058e+00   3.7825e-02   1.2942e-01   4.5914e-02   1.4223e-01   5.2814e-01   9.6301e-01   7.3336e-02   9.2366e-01   8.9276e-02
-#> 31:    1.0160e+02  -4.0900e+00  -2.2455e+00  -4.0514e+00  -9.8754e-01  -2.2617e-01   5.9905e+00   3.5933e-02   1.2295e-01   4.3618e-02   1.3512e-01   5.2898e-01   1.0441e+00   7.6262e-02   1.0227e+00   8.3759e-02
-#> 32:    1.0193e+02  -4.0967e+00  -2.2599e+00  -4.0295e+00  -9.8917e-01  -1.6626e-01   5.6910e+00   3.4137e-02   1.2620e-01   4.1437e-02   1.4303e-01   5.0253e-01   9.8083e-01   7.4136e-02   1.0031e+00   8.5124e-02
-#> 33:    1.0215e+02  -4.0713e+00  -2.2563e+00  -4.0313e+00  -9.7361e-01  -1.8246e-01   5.4065e+00   3.2430e-02   1.1989e-01   3.9365e-02   1.5371e-01   4.7741e-01   9.6935e-01   8.0491e-02   9.7610e-01   8.0590e-02
-#> 34:    1.0251e+02  -4.0707e+00  -2.2635e+00  -4.0387e+00  -9.2149e-01  -1.3452e-01   6.3940e+00   3.0808e-02   1.1389e-01   3.7397e-02   1.6720e-01   4.5354e-01   9.2449e-01   7.4355e-02   1.0505e+00   8.3049e-02
-#> 35:    1.0278e+02  -4.0579e+00  -2.2877e+00  -4.0289e+00  -9.6632e-01  -1.2910e-01   6.0743e+00   2.9268e-02   1.0820e-01   3.5527e-02   1.7242e-01   4.3086e-01   1.0129e+00   7.3224e-02   1.0035e+00   7.9411e-02
-#> 36:    1.0283e+02  -4.0771e+00  -2.2977e+00  -4.0108e+00  -9.5228e-01  -2.1781e-01   5.7706e+00   2.7805e-02   1.0279e-01   3.3751e-02   1.7034e-01   4.0932e-01   9.0249e-01   7.9917e-02   9.4562e-01   8.2391e-02
-#> 37:    1.0228e+02  -4.0442e+00  -2.3061e+00  -4.0150e+00  -9.5376e-01  -1.4873e-01   5.4821e+00   2.6414e-02   9.7651e-02   3.2063e-02   1.7772e-01   3.8885e-01   9.0446e-01   8.1418e-02   9.7276e-01   8.3331e-02
-#> 38:    1.0220e+02  -4.0454e+00  -2.3204e+00  -4.0207e+00  -9.3198e-01  -1.9324e-01   5.2080e+00   2.5094e-02   1.0946e-01   3.0460e-02   1.6883e-01   3.6941e-01   8.9159e-01   7.8645e-02   9.5848e-01   8.2734e-02
-#> 39:    1.0193e+02  -4.0306e+00  -2.2926e+00  -4.0131e+00  -9.3448e-01  -2.1869e-01   6.7005e+00   2.3839e-02   1.0399e-01   2.8937e-02   1.6039e-01   3.5571e-01   9.0078e-01   7.8982e-02   9.3495e-01   8.3462e-02
-#> 40:    1.0217e+02  -4.0463e+00  -2.2823e+00  -4.0209e+00  -9.2912e-01  -2.3580e-01   8.7857e+00   2.2647e-02   9.8789e-02   2.7490e-02   1.5418e-01   3.3792e-01   8.5126e-01   7.8849e-02   9.5510e-01   8.3011e-02
-#> 41:    1.0210e+02  -4.0564e+00  -2.2213e+00  -4.0041e+00  -9.4137e-01  -2.4103e-01   9.2761e+00   2.1515e-02   9.5179e-02   2.6116e-02   1.4795e-01   3.9870e-01   9.8312e-01   7.1947e-02   1.0015e+00   8.1407e-02
-#> 42:    1.0201e+02  -4.0204e+00  -2.2598e+00  -3.9984e+00  -9.4412e-01  -2.6838e-01   8.8123e+00   2.0439e-02   9.0420e-02   2.4810e-02   1.5013e-01   4.0334e-01   9.5583e-01   7.5617e-02   9.5131e-01   8.2343e-02
-#> 43:    1.0244e+02  -4.0107e+00  -2.2178e+00  -3.9923e+00  -9.4481e-01  -3.1831e-01   8.3717e+00   1.9417e-02   9.5791e-02   2.3569e-02   1.5440e-01   4.8194e-01   9.4582e-01   7.4374e-02   9.7798e-01   8.3391e-02
-#> 44:    1.0211e+02  -4.0193e+00  -2.2379e+00  -3.9784e+00  -9.2192e-01  -3.0224e-01   7.9531e+00   1.8446e-02   9.1002e-02   2.6623e-02   1.4668e-01   4.5785e-01   9.4162e-01   7.4503e-02   9.3229e-01   7.8428e-02
-#> 45:    1.0183e+02  -4.0198e+00  -2.2150e+00  -3.9966e+00  -9.6219e-01  -3.0236e-01   7.5554e+00   1.7524e-02   8.6452e-02   2.8045e-02   1.4346e-01   4.3495e-01   9.3318e-01   7.5937e-02   9.4917e-01   8.2946e-02
-#> 46:    1.0132e+02  -4.0245e+00  -2.2215e+00  -3.9954e+00  -9.4368e-01  -2.6878e-01   7.1777e+00   1.6648e-02   9.5839e-02   2.6909e-02   1.4633e-01   4.1321e-01   9.7698e-01   7.1947e-02   9.6599e-01   8.3812e-02
-#> 47:    1.0138e+02  -4.0076e+00  -2.2741e+00  -4.0047e+00  -9.0608e-01  -2.2839e-01   6.8188e+00   1.5815e-02   9.2192e-02   2.5563e-02   1.6160e-01   3.9255e-01   9.3678e-01   7.4216e-02   1.0295e+00   7.9396e-02
-#> 48:    1.0102e+02  -4.0235e+00  -2.2764e+00  -4.0123e+00  -9.1050e-01  -2.0555e-01   6.4778e+00   1.5024e-02   8.7583e-02   2.4285e-02   1.6368e-01   3.7292e-01   9.2204e-01   7.6976e-02   1.0289e+00   8.1381e-02
-#> 49:    1.0074e+02  -4.0407e+00  -2.2583e+00  -4.0142e+00  -9.2682e-01  -2.5941e-01   6.1540e+00   1.4273e-02   8.3203e-02   2.3071e-02   1.8251e-01   3.5427e-01   9.0436e-01   7.4192e-02   1.0237e+00   8.2178e-02
-#> 50:    1.0046e+02  -4.0626e+00  -2.2464e+00  -4.0201e+00  -9.3021e-01  -2.6983e-01   5.8463e+00   1.4303e-02   7.9043e-02   2.3395e-02   1.7339e-01   3.3846e-01   9.1334e-01   7.8046e-02   9.5881e-01   8.1223e-02
-#> 51:    1.0022e+02  -4.0414e+00  -2.2373e+00  -4.0107e+00  -9.2183e-01  -2.6371e-01   5.8667e+00   1.8681e-02   7.5091e-02   2.2225e-02   1.6472e-01   3.7327e-01   9.4906e-01   8.0171e-02   1.0278e+00   8.7157e-02
-#> 52:    1.0059e+02  -4.0444e+00  -2.2676e+00  -4.0263e+00  -9.1269e-01  -2.1748e-01   5.5734e+00   1.7747e-02   7.1337e-02   2.1114e-02   1.5648e-01   3.5461e-01   8.6417e-01   8.2918e-02   1.0332e+00   8.1690e-02
-#> 53:    1.0071e+02  -4.0384e+00  -2.2530e+00  -4.0171e+00  -9.2997e-01  -2.5319e-01   5.2947e+00   1.6860e-02   6.7770e-02   2.0058e-02   1.6621e-01   3.3688e-01   8.9792e-01   7.8990e-02   1.0230e+00   7.9862e-02
-#> 54:    1.0067e+02  -4.0271e+00  -2.2540e+00  -4.0251e+00  -9.2151e-01  -2.2197e-01   5.0300e+00   1.6017e-02   6.4381e-02   1.9055e-02   1.7025e-01   3.2003e-01   8.7999e-01   8.0187e-02   1.0487e+00   8.1091e-02
-#> 55:    1.0083e+02  -4.0326e+00  -2.2090e+00  -4.0230e+00  -9.2078e-01  -2.4936e-01   4.8429e+00   1.5216e-02   6.1162e-02   1.8103e-02   1.7211e-01   3.0403e-01   8.8923e-01   8.2248e-02   1.0522e+00   8.0777e-02
-#> 56:    1.0082e+02  -4.0284e+00  -2.2350e+00  -4.0083e+00  -8.9532e-01  -1.9565e-01   5.3306e+00   1.4455e-02   5.8104e-02   1.7197e-02   1.6350e-01   2.8883e-01   8.7438e-01   7.9530e-02   1.0748e+00   7.9892e-02
-#> 57:    1.0089e+02  -4.0118e+00  -2.2585e+00  -3.9924e+00  -9.5279e-01  -2.7691e-01   5.4228e+00   1.3733e-02   5.5199e-02   1.6338e-02   1.9088e-01   2.7439e-01   9.3164e-01   8.0286e-02   1.1149e+00   8.3224e-02
-#> 58:    1.0103e+02  -4.0117e+00  -2.2470e+00  -3.9628e+00  -9.5632e-01  -3.1385e-01   5.1517e+00   1.3046e-02   6.2482e-02   1.5521e-02   1.8744e-01   2.8144e-01   9.6857e-01   8.0586e-02   1.0149e+00   8.0615e-02
-#> 59:    1.0110e+02  -4.0400e+00  -2.2319e+00  -3.9749e+00  -9.3280e-01  -3.1491e-01   4.8941e+00   1.4375e-02   7.6521e-02   1.9982e-02   1.8994e-01   2.6736e-01   9.9294e-01   7.6723e-02   9.8321e-01   8.4135e-02
-#> 60:    1.0135e+02  -4.0401e+00  -2.2969e+00  -4.0006e+00  -9.3649e-01  -2.7105e-01   4.6494e+00   1.5352e-02   7.2695e-02   1.8983e-02   1.8339e-01   2.5400e-01   9.7671e-01   8.0731e-02   1.0344e+00   8.4798e-02
-#> 61:    1.0139e+02  -4.0447e+00  -2.3267e+00  -4.0036e+00  -9.2609e-01  -2.4279e-01   4.4169e+00   1.4584e-02   6.9060e-02   1.8034e-02   1.7844e-01   2.4130e-01   9.4921e-01   8.1065e-02   1.0031e+00   8.2364e-02
-#> 62:    1.0187e+02  -4.0605e+00  -2.2435e+00  -4.0093e+00  -9.4594e-01  -2.2911e-01   4.1961e+00   1.3855e-02   6.5607e-02   2.0229e-02   1.6951e-01   2.2923e-01   8.5507e-01   8.5043e-02   1.0003e+00   8.4881e-02
-#> 63:    1.0181e+02  -4.0665e+00  -2.2106e+00  -3.9954e+00  -9.5259e-01  -2.2539e-01   3.9863e+00   1.3162e-02   6.2327e-02   1.9217e-02   2.0722e-01   2.1777e-01   9.2699e-01   7.9303e-02   9.8900e-01   8.5477e-02
-#> 64:    1.0178e+02  -4.0641e+00  -2.2152e+00  -3.9904e+00  -9.7044e-01  -2.2671e-01   3.8289e+00   1.2504e-02   5.9210e-02   1.8256e-02   2.1010e-01   2.0688e-01   8.6741e-01   8.9748e-02   9.9564e-01   8.6675e-02
-#> 65:    1.0149e+02  -4.0871e+00  -2.2063e+00  -4.0000e+00  -9.7253e-01  -2.0360e-01   3.6375e+00   1.1879e-02   5.8060e-02   1.7344e-02   2.3758e-01   1.9654e-01   9.1092e-01   8.6259e-02   1.0674e+00   8.6171e-02
-#> 66:    1.0131e+02  -4.0863e+00  -2.2283e+00  -4.0026e+00  -9.6884e-01  -2.2153e-01   3.4556e+00   1.1285e-02   5.5157e-02   1.6476e-02   2.5128e-01   1.8671e-01   9.2512e-01   7.7687e-02   1.0847e+00   8.2689e-02
-#> 67:    1.0124e+02  -4.0691e+00  -2.2261e+00  -4.0021e+00  -9.2647e-01  -2.9309e-01   3.2828e+00   1.0721e-02   5.2400e-02   1.5653e-02   2.3872e-01   1.7738e-01   8.3514e-01   8.7680e-02   1.0093e+00   8.1515e-02
-#> 68:    1.0160e+02  -4.0653e+00  -2.2627e+00  -3.9685e+00  -9.5325e-01  -2.9870e-01   3.1187e+00   1.0185e-02   5.0455e-02   1.6013e-02   2.2678e-01   1.6851e-01   9.3016e-01   8.4873e-02   1.0357e+00   8.0066e-02
-#> 69:    1.0154e+02  -4.0667e+00  -2.2536e+00  -3.9686e+00  -9.8329e-01  -2.1749e-01   2.9628e+00   9.6753e-03   4.7932e-02   1.6408e-02   2.1544e-01   1.6008e-01   9.4932e-01   8.5396e-02   1.0298e+00   8.2915e-02
-#> 70:    1.0140e+02  -4.0718e+00  -2.2809e+00  -4.0031e+00  -9.7818e-01  -1.5912e-01   2.8146e+00   1.2376e-02   4.5536e-02   1.5606e-02   2.0467e-01   1.5208e-01   9.8171e-01   8.4966e-02   1.0881e+00   8.4583e-02
-#> 71:    1.0119e+02  -4.0810e+00  -2.2832e+00  -3.9945e+00  -9.7859e-01  -1.6288e-01   2.6739e+00   1.1757e-02   4.3259e-02   2.2477e-02   1.9444e-01   1.4447e-01   9.2355e-01   8.4027e-02   1.0557e+00   8.3942e-02
-#> 72:    1.0133e+02  -4.0904e+00  -2.2582e+00  -4.0034e+00  -1.0103e+00  -1.9818e-01   2.5402e+00   1.1169e-02   6.0710e-02   2.4943e-02   1.8472e-01   1.3725e-01   8.8530e-01   8.8313e-02   9.6043e-01   8.6565e-02
-#> 73:    1.0081e+02  -4.0852e+00  -2.2408e+00  -4.0324e+00  -9.8147e-01  -2.0245e-01   2.4132e+00   1.0611e-02   6.0672e-02   2.3696e-02   1.7586e-01   1.5058e-01   9.8632e-01   8.0072e-02   1.0754e+00   8.4211e-02
-#> 74:    1.0096e+02  -4.0784e+00  -2.2415e+00  -4.0085e+00  -9.6374e-01  -2.1820e-01   2.2925e+00   1.0080e-02   7.8175e-02   2.2511e-02   2.0451e-01   1.4305e-01   9.7218e-01   7.5856e-02   1.0703e+00   8.2684e-02
-#> 75:    1.0059e+02  -4.0614e+00  -2.2571e+00  -4.0069e+00  -9.6858e-01  -2.2415e-01   2.1779e+00   9.5763e-03   7.4266e-02   2.1385e-02   2.0050e-01   1.3590e-01   9.4625e-01   8.3873e-02   1.0545e+00   8.0628e-02
-#> 76:    1.0071e+02  -4.0570e+00  -2.2509e+00  -4.0111e+00  -9.4159e-01  -2.0936e-01   2.0690e+00   9.0975e-03   1.0546e-01   2.0316e-02   1.9048e-01   1.2911e-01   9.1139e-01   8.4290e-02   1.0164e+00   8.0587e-02
-#> 77:    1.0056e+02  -4.0315e+00  -2.2434e+00  -4.0068e+00  -9.1913e-01  -2.0655e-01   1.9656e+00   8.6426e-03   1.2867e-01   1.9300e-02   1.8971e-01   1.5112e-01   9.1748e-01   8.0221e-02   1.0080e+00   8.2126e-02
-#> 78:    1.0054e+02  -4.0350e+00  -2.2335e+00  -4.0109e+00  -9.4315e-01  -1.7472e-01   2.6310e+00   8.2105e-03   1.3206e-01   1.8867e-02   2.0835e-01   1.8443e-01   9.7893e-01   7.9595e-02   1.0622e+00   8.3669e-02
-#> 79:    1.0036e+02  -4.0500e+00  -2.2739e+00  -4.0223e+00  -9.6070e-01  -1.8756e-01   2.5665e+00   7.7999e-03   1.2546e-01   1.7924e-02   1.9794e-01   2.0106e-01   9.4360e-01   8.0070e-02   1.0209e+00   8.4807e-02
-#> 80:    1.0030e+02  -4.0522e+00  -2.2890e+00  -4.0149e+00  -9.2615e-01  -2.1233e-01   2.4382e+00   7.4099e-03   1.2570e-01   1.7028e-02   1.8804e-01   2.4730e-01   9.6559e-01   8.0105e-02   1.0382e+00   7.9028e-02
-#> 81:    1.0004e+02  -4.0462e+00  -2.2766e+00  -4.0158e+00  -9.0841e-01  -2.3731e-01   3.0663e+00   7.0394e-03   1.2300e-01   1.6176e-02   1.7864e-01   2.3493e-01   8.8273e-01   8.0620e-02   1.0835e+00   7.9915e-02
-#> 82:    1.0015e+02  -4.0106e+00  -2.2696e+00  -3.9845e+00  -9.2535e-01  -2.7387e-01   2.9130e+00   6.6875e-03   1.5058e-01   1.5368e-02   1.6971e-01   2.4826e-01   1.0039e+00   7.8035e-02   1.1181e+00   8.5136e-02
-#> 83:    1.0019e+02  -4.0111e+00  -2.2266e+00  -3.9884e+00  -8.8579e-01  -2.3822e-01   2.7674e+00   6.3531e-03   1.9061e-01   1.4599e-02   1.6122e-01   2.3585e-01   1.0256e+00   8.1065e-02   1.0988e+00   8.4111e-02
-#> 84:    99.9333   -4.0014   -2.2848   -3.9877   -0.8906   -0.2014    2.6290    0.0060    0.2388    0.0139    0.1532    0.2628    0.9936    0.0809    1.1059    0.0847
-#> 85:    99.6658   -4.0093   -2.2848   -3.9884   -0.8922   -0.2517    2.4976    0.0057    0.2269    0.0132    0.1455    0.2920    0.9705    0.0823    1.0458    0.0834
-#> 86:    99.8823   -4.0064   -2.2659   -4.0038   -0.9174   -0.1848    2.3727    0.0054    0.2155    0.0125    0.1382    0.2774    0.9699    0.0796    0.9808    0.0839
-#> 87:    1.0051e+02  -4.0156e+00  -2.2877e+00  -4.0160e+00  -8.9867e-01  -1.3463e-01   2.3477e+00   6.2688e-03   2.0474e-01   1.1891e-02   1.4859e-01   2.6352e-01   9.0742e-01   7.8361e-02   1.0082e+00   8.1020e-02
-#> 88:    1.0036e+02  -4.0013e+00  -2.2738e+00  -4.0184e+00  -9.1589e-01  -1.4154e-01   3.0581e+00   7.7930e-03   2.5551e-01   1.1297e-02   1.4116e-01   2.5035e-01   9.8581e-01   7.6769e-02   9.7255e-01   8.8653e-02
-#> 89:    1.0031e+02  -4.0155e+00  -2.3418e+00  -4.0080e+00  -8.8958e-01  -1.4006e-01   3.3754e+00   7.4891e-03   2.4274e-01   1.2919e-02   1.3411e-01   2.3783e-01   8.9921e-01   8.3685e-02   9.2657e-01   8.1804e-02
-#> 90:    1.0044e+02  -4.0279e+00  -2.3328e+00  -4.0081e+00  -9.1868e-01  -1.3077e-01   3.6776e+00   1.1221e-02   2.3380e-01   1.2419e-02   1.4247e-01   2.2594e-01   8.8620e-01   8.0520e-02   9.0269e-01   8.2413e-02
-#> 91:    1.0007e+02  -4.0329e+00  -2.3865e+00  -4.0145e+00  -8.9566e-01  -1.2400e-01   3.7450e+00   1.0660e-02   2.2211e-01   1.3667e-02   1.3534e-01   2.1539e-01   9.5638e-01   8.0235e-02   9.4346e-01   8.5828e-02
-#> 92:    1.0025e+02  -4.0506e+00  -2.3252e+00  -4.0445e+00  -9.2023e-01  -5.6654e-02   3.9282e+00   1.0127e-02   2.4912e-01   1.2984e-02   1.4349e-01   2.6955e-01   9.6021e-01   7.7975e-02   9.1878e-01   8.6695e-02
-#> 93:    1.0091e+02  -4.0566e+00  -2.2760e+00  -4.0422e+00  -9.2960e-01  -5.8179e-02   3.7318e+00   9.6210e-03   2.6385e-01   1.3422e-02   1.5136e-01   2.5607e-01   9.7012e-01   7.7323e-02   1.0157e+00   8.6123e-02
-#> 94:    1.0045e+02  -4.0682e+00  -2.3163e+00  -4.0391e+00  -9.3398e-01  -1.0367e-01   4.0009e+00   9.1399e-03   2.5066e-01   1.2751e-02   1.6029e-01   2.9867e-01   9.1442e-01   8.0048e-02   9.7607e-01   8.5436e-02
-#> 95:    1.0029e+02  -4.0790e+00  -2.2791e+00  -4.0470e+00  -9.4031e-01  -7.2610e-02   3.8008e+00   8.6829e-03   2.3813e-01   1.2114e-02   1.5227e-01   2.8373e-01   8.9105e-01   8.2168e-02   9.5542e-01   8.5308e-02
-#> 96:    1.0017e+02  -4.0818e+00  -2.3204e+00  -4.0507e+00  -9.2181e-01  -7.5195e-02   3.6108e+00   8.2488e-03   2.2622e-01   1.1508e-02   1.5273e-01   2.6955e-01   9.3179e-01   7.7026e-02   1.0092e+00   8.4966e-02
-#> 97:    1.0007e+02  -4.0721e+00  -2.3606e+00  -4.0453e+00  -9.4375e-01  -7.2811e-02   3.4303e+00   1.0904e-02   2.1585e-01   1.2641e-02   1.8282e-01   2.5788e-01   9.3750e-01   8.0427e-02   9.3193e-01   8.3262e-02
-#> 98:    1.0024e+02  -4.1025e+00  -2.3916e+00  -4.0401e+00  -9.6711e-01  -6.7764e-02   3.2587e+00   1.0359e-02   2.0506e-01   1.8712e-02   1.9260e-01   2.4499e-01   1.0086e+00   7.7282e-02   9.6010e-01   8.1760e-02
-#> 99:    1.0024e+02  -4.0755e+00  -2.3237e+00  -4.0581e+00  -9.5543e-01  -8.1716e-02   3.0958e+00   9.8408e-03   1.9481e-01   1.7973e-02   1.8297e-01   2.5653e-01   8.6589e-01   7.7940e-02   9.2919e-01   8.4396e-02
-#> 100:    1.0039e+02  -4.0828e+00  -2.2976e+00  -4.0616e+00  -9.8223e-01  -8.5593e-02   3.9873e+00   9.3488e-03   1.8507e-01   1.8837e-02   1.7382e-01   2.4370e-01   8.6471e-01   8.4021e-02   9.4587e-01   8.1697e-02
-#> 101:    1.0089e+02  -4.0738e+00  -2.3406e+00  -4.0465e+00  -9.4824e-01  -4.4055e-02   5.2624e+00   8.8814e-03   1.8051e-01   1.7896e-02   1.6513e-01   2.3288e-01   8.4179e-01   8.2487e-02   8.8097e-01   8.1625e-02
-#> 102:    1.0090e+02  -4.0777e+00  -2.3244e+00  -4.0500e+00  -9.4069e-01  -5.2554e-02   5.5339e+00   8.4373e-03   1.7148e-01   1.7001e-02   1.5688e-01   2.2124e-01   9.0419e-01   7.8446e-02   9.4721e-01   8.0896e-02
-#> 103:    1.0067e+02  -4.0658e+00  -2.3188e+00  -4.0312e+00  -9.5981e-01  -7.3735e-02   7.0281e+00   8.0154e-03   1.6291e-01   1.6151e-02   1.7019e-01   2.1018e-01   9.3631e-01   8.1516e-02   9.8773e-01   8.0587e-02
-#> 104:    1.0015e+02  -4.0729e+00  -2.3830e+00  -4.0458e+00  -9.4446e-01  -5.0075e-02   6.6767e+00   7.6147e-03   1.5476e-01   1.5343e-02   1.6822e-01   1.9967e-01   8.2373e-01   8.3029e-02   9.6909e-01   7.9505e-02
-#> 105:    1.0022e+02  -4.0888e+00  -2.3301e+00  -4.0411e+00  -9.5279e-01  -1.1412e-01   6.3429e+00   7.2339e-03   1.4702e-01   1.4576e-02   1.8886e-01   2.2088e-01   9.2925e-01   7.3020e-02   1.0450e+00   8.6511e-02
-#> 106:    1.0013e+02  -4.0846e+00  -2.3428e+00  -4.0530e+00  -9.1649e-01  -8.1899e-02   6.0257e+00   6.8722e-03   1.3967e-01   1.8939e-02   1.8350e-01   2.1970e-01   9.4571e-01   8.6259e-02   8.8509e-01   8.1023e-02
-#> 107:    1.0026e+02  -4.0954e+00  -2.3362e+00  -4.0586e+00  -9.6302e-01  -8.0898e-03   5.7244e+00   6.5286e-03   1.3269e-01   2.2595e-02   2.0043e-01   2.4151e-01   8.8882e-01   8.8155e-02   8.2466e-01   8.5467e-02
-#> 108:    1.0109e+02  -4.0796e+00  -2.3980e+00  -4.0841e+00  -9.5525e-01   2.0583e-02   5.4382e+00   6.2022e-03   1.2606e-01   3.4423e-02   2.2509e-01   2.3732e-01   9.0211e-01   8.1331e-02   9.2728e-01   8.4409e-02
-#> 109:    1.0091e+02  -4.0872e+00  -2.3614e+00  -4.0620e+00  -9.5950e-01  -1.8283e-02   5.1663e+00   6.1750e-03   1.1975e-01   3.2702e-02   2.1384e-01   2.2546e-01   9.7296e-01   7.7298e-02   9.7366e-01   8.3784e-02
-#> 110:    1.0137e+02  -4.0637e+00  -2.3734e+00  -4.0781e+00  -9.3874e-01  -6.0140e-03   4.9080e+00   6.5148e-03   1.1376e-01   3.1066e-02   2.0314e-01   2.3943e-01   9.2451e-01   8.4473e-02   9.7311e-01   8.4958e-02
-#> 111:    1.0181e+02  -4.0588e+00  -2.3200e+00  -4.0792e+00  -9.9395e-01  -3.1776e-02   4.6626e+00   9.9112e-03   1.0808e-01   4.1755e-02   1.9299e-01   2.9896e-01   1.0697e+00   7.1561e-02   1.0062e+00   8.8034e-02
-#> 112:    1.0222e+02  -4.0566e+00  -2.3525e+00  -4.0607e+00  -9.6055e-01  -6.3691e-02   4.4850e+00   9.4157e-03   1.0267e-01   4.0540e-02   1.8334e-01   3.5699e-01   1.0213e+00   7.5944e-02   1.0070e+00   8.3434e-02
-#> 113:    1.0189e+02  -4.0478e+00  -2.3774e+00  -4.0434e+00  -9.6638e-01  -6.7729e-02   5.1753e+00   8.9449e-03   9.7539e-02   3.8513e-02   2.0339e-01   3.4044e-01   9.5484e-01   7.7854e-02   9.8545e-01   8.1852e-02
-#> 114:    1.0225e+02  -4.0334e+00  -2.3728e+00  -4.0502e+00  -9.4795e-01  -7.3569e-02   4.9165e+00   8.8152e-03   9.2662e-02   3.7310e-02   2.0002e-01   3.2342e-01   9.3586e-01   8.1063e-02   9.5652e-01   8.3067e-02
-#> 115:    1.0196e+02  -4.0302e+00  -2.3599e+00  -4.0812e+00  -9.6783e-01   7.1536e-03   4.8473e+00   9.4780e-03   1.0791e-01   3.7184e-02   1.9002e-01   3.0725e-01   9.1488e-01   7.6079e-02   1.0104e+00   8.7136e-02
-#> 116:    1.0150e+02  -4.0420e+00  -2.3637e+00  -4.0535e+00  -9.4545e-01  -7.6387e-02   4.6049e+00   9.6408e-03   1.0251e-01   3.8115e-02   1.8052e-01   2.9189e-01   9.0583e-01   8.2597e-02   9.5680e-01   8.1246e-02
-#> 117:    1.0161e+02  -4.0606e+00  -2.3853e+00  -4.0750e+00  -9.7273e-01  -2.7338e-03   4.3747e+00   9.1587e-03   9.7386e-02   3.7863e-02   1.8701e-01   2.7729e-01   8.4511e-01   8.4164e-02   9.4149e-01   8.0525e-02
-#> 118:    1.0174e+02  -4.0727e+00  -2.3776e+00  -4.0850e+00  -9.6982e-01  -1.2188e-03   4.1560e+00   8.7008e-03   9.2516e-02   4.9300e-02   2.1364e-01   2.6343e-01   9.5447e-01   8.6627e-02   9.1835e-01   8.1284e-02
-#> 119:    1.0141e+02  -4.0887e+00  -2.3138e+00  -4.0772e+00  -9.9409e-01  -5.0120e-02   3.9482e+00   8.2658e-03   8.7891e-02   4.6835e-02   2.5364e-01   2.5026e-01   9.4576e-01   8.4355e-02   9.5762e-01   8.5430e-02
-#> 120:    1.0116e+02  -4.1014e+00  -2.3328e+00  -4.0418e+00  -9.7139e-01  -8.9664e-02   3.7508e+00   7.8525e-03   8.3496e-02   4.4493e-02   2.4096e-01   2.3774e-01   9.2816e-01   8.5558e-02   9.7817e-01   8.5169e-02
-#> 121:    1.0099e+02  -4.0876e+00  -2.3277e+00  -4.0746e+00  -9.5453e-01  -2.6752e-02   3.5632e+00   7.4598e-03   7.9321e-02   4.2269e-02   2.2891e-01   2.2586e-01   8.9613e-01   8.0488e-02   9.7590e-01   8.4798e-02
-#> 122:    1.0171e+02  -4.0620e+00  -2.3349e+00  -4.0659e+00  -9.4420e-01  -1.6907e-02   3.3851e+00   7.0869e-03   8.8424e-02   4.0155e-02   2.1747e-01   2.1456e-01   9.0159e-01   7.8017e-02   9.8579e-01   8.4585e-02
-#> 123:    1.0191e+02  -4.0708e+00  -2.3487e+00  -4.0827e+00  -9.5025e-01  -5.7459e-03   3.2158e+00   6.7325e-03   1.0499e-01   3.8147e-02   2.0659e-01   2.0384e-01   9.6378e-01   7.4758e-02   9.6268e-01   8.4712e-02
-#> 124:    1.0224e+02  -4.0798e+00  -2.2989e+00  -4.0724e+00  -9.8452e-01  -3.1802e-02   3.0550e+00   6.3959e-03   9.9739e-02   3.6240e-02   1.9626e-01   1.9364e-01   9.4424e-01   7.4219e-02   9.9842e-01   8.4793e-02
-#> 125:    1.0242e+02  -4.0710e+00  -2.3242e+00  -4.0661e+00  -1.0094e+00  -2.9970e-02   2.9023e+00   6.0761e-03   9.4752e-02   3.6130e-02   1.8645e-01   1.8396e-01   9.2576e-01   8.0533e-02   9.9407e-01   8.1660e-02
-#> 126:    1.0254e+02  -4.0685e+00  -2.3356e+00  -4.0599e+00  -1.0031e+00   4.0250e-03   2.7571e+00   5.7723e-03   1.0658e-01   3.4324e-02   1.7971e-01   1.7476e-01   9.4870e-01   7.4027e-02   9.2757e-01   8.3091e-02
-#> 127:    1.0270e+02  -4.0492e+00  -2.3174e+00  -4.0476e+00  -9.9898e-01  -6.3197e-02   2.6193e+00   5.4837e-03   1.0746e-01   3.2607e-02   1.7072e-01   1.6603e-01   9.0721e-01   7.7941e-02   9.4624e-01   8.1077e-02
-#> 128:    1.0284e+02  -4.0582e+00  -2.2991e+00  -4.0331e+00  -9.9114e-01  -5.6800e-02   2.4883e+00   5.2095e-03   1.2321e-01   3.1304e-02   1.6219e-01   1.5772e-01   8.7403e-01   8.4147e-02   8.9187e-01   8.5089e-02
-#> 129:    1.0275e+02  -4.0773e+00  -2.2935e+00  -4.0389e+00  -9.9661e-01  -7.4747e-02   2.3639e+00   4.9922e-03   1.1705e-01   2.9738e-02   1.9667e-01   1.4984e-01   9.1481e-01   8.4947e-02   9.3224e-01   8.5270e-02
-#> 130:    1.0222e+02  -4.0835e+00  -2.3177e+00  -4.0343e+00  -1.0044e+00  -7.6530e-02   2.2457e+00   4.7426e-03   1.1120e-01   3.1348e-02   2.0663e-01   1.4235e-01   1.0173e+00   7.4769e-02   9.9905e-01   8.6058e-02
-#> 131:    1.0202e+02  -4.0767e+00  -2.2497e+00  -4.0270e+00  -1.0015e+00  -1.4868e-01   2.1334e+00   5.5790e-03   1.0564e-01   2.9781e-02   2.1254e-01   1.3523e-01   1.0223e+00   7.7587e-02   9.4151e-01   8.4206e-02
-#> 132:    1.0191e+02  -4.0756e+00  -2.2363e+00  -4.0081e+00  -9.7264e-01  -2.0991e-01   2.0268e+00   5.3000e-03   1.0184e-01   2.8291e-02   2.0191e-01   1.7667e-01   9.2404e-01   7.9813e-02   9.2266e-01   8.6307e-02
-#> 133:    1.0187e+02  -4.0743e+00  -2.1951e+00  -4.0196e+00  -9.7534e-01  -1.8742e-01   1.9254e+00   5.0350e-03   9.6744e-02   2.6877e-02   1.9181e-01   1.6784e-01   1.0007e+00   8.2043e-02   1.0028e+00   8.3921e-02
-#> 134:    1.0182e+02  -4.0731e+00  -2.2321e+00  -4.0041e+00  -9.2800e-01  -1.4985e-01   1.8291e+00   4.7833e-03   9.1906e-02   2.7751e-02   1.8222e-01   1.6415e-01   9.7093e-01   7.5558e-02   9.8455e-01   8.4921e-02
-#> 135:    1.0188e+02  -4.0724e+00  -2.2774e+00  -4.0213e+00  -9.3930e-01  -1.7385e-01   1.7377e+00   4.5441e-03   8.7311e-02   2.6363e-02   1.7311e-01   1.5594e-01   9.4053e-01   8.3922e-02   9.8689e-01   8.1203e-02
-#> 136:    1.0202e+02  -4.0712e+00  -2.2711e+00  -4.0128e+00  -9.8747e-01  -1.3610e-01   1.6508e+00   4.3169e-03   1.0383e-01   2.5045e-02   1.8004e-01   1.4814e-01   9.6497e-01   8.1397e-02   1.0782e+00   8.2539e-02
-#> 137:    1.0228e+02  -4.0676e+00  -2.2403e+00  -4.0069e+00  -9.7761e-01  -1.5314e-01   1.5683e+00   4.1011e-03   1.0931e-01   2.4722e-02   1.8328e-01   1.4074e-01   9.8300e-01   7.5906e-02   1.0221e+00   8.2306e-02
-#> 138:    1.0229e+02  -4.0654e+00  -2.2510e+00  -3.9908e+00  -1.0400e+00  -1.4173e-01   1.4899e+00   4.2166e-03   1.3448e-01   2.3486e-02   1.8272e-01   1.3370e-01   1.0305e+00   8.0580e-02   1.0988e+00   8.3512e-02
-#> 139:    1.0258e+02  -4.0599e+00  -2.2207e+00  -3.9622e+00  -1.0058e+00  -2.6676e-01   1.4154e+00   4.0057e-03   1.5190e-01   2.2312e-02   1.7359e-01   1.2702e-01   9.6425e-01   8.6887e-02   1.0373e+00   8.3853e-02
-#> 140:    1.0224e+02  -4.0665e+00  -2.2479e+00  -4.0063e+00  -1.0054e+00  -1.6109e-01   1.3446e+00   3.8054e-03   1.4430e-01   2.4389e-02   1.6697e-01   1.2066e-01   9.9245e-01   8.3900e-02   1.1218e+00   8.2527e-02
-#> 141:    1.0245e+02  -4.0843e+00  -2.2024e+00  -3.9657e+00  -1.0057e+00  -2.4900e-01   1.2774e+00   3.6152e-03   1.3709e-01   2.3170e-02   1.8559e-01   1.1463e-01   9.4091e-01   8.7616e-02   1.0760e+00   8.1871e-02
-#> 142:    1.0253e+02  -4.0972e+00  -2.1943e+00  -3.9649e+00  -1.0160e+00  -2.9535e-01   1.2135e+00   3.4344e-03   1.6892e-01   2.2011e-02   1.7631e-01   1.0890e-01   9.2146e-01   9.0207e-02   1.0645e+00   8.5078e-02
-#> 143:    1.0252e+02  -4.1005e+00  -2.1652e+00  -3.9687e+00  -1.0445e+00  -2.4274e-01   2.0559e+00   3.9136e-03   1.6047e-01   2.0911e-02   1.6750e-01   1.0345e-01   9.0785e-01   8.5522e-02   1.1734e+00   8.5544e-02
-#> 144:    1.0257e+02  -4.1199e+00  -2.1994e+00  -3.9618e+00  -1.0480e+00  -2.0099e-01   1.9531e+00   4.2739e-03   1.5745e-01   1.9865e-02   1.6053e-01   9.8282e-02   9.3710e-01   8.5496e-02   1.0597e+00   8.4335e-02
-#> 145:    1.0282e+02  -4.1356e+00  -2.1489e+00  -3.9708e+00  -1.0268e+00  -2.2250e-01   1.8554e+00   4.0602e-03   1.7177e-01   1.8872e-02   1.5251e-01   9.3368e-02   9.5312e-01   8.3609e-02   1.0695e+00   8.3492e-02
-#> 146:    1.0282e+02  -4.1443e+00  -2.2103e+00  -3.9821e+00  -1.0080e+00  -2.2414e-01   1.7627e+00   4.0693e-03   1.6460e-01   1.7928e-02   1.5576e-01   8.8699e-02   9.8656e-01   8.4549e-02   1.0251e+00   7.9572e-02
-#> 147:    1.0295e+02  -4.1363e+00  -2.1920e+00  -3.9828e+00  -1.0567e+00  -1.9047e-01   1.6745e+00   3.8659e-03   1.6104e-01   1.7032e-02   1.6551e-01   8.4264e-02   9.4144e-01   8.7085e-02   1.0623e+00   8.1949e-02
-#> 148:    1.0299e+02  -4.1336e+00  -2.1967e+00  -3.9921e+00  -1.0425e+00  -1.7466e-01   1.7992e+00   3.6726e-03   1.5298e-01   1.9937e-02   1.9453e-01   8.0051e-02   9.9498e-01   8.3001e-02   1.0884e+00   8.1599e-02
-#> 149:    1.0292e+02  -4.1282e+00  -2.2741e+00  -4.0028e+00  -1.0650e+00  -1.4879e-01   2.1425e+00   3.4890e-03   1.4534e-01   1.8941e-02   2.0240e-01   7.6049e-02   1.0080e+00   7.9550e-02   1.1679e+00   7.9115e-02
-#> 150:    1.0302e+02  -4.1402e+00  -2.2769e+00  -4.0056e+00  -1.0488e+00  -1.2845e-01   2.7814e+00   3.3145e-03   1.3807e-01   2.0220e-02   1.9228e-01   7.2246e-02   9.9253e-01   8.0215e-02   1.0075e+00   8.2295e-02
-#> 151:    1.0304e+02  -4.1281e+00  -2.2250e+00  -4.0169e+00  -1.0448e+00  -1.4468e-01   2.6423e+00   3.1488e-03   1.3117e-01   2.1298e-02   1.8267e-01   6.8634e-02   1.0207e+00   8.0317e-02   1.0813e+00   8.5492e-02
-#> 152:    1.0321e+02  -4.1291e+00  -2.2281e+00  -4.0180e+00  -1.0232e+00  -1.4990e-01   1.6327e+00   2.8585e-03   1.0498e-01   1.8944e-02   1.6146e-01   5.0784e-02   9.5663e-01   7.9113e-02   1.1344e+00   8.2687e-02
-#> 153:    1.0309e+02  -4.1280e+00  -2.2030e+00  -4.0149e+00  -1.0198e+00  -1.3442e-01   1.6757e+00   3.4142e-03   9.0693e-02   2.2471e-02   1.6167e-01   3.6279e-02   9.6659e-01   8.1655e-02   1.0345e+00   8.6113e-02
-#> 154:    1.0298e+02  -4.1506e+00  -2.2176e+00  -3.9851e+00  -1.0417e+00  -1.6429e-01   1.9656e+00   3.3408e-03   9.5697e-02   2.1721e-02   1.6754e-01   2.9142e-02   1.0379e+00   7.9957e-02   1.0132e+00   8.5327e-02
-#> 155:    1.0328e+02  -4.1204e+00  -2.2287e+00  -3.9772e+00  -1.0135e+00  -2.0459e-01   1.9195e+00   3.3987e-03   1.0293e-01   1.6897e-02   1.9470e-01   2.0826e-02   9.4310e-01   8.0528e-02   1.0639e+00   8.1926e-02
-#> 156:    1.0338e+02  -4.1272e+00  -2.1962e+00  -3.9743e+00  -1.0491e+00  -1.8971e-01   1.7194e+00   3.2287e-03   7.8468e-02   1.8220e-02   1.8015e-01   2.0956e-02   9.2992e-01   8.6295e-02   9.5939e-01   8.1945e-02
-#> 157:    1.0331e+02  -4.1188e+00  -2.1783e+00  -3.9779e+00  -1.0506e+00  -1.9810e-01   1.1127e+00   2.7176e-03   6.1234e-02   1.3748e-02   2.0147e-01   3.4800e-02   9.3006e-01   8.4794e-02   1.0579e+00   8.1604e-02
-#> 158:    1.0326e+02  -4.1162e+00  -2.1734e+00  -3.9827e+00  -1.0632e+00  -2.0171e-01   1.3289e+00   2.7407e-03   7.1465e-02   1.2306e-02   2.1511e-01   3.4923e-02   8.9200e-01   8.4554e-02   1.1179e+00   8.2301e-02
-#> 159:    1.0358e+02  -4.1075e+00  -2.2069e+00  -3.9725e+00  -1.0445e+00  -1.8044e-01   1.6656e+00   2.5282e-03   6.4340e-02   1.3587e-02   2.0355e-01   2.7629e-02   8.9557e-01   8.3727e-02   1.0560e+00   8.0934e-02
-#> 160:    1.0364e+02  -4.1182e+00  -2.1514e+00  -3.9750e+00  -1.0378e+00  -2.2449e-01   1.8413e+00   3.5609e-03   7.2072e-02   1.5648e-02   2.0999e-01   3.1283e-02   9.1468e-01   8.2340e-02   1.0016e+00   8.0955e-02
-#> 161:    1.0387e+02  -4.0964e+00  -2.1926e+00  -3.9808e+00  -1.0397e+00  -2.5178e-01   2.3706e+00   2.4158e-03   7.4658e-02   1.7789e-02   1.8587e-01   3.1647e-02   8.8257e-01   8.4503e-02   9.5909e-01   8.2216e-02
-#> 162:    1.0399e+02  -4.0992e+00  -2.2056e+00  -3.9647e+00  -1.0388e+00  -2.4824e-01   1.9736e+00   2.2302e-03   1.0445e-01   1.9729e-02   1.9531e-01   2.9879e-02   8.3560e-01   8.6622e-02   9.5407e-01   7.9625e-02
-#> 163:    1.0366e+02  -4.0956e+00  -2.1684e+00  -3.9612e+00  -1.0058e+00  -2.6882e-01   2.5872e+00   1.6246e-03   8.1892e-02   2.2777e-02   2.2429e-01   2.8371e-02   8.4799e-01   9.0947e-02   9.5842e-01   8.2649e-02
-#> 164:    1.0325e+02  -4.0878e+00  -2.1946e+00  -3.9781e+00  -9.8890e-01  -2.6917e-01   2.0805e+00   1.3401e-03   8.2477e-02   2.6550e-02   1.8386e-01   2.4255e-02   8.5728e-01   8.9778e-02   9.1439e-01   7.9784e-02
-#> 165:    1.0282e+02  -4.0801e+00  -2.1928e+00  -3.9664e+00  -9.9558e-01  -2.6059e-01   1.4087e+00   1.2155e-03   5.8081e-02   2.3833e-02   2.1871e-01   2.0911e-02   8.6998e-01   8.9895e-02   9.9363e-01   8.0284e-02
-#> 166:    1.0285e+02  -4.0942e+00  -2.1855e+00  -3.9889e+00  -1.0234e+00  -2.4125e-01   8.5034e-01   6.8919e-04   6.5725e-02   2.3045e-02   2.1221e-01   2.6083e-02   8.7024e-01   9.4598e-02   9.5824e-01   8.3361e-02
-#> 167:    1.0267e+02  -4.0904e+00  -2.2131e+00  -3.9917e+00  -9.9055e-01  -2.1449e-01   9.1382e-01   4.6145e-04   8.1337e-02   2.2154e-02   2.1431e-01   2.7524e-02   8.4730e-01   8.3563e-02   9.9458e-01   8.0138e-02
-#> 168:    1.0249e+02  -4.0954e+00  -2.2174e+00  -3.9868e+00  -9.9799e-01  -1.8848e-01   6.5737e-01   4.2757e-04   6.9428e-02   2.8833e-02   2.0256e-01   4.1573e-02   9.8269e-01   7.6264e-02   1.0011e+00   8.1357e-02
-#> 169:    1.0252e+02  -4.0995e+00  -2.2132e+00  -3.9792e+00  -9.8661e-01  -2.2724e-01   5.4553e-01   3.9691e-04   4.2460e-02   2.7545e-02   2.2594e-01   4.9079e-02   9.6027e-01   8.1006e-02   1.0261e+00   8.5194e-02
-#> 170:    1.0246e+02  -4.1056e+00  -2.2389e+00  -3.9785e+00  -1.0354e+00  -2.4212e-01   4.5653e-01   2.8583e-04   2.8936e-02   2.5026e-02   1.8496e-01   4.3514e-02   9.2689e-01   9.6050e-02   9.9096e-01   8.3466e-02
-#> 171:    1.0238e+02  -4.1027e+00  -2.2592e+00  -3.9859e+00  -1.0106e+00  -2.3962e-01   5.1080e-01   2.6715e-04   3.2138e-02   2.7859e-02   1.6505e-01   6.2560e-02   9.1886e-01   9.0993e-02   9.4634e-01   8.3542e-02
-#> 172:    1.0242e+02  -4.0998e+00  -2.2415e+00  -3.9999e+00  -1.0234e+00  -2.2610e-01   5.1154e-01   1.8668e-04   2.2768e-02   2.9930e-02   2.0056e-01   7.5570e-02   9.4948e-01   8.4742e-02   9.1357e-01   8.3596e-02
-#> 173:    1.0232e+02  -4.1005e+00  -2.2382e+00  -4.0022e+00  -1.0017e+00  -1.8406e-01   3.2169e-01   2.0484e-04   2.4102e-02   2.9249e-02   2.0445e-01   1.1517e-01   9.5169e-01   8.3951e-02   9.0402e-01   8.3130e-02
-#> 174:    1.0233e+02  -4.0990e+00  -2.2337e+00  -3.9975e+00  -1.0298e+00  -1.8028e-01   4.2668e-01   2.1409e-04   2.4350e-02   2.4159e-02   2.0114e-01   1.4344e-01   9.3446e-01   8.6704e-02   9.6511e-01   8.3994e-02
-#> 175:    1.0236e+02  -4.0991e+00  -2.2315e+00  -3.9883e+00  -1.0110e+00  -2.2190e-01   4.1564e-01   2.5844e-04   3.5664e-02   2.1844e-02   2.0315e-01   1.2876e-01   8.9006e-01   8.3016e-02   9.2369e-01   8.0410e-02
-#> 176:    1.0222e+02  -4.0983e+00  -2.1991e+00  -3.9924e+00  -1.0148e+00  -2.3133e-01   1.7684e-01   2.5312e-04   5.3516e-02   2.2568e-02   2.0010e-01   1.0721e-01   8.9884e-01   7.6042e-02   1.0110e+00   7.9890e-02
-#> 177:    1.0219e+02  -4.1022e+00  -2.2129e+00  -3.9804e+00  -1.0286e+00  -1.9916e-01   1.9962e-01   3.0338e-04   6.9476e-02   2.0133e-02   1.8707e-01   1.0631e-01   8.7419e-01   8.3199e-02   9.5450e-01   8.2626e-02
-#> 178:    1.0225e+02  -4.1022e+00  -2.2135e+00  -4.0057e+00  -1.0264e+00  -2.2859e-01   2.1742e-01   2.9489e-04   5.1238e-02   2.2227e-02   1.7924e-01   1.4496e-01   8.5487e-01   8.3885e-02   9.7315e-01   8.1406e-02
-#> 179:    1.0234e+02  -4.1015e+00  -2.2170e+00  -3.9999e+00  -1.0177e+00  -2.0895e-01   2.1196e-01   3.0802e-04   5.7417e-02   2.6776e-02   1.7214e-01   1.5197e-01   8.8641e-01   7.7789e-02   9.2725e-01   8.1277e-02
-#> 180:    1.0243e+02  -4.1034e+00  -2.2337e+00  -4.0000e+00  -1.0018e+00  -2.3492e-01   2.0521e-01   3.1261e-04   6.0162e-02   2.7277e-02   1.7524e-01   1.6673e-01   8.8472e-01   7.8939e-02   9.1311e-01   8.3794e-02
-#> 181:    1.0244e+02  -4.1031e+00  -2.2415e+00  -3.9951e+00  -9.9356e-01  -1.9938e-01   1.4850e-01   2.7894e-04   5.5244e-02   3.2404e-02   2.0701e-01   2.1022e-01   8.7495e-01   8.1883e-02   9.7574e-01   8.4575e-02
-#> 182:    1.0245e+02  -4.1066e+00  -2.2849e+00  -4.0083e+00  -1.0260e+00  -1.9418e-01   1.0783e-01   1.7359e-04   2.9632e-02   3.2098e-02   2.0294e-01   1.7919e-01   9.0795e-01   9.1179e-02   9.8651e-01   8.3561e-02
-#> 183:    1.0248e+02  -4.1066e+00  -2.2844e+00  -4.0201e+00  -1.0102e+00  -1.5510e-01   9.2727e-02   1.4337e-04   2.8436e-02   4.3941e-02   1.9683e-01   2.1943e-01   9.0334e-01   8.2113e-02   8.9037e-01   8.4506e-02
-#> 184:    1.0239e+02  -4.1032e+00  -2.2726e+00  -4.0270e+00  -1.0162e+00  -1.4921e-01   9.0062e-02   1.0820e-04   3.5099e-02   4.7338e-02   1.8488e-01   2.2174e-01   9.1525e-01   7.9986e-02   8.6762e-01   8.4376e-02
-#> 185:    1.0240e+02  -4.1028e+00  -2.3201e+00  -4.0248e+00  -9.8758e-01  -1.7235e-01   9.2455e-02   8.9653e-05   4.7097e-02   4.5964e-02   1.9093e-01   1.9093e-01   9.5192e-01   7.6980e-02   9.4058e-01   8.2740e-02
-#> 186:    1.0250e+02  -4.1020e+00  -2.3095e+00  -4.0326e+00  -9.9767e-01  -1.2041e-01   1.0792e-01   7.3472e-05   3.6352e-02   4.6680e-02   1.7527e-01   1.7411e-01   9.6831e-01   8.3088e-02   9.7978e-01   8.1096e-02
-#> 187:    1.0254e+02  -4.1022e+00  -2.3078e+00  -4.0329e+00  -1.0166e+00  -1.1644e-01   8.2987e-02   7.9222e-05   3.8388e-02   6.0452e-02   2.3498e-01   1.7389e-01   1.0450e+00   8.0354e-02   9.7366e-01   8.2504e-02
-#> 188:    1.0253e+02  -4.1022e+00  -2.3172e+00  -4.0401e+00  -1.0276e+00  -8.2442e-02   8.3913e-02   7.1884e-05   4.3025e-02   4.8383e-02   1.9392e-01   1.6073e-01   9.7466e-01   7.5977e-02   9.0319e-01   8.4648e-02
-#> 189:    1.0256e+02  -4.1013e+00  -2.3037e+00  -4.0402e+00  -1.0004e+00  -1.5946e-01   9.6273e-02   8.0773e-05   4.6130e-02   5.2356e-02   2.1044e-01   2.0403e-01   9.2931e-01   8.2686e-02   9.0103e-01   8.5442e-02
-#> 190:    1.0245e+02  -4.1021e+00  -2.3143e+00  -4.0314e+00  -9.9314e-01  -8.5545e-02   8.0660e-02   7.3369e-05   4.1713e-02   4.4940e-02   1.7715e-01   1.6886e-01   9.7982e-01   8.1720e-02   8.9868e-01   8.4964e-02
-#> 191:    1.0251e+02  -4.1021e+00  -2.2849e+00  -4.0229e+00  -1.0346e+00  -9.0261e-02   6.1956e-02   9.4824e-05   5.8037e-02   4.0685e-02   1.8455e-01   2.2838e-01   9.9679e-01   7.7457e-02   9.4591e-01   8.5446e-02
-#> 192:    1.0249e+02  -4.1012e+00  -2.2915e+00  -4.0452e+00  -1.0323e+00  -1.1123e-01   5.1409e-02   1.1452e-04   7.2457e-02   3.6376e-02   1.6706e-01   2.1050e-01   8.7970e-01   8.6881e-02   9.2230e-01   8.6563e-02
-#> 193:    1.0249e+02  -4.1011e+00  -2.3104e+00  -4.0569e+00  -1.0032e+00  -2.9383e-02   4.2462e-02   9.6872e-05   4.9405e-02   4.6840e-02   1.7348e-01   1.4473e-01   9.1758e-01   8.1380e-02   1.0057e+00   8.4481e-02
-#> 194:    1.0250e+02  -4.1009e+00  -2.2960e+00  -4.0567e+00  -9.9145e-01  -1.0640e-01   2.6698e-02   5.3298e-05   4.3880e-02   5.1866e-02   2.0619e-01   1.4008e-01   9.8306e-01   8.0320e-02   9.8405e-01   8.0106e-02
-#> 195:    1.0252e+02  -4.1001e+00  -2.2779e+00  -4.0677e+00  -9.9960e-01  -5.5605e-02   1.9114e-02   5.6472e-05   4.5810e-02   5.1552e-02   1.8363e-01   1.2037e-01   9.9334e-01   8.2093e-02   9.9128e-01   8.3930e-02
-#> 196:    1.0251e+02  -4.0988e+00  -2.2515e+00  -4.0555e+00  -9.9701e-01  -1.0235e-01   1.3362e-02   3.2648e-05   4.0337e-02   4.4117e-02   1.9469e-01   1.2907e-01   9.1150e-01   8.5071e-02   9.7929e-01   8.2761e-02
-#> 197:    1.0253e+02  -4.0985e+00  -2.2589e+00  -4.0427e+00  -1.0251e+00  -9.4695e-02   1.7104e-02   2.3125e-05   4.1773e-02   3.3831e-02   2.1013e-01   1.3727e-01   9.1462e-01   8.1836e-02   9.7695e-01   8.1326e-02
-#> 198:    1.0253e+02  -4.0992e+00  -2.2745e+00  -4.0327e+00  -9.8743e-01  -1.4108e-01   9.3331e-03   2.3064e-05   3.7271e-02   2.7379e-02   2.1190e-01   9.3733e-02   9.0916e-01   8.4247e-02   9.8720e-01   7.7405e-02
-#> 199:    1.0251e+02  -4.0981e+00  -2.2770e+00  -4.0275e+00  -1.0216e+00  -1.3364e-01   8.3776e-03   2.3195e-05   4.6827e-02   3.2861e-02   1.9817e-01   8.7748e-02   9.1184e-01   8.3773e-02   9.5209e-01   7.9056e-02
-#> 200:    1.0252e+02  -4.0992e+00  -2.2757e+00  -4.0277e+00  -9.9266e-01  -8.4583e-02   6.8073e-03   2.9414e-05   5.3404e-02   2.5942e-02   1.9915e-01   7.4937e-02   8.7168e-01   8.5197e-02   9.3606e-01   8.0739e-02
-#> 201:    1.0252e+02  -4.0989e+00  -2.2706e+00  -4.0333e+00  -9.8978e-01  -8.7996e-02   5.9272e-03   2.4268e-05   5.4295e-02   2.9276e-02   2.0543e-01   7.1533e-02   9.0557e-01   8.3204e-02   9.4913e-01   8.0398e-02
-#> 202:    1.0251e+02  -4.0990e+00  -2.2661e+00  -4.0324e+00  -9.8785e-01  -9.8008e-02   5.7831e-03   2.1967e-05   5.7627e-02   3.0606e-02   2.1414e-01   6.9475e-02   9.2255e-01   8.2143e-02   9.5633e-01   8.1333e-02
-#> 203:    1.0251e+02  -4.0992e+00  -2.2586e+00  -4.0297e+00  -9.9017e-01  -1.1012e-01   6.4046e-03   2.2234e-05   5.7955e-02   3.0102e-02   2.0473e-01   6.8225e-02   9.2900e-01   8.3228e-02   9.5862e-01   8.1460e-02
-#> 204:    1.0251e+02  -4.0995e+00  -2.2570e+00  -4.0280e+00  -9.9135e-01  -1.0718e-01   6.5386e-03   2.2043e-05   5.6949e-02   2.9096e-02   2.0562e-01   6.8687e-02   9.3306e-01   8.2703e-02   9.6581e-01   8.1671e-02
-#> 205:    1.0250e+02  -4.0997e+00  -2.2569e+00  -4.0256e+00  -9.9350e-01  -1.1491e-01   6.1521e-03   2.2570e-05   5.5450e-02   2.8152e-02   2.0423e-01   7.2820e-02   9.2469e-01   8.3272e-02   9.7372e-01   8.0814e-02
-#> 206:    1.0250e+02  -4.0997e+00  -2.2567e+00  -4.0269e+00  -9.9869e-01  -1.1438e-01   5.9720e-03   2.3307e-05   5.5103e-02   2.8506e-02   2.0414e-01   7.8225e-02   9.2768e-01   8.3328e-02   9.8294e-01   8.0918e-02
-#> 207:    1.0250e+02  -4.0998e+00  -2.2657e+00  -4.0311e+00  -1.0000e+00  -1.0595e-01   6.0030e-03   2.4031e-05   5.4378e-02   2.9468e-02   2.0222e-01   8.1455e-02   9.3397e-01   8.3285e-02   9.8989e-01   8.0967e-02
-#> 208:    1.0250e+02  -4.0999e+00  -2.2759e+00  -4.0330e+00  -1.0001e+00  -9.6916e-02   5.9586e-03   2.3690e-05   5.3811e-02   2.9674e-02   1.9979e-01   8.1206e-02   9.3593e-01   8.4094e-02   9.8891e-01   8.1107e-02
-#> 209:    1.0250e+02  -4.0998e+00  -2.2836e+00  -4.0344e+00  -1.0016e+00  -8.9119e-02   5.6137e-03   2.3512e-05   5.4159e-02   2.9780e-02   1.9778e-01   8.2635e-02   9.4080e-01   8.3757e-02   9.9062e-01   8.0979e-02
-#> 210:    1.0251e+02  -4.0998e+00  -2.2898e+00  -4.0334e+00  -1.0017e+00  -8.3861e-02   5.2428e-03   2.3117e-05   5.4271e-02   2.9112e-02   1.9539e-01   8.3602e-02   9.4410e-01   8.4262e-02   9.8944e-01   8.1260e-02
-#> 211:    1.0251e+02  -4.0998e+00  -2.2968e+00  -4.0329e+00  -9.9953e-01  -8.2036e-02   4.9312e-03   2.2863e-05   5.5392e-02   2.8432e-02   1.9466e-01   8.3724e-02   9.5395e-01   8.4317e-02   9.9876e-01   8.1402e-02
-#> 212:    1.0251e+02  -4.0997e+00  -2.2982e+00  -4.0327e+00  -1.0018e+00  -8.2942e-02   4.6622e-03   2.3364e-05   5.5864e-02   2.7552e-02   1.9313e-01   8.3815e-02   9.5374e-01   8.4223e-02   1.0049e+00   8.1479e-02
-#> 213:    1.0251e+02  -4.0995e+00  -2.2996e+00  -4.0322e+00  -1.0027e+00  -8.4931e-02   4.4988e-03   2.4085e-05   5.6000e-02   2.6729e-02   1.9184e-01   8.3522e-02   9.5091e-01   8.4321e-02   1.0026e+00   8.1310e-02
-#> 214:    1.0251e+02  -4.0994e+00  -2.2997e+00  -4.0326e+00  -1.0033e+00  -8.7810e-02   4.3582e-03   2.5253e-05   5.6470e-02   2.6179e-02   1.9110e-01   8.5338e-02   9.5311e-01   8.4118e-02   1.0062e+00   8.1320e-02
-#> 215:    1.0251e+02  -4.0993e+00  -2.3013e+00  -4.0331e+00  -1.0042e+00  -8.5053e-02   4.3765e-03   2.6370e-05   5.6978e-02   2.5984e-02   1.8960e-01   8.6633e-02   9.5505e-01   8.3787e-02   1.0092e+00   8.1298e-02
-#> 216:    1.0251e+02  -4.0993e+00  -2.3032e+00  -4.0320e+00  -1.0033e+00  -8.5521e-02   4.4127e-03   2.7607e-05   5.7092e-02   2.5514e-02   1.8916e-01   8.8986e-02   9.5571e-01   8.3655e-02   1.0106e+00   8.1177e-02
-#> 217:    1.0251e+02  -4.0993e+00  -2.3050e+00  -4.0309e+00  -1.0039e+00  -8.5267e-02   4.4663e-03   2.8101e-05   5.7536e-02   2.5186e-02   1.8803e-01   9.0776e-02   9.5624e-01   8.3792e-02   1.0100e+00   8.1214e-02
-#> 218:    1.0251e+02  -4.0993e+00  -2.3068e+00  -4.0309e+00  -1.0052e+00  -8.3353e-02   4.4833e-03   2.7541e-05   5.7391e-02   2.4589e-02   1.8691e-01   9.4302e-02   9.5168e-01   8.4114e-02   1.0124e+00   8.1211e-02
-#> 219:    1.0251e+02  -4.0993e+00  -2.3077e+00  -4.0316e+00  -1.0049e+00  -8.0885e-02   4.4529e-03   2.6825e-05   5.7273e-02   2.3909e-02   1.8700e-01   9.6040e-02   9.4675e-01   8.4115e-02   1.0115e+00   8.1075e-02
-#> 220:    1.0251e+02  -4.0993e+00  -2.3095e+00  -4.0327e+00  -1.0051e+00  -7.6386e-02   4.5217e-03   2.6724e-05   5.7342e-02   2.3648e-02   1.8752e-01   9.7466e-02   9.4316e-01   8.4134e-02   1.0099e+00   8.1206e-02
-#> 221:    1.0251e+02  -4.0993e+00  -2.3120e+00  -4.0339e+00  -1.0050e+00  -7.3314e-02   4.5361e-03   2.6133e-05   5.7387e-02   2.3612e-02   1.8744e-01   9.9108e-02   9.4164e-01   8.4073e-02   1.0096e+00   8.1143e-02
-#> 222:    1.0251e+02  -4.0993e+00  -2.3136e+00  -4.0355e+00  -1.0049e+00  -6.8041e-02   4.5806e-03   2.5728e-05   5.7827e-02   2.3466e-02   1.8681e-01   9.9150e-02   9.4237e-01   8.3991e-02   1.0116e+00   8.1192e-02
-#> 223:    1.0251e+02  -4.0993e+00  -2.3144e+00  -4.0364e+00  -1.0047e+00  -6.6770e-02   4.5349e-03   2.5412e-05   5.8823e-02   2.3232e-02   1.8728e-01   9.9882e-02   9.4051e-01   8.3808e-02   1.0097e+00   8.1028e-02
-#> 224:    1.0251e+02  -4.0992e+00  -2.3155e+00  -4.0373e+00  -1.0040e+00  -6.4487e-02   4.4985e-03   2.5094e-05   6.0294e-02   2.3022e-02   1.8652e-01   1.0114e-01   9.3800e-01   8.3696e-02   1.0099e+00   8.0990e-02
-#> 225:    1.0251e+02  -4.0992e+00  -2.3167e+00  -4.0384e+00  -1.0041e+00  -6.2966e-02   4.4783e-03   2.4741e-05   6.0569e-02   2.2900e-02   1.8622e-01   1.0072e-01   9.3574e-01   8.3833e-02   1.0075e+00   8.0893e-02
-#> 226:    1.0251e+02  -4.0993e+00  -2.3173e+00  -4.0395e+00  -1.0036e+00  -6.0541e-02   4.4466e-03   2.4601e-05   6.0661e-02   2.2897e-02   1.8544e-01   1.0160e-01   9.3842e-01   8.3565e-02   1.0064e+00   8.1006e-02
-#> 227:    1.0251e+02  -4.0993e+00  -2.3183e+00  -4.0403e+00  -1.0028e+00  -5.9061e-02   4.4290e-03   2.4610e-05   6.1093e-02   2.2836e-02   1.8582e-01   1.0184e-01   9.3983e-01   8.3421e-02   1.0066e+00   8.1225e-02
-#> 228:    1.0251e+02  -4.0993e+00  -2.3190e+00  -4.0405e+00  -1.0027e+00  -5.8994e-02   4.4377e-03   2.4228e-05   6.0957e-02   2.2540e-02   1.8424e-01   1.0104e-01   9.4056e-01   8.3559e-02   1.0085e+00   8.1266e-02
-#> 229:    1.0251e+02  -4.0993e+00  -2.3206e+00  -4.0398e+00  -1.0026e+00  -5.9258e-02   4.5021e-03   2.3801e-05   6.0331e-02   2.2380e-02   1.8409e-01   9.9681e-02   9.4320e-01   8.3678e-02   1.0111e+00   8.1236e-02
-#> 230:    1.0251e+02  -4.0994e+00  -2.3217e+00  -4.0401e+00  -1.0028e+00  -5.7766e-02   4.5320e-03   2.3519e-05   5.9913e-02   2.2317e-02   1.8484e-01   9.9325e-02   9.4418e-01   8.3884e-02   1.0144e+00   8.1294e-02
-#> 231:    1.0251e+02  -4.0994e+00  -2.3223e+00  -4.0400e+00  -1.0036e+00  -5.7213e-02   4.6519e-03   2.3658e-05   5.9386e-02   2.2185e-02   1.8526e-01   9.8374e-02   9.4356e-01   8.4167e-02   1.0171e+00   8.1315e-02
-#> 232:    1.0251e+02  -4.0994e+00  -2.3231e+00  -4.0400e+00  -1.0045e+00  -5.5248e-02   4.7067e-03   2.3117e-05   5.9583e-02   2.2248e-02   1.8574e-01   9.7396e-02   9.4340e-01   8.4212e-02   1.0179e+00   8.1401e-02
-#> 233:    1.0251e+02  -4.0994e+00  -2.3237e+00  -4.0401e+00  -1.0046e+00  -5.4085e-02   4.7534e-03   2.2858e-05   5.8985e-02   2.2248e-02   1.8649e-01   9.7364e-02   9.4271e-01   8.4248e-02   1.0189e+00   8.1456e-02
-#> 234:    1.0251e+02  -4.0995e+00  -2.3238e+00  -4.0400e+00  -1.0042e+00  -5.2957e-02   4.8433e-03   2.2715e-05   5.8868e-02   2.2174e-02   1.8630e-01   9.7975e-02   9.4382e-01   8.4160e-02   1.0210e+00   8.1665e-02
-#> 235:    1.0251e+02  -4.0995e+00  -2.3248e+00  -4.0396e+00  -1.0044e+00  -5.3132e-02   4.8769e-03   2.2540e-05   5.9052e-02   2.2120e-02   1.8627e-01   9.8772e-02   9.4330e-01   8.4170e-02   1.0196e+00   8.1627e-02
-#> 236:    1.0251e+02  -4.0995e+00  -2.3244e+00  -4.0392e+00  -1.0052e+00  -5.3786e-02   4.8860e-03   2.2664e-05   5.8981e-02   2.2095e-02   1.8771e-01   9.8852e-02   9.4172e-01   8.4214e-02   1.0191e+00   8.1698e-02
-#> 237:    1.0251e+02  -4.0996e+00  -2.3231e+00  -4.0386e+00  -1.0056e+00  -5.5158e-02   4.8731e-03   2.2576e-05   5.8788e-02   2.2037e-02   1.8860e-01   9.9599e-02   9.4242e-01   8.4097e-02   1.0198e+00   8.1684e-02
-#> 238:    1.0251e+02  -4.0996e+00  -2.3222e+00  -4.0384e+00  -1.0054e+00  -5.6412e-02   4.8673e-03   2.2575e-05   5.8733e-02   2.1962e-02   1.8874e-01   9.9196e-02   9.4097e-01   8.4103e-02   1.0208e+00   8.1649e-02
-#> 239:    1.0251e+02  -4.0996e+00  -2.3212e+00  -4.0382e+00  -1.0068e+00  -5.7131e-02   4.8223e-03   2.2398e-05   5.8674e-02   2.1817e-02   1.8926e-01   9.9323e-02   9.4261e-01   8.4059e-02   1.0229e+00   8.1670e-02
-#> 240:    1.0251e+02  -4.0996e+00  -2.3216e+00  -4.0376e+00  -1.0073e+00  -5.6962e-02   4.7984e-03   2.2260e-05   5.8558e-02   2.1632e-02   1.8892e-01   9.9232e-02   9.4434e-01   8.4130e-02   1.0237e+00   8.1679e-02
-#> 241:    1.0251e+02  -4.0996e+00  -2.3216e+00  -4.0371e+00  -1.0078e+00  -5.6984e-02   4.7767e-03   2.2074e-05   5.9552e-02   2.1436e-02   1.8860e-01   9.9285e-02   9.4491e-01   8.4026e-02   1.0247e+00   8.1680e-02
-#> 242:    1.0251e+02  -4.0996e+00  -2.3222e+00  -4.0372e+00  -1.0079e+00  -5.6422e-02   4.7880e-03   2.2014e-05   6.0033e-02   2.1277e-02   1.8860e-01   9.8674e-02   9.4359e-01   8.3991e-02   1.0255e+00   8.1634e-02
-#> 243:    1.0251e+02  -4.0995e+00  -2.3227e+00  -4.0376e+00  -1.0079e+00  -5.4330e-02   4.7944e-03   2.1687e-05   6.0189e-02   2.1088e-02   1.8830e-01   9.7952e-02   9.4207e-01   8.4036e-02   1.0257e+00   8.1666e-02
-#> 244:    1.0251e+02  -4.0995e+00  -2.3237e+00  -4.0385e+00  -1.0076e+00  -5.2834e-02   4.7916e-03   2.1467e-05   6.0432e-02   2.1062e-02   1.8810e-01   9.7065e-02   9.4039e-01   8.4075e-02   1.0248e+00   8.1599e-02
-#> 245:    1.0251e+02  -4.0995e+00  -2.3249e+00  -4.0390e+00  -1.0073e+00  -5.0542e-02   4.7926e-03   2.1549e-05   6.1095e-02   2.0981e-02   1.8814e-01   9.6715e-02   9.3900e-01   8.4049e-02   1.0226e+00   8.1505e-02
-#> 246:    1.0251e+02  -4.0995e+00  -2.3261e+00  -4.0398e+00  -1.0066e+00  -4.7686e-02   4.8114e-03   2.1557e-05   6.1692e-02   2.0969e-02   1.8783e-01   9.6477e-02   9.3880e-01   8.4024e-02   1.0211e+00   8.1456e-02
-#> 247:    1.0251e+02  -4.0996e+00  -2.3270e+00  -4.0406e+00  -1.0063e+00  -4.5794e-02   4.7864e-03   2.1709e-05   6.1819e-02   2.0928e-02   1.8765e-01   9.5549e-02   9.3939e-01   8.4076e-02   1.0201e+00   8.1427e-02
-#> 248:    1.0251e+02  -4.0995e+00  -2.3282e+00  -4.0412e+00  -1.0064e+00  -4.3009e-02   4.7307e-03   2.1707e-05   6.2309e-02   2.0970e-02   1.8795e-01   9.5221e-02   9.3898e-01   8.4080e-02   1.0197e+00   8.1501e-02
-#> 249:    1.0251e+02  -4.0996e+00  -2.3298e+00  -4.0417e+00  -1.0070e+00  -4.1062e-02   4.7070e-03   2.1737e-05   6.2607e-02   2.1094e-02   1.8796e-01   9.5103e-02   9.3917e-01   8.4069e-02   1.0194e+00   8.1525e-02
-#> 250:    1.0251e+02  -4.0996e+00  -2.3313e+00  -4.0420e+00  -1.0073e+00  -3.9250e-02   4.7191e-03   2.1947e-05   6.2963e-02   2.1053e-02   1.8834e-01   9.4954e-02   9.3851e-01   8.4115e-02   1.0190e+00   8.1496e-02
-#> 251:    1.0251e+02  -4.0997e+00  -2.3317e+00  -4.0424e+00  -1.0078e+00  -3.7549e-02   4.7501e-03   2.2063e-05   6.3160e-02   2.0958e-02   1.8840e-01   9.4783e-02   9.3749e-01   8.4137e-02   1.0185e+00   8.1476e-02
-#> 252:    1.0251e+02  -4.0997e+00  -2.3319e+00  -4.0424e+00  -1.0083e+00  -3.6657e-02   4.7441e-03   2.2081e-05   6.3250e-02   2.0891e-02   1.8911e-01   9.4954e-02   9.3708e-01   8.4108e-02   1.0180e+00   8.1479e-02
-#> 253:    1.0251e+02  -4.0997e+00  -2.3323e+00  -4.0425e+00  -1.0085e+00  -3.5826e-02   4.7409e-03   2.2021e-05   6.3513e-02   2.0810e-02   1.8920e-01   9.5196e-02   9.3509e-01   8.4179e-02   1.0184e+00   8.1440e-02
-#> 254:    1.0251e+02  -4.0997e+00  -2.3324e+00  -4.0426e+00  -1.0086e+00  -3.6456e-02   4.7046e-03   2.1929e-05   6.3535e-02   2.0859e-02   1.9010e-01   9.5077e-02   9.3362e-01   8.4279e-02   1.0185e+00   8.1371e-02
-#> 255:    1.0251e+02  -4.0997e+00  -2.3313e+00  -4.0424e+00  -1.0088e+00  -3.7358e-02   4.6636e-03   2.1827e-05   6.3864e-02   2.0820e-02   1.9126e-01   9.4979e-02   9.3183e-01   8.4380e-02   1.0185e+00   8.1434e-02
-#> 256:    1.0251e+02  -4.0997e+00  -2.3306e+00  -4.0423e+00  -1.0086e+00  -3.8558e-02   4.6418e-03   2.1776e-05   6.4176e-02   2.0845e-02   1.9175e-01   9.4890e-02   9.3144e-01   8.4436e-02   1.0188e+00   8.1420e-02
-#> 257:    1.0251e+02  -4.0997e+00  -2.3297e+00  -4.0419e+00  -1.0092e+00  -3.9580e-02   4.6134e-03   2.1742e-05   6.4408e-02   2.0751e-02   1.9188e-01   9.4692e-02   9.3113e-01   8.4507e-02   1.0187e+00   8.1412e-02
-#> 258:    1.0251e+02  -4.0997e+00  -2.3287e+00  -4.0415e+00  -1.0090e+00  -4.0619e-02   4.5918e-03   2.1710e-05   6.4634e-02   2.0663e-02   1.9172e-01   9.4422e-02   9.3104e-01   8.4479e-02   1.0189e+00   8.1395e-02
-#> 259:    1.0251e+02  -4.0997e+00  -2.3284e+00  -4.0412e+00  -1.0086e+00  -4.1245e-02   4.5889e-03   2.1741e-05   6.5035e-02   2.0678e-02   1.9132e-01   9.3998e-02   9.2986e-01   8.4448e-02   1.0177e+00   8.1368e-02
-#> 260:    1.0251e+02  -4.0997e+00  -2.3283e+00  -4.0410e+00  -1.0084e+00  -4.1907e-02   4.5818e-03   2.1877e-05   6.5755e-02   2.0691e-02   1.9113e-01   9.3631e-02   9.2955e-01   8.4378e-02   1.0172e+00   8.1346e-02
-#> 261:    1.0251e+02  -4.0998e+00  -2.3282e+00  -4.0409e+00  -1.0087e+00  -4.2022e-02   4.5724e-03   2.1946e-05   6.6396e-02   2.0714e-02   1.9084e-01   9.3140e-02   9.2882e-01   8.4426e-02   1.0166e+00   8.1329e-02
-#> 262:    1.0251e+02  -4.0997e+00  -2.3275e+00  -4.0408e+00  -1.0092e+00  -4.2439e-02   4.5357e-03   2.1842e-05   6.6895e-02   2.0692e-02   1.9082e-01   9.2527e-02   9.2811e-01   8.4447e-02   1.0168e+00   8.1339e-02
-#> 263:    1.0251e+02  -4.0998e+00  -2.3269e+00  -4.0407e+00  -1.0097e+00  -4.2867e-02   4.5244e-03   2.1830e-05   6.7068e-02   2.0721e-02   1.9077e-01   9.2003e-02   9.2800e-01   8.4366e-02   1.0171e+00   8.1343e-02
-#> 264:    1.0251e+02  -4.0998e+00  -2.3262e+00  -4.0403e+00  -1.0102e+00  -4.3066e-02   4.4987e-03   2.1812e-05   6.7458e-02   2.0718e-02   1.9065e-01   9.1528e-02   9.2710e-01   8.4389e-02   1.0163e+00   8.1355e-02
-#> 265:    1.0251e+02  -4.0998e+00  -2.3264e+00  -4.0401e+00  -1.0105e+00  -4.3042e-02   4.4865e-03   2.1721e-05   6.7680e-02   2.0722e-02   1.9057e-01   9.1243e-02   9.2631e-01   8.4430e-02   1.0154e+00   8.1321e-02
-#> 266:    1.0251e+02  -4.0998e+00  -2.3264e+00  -4.0397e+00  -1.0107e+00  -4.3247e-02   4.4552e-03   2.1609e-05   6.8246e-02   2.0757e-02   1.9054e-01   9.1222e-02   9.2659e-01   8.4381e-02   1.0154e+00   8.1290e-02
-#> 267:    1.0251e+02  -4.0999e+00  -2.3261e+00  -4.0396e+00  -1.0107e+00  -4.4145e-02   4.4367e-03   2.1505e-05   6.8834e-02   2.0735e-02   1.9038e-01   9.1594e-02   9.2661e-01   8.4338e-02   1.0153e+00   8.1308e-02
-#> 268:    1.0251e+02  -4.0999e+00  -2.3249e+00  -4.0395e+00  -1.0112e+00  -4.5394e-02   4.4239e-03   2.1411e-05   6.9776e-02   2.0749e-02   1.9017e-01   9.1916e-02   9.2711e-01   8.4286e-02   1.0158e+00   8.1400e-02
-#> 269:    1.0251e+02  -4.0999e+00  -2.3236e+00  -4.0391e+00  -1.0112e+00  -4.6744e-02   4.4119e-03   2.1310e-05   7.0528e-02   2.0709e-02   1.9026e-01   9.2008e-02   9.2638e-01   8.4248e-02   1.0160e+00   8.1389e-02
-#> 270:    1.0251e+02  -4.0999e+00  -2.3231e+00  -4.0388e+00  -1.0116e+00  -4.7514e-02   4.3782e-03   2.1160e-05   7.1513e-02   2.0724e-02   1.9006e-01   9.1551e-02   9.2668e-01   8.4246e-02   1.0149e+00   8.1419e-02
-#> 271:    1.0251e+02  -4.0999e+00  -2.3228e+00  -4.0387e+00  -1.0117e+00  -4.7755e-02   4.3389e-03   2.1121e-05   7.1868e-02   2.0670e-02   1.8969e-01   9.1369e-02   9.2678e-01   8.4228e-02   1.0145e+00   8.1437e-02
-#> 272:    1.0251e+02  -4.0999e+00  -2.3222e+00  -4.0387e+00  -1.0121e+00  -4.8163e-02   4.3080e-03   2.1146e-05   7.2226e-02   2.0710e-02   1.8983e-01   9.0962e-02   9.2639e-01   8.4261e-02   1.0132e+00   8.1523e-02
-#> 273:    1.0251e+02  -4.0999e+00  -2.3216e+00  -4.0389e+00  -1.0122e+00  -4.8336e-02   4.2916e-03   2.1202e-05   7.2734e-02   2.0689e-02   1.8982e-01   9.0422e-02   9.2618e-01   8.4177e-02   1.0134e+00   8.1561e-02
-#> 274:    1.0251e+02  -4.0999e+00  -2.3211e+00  -4.0388e+00  -1.0124e+00  -4.8286e-02   4.2592e-03   2.1201e-05   7.3324e-02   2.0658e-02   1.9015e-01   8.9938e-02   9.2530e-01   8.4133e-02   1.0133e+00   8.1562e-02
-#> 275:    1.0251e+02  -4.0999e+00  -2.3211e+00  -4.0387e+00  -1.0128e+00  -4.8312e-02   4.2368e-03   2.1092e-05   7.3673e-02   2.0639e-02   1.9018e-01   8.9708e-02   9.2404e-01   8.4155e-02   1.0130e+00   8.1535e-02
-#> 276:    1.0251e+02  -4.0999e+00  -2.3212e+00  -4.0386e+00  -1.0126e+00  -4.8249e-02   4.2070e-03   2.0985e-05   7.4089e-02   2.0674e-02   1.8992e-01   8.9341e-02   9.2339e-01   8.4163e-02   1.0121e+00   8.1515e-02
-#> 277:    1.0251e+02  -4.0999e+00  -2.3212e+00  -4.0387e+00  -1.0123e+00  -4.8743e-02   4.1781e-03   2.0914e-05   7.4488e-02   2.0779e-02   1.8959e-01   8.9106e-02   9.2352e-01   8.4100e-02   1.0112e+00   8.1477e-02
-#> 278:    1.0251e+02  -4.0999e+00  -2.3213e+00  -4.0385e+00  -1.0118e+00  -4.9468e-02   4.1782e-03   2.0802e-05   7.4843e-02   2.0859e-02   1.8970e-01   8.8995e-02   9.2374e-01   8.4037e-02   1.0103e+00   8.1458e-02
-#> 279:    1.0251e+02  -4.0999e+00  -2.3213e+00  -4.0384e+00  -1.0115e+00  -4.9612e-02   4.1736e-03   2.0737e-05   7.5385e-02   2.0899e-02   1.8969e-01   8.8806e-02   9.2347e-01   8.3989e-02   1.0095e+00   8.1440e-02
-#> 280:    1.0251e+02  -4.0999e+00  -2.3213e+00  -4.0382e+00  -1.0114e+00  -5.0460e-02   4.1900e-03   2.0708e-05   7.6051e-02   2.0933e-02   1.8968e-01   8.9243e-02   9.2293e-01   8.3972e-02   1.0085e+00   8.1467e-02
-#> 281:    1.0251e+02  -4.0999e+00  -2.3215e+00  -4.0378e+00  -1.0113e+00  -5.0583e-02   4.2096e-03   2.0638e-05   7.6759e-02   2.1003e-02   1.8941e-01   8.9450e-02   9.2294e-01   8.4027e-02   1.0080e+00   8.1467e-02
-#> 282:    1.0251e+02  -4.0999e+00  -2.3218e+00  -4.0380e+00  -1.0114e+00  -5.0276e-02   4.2061e-03   2.0669e-05   7.7323e-02   2.1016e-02   1.8946e-01   8.9456e-02   9.2386e-01   8.3996e-02   1.0095e+00   8.1446e-02
-#> 283:    1.0251e+02  -4.0999e+00  -2.3224e+00  -4.0383e+00  -1.0115e+00  -4.9357e-02   4.2005e-03   2.0601e-05   7.7856e-02   2.1072e-02   1.8968e-01   8.9327e-02   9.2480e-01   8.3964e-02   1.0101e+00   8.1418e-02
-#> 284:    1.0251e+02  -4.0999e+00  -2.3226e+00  -4.0386e+00  -1.0110e+00  -4.8703e-02   4.1977e-03   2.0549e-05   7.8183e-02   2.1122e-02   1.8956e-01   8.9430e-02   9.2470e-01   8.3898e-02   1.0098e+00   8.1428e-02
-#> 285:    1.0251e+02  -4.0999e+00  -2.3232e+00  -4.0389e+00  -1.0110e+00  -4.7526e-02   4.2063e-03   2.0546e-05   7.8449e-02   2.1151e-02   1.8967e-01   8.9133e-02   9.2438e-01   8.3889e-02   1.0089e+00   8.1428e-02
-#> 286:    1.0251e+02  -4.0999e+00  -2.3242e+00  -4.0389e+00  -1.0103e+00  -4.6191e-02   4.2076e-03   2.0486e-05   7.8629e-02   2.1133e-02   1.8970e-01   8.8773e-02   9.2471e-01   8.3861e-02   1.0087e+00   8.1427e-02
-#> 287:    1.0251e+02  -4.0999e+00  -2.3243e+00  -4.0391e+00  -1.0105e+00  -4.5159e-02   4.1980e-03   2.0488e-05   7.8916e-02   2.1071e-02   1.8955e-01   8.8297e-02   9.2415e-01   8.3957e-02   1.0084e+00   8.1464e-02
-#> 288:    1.0251e+02  -4.0999e+00  -2.3237e+00  -4.0392e+00  -1.0109e+00  -4.4970e-02   4.1921e-03   2.0495e-05   7.8764e-02   2.0953e-02   1.8988e-01   8.8160e-02   9.2539e-01   8.3963e-02   1.0103e+00   8.1466e-02
-#> 289:    1.0251e+02  -4.0999e+00  -2.3232e+00  -4.0392e+00  -1.0114e+00  -4.4592e-02   4.1763e-03   2.0584e-05   7.8632e-02   2.0841e-02   1.8982e-01   8.8037e-02   9.2559e-01   8.4031e-02   1.0111e+00   8.1469e-02
-#> 290:    1.0251e+02  -4.0999e+00  -2.3228e+00  -4.0393e+00  -1.0118e+00  -4.4506e-02   4.1574e-03   2.0479e-05   7.8482e-02   2.0726e-02   1.8968e-01   8.7644e-02   9.2519e-01   8.4079e-02   1.0117e+00   8.1474e-02
-#> 291:    1.0251e+02  -4.0999e+00  -2.3223e+00  -4.0392e+00  -1.0120e+00  -4.4578e-02   4.1365e-03   2.0488e-05   7.8220e-02   2.0662e-02   1.8952e-01   8.7558e-02   9.2534e-01   8.4128e-02   1.0119e+00   8.1459e-02
-#> 292:    1.0251e+02  -4.0999e+00  -2.3219e+00  -4.0392e+00  -1.0120e+00  -4.4486e-02   4.1205e-03   2.0514e-05   7.8288e-02   2.0601e-02   1.8947e-01   8.7669e-02   9.2591e-01   8.4106e-02   1.0124e+00   8.1443e-02
-#> 293:    1.0251e+02  -4.0999e+00  -2.3217e+00  -4.0395e+00  -1.0120e+00  -4.3914e-02   4.1076e-03   2.0606e-05   7.8474e-02   2.0557e-02   1.8960e-01   8.7970e-02   9.2580e-01   8.4052e-02   1.0124e+00   8.1443e-02
-#> 294:    1.0251e+02  -4.0998e+00  -2.3218e+00  -4.0399e+00  -1.0123e+00  -4.3173e-02   4.1124e-03   2.0598e-05   7.8561e-02   2.0485e-02   1.8979e-01   8.7954e-02   9.2624e-01   8.4027e-02   1.0132e+00   8.1419e-02
-#> 295:    1.0251e+02  -4.0998e+00  -2.3220e+00  -4.0399e+00  -1.0123e+00  -4.2805e-02   4.1150e-03   2.0599e-05   7.8804e-02   2.0397e-02   1.8985e-01   8.8079e-02   9.2637e-01   8.3980e-02   1.0139e+00   8.1382e-02
-#> 296:    1.0251e+02  -4.0998e+00  -2.3224e+00  -4.0401e+00  -1.0121e+00  -4.2813e-02   4.1342e-03   2.0618e-05   7.9093e-02   2.0359e-02   1.8980e-01   8.8328e-02   9.2555e-01   8.3955e-02   1.0137e+00   8.1344e-02
-#> 297:    1.0251e+02  -4.0998e+00  -2.3225e+00  -4.0403e+00  -1.0118e+00  -4.2861e-02   4.1653e-03   2.0599e-05   7.9236e-02   2.0318e-02   1.8969e-01   8.8659e-02   9.2477e-01   8.3916e-02   1.0135e+00   8.1323e-02
-#> 298:    1.0251e+02  -4.0997e+00  -2.3228e+00  -4.0404e+00  -1.0116e+00  -4.2874e-02   4.2066e-03   2.0567e-05   7.9391e-02   2.0249e-02   1.8973e-01   8.8706e-02   9.2359e-01   8.3939e-02   1.0134e+00   8.1277e-02
-#> 299:    1.0251e+02  -4.0997e+00  -2.3224e+00  -4.0404e+00  -1.0113e+00  -4.3190e-02   4.2168e-03   2.0532e-05   7.9379e-02   2.0187e-02   1.8973e-01   8.8757e-02   9.2294e-01   8.3916e-02   1.0137e+00   8.1243e-02
-#> 300:    1.0251e+02  -4.0997e+00  -2.3221e+00  -4.0405e+00  -1.0111e+00  -4.3480e-02   4.2289e-03   2.0490e-05   7.9314e-02   2.0140e-02   1.8983e-01   8.8620e-02   9.2242e-01   8.3900e-02   1.0137e+00   8.1210e-02
-#> 301:    1.0251e+02  -4.0997e+00  -2.3213e+00  -4.0404e+00  -1.0109e+00  -4.4169e-02   4.2524e-03   2.0546e-05   7.9499e-02   2.0117e-02   1.8991e-01   8.8503e-02   9.2226e-01   8.3843e-02   1.0136e+00   8.1235e-02
-#> 302:    1.0251e+02  -4.0997e+00  -2.3205e+00  -4.0403e+00  -1.0108e+00  -4.5199e-02   4.2709e-03   2.0511e-05   7.9674e-02   2.0085e-02   1.8969e-01   8.8687e-02   9.2207e-01   8.3852e-02   1.0134e+00   8.1262e-02
-#> 303:    1.0251e+02  -4.0997e+00  -2.3199e+00  -4.0401e+00  -1.0106e+00  -4.6193e-02   4.2807e-03   2.0440e-05   7.9845e-02   2.0104e-02   1.8985e-01   8.8661e-02   9.2135e-01   8.3843e-02   1.0128e+00   8.1274e-02
-#> 304:    1.0251e+02  -4.0997e+00  -2.3189e+00  -4.0398e+00  -1.0105e+00  -4.7180e-02   4.3058e-03   2.0450e-05   7.9808e-02   2.0159e-02   1.8987e-01   8.8660e-02   9.2076e-01   8.3856e-02   1.0120e+00   8.1277e-02
-#> 305:    1.0251e+02  -4.0997e+00  -2.3180e+00  -4.0396e+00  -1.0102e+00  -4.8474e-02   4.3050e-03   2.0527e-05   7.9932e-02   2.0184e-02   1.8970e-01   8.8567e-02   9.1986e-01   8.3867e-02   1.0111e+00   8.1290e-02
-#> 306:    1.0251e+02  -4.0997e+00  -2.3175e+00  -4.0393e+00  -1.0101e+00  -4.9308e-02   4.3055e-03   2.0586e-05   8.0113e-02   2.0178e-02   1.8971e-01   8.8307e-02   9.1930e-01   8.3865e-02   1.0112e+00   8.1290e-02
-#> 307:    1.0251e+02  -4.0997e+00  -2.3175e+00  -4.0393e+00  -1.0103e+00  -4.9278e-02   4.3027e-03   2.0441e-05   8.0168e-02   2.0211e-02   1.8973e-01   8.7993e-02   9.1919e-01   8.3837e-02   1.0109e+00   8.1287e-02
-#> 308:    1.0251e+02  -4.0998e+00  -2.3175e+00  -4.0394e+00  -1.0103e+00  -4.9430e-02   4.2899e-03   2.0384e-05   8.0417e-02   2.0187e-02   1.8983e-01   8.7757e-02   9.1937e-01   8.3778e-02   1.0106e+00   8.1289e-02
-#> 309:    1.0251e+02  -4.0998e+00  -2.3175e+00  -4.0393e+00  -1.0103e+00  -4.9319e-02   4.2773e-03   2.0349e-05   8.0807e-02   2.0161e-02   1.8959e-01   8.7493e-02   9.1950e-01   8.3734e-02   1.0108e+00   8.1279e-02
-#> 310:    1.0251e+02  -4.0998e+00  -2.3174e+00  -4.0393e+00  -1.0101e+00  -4.8880e-02   4.2710e-03   2.0327e-05   8.1202e-02   2.0116e-02   1.8983e-01   8.7251e-02   9.1864e-01   8.3730e-02   1.0108e+00   8.1294e-02
-#> 311:    1.0251e+02  -4.0998e+00  -2.3174e+00  -4.0394e+00  -1.0100e+00  -4.8080e-02   4.2611e-03   2.0272e-05   8.1332e-02   2.0078e-02   1.9003e-01   8.6995e-02   9.1844e-01   8.3699e-02   1.0105e+00   8.1319e-02
-#> 312:    1.0251e+02  -4.0998e+00  -2.3173e+00  -4.0394e+00  -1.0100e+00  -4.7724e-02   4.2663e-03   2.0239e-05   8.1553e-02   2.0021e-02   1.8982e-01   8.6721e-02   9.1838e-01   8.3721e-02   1.0100e+00   8.1312e-02
-#> 313:    1.0251e+02  -4.0998e+00  -2.3170e+00  -4.0395e+00  -1.0100e+00  -4.7216e-02   4.2775e-03   2.0213e-05   8.2001e-02   1.9971e-02   1.8980e-01   8.6651e-02   9.1837e-01   8.3697e-02   1.0100e+00   8.1318e-02
-#> 314:    1.0251e+02  -4.0998e+00  -2.3169e+00  -4.0398e+00  -1.0100e+00  -4.6902e-02   4.2949e-03   2.0265e-05   8.2392e-02   1.9922e-02   1.8988e-01   8.6426e-02   9.1845e-01   8.3722e-02   1.0103e+00   8.1309e-02
-#> 315:    1.0251e+02  -4.0998e+00  -2.3168e+00  -4.0399e+00  -1.0102e+00  -4.6480e-02   4.3206e-03   2.0314e-05   8.2534e-02   1.9912e-02   1.8972e-01   8.6211e-02   9.1792e-01   8.3758e-02   1.0103e+00   8.1337e-02
-#> 316:    1.0251e+02  -4.0998e+00  -2.3169e+00  -4.0400e+00  -1.0100e+00  -4.6238e-02   4.3456e-03   2.0323e-05   8.2729e-02   1.9936e-02   1.8975e-01   8.5856e-02   9.1759e-01   8.3814e-02   1.0095e+00   8.1353e-02
-#> 317:    1.0251e+02  -4.0998e+00  -2.3169e+00  -4.0402e+00  -1.0103e+00  -4.5470e-02   4.3521e-03   2.0275e-05   8.2864e-02   1.9965e-02   1.8980e-01   8.5438e-02   9.1755e-01   8.3894e-02   1.0088e+00   8.1373e-02
-#> 318:    1.0251e+02  -4.0998e+00  -2.3169e+00  -4.0402e+00  -1.0106e+00  -4.5001e-02   4.3661e-03   2.0191e-05   8.2949e-02   1.9983e-02   1.9001e-01   8.5203e-02   9.1746e-01   8.3944e-02   1.0078e+00   8.1401e-02
-#> 319:    1.0251e+02  -4.0998e+00  -2.3169e+00  -4.0403e+00  -1.0108e+00  -4.4545e-02   4.3665e-03   2.0114e-05   8.2694e-02   2.0003e-02   1.9041e-01   8.4997e-02   9.1774e-01   8.3940e-02   1.0073e+00   8.1417e-02
-#> 320:    1.0251e+02  -4.0998e+00  -2.3171e+00  -4.0402e+00  -1.0109e+00  -4.4419e-02   4.3600e-03   2.0043e-05   8.2516e-02   1.9999e-02   1.9044e-01   8.4873e-02   9.1798e-01   8.3932e-02   1.0070e+00   8.1420e-02
-#> 321:    1.0251e+02  -4.0998e+00  -2.3170e+00  -4.0401e+00  -1.0107e+00  -4.4267e-02   4.3539e-03   1.9995e-05   8.2307e-02   1.9967e-02   1.9050e-01   8.4982e-02   9.1814e-01   8.3919e-02   1.0067e+00   8.1429e-02
-#> 322:    1.0251e+02  -4.0998e+00  -2.3170e+00  -4.0400e+00  -1.0106e+00  -4.4240e-02   4.3331e-03   1.9984e-05   8.2305e-02   1.9961e-02   1.9054e-01   8.5443e-02   9.1821e-01   8.3910e-02   1.0065e+00   8.1424e-02
-#> 323:    1.0251e+02  -4.0998e+00  -2.3166e+00  -4.0397e+00  -1.0105e+00  -4.4793e-02   4.3199e-03   1.9921e-05   8.2300e-02   1.9935e-02   1.9078e-01   8.6081e-02   9.1836e-01   8.3854e-02   1.0062e+00   8.1448e-02
-#> 324:    1.0251e+02  -4.0998e+00  -2.3167e+00  -4.0395e+00  -1.0104e+00  -4.4862e-02   4.3167e-03   1.9926e-05   8.2063e-02   1.9919e-02   1.9086e-01   8.6736e-02   9.1865e-01   8.3834e-02   1.0060e+00   8.1439e-02
-#> 325:    1.0251e+02  -4.0998e+00  -2.3166e+00  -4.0394e+00  -1.0103e+00  -4.5123e-02   4.3012e-03   1.9902e-05   8.1871e-02   1.9888e-02   1.9103e-01   8.7030e-02   9.1829e-01   8.3865e-02   1.0059e+00   8.1436e-02
-#> 326:    1.0251e+02  -4.0998e+00  -2.3166e+00  -4.0393e+00  -1.0100e+00  -4.5111e-02   4.2839e-03   1.9869e-05   8.2016e-02   1.9843e-02   1.9083e-01   8.7106e-02   9.1802e-01   8.3847e-02   1.0058e+00   8.1427e-02
-#> 327:    1.0251e+02  -4.0998e+00  -2.3165e+00  -4.0393e+00  -1.0101e+00  -4.5297e-02   4.2847e-03   1.9858e-05   8.2297e-02   1.9823e-02   1.9075e-01   8.7398e-02   9.1826e-01   8.3771e-02   1.0054e+00   8.1451e-02
-#> 328:    1.0251e+02  -4.0998e+00  -2.3162e+00  -4.0393e+00  -1.0100e+00  -4.5633e-02   4.2864e-03   1.9877e-05   8.2486e-02   1.9809e-02   1.9060e-01   8.7863e-02   9.1822e-01   8.3706e-02   1.0049e+00   8.1482e-02
-#> 329:    1.0251e+02  -4.0998e+00  -2.3163e+00  -4.0392e+00  -1.0098e+00  -4.5698e-02   4.3097e-03   1.9869e-05   8.2469e-02   1.9795e-02   1.9047e-01   8.8220e-02   9.1805e-01   8.3704e-02   1.0045e+00   8.1502e-02
-#> 330:    1.0251e+02  -4.0998e+00  -2.3168e+00  -4.0390e+00  -1.0099e+00  -4.5752e-02   4.3120e-03   1.9810e-05   8.2684e-02   1.9770e-02   1.9049e-01   8.8495e-02   9.1779e-01   8.3731e-02   1.0046e+00   8.1500e-02
-#> 331:    1.0251e+02  -4.0998e+00  -2.3170e+00  -4.0390e+00  -1.0099e+00  -4.5957e-02   4.3052e-03   1.9736e-05   8.2748e-02   1.9734e-02   1.9034e-01   8.8651e-02   9.1818e-01   8.3707e-02   1.0050e+00   8.1489e-02
-#> 332:    1.0251e+02  -4.0998e+00  -2.3171e+00  -4.0391e+00  -1.0098e+00  -4.5788e-02   4.2994e-03   1.9733e-05   8.2906e-02   1.9711e-02   1.9035e-01   8.8647e-02   9.1835e-01   8.3660e-02   1.0052e+00   8.1490e-02
-#> 333:    1.0251e+02  -4.0998e+00  -2.3173e+00  -4.0392e+00  -1.0099e+00  -4.5316e-02   4.2822e-03   1.9667e-05   8.2967e-02   1.9695e-02   1.9041e-01   8.8729e-02   9.1832e-01   8.3666e-02   1.0056e+00   8.1484e-02
-#> 334:    1.0251e+02  -4.0998e+00  -2.3179e+00  -4.0394e+00  -1.0097e+00  -4.4740e-02   4.2668e-03   1.9593e-05   8.3055e-02   1.9702e-02   1.9058e-01   8.8853e-02   9.1799e-01   8.3687e-02   1.0056e+00   8.1457e-02
-#> 335:    1.0251e+02  -4.0998e+00  -2.3181e+00  -4.0395e+00  -1.0095e+00  -4.4451e-02   4.2558e-03   1.9535e-05   8.3023e-02   1.9762e-02   1.9027e-01   8.9035e-02   9.1828e-01   8.3673e-02   1.0052e+00   8.1469e-02
-#> 336:    1.0251e+02  -4.0998e+00  -2.3178e+00  -4.0395e+00  -1.0098e+00  -4.4500e-02   4.2571e-03   1.9546e-05   8.3051e-02   1.9779e-02   1.9024e-01   8.9486e-02   9.1868e-01   8.3611e-02   1.0053e+00   8.1515e-02
-#> 337:    1.0251e+02  -4.0998e+00  -2.3179e+00  -4.0396e+00  -1.0099e+00  -4.4018e-02   4.2494e-03   1.9584e-05   8.3206e-02   1.9764e-02   1.9011e-01   8.9643e-02   9.1871e-01   8.3659e-02   1.0056e+00   8.1531e-02
-#> 338:    1.0251e+02  -4.0998e+00  -2.3180e+00  -4.0396e+00  -1.0101e+00  -4.3768e-02   4.2332e-03   1.9635e-05   8.3235e-02   1.9751e-02   1.9011e-01   8.9877e-02   9.1939e-01   8.3622e-02   1.0060e+00   8.1528e-02
-#> 339:    1.0251e+02  -4.0998e+00  -2.3186e+00  -4.0397e+00  -1.0098e+00  -4.3605e-02   4.2237e-03   1.9638e-05   8.3611e-02   1.9725e-02   1.9014e-01   8.9946e-02   9.2025e-01   8.3580e-02   1.0064e+00   8.1528e-02
-#> 340:    1.0251e+02  -4.0998e+00  -2.3190e+00  -4.0396e+00  -1.0097e+00  -4.3585e-02   4.2095e-03   1.9630e-05   8.3986e-02   1.9677e-02   1.9019e-01   8.9920e-02   9.2124e-01   8.3559e-02   1.0073e+00   8.1516e-02
-#> 341:    1.0251e+02  -4.0998e+00  -2.3191e+00  -4.0398e+00  -1.0097e+00  -4.3238e-02   4.1994e-03   1.9636e-05   8.4311e-02   1.9683e-02   1.9023e-01   8.9809e-02   9.2179e-01   8.3517e-02   1.0079e+00   8.1498e-02
-#> 342:    1.0251e+02  -4.0998e+00  -2.3194e+00  -4.0400e+00  -1.0097e+00  -4.2748e-02   4.1886e-03   1.9661e-05   8.4345e-02   1.9684e-02   1.9018e-01   8.9600e-02   9.2207e-01   8.3517e-02   1.0081e+00   8.1517e-02
-#> 343:    1.0251e+02  -4.0998e+00  -2.3196e+00  -4.0402e+00  -1.0096e+00  -4.2336e-02   4.1813e-03   1.9615e-05   8.4331e-02   1.9666e-02   1.9016e-01   8.9379e-02   9.2231e-01   8.3534e-02   1.0083e+00   8.1548e-02
-#> 344:    1.0251e+02  -4.0998e+00  -2.3197e+00  -4.0403e+00  -1.0097e+00  -4.2462e-02   4.1751e-03   1.9621e-05   8.4176e-02   1.9673e-02   1.8996e-01   8.9217e-02   9.2236e-01   8.3540e-02   1.0083e+00   8.1557e-02
-#> 345:    1.0251e+02  -4.0998e+00  -2.3200e+00  -4.0403e+00  -1.0098e+00  -4.2327e-02   4.1705e-03   1.9552e-05   8.4159e-02   1.9684e-02   1.9017e-01   8.8957e-02   9.2232e-01   8.3511e-02   1.0085e+00   8.1566e-02
-#> 346:    1.0251e+02  -4.0998e+00  -2.3200e+00  -4.0403e+00  -1.0097e+00  -4.2261e-02   4.1750e-03   1.9564e-05   8.4080e-02   1.9731e-02   1.9047e-01   8.8630e-02   9.2248e-01   8.3516e-02   1.0081e+00   8.1578e-02
-#> 347:    1.0251e+02  -4.0999e+00  -2.3200e+00  -4.0403e+00  -1.0096e+00  -4.2296e-02   4.1883e-03   1.9634e-05   8.4231e-02   1.9747e-02   1.9061e-01   8.8399e-02   9.2250e-01   8.3557e-02   1.0075e+00   8.1580e-02
-#> 348:    1.0251e+02  -4.0999e+00  -2.3199e+00  -4.0404e+00  -1.0096e+00  -4.2345e-02   4.2129e-03   1.9692e-05   8.4295e-02   1.9719e-02   1.9068e-01   8.8210e-02   9.2212e-01   8.3568e-02   1.0075e+00   8.1586e-02
-#> 349:    1.0251e+02  -4.0999e+00  -2.3198e+00  -4.0404e+00  -1.0095e+00  -4.2617e-02   4.2066e-03   1.9720e-05   8.4289e-02   1.9731e-02   1.9054e-01   8.8147e-02   9.2185e-01   8.3565e-02   1.0070e+00   8.1590e-02
-#> 350:    1.0251e+02  -4.0999e+00  -2.3196e+00  -4.0405e+00  -1.0093e+00  -4.2582e-02   4.2011e-03   1.9760e-05   8.4302e-02   1.9703e-02   1.9044e-01   8.8068e-02   9.2182e-01   8.3537e-02   1.0070e+00   8.1590e-02
-#> 351:    1.0251e+02  -4.0998e+00  -2.3198e+00  -4.0405e+00  -1.0093e+00  -4.2377e-02   4.1970e-03   1.9750e-05   8.4587e-02   1.9708e-02   1.9045e-01   8.8008e-02   9.2169e-01   8.3507e-02   1.0067e+00   8.1584e-02
-#> 352:    1.0251e+02  -4.0998e+00  -2.3201e+00  -4.0405e+00  -1.0091e+00  -4.2159e-02   4.1973e-03   1.9819e-05   8.4804e-02   1.9678e-02   1.9040e-01   8.7894e-02   9.2113e-01   8.3528e-02   1.0061e+00   8.1554e-02
-#> 353:    1.0251e+02  -4.0998e+00  -2.3202e+00  -4.0405e+00  -1.0088e+00  -4.2123e-02   4.1968e-03   1.9855e-05   8.4945e-02   1.9634e-02   1.9049e-01   8.7941e-02   9.2108e-01   8.3500e-02   1.0058e+00   8.1548e-02
-#> 354:    1.0251e+02  -4.0998e+00  -2.3204e+00  -4.0404e+00  -1.0087e+00  -4.2217e-02   4.1918e-03   1.9909e-05   8.5122e-02   1.9565e-02   1.9055e-01   8.7948e-02   9.2088e-01   8.3523e-02   1.0059e+00   8.1530e-02
-#> 355:    1.0251e+02  -4.0998e+00  -2.3206e+00  -4.0404e+00  -1.0086e+00  -4.2057e-02   4.1853e-03   1.9973e-05   8.5389e-02   1.9505e-02   1.9057e-01   8.8109e-02   9.2100e-01   8.3496e-02   1.0058e+00   8.1520e-02
-#> 356:    1.0251e+02  -4.0998e+00  -2.3209e+00  -4.0403e+00  -1.0084e+00  -4.1880e-02   4.1796e-03   2.0058e-05   8.5446e-02   1.9451e-02   1.9063e-01   8.7944e-02   9.2086e-01   8.3483e-02   1.0061e+00   8.1488e-02
-#> 357:    1.0251e+02  -4.0998e+00  -2.3210e+00  -4.0404e+00  -1.0084e+00  -4.1565e-02   4.1858e-03   2.0131e-05   8.5481e-02   1.9391e-02   1.9072e-01   8.7879e-02   9.2119e-01   8.3465e-02   1.0066e+00   8.1468e-02
-#> 358:    1.0251e+02  -4.0998e+00  -2.3213e+00  -4.0404e+00  -1.0084e+00  -4.1497e-02   4.1826e-03   2.0168e-05   8.5661e-02   1.9361e-02   1.9086e-01   8.7635e-02   9.2095e-01   8.3475e-02   1.0069e+00   8.1445e-02
-#> 359:    1.0251e+02  -4.0997e+00  -2.3212e+00  -4.0405e+00  -1.0083e+00  -4.1127e-02   4.1993e-03   2.0188e-05   8.5904e-02   1.9347e-02   1.9078e-01   8.7558e-02   9.2087e-01   8.3451e-02   1.0068e+00   8.1461e-02
-#> 360:    1.0251e+02  -4.0997e+00  -2.3215e+00  -4.0405e+00  -1.0082e+00  -4.0919e-02   4.2006e-03   2.0173e-05   8.6133e-02   1.9333e-02   1.9071e-01   8.7479e-02   9.2061e-01   8.3439e-02   1.0067e+00   8.1453e-02
-#> 361:    1.0251e+02  -4.0997e+00  -2.3218e+00  -4.0406e+00  -1.0084e+00  -4.0317e-02   4.2013e-03   2.0253e-05   8.6558e-02   1.9351e-02   1.9075e-01   8.7309e-02   9.2060e-01   8.3425e-02   1.0069e+00   8.1464e-02
-#> 362:    1.0251e+02  -4.0997e+00  -2.3221e+00  -4.0407e+00  -1.0086e+00  -3.9991e-02   4.2004e-03   2.0305e-05   8.6952e-02   1.9369e-02   1.9077e-01   8.7106e-02   9.2037e-01   8.3462e-02   1.0072e+00   8.1464e-02
-#> 363:    1.0251e+02  -4.0997e+00  -2.3224e+00  -4.0407e+00  -1.0086e+00  -3.9745e-02   4.1920e-03   2.0350e-05   8.7210e-02   1.9373e-02   1.9095e-01   8.6967e-02   9.2025e-01   8.3462e-02   1.0070e+00   8.1489e-02
-#> 364:    1.0251e+02  -4.0997e+00  -2.3225e+00  -4.0407e+00  -1.0088e+00  -3.9585e-02   4.1826e-03   2.0355e-05   8.7449e-02   1.9353e-02   1.9099e-01   8.7119e-02   9.2081e-01   8.3468e-02   1.0070e+00   8.1514e-02
-#> 365:    1.0251e+02  -4.0997e+00  -2.3224e+00  -4.0407e+00  -1.0088e+00  -3.9531e-02   4.1781e-03   2.0298e-05   8.7646e-02   1.9346e-02   1.9083e-01   8.6997e-02   9.2106e-01   8.3455e-02   1.0068e+00   8.1546e-02
-#> 366:    1.0251e+02  -4.0997e+00  -2.3223e+00  -4.0407e+00  -1.0088e+00  -3.9436e-02   4.1805e-03   2.0301e-05   8.7772e-02   1.9354e-02   1.9074e-01   8.7057e-02   9.2118e-01   8.3426e-02   1.0064e+00   8.1555e-02
-#> 367:    1.0251e+02  -4.0997e+00  -2.3223e+00  -4.0408e+00  -1.0088e+00  -3.9172e-02   4.1791e-03   2.0368e-05   8.7914e-02   1.9333e-02   1.9063e-01   8.6948e-02   9.2106e-01   8.3409e-02   1.0060e+00   8.1558e-02
-#> 368:    1.0251e+02  -4.0997e+00  -2.3222e+00  -4.0410e+00  -1.0088e+00  -3.8640e-02   4.1857e-03   2.0343e-05   8.7937e-02   1.9334e-02   1.9051e-01   8.6857e-02   9.2143e-01   8.3379e-02   1.0058e+00   8.1564e-02
-#> 369:    1.0251e+02  -4.0997e+00  -2.3223e+00  -4.0411e+00  -1.0088e+00  -3.8331e-02   4.1862e-03   2.0309e-05   8.7933e-02   1.9319e-02   1.9046e-01   8.6689e-02   9.2126e-01   8.3410e-02   1.0053e+00   8.1559e-02
-#> 370:    1.0251e+02  -4.0997e+00  -2.3222e+00  -4.0413e+00  -1.0088e+00  -3.7984e-02   4.1921e-03   2.0301e-05   8.8082e-02   1.9313e-02   1.9050e-01   8.6622e-02   9.2101e-01   8.3424e-02   1.0049e+00   8.1559e-02
-#> 371:    1.0251e+02  -4.0998e+00  -2.3222e+00  -4.0415e+00  -1.0087e+00  -3.7729e-02   4.1972e-03   2.0277e-05   8.8271e-02   1.9308e-02   1.9035e-01   8.6655e-02   9.2092e-01   8.3426e-02   1.0046e+00   8.1575e-02
-#> 372:    1.0251e+02  -4.0998e+00  -2.3222e+00  -4.0414e+00  -1.0087e+00  -3.7571e-02   4.1922e-03   2.0292e-05   8.8651e-02   1.9317e-02   1.9025e-01   8.6528e-02   9.2126e-01   8.3440e-02   1.0046e+00   8.1576e-02
-#> 373:    1.0251e+02  -4.0998e+00  -2.3223e+00  -4.0415e+00  -1.0087e+00  -3.7327e-02   4.1971e-03   2.0343e-05   8.8865e-02   1.9290e-02   1.9002e-01   8.6437e-02   9.2122e-01   8.3475e-02   1.0044e+00   8.1571e-02
-#> 374:    1.0251e+02  -4.0998e+00  -2.3224e+00  -4.0415e+00  -1.0089e+00  -3.7275e-02   4.2072e-03   2.0450e-05   8.9078e-02   1.9306e-02   1.9002e-01   8.6224e-02   9.2111e-01   8.3480e-02   1.0047e+00   8.1569e-02
-#> 375:    1.0251e+02  -4.0998e+00  -2.3226e+00  -4.0415e+00  -1.0089e+00  -3.7080e-02   4.2062e-03   2.0489e-05   8.9178e-02   1.9320e-02   1.9016e-01   8.6141e-02   9.2116e-01   8.3483e-02   1.0047e+00   8.1586e-02
-#> 376:    1.0251e+02  -4.0998e+00  -2.3230e+00  -4.0415e+00  -1.0089e+00  -3.7043e-02   4.2105e-03   2.0517e-05   8.9291e-02   1.9325e-02   1.9018e-01   8.6033e-02   9.2114e-01   8.3474e-02   1.0046e+00   8.1572e-02
-#> 377:    1.0251e+02  -4.0998e+00  -2.3234e+00  -4.0414e+00  -1.0090e+00  -3.7302e-02   4.2097e-03   2.0524e-05   8.9438e-02   1.9333e-02   1.9012e-01   8.6018e-02   9.2123e-01   8.3476e-02   1.0046e+00   8.1545e-02
-#> 378:    1.0251e+02  -4.0998e+00  -2.3234e+00  -4.0413e+00  -1.0089e+00  -3.7617e-02   4.2161e-03   2.0520e-05   8.9567e-02   1.9305e-02   1.9012e-01   8.6106e-02   9.2115e-01   8.3444e-02   1.0049e+00   8.1534e-02
-#> 379:    1.0251e+02  -4.0998e+00  -2.3232e+00  -4.0412e+00  -1.0088e+00  -3.8039e-02   4.2231e-03   2.0484e-05   8.9704e-02   1.9276e-02   1.9015e-01   8.5914e-02   9.2060e-01   8.3438e-02   1.0048e+00   8.1532e-02
-#> 380:    1.0251e+02  -4.0998e+00  -2.3229e+00  -4.0409e+00  -1.0088e+00  -3.8613e-02   4.2221e-03   2.0452e-05   8.9751e-02   1.9293e-02   1.9018e-01   8.5907e-02   9.2032e-01   8.3428e-02   1.0045e+00   8.1545e-02
-#> 381:    1.0251e+02  -4.0998e+00  -2.3228e+00  -4.0408e+00  -1.0088e+00  -3.8992e-02   4.2177e-03   2.0475e-05   8.9641e-02   1.9314e-02   1.9014e-01   8.5978e-02   9.2015e-01   8.3429e-02   1.0040e+00   8.1535e-02
-#> 382:    1.0251e+02  -4.0998e+00  -2.3228e+00  -4.0408e+00  -1.0088e+00  -3.9393e-02   4.2092e-03   2.0508e-05   8.9624e-02   1.9352e-02   1.9010e-01   8.5929e-02   9.2037e-01   8.3422e-02   1.0037e+00   8.1535e-02
-#> 383:    1.0251e+02  -4.0998e+00  -2.3226e+00  -4.0407e+00  -1.0089e+00  -3.9650e-02   4.2080e-03   2.0503e-05   8.9621e-02   1.9349e-02   1.9000e-01   8.5735e-02   9.2021e-01   8.3436e-02   1.0038e+00   8.1544e-02
-#> 384:    1.0251e+02  -4.0998e+00  -2.3223e+00  -4.0407e+00  -1.0089e+00  -3.9709e-02   4.2111e-03   2.0489e-05   8.9690e-02   1.9347e-02   1.8985e-01   8.5516e-02   9.2025e-01   8.3420e-02   1.0037e+00   8.1541e-02
-#> 385:    1.0251e+02  -4.0998e+00  -2.3225e+00  -4.0406e+00  -1.0087e+00  -3.9762e-02   4.2130e-03   2.0458e-05   8.9795e-02   1.9380e-02   1.8978e-01   8.5306e-02   9.2055e-01   8.3405e-02   1.0034e+00   8.1518e-02
-#> 386:    1.0251e+02  -4.0998e+00  -2.3226e+00  -4.0407e+00  -1.0087e+00  -3.9801e-02   4.2117e-03   2.0473e-05   8.9838e-02   1.9386e-02   1.8986e-01   8.5045e-02   9.2034e-01   8.3388e-02   1.0036e+00   8.1512e-02
-#> 387:    1.0251e+02  -4.0998e+00  -2.3228e+00  -4.0408e+00  -1.0088e+00  -3.9548e-02   4.2221e-03   2.0474e-05   8.9914e-02   1.9399e-02   1.9001e-01   8.4840e-02   9.2080e-01   8.3373e-02   1.0037e+00   8.1503e-02
-#> 388:    1.0251e+02  -4.0998e+00  -2.3230e+00  -4.0408e+00  -1.0088e+00  -3.9408e-02   4.2272e-03   2.0464e-05   8.9977e-02   1.9383e-02   1.9000e-01   8.4644e-02   9.2070e-01   8.3377e-02   1.0034e+00   8.1494e-02
-#> 389:    1.0250e+02  -4.0998e+00  -2.3229e+00  -4.0408e+00  -1.0087e+00  -3.9326e-02   4.2285e-03   2.0459e-05   8.9927e-02   1.9366e-02   1.9001e-01   8.4485e-02   9.2063e-01   8.3367e-02   1.0032e+00   8.1487e-02
-#> 390:    1.0250e+02  -4.0998e+00  -2.3231e+00  -4.0409e+00  -1.0086e+00  -3.9130e-02   4.2286e-03   2.0423e-05   8.9894e-02   1.9331e-02   1.8996e-01   8.4434e-02   9.2054e-01   8.3339e-02   1.0032e+00   8.1481e-02
-#> 391:    1.0250e+02  -4.0998e+00  -2.3232e+00  -4.0410e+00  -1.0086e+00  -3.8976e-02   4.2242e-03   2.0419e-05   8.9782e-02   1.9299e-02   1.8992e-01   8.4344e-02   9.2089e-01   8.3320e-02   1.0032e+00   8.1480e-02
-#> 392:    1.0250e+02  -4.0998e+00  -2.3232e+00  -4.0409e+00  -1.0086e+00  -3.8856e-02   4.2179e-03   2.0396e-05   8.9773e-02   1.9263e-02   1.8984e-01   8.4469e-02   9.2084e-01   8.3309e-02   1.0034e+00   8.1489e-02
-#> 393:    1.0250e+02  -4.0998e+00  -2.3234e+00  -4.0409e+00  -1.0089e+00  -3.8820e-02   4.2135e-03   2.0375e-05   8.9746e-02   1.9259e-02   1.8972e-01   8.4731e-02   9.2088e-01   8.3310e-02   1.0031e+00   8.1481e-02
-#> 394:    1.0250e+02  -4.0998e+00  -2.3234e+00  -4.0410e+00  -1.0089e+00  -3.8759e-02   4.2123e-03   2.0382e-05   8.9791e-02   1.9271e-02   1.8958e-01   8.5075e-02   9.2064e-01   8.3316e-02   1.0028e+00   8.1483e-02
-#> 395:    1.0250e+02  -4.0998e+00  -2.3234e+00  -4.0410e+00  -1.0090e+00  -3.8565e-02   4.2179e-03   2.0420e-05   8.9844e-02   1.9279e-02   1.8948e-01   8.5286e-02   9.2070e-01   8.3311e-02   1.0027e+00   8.1499e-02
-#> 396:    1.0250e+02  -4.0998e+00  -2.3233e+00  -4.0411e+00  -1.0092e+00  -3.8505e-02   4.2207e-03   2.0445e-05   8.9863e-02   1.9281e-02   1.8944e-01   8.5452e-02   9.2053e-01   8.3326e-02   1.0028e+00   8.1524e-02
-#> 397:    1.0250e+02  -4.0998e+00  -2.3232e+00  -4.0411e+00  -1.0093e+00  -3.8366e-02   4.2115e-03   2.0410e-05   8.9792e-02   1.9287e-02   1.8938e-01   8.5649e-02   9.2063e-01   8.3351e-02   1.0034e+00   8.1519e-02
-#> 398:    1.0250e+02  -4.0998e+00  -2.3234e+00  -4.0411e+00  -1.0093e+00  -3.8179e-02   4.2049e-03   2.0362e-05   8.9718e-02   1.9281e-02   1.8943e-01   8.5813e-02   9.2065e-01   8.3391e-02   1.0040e+00   8.1513e-02
-#> 399:    1.0250e+02  -4.0998e+00  -2.3236e+00  -4.0411e+00  -1.0093e+00  -3.8020e-02   4.2015e-03   2.0320e-05   8.9743e-02   1.9283e-02   1.8934e-01   8.5899e-02   9.2056e-01   8.3426e-02   1.0045e+00   8.1500e-02
-#> 400:    1.0250e+02  -4.0998e+00  -2.3237e+00  -4.0412e+00  -1.0093e+00  -3.7796e-02   4.2017e-03   2.0296e-05   8.9684e-02   1.9297e-02   1.8932e-01   8.5849e-02   9.2107e-01   8.3413e-02   1.0051e+00   8.1502e-02
-#> 401:    1.0250e+02  -4.0998e+00  -2.3238e+00  -4.0413e+00  -1.0093e+00  -3.7697e-02   4.1959e-03   2.0275e-05   8.9618e-02   1.9291e-02   1.8914e-01   8.5796e-02   9.2086e-01   8.3480e-02   1.0051e+00   8.1510e-02
-#> 402:    1.0250e+02  -4.0998e+00  -2.3238e+00  -4.0414e+00  -1.0093e+00  -3.7639e-02   4.1863e-03   2.0273e-05   8.9522e-02   1.9285e-02   1.8898e-01   8.5723e-02   9.2041e-01   8.3534e-02   1.0053e+00   8.1520e-02
-#> 403:    1.0250e+02  -4.0998e+00  -2.3238e+00  -4.0415e+00  -1.0093e+00  -3.7634e-02   4.1878e-03   2.0250e-05   8.9456e-02   1.9288e-02   1.8895e-01   8.5791e-02   9.1990e-01   8.3549e-02   1.0055e+00   8.1545e-02
-#> 404:    1.0250e+02  -4.0999e+00  -2.3239e+00  -4.0416e+00  -1.0094e+00  -3.7581e-02   4.1854e-03   2.0292e-05   8.9326e-02   1.9326e-02   1.8902e-01   8.5928e-02   9.2016e-01   8.3542e-02   1.0053e+00   8.1565e-02
-#> 405:    1.0250e+02  -4.0999e+00  -2.3239e+00  -4.0415e+00  -1.0094e+00  -3.7740e-02   4.1804e-03   2.0333e-05   8.9304e-02   1.9334e-02   1.8892e-01   8.6225e-02   9.1978e-01   8.3559e-02   1.0052e+00   8.1588e-02
-#> 406:    1.0250e+02  -4.0999e+00  -2.3241e+00  -4.0415e+00  -1.0093e+00  -3.7837e-02   4.1866e-03   2.0375e-05   8.9281e-02   1.9322e-02   1.8906e-01   8.6421e-02   9.1972e-01   8.3556e-02   1.0051e+00   8.1596e-02
-#> 407:    1.0250e+02  -4.0999e+00  -2.3240e+00  -4.0415e+00  -1.0092e+00  -3.8211e-02   4.1948e-03   2.0335e-05   8.9117e-02   1.9303e-02   1.8913e-01   8.6644e-02   9.1975e-01   8.3592e-02   1.0052e+00   8.1594e-02
-#> 408:    1.0250e+02  -4.0999e+00  -2.3239e+00  -4.0415e+00  -1.0091e+00  -3.8144e-02   4.2081e-03   2.0320e-05   8.9057e-02   1.9287e-02   1.8912e-01   8.6825e-02   9.1992e-01   8.3572e-02   1.0054e+00   8.1577e-02
-#> 409:    1.0250e+02  -4.0999e+00  -2.3239e+00  -4.0415e+00  -1.0092e+00  -3.8261e-02   4.2186e-03   2.0295e-05   8.9007e-02   1.9339e-02   1.8923e-01   8.6869e-02   9.1991e-01   8.3568e-02   1.0053e+00   8.1578e-02
-#> 410:    1.0250e+02  -4.0999e+00  -2.3239e+00  -4.0414e+00  -1.0093e+00  -3.8478e-02   4.2150e-03   2.0311e-05   8.9089e-02   1.9427e-02   1.8939e-01   8.7036e-02   9.2050e-01   8.3537e-02   1.0051e+00   8.1581e-02
-#> 411:    1.0250e+02  -4.0999e+00  -2.3238e+00  -4.0413e+00  -1.0092e+00  -3.8732e-02   4.2116e-03   2.0289e-05   8.9015e-02   1.9467e-02   1.8939e-01   8.7005e-02   9.2025e-01   8.3538e-02   1.0049e+00   8.1581e-02
-#> 412:    1.0250e+02  -4.0999e+00  -2.3238e+00  -4.0413e+00  -1.0092e+00  -3.8793e-02   4.2085e-03   2.0295e-05   8.9020e-02   1.9477e-02   1.8946e-01   8.7080e-02   9.2047e-01   8.3532e-02   1.0049e+00   8.1575e-02
-#> 413:    1.0250e+02  -4.0999e+00  -2.3236e+00  -4.0412e+00  -1.0093e+00  -3.8937e-02   4.2069e-03   2.0288e-05   8.9121e-02   1.9495e-02   1.8939e-01   8.7203e-02   9.2043e-01   8.3528e-02   1.0046e+00   8.1581e-02
-#> 414:    1.0250e+02  -4.0999e+00  -2.3233e+00  -4.0412e+00  -1.0093e+00  -3.9068e-02   4.2065e-03   2.0272e-05   8.9126e-02   1.9508e-02   1.8939e-01   8.7485e-02   9.2038e-01   8.3517e-02   1.0046e+00   8.1589e-02
-#> 415:    1.0250e+02  -4.0999e+00  -2.3234e+00  -4.0412e+00  -1.0092e+00  -3.9299e-02   4.2117e-03   2.0277e-05   8.8971e-02   1.9564e-02   1.8955e-01   8.7734e-02   9.2051e-01   8.3502e-02   1.0048e+00   8.1575e-02
-#> 416:    1.0250e+02  -4.0999e+00  -2.3232e+00  -4.0413e+00  -1.0092e+00  -3.9575e-02   4.2122e-03   2.0269e-05   8.8909e-02   1.9609e-02   1.8954e-01   8.7910e-02   9.2061e-01   8.3488e-02   1.0045e+00   8.1561e-02
-#> 417:    1.0250e+02  -4.0999e+00  -2.3228e+00  -4.0412e+00  -1.0092e+00  -3.9794e-02   4.2133e-03   2.0289e-05   8.8845e-02   1.9606e-02   1.8949e-01   8.8036e-02   9.2065e-01   8.3481e-02   1.0047e+00   8.1558e-02
-#> 418:    1.0250e+02  -4.0999e+00  -2.3226e+00  -4.0412e+00  -1.0092e+00  -4.0019e-02   4.2209e-03   2.0279e-05   8.8864e-02   1.9618e-02   1.8939e-01   8.8094e-02   9.2062e-01   8.3490e-02   1.0044e+00   8.1566e-02
-#> 419:    1.0250e+02  -4.0999e+00  -2.3225e+00  -4.0411e+00  -1.0092e+00  -4.0090e-02   4.2242e-03   2.0258e-05   8.9089e-02   1.9644e-02   1.8924e-01   8.8285e-02   9.2082e-01   8.3484e-02   1.0040e+00   8.1567e-02
-#> 420:    1.0250e+02  -4.0999e+00  -2.3223e+00  -4.0410e+00  -1.0091e+00  -4.0260e-02   4.2298e-03   2.0249e-05   8.9215e-02   1.9640e-02   1.8919e-01   8.8683e-02   9.2127e-01   8.3454e-02   1.0041e+00   8.1564e-02
-#> 421:    1.0250e+02  -4.0998e+00  -2.3222e+00  -4.0410e+00  -1.0090e+00  -4.0359e-02   4.2292e-03   2.0289e-05   8.9366e-02   1.9642e-02   1.8928e-01   8.8905e-02   9.2154e-01   8.3452e-02   1.0038e+00   8.1572e-02
-#> 422:    1.0250e+02  -4.0998e+00  -2.3223e+00  -4.0410e+00  -1.0088e+00  -4.0380e-02   4.2311e-03   2.0289e-05   8.9318e-02   1.9636e-02   1.8934e-01   8.9025e-02   9.2137e-01   8.3486e-02   1.0039e+00   8.1562e-02
-#> 423:    1.0250e+02  -4.0998e+00  -2.3224e+00  -4.0411e+00  -1.0088e+00  -4.0256e-02   4.2283e-03   2.0277e-05   8.9324e-02   1.9645e-02   1.8923e-01   8.9305e-02   9.2129e-01   8.3484e-02   1.0038e+00   8.1565e-02
-#> 424:    1.0250e+02  -4.0998e+00  -2.3226e+00  -4.0412e+00  -1.0088e+00  -4.0075e-02   4.2333e-03   2.0245e-05   8.9193e-02   1.9657e-02   1.8914e-01   8.9480e-02   9.2122e-01   8.3487e-02   1.0039e+00   8.1587e-02
-#> 425:    1.0250e+02  -4.0998e+00  -2.3226e+00  -4.0413e+00  -1.0088e+00  -3.9950e-02   4.2360e-03   2.0257e-05   8.9170e-02   1.9644e-02   1.8924e-01   8.9622e-02   9.2104e-01   8.3492e-02   1.0042e+00   8.1599e-02
-#> 426:    1.0250e+02  -4.0998e+00  -2.3226e+00  -4.0413e+00  -1.0088e+00  -3.9789e-02   4.2376e-03   2.0245e-05   8.9143e-02   1.9654e-02   1.8917e-01   8.9791e-02   9.2100e-01   8.3514e-02   1.0039e+00   8.1607e-02
-#> 427:    1.0250e+02  -4.0998e+00  -2.3224e+00  -4.0414e+00  -1.0087e+00  -3.9766e-02   4.2469e-03   2.0228e-05   8.9102e-02   1.9656e-02   1.8913e-01   9.0076e-02   9.2110e-01   8.3499e-02   1.0037e+00   8.1607e-02
-#> 428:    1.0250e+02  -4.0998e+00  -2.3225e+00  -4.0414e+00  -1.0088e+00  -3.9662e-02   4.2522e-03   2.0205e-05   8.9151e-02   1.9669e-02   1.8912e-01   9.0312e-02   9.2102e-01   8.3483e-02   1.0036e+00   8.1599e-02
-#> 429:    1.0250e+02  -4.0998e+00  -2.3225e+00  -4.0414e+00  -1.0089e+00  -3.9547e-02   4.2615e-03   2.0187e-05   8.9103e-02   1.9681e-02   1.8907e-01   9.0576e-02   9.2082e-01   8.3488e-02   1.0035e+00   8.1592e-02
-#> 430:    1.0250e+02  -4.0998e+00  -2.3224e+00  -4.0414e+00  -1.0088e+00  -3.9593e-02   4.2613e-03   2.0159e-05   8.9075e-02   1.9692e-02   1.8894e-01   9.0762e-02   9.2073e-01   8.3487e-02   1.0035e+00   8.1603e-02
-#> 431:    1.0250e+02  -4.0998e+00  -2.3223e+00  -4.0413e+00  -1.0088e+00  -3.9929e-02   4.2668e-03   2.0112e-05   8.8982e-02   1.9682e-02   1.8901e-01   9.0997e-02   9.2043e-01   8.3487e-02   1.0036e+00   8.1604e-02
-#> 432:    1.0250e+02  -4.0998e+00  -2.3223e+00  -4.0413e+00  -1.0088e+00  -4.0182e-02   4.2693e-03   2.0089e-05   8.8860e-02   1.9659e-02   1.8898e-01   9.1110e-02   9.2024e-01   8.3490e-02   1.0036e+00   8.1585e-02
-#> 433:    1.0250e+02  -4.0998e+00  -2.3222e+00  -4.0412e+00  -1.0088e+00  -4.0415e-02   4.2706e-03   2.0081e-05   8.8670e-02   1.9650e-02   1.8899e-01   9.1199e-02   9.1999e-01   8.3485e-02   1.0036e+00   8.1587e-02
-#> 434:    1.0250e+02  -4.0998e+00  -2.3220e+00  -4.0412e+00  -1.0087e+00  -4.0405e-02   4.2661e-03   2.0060e-05   8.8576e-02   1.9667e-02   1.8897e-01   9.1180e-02   9.1998e-01   8.3468e-02   1.0034e+00   8.1594e-02
-#> 435:    1.0250e+02  -4.0998e+00  -2.3218e+00  -4.0413e+00  -1.0087e+00  -4.0471e-02   4.2639e-03   2.0050e-05   8.8450e-02   1.9671e-02   1.8891e-01   9.1156e-02   9.1970e-01   8.3469e-02   1.0033e+00   8.1602e-02
-#> 436:    1.0250e+02  -4.0998e+00  -2.3216e+00  -4.0413e+00  -1.0086e+00  -4.0478e-02   4.2614e-03   2.0025e-05   8.8470e-02   1.9677e-02   1.8892e-01   9.1234e-02   9.1948e-01   8.3484e-02   1.0033e+00   8.1608e-02
-#> 437:    1.0250e+02  -4.0998e+00  -2.3214e+00  -4.0413e+00  -1.0086e+00  -4.0648e-02   4.2569e-03   2.0021e-05   8.8378e-02   1.9694e-02   1.8896e-01   9.1289e-02   9.1946e-01   8.3486e-02   1.0034e+00   8.1608e-02
-#> 438:    1.0250e+02  -4.0998e+00  -2.3214e+00  -4.0413e+00  -1.0085e+00  -4.0807e-02   4.2559e-03   2.0029e-05   8.8244e-02   1.9704e-02   1.8898e-01   9.1352e-02   9.1920e-01   8.3494e-02   1.0034e+00   8.1604e-02
-#> 439:    1.0250e+02  -4.0998e+00  -2.3215e+00  -4.0413e+00  -1.0084e+00  -4.0814e-02   4.2472e-03   2.0035e-05   8.8064e-02   1.9736e-02   1.8905e-01   9.1469e-02   9.1900e-01   8.3510e-02   1.0032e+00   8.1602e-02
-#> 440:    1.0250e+02  -4.0998e+00  -2.3216e+00  -4.0414e+00  -1.0084e+00  -4.0845e-02   4.2385e-03   2.0044e-05   8.7953e-02   1.9775e-02   1.8906e-01   9.1482e-02   9.1902e-01   8.3529e-02   1.0029e+00   8.1605e-02
-#> 441:    1.0250e+02  -4.0998e+00  -2.3218e+00  -4.0415e+00  -1.0084e+00  -4.0561e-02   4.2293e-03   2.0096e-05   8.7978e-02   1.9848e-02   1.8914e-01   9.1431e-02   9.1890e-01   8.3545e-02   1.0026e+00   8.1618e-02
-#> 442:    1.0250e+02  -4.0998e+00  -2.3219e+00  -4.0415e+00  -1.0085e+00  -4.0297e-02   4.2190e-03   2.0140e-05   8.8016e-02   1.9884e-02   1.8912e-01   9.1373e-02   9.1910e-01   8.3556e-02   1.0025e+00   8.1632e-02
-#> 443:    1.0250e+02  -4.0998e+00  -2.3222e+00  -4.0415e+00  -1.0086e+00  -4.0124e-02   4.2172e-03   2.0182e-05   8.8183e-02   1.9921e-02   1.8920e-01   9.1354e-02   9.1928e-01   8.3555e-02   1.0023e+00   8.1646e-02
-#> 444:    1.0250e+02  -4.0999e+00  -2.3223e+00  -4.0416e+00  -1.0084e+00  -4.0120e-02   4.2226e-03   2.0208e-05   8.8142e-02   1.9980e-02   1.8916e-01   9.1269e-02   9.1934e-01   8.3540e-02   1.0020e+00   8.1653e-02
-#> 445:    1.0250e+02  -4.0999e+00  -2.3223e+00  -4.0416e+00  -1.0083e+00  -4.0180e-02   4.2279e-03   2.0283e-05   8.8188e-02   2.0009e-02   1.8925e-01   9.1096e-02   9.1924e-01   8.3538e-02   1.0017e+00   8.1644e-02
-#> 446:    1.0250e+02  -4.0999e+00  -2.3223e+00  -4.0417e+00  -1.0084e+00  -4.0083e-02   4.2373e-03   2.0357e-05   8.8255e-02   2.0030e-02   1.8937e-01   9.0921e-02   9.1921e-01   8.3535e-02   1.0015e+00   8.1652e-02
-#> 447:    1.0250e+02  -4.0999e+00  -2.3223e+00  -4.0417e+00  -1.0083e+00  -4.0032e-02   4.2591e-03   2.0418e-05   8.8322e-02   2.0055e-02   1.8931e-01   9.0741e-02   9.1928e-01   8.3527e-02   1.0011e+00   8.1662e-02
-#> 448:    1.0250e+02  -4.0999e+00  -2.3224e+00  -4.0417e+00  -1.0083e+00  -4.0042e-02   4.2759e-03   2.0499e-05   8.8372e-02   2.0083e-02   1.8935e-01   9.0554e-02   9.1942e-01   8.3524e-02   1.0010e+00   8.1661e-02
-#> 449:    1.0250e+02  -4.0999e+00  -2.3224e+00  -4.0417e+00  -1.0083e+00  -4.0219e-02   4.2779e-03   2.0525e-05   8.8377e-02   2.0104e-02   1.8937e-01   9.0424e-02   9.1970e-01   8.3510e-02   1.0009e+00   8.1654e-02
-#> 450:    1.0250e+02  -4.0999e+00  -2.3223e+00  -4.0416e+00  -1.0084e+00  -4.0390e-02   4.2779e-03   2.0520e-05   8.8387e-02   2.0120e-02   1.8939e-01   9.0277e-02   9.1991e-01   8.3489e-02   1.0010e+00   8.1662e-02
-#> 451:    1.0250e+02  -4.0999e+00  -2.3221e+00  -4.0415e+00  -1.0085e+00  -4.0403e-02   4.2785e-03   2.0554e-05   8.8442e-02   2.0130e-02   1.8934e-01   9.0032e-02   9.2001e-01   8.3485e-02   1.0011e+00   8.1676e-02
-#> 452:    1.0250e+02  -4.0999e+00  -2.3220e+00  -4.0415e+00  -1.0084e+00  -4.0503e-02   4.2730e-03   2.0537e-05   8.8507e-02   2.0135e-02   1.8926e-01   8.9777e-02   9.2031e-01   8.3473e-02   1.0013e+00   8.1671e-02
-#> 453:    1.0250e+02  -4.0999e+00  -2.3221e+00  -4.0415e+00  -1.0084e+00  -4.0716e-02   4.2650e-03   2.0525e-05   8.8565e-02   2.0168e-02   1.8921e-01   8.9653e-02   9.2030e-01   8.3473e-02   1.0010e+00   8.1665e-02
-#> 454:    1.0250e+02  -4.0999e+00  -2.3221e+00  -4.0415e+00  -1.0083e+00  -4.0900e-02   4.2583e-03   2.0505e-05   8.8572e-02   2.0194e-02   1.8912e-01   8.9524e-02   9.2039e-01   8.3457e-02   1.0009e+00   8.1658e-02
-#> 455:    1.0250e+02  -4.0999e+00  -2.3220e+00  -4.0415e+00  -1.0083e+00  -4.0930e-02   4.2524e-03   2.0495e-05   8.8643e-02   2.0246e-02   1.8914e-01   8.9416e-02   9.2035e-01   8.3454e-02   1.0006e+00   8.1655e-02
-#> 456:    1.0250e+02  -4.0999e+00  -2.3218e+00  -4.0414e+00  -1.0084e+00  -4.1008e-02   4.2455e-03   2.0482e-05   8.8831e-02   2.0290e-02   1.8904e-01   8.9438e-02   9.2042e-01   8.3448e-02   1.0005e+00   8.1672e-02
-#> 457:    1.0250e+02  -4.0999e+00  -2.3216e+00  -4.0414e+00  -1.0085e+00  -4.1073e-02   4.2376e-03   2.0479e-05   8.8831e-02   2.0310e-02   1.8893e-01   8.9411e-02   9.2049e-01   8.3438e-02   1.0005e+00   8.1677e-02
-#> 458:    1.0250e+02  -4.0999e+00  -2.3215e+00  -4.0414e+00  -1.0085e+00  -4.1036e-02   4.2288e-03   2.0479e-05   8.8894e-02   2.0311e-02   1.8879e-01   8.9378e-02   9.2055e-01   8.3419e-02   1.0006e+00   8.1689e-02
-#> 459:    1.0250e+02  -4.0999e+00  -2.3216e+00  -4.0414e+00  -1.0085e+00  -4.1084e-02   4.2296e-03   2.0472e-05   8.8976e-02   2.0290e-02   1.8876e-01   8.9365e-02   9.2056e-01   8.3404e-02   1.0007e+00   8.1678e-02
-#> 460:    1.0250e+02  -4.0999e+00  -2.3215e+00  -4.0414e+00  -1.0084e+00  -4.1065e-02   4.2257e-03   2.0473e-05   8.8978e-02   2.0254e-02   1.8871e-01   8.9287e-02   9.2061e-01   8.3386e-02   1.0007e+00   8.1663e-02
-#> 461:    1.0250e+02  -4.0999e+00  -2.3213e+00  -4.0414e+00  -1.0084e+00  -4.1142e-02   4.2254e-03   2.0441e-05   8.8952e-02   2.0238e-02   1.8864e-01   8.9236e-02   9.2067e-01   8.3359e-02   1.0007e+00   8.1670e-02
-#> 462:    1.0250e+02  -4.0999e+00  -2.3213e+00  -4.0413e+00  -1.0083e+00  -4.1199e-02   4.2230e-03   2.0409e-05   8.9161e-02   2.0235e-02   1.8852e-01   8.9179e-02   9.2070e-01   8.3339e-02   1.0005e+00   8.1686e-02
-#> 463:    1.0250e+02  -4.0999e+00  -2.3214e+00  -4.0413e+00  -1.0084e+00  -4.1131e-02   4.2191e-03   2.0397e-05   8.9356e-02   2.0251e-02   1.8850e-01   8.9138e-02   9.2098e-01   8.3308e-02   1.0003e+00   8.1688e-02
-#> 464:    1.0250e+02  -4.0999e+00  -2.3213e+00  -4.0414e+00  -1.0084e+00  -4.0937e-02   4.2187e-03   2.0395e-05   8.9553e-02   2.0237e-02   1.8848e-01   8.9097e-02   9.2108e-01   8.3293e-02   1.0001e+00   8.1684e-02
-#> 465:    1.0250e+02  -4.0999e+00  -2.3213e+00  -4.0414e+00  -1.0086e+00  -4.0873e-02   4.2226e-03   2.0374e-05   8.9675e-02   2.0210e-02   1.8854e-01   8.9045e-02   9.2115e-01   8.3282e-02   1.0002e+00   8.1678e-02
-#> 466:    1.0250e+02  -4.0999e+00  -2.3213e+00  -4.0414e+00  -1.0085e+00  -4.1046e-02   4.2312e-03   2.0379e-05   8.9703e-02   2.0232e-02   1.8852e-01   8.9031e-02   9.2100e-01   8.3294e-02   9.9982e-01   8.1665e-02
-#> 467:    1.0250e+02  -4.0999e+00  -2.3214e+00  -4.0414e+00  -1.0086e+00  -4.1081e-02   4.2382e-03   2.0421e-05   8.9802e-02   2.0266e-02   1.8851e-01   8.9175e-02   9.2124e-01   8.3271e-02   9.9943e-01   8.1671e-02
-#> 468:    1.0250e+02  -4.0999e+00  -2.3215e+00  -4.0414e+00  -1.0085e+00  -4.1107e-02   4.2412e-03   2.0446e-05   8.9937e-02   2.0281e-02   1.8857e-01   8.9238e-02   9.2125e-01   8.3255e-02   9.9912e-01   8.1659e-02
-#> 469:    1.0250e+02  -4.0999e+00  -2.3214e+00  -4.0414e+00  -1.0084e+00  -4.1269e-02   4.2380e-03   2.0449e-05   8.9938e-02   2.0285e-02   1.8867e-01   8.9378e-02   9.2144e-01   8.3225e-02   9.9906e-01   8.1651e-02
-#> 470:    1.0250e+02  -4.0999e+00  -2.3212e+00  -4.0413e+00  -1.0083e+00  -4.1552e-02   4.2384e-03   2.0437e-05   8.9924e-02   2.0280e-02   1.8878e-01   8.9520e-02   9.2149e-01   8.3205e-02   9.9880e-01   8.1648e-02
-#> 471:    1.0250e+02  -4.0999e+00  -2.3210e+00  -4.0412e+00  -1.0082e+00  -4.2096e-02   4.2375e-03   2.0433e-05   8.9875e-02   2.0267e-02   1.8880e-01   8.9608e-02   9.2149e-01   8.3221e-02   9.9869e-01   8.1642e-02
-#> 472:    1.0250e+02  -4.0999e+00  -2.3210e+00  -4.0411e+00  -1.0081e+00  -4.2380e-02   4.2446e-03   2.0435e-05   8.9823e-02   2.0262e-02   1.8885e-01   8.9602e-02   9.2156e-01   8.3233e-02   9.9868e-01   8.1643e-02
-#> 473:    1.0250e+02  -4.0999e+00  -2.3210e+00  -4.0410e+00  -1.0080e+00  -4.2522e-02   4.2486e-03   2.0429e-05   8.9793e-02   2.0231e-02   1.8877e-01   8.9608e-02   9.2177e-01   8.3210e-02   9.9901e-01   8.1637e-02
-#> 474:    1.0250e+02  -4.0999e+00  -2.3209e+00  -4.0410e+00  -1.0079e+00  -4.2640e-02   4.2536e-03   2.0403e-05   8.9731e-02   2.0213e-02   1.8876e-01   8.9632e-02   9.2177e-01   8.3192e-02   9.9942e-01   8.1632e-02
-#> 475:    1.0250e+02  -4.0999e+00  -2.3208e+00  -4.0409e+00  -1.0079e+00  -4.2882e-02   4.2576e-03   2.0375e-05   8.9666e-02   2.0190e-02   1.8866e-01   8.9718e-02   9.2160e-01   8.3218e-02   9.9931e-01   8.1622e-02
-#> 476:    1.0250e+02  -4.0999e+00  -2.3207e+00  -4.0409e+00  -1.0080e+00  -4.2983e-02   4.2599e-03   2.0368e-05   8.9563e-02   2.0171e-02   1.8859e-01   8.9777e-02   9.2162e-01   8.3236e-02   9.9932e-01   8.1620e-02
-#> 477:    1.0250e+02  -4.0999e+00  -2.3205e+00  -4.0410e+00  -1.0081e+00  -4.3022e-02   4.2570e-03   2.0364e-05   8.9440e-02   2.0166e-02   1.8860e-01   8.9785e-02   9.2171e-01   8.3236e-02   9.9940e-01   8.1633e-02
-#> 478:    1.0250e+02  -4.0999e+00  -2.3203e+00  -4.0410e+00  -1.0080e+00  -4.3129e-02   4.2505e-03   2.0371e-05   8.9374e-02   2.0151e-02   1.8859e-01   8.9826e-02   9.2171e-01   8.3224e-02   9.9970e-01   8.1620e-02
-#> 479:    1.0250e+02  -4.1000e+00  -2.3201e+00  -4.0410e+00  -1.0080e+00  -4.3186e-02   4.2440e-03   2.0373e-05   8.9355e-02   2.0133e-02   1.8858e-01   8.9837e-02   9.2168e-01   8.3214e-02   9.9991e-01   8.1621e-02
-#> 480:    1.0250e+02  -4.1000e+00  -2.3198e+00  -4.0410e+00  -1.0080e+00  -4.3477e-02   4.2424e-03   2.0440e-05   8.9311e-02   2.0121e-02   1.8857e-01   8.9848e-02   9.2158e-01   8.3221e-02   9.9995e-01   8.1627e-02
-#> 481:    1.0250e+02  -4.1000e+00  -2.3194e+00  -4.0410e+00  -1.0079e+00  -4.3647e-02   4.2358e-03   2.0479e-05   8.9315e-02   2.0096e-02   1.8851e-01   8.9865e-02   9.2159e-01   8.3197e-02   1.0002e+00   8.1642e-02
-#> 482:    1.0250e+02  -4.1000e+00  -2.3188e+00  -4.0409e+00  -1.0079e+00  -4.3909e-02   4.2370e-03   2.0551e-05   8.9382e-02   2.0085e-02   1.8840e-01   8.9799e-02   9.2147e-01   8.3229e-02   1.0001e+00   8.1656e-02
-#> 483:    1.0250e+02  -4.1000e+00  -2.3189e+00  -4.0409e+00  -1.0078e+00  -4.4169e-02   4.2467e-03   2.0587e-05   8.9377e-02   2.0054e-02   1.8838e-01   8.9943e-02   9.2130e-01   8.3237e-02   1.0003e+00   8.1650e-02
-#> 484:    1.0250e+02  -4.1000e+00  -2.3188e+00  -4.0408e+00  -1.0078e+00  -4.4346e-02   4.2627e-03   2.0605e-05   8.9450e-02   2.0020e-02   1.8840e-01   9.0090e-02   9.2114e-01   8.3237e-02   1.0004e+00   8.1639e-02
-#> 485:    1.0250e+02  -4.1000e+00  -2.3185e+00  -4.0408e+00  -1.0079e+00  -4.4414e-02   4.2737e-03   2.0594e-05   8.9541e-02   1.9999e-02   1.8842e-01   9.0237e-02   9.2116e-01   8.3227e-02   1.0004e+00   8.1641e-02
-#> 486:    1.0250e+02  -4.1000e+00  -2.3183e+00  -4.0408e+00  -1.0080e+00  -4.4572e-02   4.2902e-03   2.0581e-05   8.9733e-02   1.9978e-02   1.8837e-01   9.0412e-02   9.2098e-01   8.3224e-02   1.0003e+00   8.1642e-02
-#> 487:    1.0250e+02  -4.1000e+00  -2.3182e+00  -4.0407e+00  -1.0081e+00  -4.4698e-02   4.2979e-03   2.0560e-05   8.9822e-02   1.9954e-02   1.8827e-01   9.0744e-02   9.2114e-01   8.3212e-02   1.0003e+00   8.1644e-02
-#> 488:    1.0250e+02  -4.1000e+00  -2.3180e+00  -4.0406e+00  -1.0081e+00  -4.4892e-02   4.3035e-03   2.0549e-05   8.9849e-02   1.9928e-02   1.8816e-01   9.1000e-02   9.2118e-01   8.3206e-02   1.0003e+00   8.1644e-02
-#> 489:    1.0250e+02  -4.1000e+00  -2.3180e+00  -4.0406e+00  -1.0081e+00  -4.5037e-02   4.2987e-03   2.0515e-05   8.9843e-02   1.9906e-02   1.8815e-01   9.1260e-02   9.2116e-01   8.3190e-02   1.0001e+00   8.1633e-02
-#> 490:    1.0250e+02  -4.1000e+00  -2.3179e+00  -4.0405e+00  -1.0081e+00  -4.5139e-02   4.2930e-03   2.0508e-05   8.9827e-02   1.9887e-02   1.8814e-01   9.1545e-02   9.2114e-01   8.3178e-02   9.9991e-01   8.1624e-02
-#> 491:    1.0250e+02  -4.1000e+00  -2.3179e+00  -4.0405e+00  -1.0081e+00  -4.5107e-02   4.2871e-03   2.0490e-05   8.9765e-02   1.9855e-02   1.8814e-01   9.1702e-02   9.2089e-01   8.3179e-02   9.9986e-01   8.1624e-02
-#> 492:    1.0250e+02  -4.1000e+00  -2.3178e+00  -4.0405e+00  -1.0080e+00  -4.5192e-02   4.2818e-03   2.0470e-05   8.9791e-02   1.9831e-02   1.8810e-01   9.1846e-02   9.2086e-01   8.3164e-02   9.9977e-01   8.1630e-02
-#> 493:    1.0250e+02  -4.1000e+00  -2.3179e+00  -4.0406e+00  -1.0078e+00  -4.4968e-02   4.2782e-03   2.0452e-05   8.9797e-02   1.9804e-02   1.8806e-01   9.1987e-02   9.2080e-01   8.3146e-02   9.9982e-01   8.1627e-02
-#> 494:    1.0250e+02  -4.1000e+00  -2.3180e+00  -4.0406e+00  -1.0078e+00  -4.4773e-02   4.2766e-03   2.0453e-05   8.9696e-02   1.9781e-02   1.8805e-01   9.2096e-02   9.2057e-01   8.3148e-02   9.9999e-01   8.1611e-02
-#> 495:    1.0250e+02  -4.1000e+00  -2.3181e+00  -4.0408e+00  -1.0078e+00  -4.4647e-02   4.2798e-03   2.0446e-05   8.9661e-02   1.9763e-02   1.8804e-01   9.2155e-02   9.2039e-01   8.3137e-02   9.9999e-01   8.1599e-02
-#> 496:    1.0250e+02  -4.1000e+00  -2.3182e+00  -4.0408e+00  -1.0079e+00  -4.4482e-02   4.2851e-03   2.0434e-05   8.9630e-02   1.9750e-02   1.8796e-01   9.2258e-02   9.2042e-01   8.3124e-02   1.0000e+00   8.1601e-02
-#> 497:    1.0250e+02  -4.1000e+00  -2.3184e+00  -4.0409e+00  -1.0079e+00  -4.4175e-02   4.2866e-03   2.0423e-05   8.9656e-02   1.9743e-02   1.8789e-01   9.2225e-02   9.2017e-01   8.3126e-02   1.0002e+00   8.1616e-02
-#> 498:    1.0250e+02  -4.1000e+00  -2.3187e+00  -4.0409e+00  -1.0079e+00  -4.3826e-02   4.2847e-03   2.0406e-05   8.9587e-02   1.9730e-02   1.8781e-01   9.2143e-02   9.2017e-01   8.3156e-02   1.0002e+00   8.1613e-02
-#> 499:    1.0250e+02  -4.1000e+00  -2.3190e+00  -4.0409e+00  -1.0078e+00  -4.3529e-02   4.2806e-03   2.0397e-05   8.9653e-02   1.9712e-02   1.8779e-01   9.2107e-02   9.2028e-01   8.3172e-02   1.0004e+00   8.1607e-02
-#> 500:    1.0250e+02  -4.1000e+00  -2.3193e+00  -4.0409e+00  -1.0077e+00  -4.3241e-02   4.2787e-03   2.0390e-05   8.9759e-02   1.9689e-02   1.8773e-01   9.2021e-02   9.2029e-01   8.3203e-02   1.0006e+00   8.1613e-02
-#> Calculating covariance matrix
-#> 
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> Needed Covariates:
-#> [1] "CMT"
-#> Calculating residuals/tables
-#> done
-# The following takes a very long time but gives
-f_nlmixr_dfop_sfo_focei <- nlmixr(f_mmkin_dfop_sfo, est = "focei")
-#> ℹ parameter labels from comments are typically ignored in non-interactive mode
-#> ℹ Need to run with the source intact to parse comments
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → creating full model...
-#> → pruning branches (`if`/`else`)...
-#> ✔ done
-#> → loading into symengine environment...
-#> ✔ done
-#> → calculate jacobian
-#> 
-#> → calculate sensitivities
-#> 
-#> → calculate ∂(f)/∂(η)
-#> 
-#> → calculate ∂(R²)/∂(η)
-#> 
-#> → finding duplicate expressions in inner model...
-#> 
-#> → optimizing duplicate expressions in inner model...
-#> 
-#> → finding duplicate expressions in EBE model...
-#> 
-#> → optimizing duplicate expressions in EBE model...
-#> 
-#> → compiling inner model...
-#>  
-#> ✔ done
-#> → finding duplicate expressions in FD model...
-#> 
-#> → optimizing duplicate expressions in FD model...
-#> 
-#> → compiling EBE model...
-#>  
-#> ✔ done
-#> → compiling events FD model...
-#>  
-#> ✔ done
-#> Needed Covariates:
-#> [1] "CMT"
-#> Key: U: Unscaled Parameters; X: Back-transformed parameters; G: Gill difference gradient approximation
-#> F: Forward difference gradient approximation
-#> C: Central difference gradient approximation
-#> M: Mixed forward and central difference gradient approximation
-#> Unscaled parameters for Omegas=chol(solve(omega));
-#> Diagonals are transformed, as specified by foceiControl(diagXform=)
-#> |-----+---------------+-----------+-----------+-----------+-----------|
-#> |    #| Objective Fun |  parent_0 |  log_k_m1 |f_parent_qlogis |    log_k1 |
-#> |.....................|    log_k2 |  g_qlogis | sigma_low |  rsd_high |
-#> |.....................|        o1 |        o2 |        o3 |        o4 |
-#> |.....................|        o5 |        o6 |...........|...........|
-#> |    1|     496.69520 |     1.000 |    -1.000 |   -0.9393 |   -0.9673 |
-#> |.....................|    -1.000 |   -0.9214 |   -0.9072 |   -0.9199 |
-#> |.....................|   -0.9082 |   -0.8909 |   -0.8969 |   -0.8991 |
-#> |.....................|   -0.8928 |   -0.8991 |...........|...........|
-#> |    U|      496.6952 |     100.0 |    -4.100 |   -0.9400 |    -2.400 |
-#> |.....................|    -4.100 |  -0.01100 |    0.7300 |   0.06700 |
-#> |.....................|    0.6756 |     1.581 |     1.265 |     1.151 |
-#> |.....................|     1.477 |     1.151 |...........|...........|
-#> |    X|      496.6952 |     100.0 |   0.01657 |    0.2809 |   0.09072 |
-#> |.....................|   0.01657 |    0.4973 |    0.7300 |   0.06700 |
-#> |.....................|    0.6756 |     1.581 |     1.265 |     1.151 |
-#> |.....................|     1.477 |     1.151 |...........|...........|
-#> |    G|    Gill Diff. |    -72.99 |    -3.907 |   -0.8109 |   0.02803 |
-#> |.....................|    -1.841 |  0.006841 |    -22.18 |    -32.78 |
-#> |.....................|     3.538 |    -16.93 |    -12.84 |    -12.77 |
-#> |.....................|    -15.02 |    -9.608 |...........|...........|
-#> |    2|     1346.5436 |     1.823 |   -0.9559 |   -0.9301 |   -0.9677 |
-#> |.....................|   -0.9792 |   -0.9215 |   -0.6570 |   -0.5501 |
-#> |.....................|   -0.9482 |   -0.6999 |   -0.7521 |   -0.7551 |
-#> |.....................|   -0.7234 |   -0.7907 |...........|...........|
-#> |    U|     1346.5436 |     182.3 |    -4.056 |   -0.9314 |    -2.400 |
-#> |.....................|    -4.079 |  -0.01100 |    0.8213 |   0.07939 |
-#> |.....................|    0.6486 |     1.883 |     1.449 |     1.317 |
-#> |.....................|     1.728 |     1.276 |...........|...........|
-#> |    X|     1346.5436 |     182.3 |   0.01732 |    0.2826 |   0.09069 |
-#> |.....................|   0.01692 |    0.4972 |    0.8213 |   0.07939 |
-#> |.....................|    0.6486 |     1.883 |     1.449 |     1.317 |
-#> |.....................|     1.728 |     1.276 |...........|...........|
-#> |    3|     512.48246 |     1.082 |   -0.9956 |   -0.9384 |   -0.9674 |
-#> |.....................|   -0.9979 |   -0.9214 |   -0.8822 |   -0.8830 |
-#> |.....................|   -0.9122 |   -0.8718 |   -0.8824 |   -0.8847 |
-#> |.....................|   -0.8759 |   -0.8883 |...........|...........|
-#> |    U|     512.48246 |     108.2 |    -4.096 |   -0.9391 |    -2.400 |
-#> |.....................|    -4.098 |  -0.01100 |    0.7391 |   0.06824 |
-#> |.....................|    0.6729 |     1.611 |     1.284 |     1.167 |
-#> |.....................|     1.502 |     1.163 |...........|...........|
-#> |    X|     512.48246 |     108.2 |   0.01665 |    0.2811 |   0.09072 |
-#> |.....................|   0.01661 |    0.4973 |    0.7391 |   0.06824 |
-#> |.....................|    0.6729 |     1.611 |     1.284 |     1.167 |
-#> |.....................|     1.502 |     1.163 |...........|...........|
-#> |    4|     495.95762 |     1.015 |   -0.9992 |   -0.9391 |   -0.9673 |
-#> |.....................|   -0.9996 |   -0.9214 |   -0.9027 |   -0.9133 |
-#> |.....................|   -0.9090 |   -0.8874 |   -0.8943 |   -0.8965 |
-#> |.....................|   -0.8898 |   -0.8972 |...........|...........|
-#> |    U|     495.95762 |     101.5 |    -4.099 |   -0.9398 |    -2.400 |
-#> |.....................|    -4.100 |  -0.01100 |    0.7316 |   0.06722 |
-#> |.....................|    0.6751 |     1.587 |     1.269 |     1.154 |
-#> |.....................|     1.482 |     1.153 |...........|...........|
-#> |    X|     495.95762 |     101.5 |   0.01659 |    0.2809 |   0.09072 |
-#> |.....................|   0.01658 |    0.4973 |    0.7316 |   0.06722 |
-#> |.....................|    0.6751 |     1.587 |     1.269 |     1.154 |
-#> |.....................|     1.482 |     1.153 |...........|...........|
-#> |    F| Forward Diff. |     41.81 |    -3.013 |  -0.08916 |   -0.3303 |
-#> |.....................|    -1.914 |  0.005472 |    -23.39 |    -29.38 |
-#> |.....................|     3.465 |    -17.07 |    -12.49 |    -12.74 |
-#> |.....................|    -15.23 |    -9.735 |...........|...........|
-#> |    5|     495.32815 |     1.003 |   -0.9984 |   -0.9391 |   -0.9673 |
-#> |.....................|   -0.9991 |   -0.9214 |   -0.8962 |   -0.9051 |
-#> |.....................|   -0.9099 |   -0.8826 |   -0.8908 |   -0.8930 |
-#> |.....................|   -0.8855 |   -0.8944 |...........|...........|
-#> |    U|     495.32815 |     100.3 |    -4.098 |   -0.9398 |    -2.400 |
-#> |.....................|    -4.099 |  -0.01100 |    0.7340 |   0.06750 |
-#> |.....................|    0.6745 |     1.594 |     1.273 |     1.158 |
-#> |.....................|     1.488 |     1.156 |...........|...........|
-#> |    X|     495.32815 |     100.3 |   0.01660 |    0.2809 |   0.09073 |
-#> |.....................|   0.01659 |    0.4973 |    0.7340 |   0.06750 |
-#> |.....................|    0.6745 |     1.594 |     1.273 |     1.158 |
-#> |.....................|     1.488 |     1.156 |...........|...........|
-#> |    F| Forward Diff. |    -47.70 |    -3.739 |   -0.6694 |  -0.04580 |
-#> |.....................|    -1.870 |  0.006670 |    -22.76 |    -30.26 |
-#> |.....................|     3.613 |    -16.75 |    -12.29 |    -12.38 |
-#> |.....................|    -15.09 |    -9.486 |...........|...........|
-#> |    6|     494.72051 |     1.016 |   -0.9974 |   -0.9389 |   -0.9672 |
-#> |.....................|   -0.9986 |   -0.9214 |   -0.8902 |   -0.8971 |
-#> |.....................|   -0.9109 |   -0.8782 |   -0.8876 |   -0.8897 |
-#> |.....................|   -0.8816 |   -0.8919 |...........|...........|
-#> |    U|     494.72051 |     101.6 |    -4.097 |   -0.9397 |    -2.400 |
-#> |.....................|    -4.099 |  -0.01100 |    0.7362 |   0.06777 |
-#> |.....................|    0.6738 |     1.601 |     1.277 |     1.162 |
-#> |.....................|     1.494 |     1.159 |...........|...........|
-#> |    X|     494.72051 |     101.6 |   0.01662 |    0.2810 |   0.09073 |
-#> |.....................|   0.01660 |    0.4973 |    0.7362 |   0.06777 |
-#> |.....................|    0.6738 |     1.601 |     1.277 |     1.162 |
-#> |.....................|     1.494 |     1.159 |...........|...........|
-#> |    F| Forward Diff. |     48.34 |    -2.939 |  -0.03847 |   -0.3608 |
-#> |.....................|    -1.945 |  0.005434 |    -20.90 |    -26.17 |
-#> |.....................|     3.821 |    -17.00 |    -12.53 |    -12.70 |
-#> |.....................|    -15.56 |    -9.587 |...........|...........|
-#> |    7|     494.15722 |     1.003 |   -0.9966 |   -0.9389 |   -0.9671 |
-#> |.....................|   -0.9981 |   -0.9214 |   -0.8845 |   -0.8900 |
-#> |.....................|   -0.9119 |   -0.8736 |   -0.8842 |   -0.8863 |
-#> |.....................|   -0.8773 |   -0.8893 |...........|...........|
-#> |    U|     494.15722 |     100.3 |    -4.097 |   -0.9396 |    -2.400 |
-#> |.....................|    -4.098 |  -0.01100 |    0.7383 |   0.06800 |
-#> |.....................|    0.6731 |     1.608 |     1.282 |     1.166 |
-#> |.....................|     1.500 |     1.162 |...........|...........|
-#> |    X|     494.15722 |     100.3 |   0.01663 |    0.2810 |   0.09074 |
-#> |.....................|   0.01660 |    0.4973 |    0.7383 |   0.06800 |
-#> |.....................|    0.6731 |     1.608 |     1.282 |     1.166 |
-#> |.....................|     1.500 |     1.162 |...........|...........|
-#> |    F| Forward Diff. |    -50.36 |    -3.770 |   -0.7003 |  -0.03307 |
-#> |.....................|    -1.882 |  0.006830 |    -20.02 |    -28.64 |
-#> |.....................|     3.020 |    -16.49 |    -12.31 |    -12.33 |
-#> |.....................|    -14.87 |    -9.319 |...........|...........|
-#> |    8|     493.49185 |     1.015 |   -0.9955 |   -0.9387 |   -0.9671 |
-#> |.....................|   -0.9975 |   -0.9214 |   -0.8787 |   -0.8818 |
-#> |.....................|   -0.9128 |   -0.8688 |   -0.8806 |   -0.8827 |
-#> |.....................|   -0.8730 |   -0.8866 |...........|...........|
-#> |    U|     493.49185 |     101.5 |    -4.096 |   -0.9395 |    -2.400 |
-#> |.....................|    -4.098 |  -0.01100 |    0.7404 |   0.06828 |
-#> |.....................|    0.6725 |     1.616 |     1.286 |     1.170 |
-#> |.....................|     1.507 |     1.165 |...........|...........|
-#> |    X|     493.49185 |     101.5 |   0.01665 |    0.2810 |   0.09074 |
-#> |.....................|   0.01661 |    0.4973 |    0.7404 |   0.06828 |
-#> |.....................|    0.6725 |     1.616 |     1.286 |     1.170 |
-#> |.....................|     1.507 |     1.165 |...........|...........|
-#> |    F| Forward Diff. |     41.03 |    -2.976 |  -0.07989 |   -0.3421 |
-#> |.....................|    -1.950 |  0.005619 |    -20.95 |    -25.58 |
-#> |.....................|     3.377 |    -16.59 |    -11.95 |    -12.23 |
-#> |.....................|    -14.73 |    -9.398 |...........|...........|
-#> |    9|     492.95463 |     1.003 |   -0.9946 |   -0.9387 |   -0.9670 |
-#> |.....................|   -0.9969 |   -0.9215 |   -0.8725 |   -0.8742 |
-#> |.....................|   -0.9138 |   -0.8639 |   -0.8771 |   -0.8790 |
-#> |.....................|   -0.8686 |   -0.8839 |...........|...........|
-#> |    U|     492.95463 |     100.3 |    -4.095 |   -0.9394 |    -2.400 |
-#> |.....................|    -4.097 |  -0.01100 |    0.7427 |   0.06853 |
-#> |.....................|    0.6718 |     1.624 |     1.291 |     1.174 |
-#> |.....................|     1.513 |     1.168 |...........|...........|
-#> |    X|     492.95463 |     100.3 |   0.01666 |    0.2810 |   0.09075 |
-#> |.....................|   0.01662 |    0.4973 |    0.7427 |   0.06853 |
-#> |.....................|    0.6718 |     1.624 |     1.291 |     1.174 |
-#> |.....................|     1.513 |     1.168 |...........|...........|
-#> |    F| Forward Diff. |    -49.97 |    -3.772 |   -0.7121 |  -0.02926 |
-#> |.....................|    -1.890 |  0.006985 |    -18.86 |    -26.85 |
-#> |.....................|     2.866 |    -16.28 |    -11.70 |    -11.82 |
-#> |.....................|    -14.59 |    -9.132 |...........|...........|
-#> |   10|     492.31444 |     1.015 |   -0.9935 |   -0.9385 |   -0.9670 |
-#> |.....................|   -0.9964 |   -0.9215 |   -0.8668 |   -0.8662 |
-#> |.....................|   -0.9147 |   -0.8589 |   -0.8735 |   -0.8755 |
-#> |.....................|   -0.8642 |   -0.8811 |...........|...........|
-#> |    U|     492.31444 |     101.5 |    -4.094 |   -0.9393 |    -2.400 |
-#> |.....................|    -4.096 |  -0.01100 |    0.7448 |   0.06880 |
-#> |.....................|    0.6712 |     1.632 |     1.295 |     1.178 |
-#> |.....................|     1.520 |     1.172 |...........|...........|
-#> |    X|     492.31444 |     101.5 |   0.01668 |    0.2810 |   0.09075 |
-#> |.....................|   0.01663 |    0.4972 |    0.7448 |   0.06880 |
-#> |.....................|    0.6712 |     1.632 |     1.295 |     1.178 |
-#> |.....................|     1.520 |     1.172 |...........|...........|
-#> |    F| Forward Diff. |     40.47 |    -2.944 |  -0.07505 |   -0.3464 |
-#> |.....................|    -1.962 |  0.005707 |    -18.58 |    -22.75 |
-#> |.....................|     3.454 |    -16.50 |    -11.93 |    -12.14 |
-#> |.....................|    -15.04 |    -9.193 |...........|...........|
-#> |   11|     491.79472 |     1.003 |   -0.9926 |   -0.9385 |   -0.9669 |
-#> |.....................|   -0.9957 |   -0.9215 |   -0.8609 |   -0.8590 |
-#> |.....................|   -0.9158 |   -0.8537 |   -0.8697 |   -0.8716 |
-#> |.....................|   -0.8594 |   -0.8781 |...........|...........|
-#> |    U|     491.79472 |     100.3 |    -4.093 |   -0.9392 |    -2.400 |
-#> |.....................|    -4.096 |  -0.01100 |    0.7469 |   0.06904 |
-#> |.....................|    0.6705 |     1.640 |     1.300 |     1.183 |
-#> |.....................|     1.527 |     1.175 |...........|...........|
-#> |    X|     491.79472 |     100.3 |   0.01670 |    0.2811 |   0.09076 |
-#> |.....................|   0.01664 |    0.4972 |    0.7469 |   0.06904 |
-#> |.....................|    0.6705 |     1.640 |     1.300 |     1.183 |
-#> |.....................|     1.527 |     1.175 |...........|...........|
-#> |    F| Forward Diff. |    -48.84 |    -3.756 |   -0.7183 |  -0.02810 |
-#> |.....................|    -1.902 |  0.007122 |    -19.51 |    -25.13 |
-#> |.....................|     2.711 |    -16.03 |    -11.73 |    -11.80 |
-#> |.....................|    -14.28 |    -8.965 |...........|...........|
-#> |   12|     491.12641 |     1.014 |   -0.9913 |   -0.9383 |   -0.9669 |
-#> |.....................|   -0.9951 |   -0.9215 |   -0.8546 |   -0.8511 |
-#> |.....................|   -0.9167 |   -0.8483 |   -0.8658 |   -0.8677 |
-#> |.....................|   -0.8546 |   -0.8752 |...........|...........|
-#> |    U|     491.12641 |     101.4 |    -4.091 |   -0.9390 |    -2.400 |
-#> |.....................|    -4.095 |  -0.01100 |    0.7492 |   0.06931 |
-#> |.....................|    0.6699 |     1.648 |     1.305 |     1.187 |
-#> |.....................|     1.534 |     1.178 |...........|...........|
-#> |    X|     491.12641 |     101.4 |   0.01672 |    0.2811 |   0.09076 |
-#> |.....................|   0.01665 |    0.4972 |    0.7492 |   0.06931 |
-#> |.....................|    0.6699 |     1.648 |     1.305 |     1.187 |
-#> |.....................|     1.534 |     1.178 |...........|...........|
-#> |    F| Forward Diff. |     34.57 |    -2.950 |   -0.1076 |   -0.3310 |
-#> |.....................|    -1.967 |  0.005897 |    -18.06 |    -21.71 |
-#> |.....................|     3.154 |    -16.24 |    -11.62 |    -11.87 |
-#> |.....................|    -14.73 |    -8.995 |...........|...........|
-#> |   13|     490.65951 |     1.002 |   -0.9903 |   -0.9382 |   -0.9668 |
-#> |.....................|   -0.9944 |   -0.9215 |   -0.8485 |   -0.8438 |
-#> |.....................|   -0.9178 |   -0.8429 |   -0.8619 |   -0.8637 |
-#> |.....................|   -0.8496 |   -0.8721 |...........|...........|
-#> |    U|     490.65951 |     100.2 |    -4.090 |   -0.9390 |    -2.399 |
-#> |.....................|    -4.094 |  -0.01100 |    0.7514 |   0.06955 |
-#> |.....................|    0.6692 |     1.657 |     1.310 |     1.192 |
-#> |.....................|     1.541 |     1.182 |...........|...........|
-#> |    X|     490.65951 |     100.2 |   0.01673 |    0.2811 |   0.09077 |
-#> |.....................|   0.01667 |    0.4972 |    0.7514 |   0.06955 |
-#> |.....................|    0.6692 |     1.657 |     1.310 |     1.192 |
-#> |.....................|     1.541 |     1.182 |...........|...........|
-#> |    F| Forward Diff. |    -50.76 |    -3.759 |   -0.7472 |  -0.01668 |
-#> |.....................|    -1.908 |  0.007323 |    -16.70 |    -21.90 |
-#> |.....................|     3.094 |    -15.72 |    -11.38 |    -11.47 |
-#> |.....................|    -14.04 |    -8.745 |...........|...........|
-#> |   14|     490.01300 |     1.014 |   -0.9891 |   -0.9380 |   -0.9667 |
-#> |.....................|   -0.9937 |   -0.9215 |   -0.8428 |   -0.8366 |
-#> |.....................|   -0.9189 |   -0.8372 |   -0.8579 |   -0.8596 |
-#> |.....................|   -0.8446 |   -0.8690 |...........|...........|
-#> |    U|       490.013 |     101.4 |    -4.089 |   -0.9388 |    -2.399 |
-#> |.....................|    -4.094 |  -0.01100 |    0.7535 |   0.06979 |
-#> |.....................|    0.6684 |     1.666 |     1.315 |     1.196 |
-#> |.....................|     1.549 |     1.186 |...........|...........|
-#> |    X|       490.013 |     101.4 |   0.01676 |    0.2811 |   0.09077 |
-#> |.....................|   0.01668 |    0.4972 |    0.7535 |   0.06979 |
-#> |.....................|    0.6684 |     1.666 |     1.315 |     1.196 |
-#> |.....................|     1.549 |     1.186 |...........|...........|
-#> |    F| Forward Diff. |     34.25 |    -2.890 |  -0.09666 |   -0.3362 |
-#> |.....................|    -1.973 |  0.006003 |    -17.09 |    -20.19 |
-#> |.....................|     3.007 |    -15.95 |    -11.25 |    -11.56 |
-#> |.....................|    -14.42 |    -8.788 |...........|...........|
-#> |   15|     489.51603 |     1.003 |   -0.9880 |   -0.9380 |   -0.9666 |
-#> |.....................|   -0.9930 |   -0.9215 |   -0.8366 |   -0.8294 |
-#> |.....................|   -0.9200 |   -0.8313 |   -0.8537 |   -0.8553 |
-#> |.....................|   -0.8392 |   -0.8658 |...........|...........|
-#> |    U|     489.51603 |     100.3 |    -4.088 |   -0.9388 |    -2.399 |
-#> |.....................|    -4.093 |  -0.01100 |    0.7558 |   0.07003 |
-#> |.....................|    0.6677 |     1.675 |     1.320 |     1.201 |
-#> |.....................|     1.556 |     1.189 |...........|...........|
-#> |    X|     489.51603 |     100.3 |   0.01677 |    0.2812 |   0.09078 |
-#> |.....................|   0.01669 |    0.4972 |    0.7558 |   0.07003 |
-#> |.....................|    0.6677 |     1.675 |     1.320 |     1.201 |
-#> |.....................|     1.556 |     1.189 |...........|...........|
-#> |    F| Forward Diff. |    -45.29 |    -3.673 |   -0.7179 |  -0.03084 |
-#> |.....................|    -1.907 |  0.007423 |    -17.34 |    -21.86 |
-#> |.....................|     2.565 |    -15.52 |    -11.05 |    -11.19 |
-#> |.....................|    -14.28 |    -8.545 |...........|...........|
-#> |   16|     488.89410 |     1.014 |   -0.9866 |   -0.9377 |   -0.9666 |
-#> |.....................|   -0.9922 |   -0.9215 |   -0.8304 |   -0.8220 |
-#> |.....................|   -0.9210 |   -0.8254 |   -0.8495 |   -0.8510 |
-#> |.....................|   -0.8337 |   -0.8625 |...........|...........|
-#> |    U|      488.8941 |     101.4 |    -4.087 |   -0.9385 |    -2.399 |
-#> |.....................|    -4.092 |  -0.01100 |    0.7580 |   0.07028 |
-#> |.....................|    0.6670 |     1.685 |     1.325 |     1.206 |
-#> |.....................|     1.565 |     1.193 |...........|...........|
-#> |    X|      488.8941 |     101.4 |   0.01680 |    0.2812 |   0.09079 |
-#> |.....................|   0.01670 |    0.4972 |    0.7580 |   0.07028 |
-#> |.....................|    0.6670 |     1.685 |     1.325 |     1.206 |
-#> |.....................|     1.565 |     1.193 |...........|...........|
-#> |    F| Forward Diff. |     32.56 |    -2.827 |  -0.09853 |   -0.3366 |
-#> |.....................|    -1.968 |  0.006143 |    -15.42 |    -18.16 |
-#> |.....................|     2.733 |    -15.52 |    -10.94 |    -11.25 |
-#> |.....................|    -14.13 |    -8.583 |...........|...........|
-#> |   17|     488.48678 |     1.002 |   -0.9855 |   -0.9377 |   -0.9664 |
-#> |.....................|   -0.9915 |   -0.9215 |   -0.8246 |   -0.8152 |
-#> |.....................|   -0.9220 |   -0.8195 |   -0.8454 |   -0.8468 |
-#> |.....................|   -0.8284 |   -0.8593 |...........|...........|
-#> |    U|     488.48678 |     100.2 |    -4.086 |   -0.9385 |    -2.399 |
-#> |.....................|    -4.091 |  -0.01100 |    0.7601 |   0.07051 |
-#> |.....................|    0.6663 |     1.694 |     1.331 |     1.211 |
-#> |.....................|     1.572 |     1.197 |...........|...........|
-#> |    X|     488.48678 |     100.2 |   0.01681 |    0.2812 |   0.09080 |
-#> |.....................|   0.01671 |    0.4972 |    0.7601 |   0.07051 |
-#> |.....................|    0.6663 |     1.694 |     1.331 |     1.211 |
-#> |.....................|     1.572 |     1.197 |...........|...........|
-#> |    F| Forward Diff. |    -50.86 |    -3.681 |   -0.7723 |-0.0007467 |
-#> |.....................|    -1.892 |  0.007742 |    -16.40 |    -20.55 |
-#> |.....................|     2.306 |    -15.16 |    -10.65 |    -10.82 |
-#> |.....................|    -14.00 |    -8.331 |...........|...........|
-#> |   18|     487.81394 |     1.012 |   -0.9841 |   -0.9374 |   -0.9664 |
-#> |.....................|   -0.9907 |   -0.9215 |   -0.8186 |   -0.8083 |
-#> |.....................|   -0.9229 |   -0.8132 |   -0.8411 |   -0.8424 |
-#> |.....................|   -0.8225 |   -0.8558 |...........|...........|
-#> |    U|     487.81394 |     101.2 |    -4.084 |   -0.9383 |    -2.399 |
-#> |.....................|    -4.091 |  -0.01100 |    0.7623 |   0.07074 |
-#> |.....................|    0.6657 |     1.704 |     1.336 |     1.216 |
-#> |.....................|     1.581 |     1.201 |...........|...........|
-#> |    X|     487.81394 |     101.2 |   0.01684 |    0.2812 |   0.09080 |
-#> |.....................|   0.01673 |    0.4972 |    0.7623 |   0.07074 |
-#> |.....................|    0.6657 |     1.704 |     1.336 |     1.216 |
-#> |.....................|     1.581 |     1.201 |...........|...........|
-#> |    F| Forward Diff. |     24.73 |    -2.818 |   -0.1513 |   -0.3103 |
-#> |.....................|    -1.952 |  0.006413 |    -14.43 |    -16.89 |
-#> |.....................|     2.774 |    -15.21 |    -10.56 |    -10.91 |
-#> |.....................|    -13.80 |    -8.354 |...........|...........|
-#> |   19|     487.41354 |     1.002 |   -0.9829 |   -0.9374 |   -0.9663 |
-#> |.....................|   -0.9898 |   -0.9215 |   -0.8126 |   -0.8013 |
-#> |.....................|   -0.9240 |   -0.8068 |   -0.8367 |   -0.8378 |
-#> |.....................|   -0.8167 |   -0.8523 |...........|...........|
-#> |    U|     487.41354 |     100.2 |    -4.083 |   -0.9382 |    -2.399 |
-#> |.....................|    -4.090 |  -0.01100 |    0.7645 |   0.07098 |
-#> |.....................|    0.6649 |     1.714 |     1.342 |     1.221 |
-#> |.....................|     1.590 |     1.205 |...........|...........|
-#> |    X|     487.41354 |     100.2 |   0.01686 |    0.2813 |   0.09082 |
-#> |.....................|   0.01674 |    0.4972 |    0.7645 |   0.07098 |
-#> |.....................|    0.6649 |     1.714 |     1.342 |     1.221 |
-#> |.....................|     1.590 |     1.205 |...........|...........|
-#> |    F| Forward Diff. |    -49.04 |    -3.605 |   -0.7738 | -0.005231 |
-#> |.....................|    -1.885 |  0.007887 |    -13.75 |    -19.14 |
-#> |.....................|     2.153 |    -14.90 |    -10.33 |    -10.54 |
-#> |.....................|    -13.68 |    -8.125 |...........|...........|
-#> |   20|     486.77105 |     1.012 |   -0.9814 |   -0.9371 |   -0.9662 |
-#> |.....................|   -0.9889 |   -0.9215 |   -0.8076 |   -0.7947 |
-#> |.....................|   -0.9250 |   -0.7999 |   -0.8321 |   -0.8330 |
-#> |.....................|   -0.8104 |   -0.8486 |...........|...........|
-#> |    U|     486.77105 |     101.2 |    -4.081 |   -0.9380 |    -2.399 |
-#> |.....................|    -4.089 |  -0.01100 |    0.7664 |   0.07119 |
-#> |.....................|    0.6643 |     1.725 |     1.347 |     1.227 |
-#> |.....................|     1.599 |     1.209 |...........|...........|
-#> |    X|     486.77105 |     101.2 |   0.01688 |    0.2813 |   0.09082 |
-#> |.....................|   0.01676 |    0.4972 |    0.7664 |   0.07119 |
-#> |.....................|    0.6643 |     1.725 |     1.347 |     1.227 |
-#> |.....................|     1.599 |     1.209 |...........|...........|
-#> |    F| Forward Diff. |     24.27 |    -2.713 |   -0.1438 |   -0.3142 |
-#> |.....................|    -1.939 |  0.006562 |    -14.18 |    -16.12 |
-#> |.....................|     2.525 |    -14.86 |    -10.17 |    -10.57 |
-#> |.....................|    -13.46 |    -8.131 |...........|...........|
-#> |   21|     486.40106 |     1.002 |   -0.9802 |   -0.9371 |   -0.9661 |
-#> |.....................|   -0.9881 |   -0.9215 |   -0.8015 |   -0.7878 |
-#> |.....................|   -0.9261 |   -0.7935 |   -0.8277 |   -0.8285 |
-#> |.....................|   -0.8046 |   -0.8452 |...........|...........|
-#> |    U|     486.40106 |     100.2 |    -4.080 |   -0.9379 |    -2.399 |
-#> |.....................|    -4.088 |  -0.01100 |    0.7686 |   0.07143 |
-#> |.....................|    0.6635 |     1.735 |     1.353 |     1.232 |
-#> |.....................|     1.608 |     1.213 |...........|...........|
-#> |    X|     486.40106 |     100.2 |   0.01690 |    0.2813 |   0.09083 |
-#> |.....................|   0.01677 |    0.4972 |    0.7686 |   0.07143 |
-#> |.....................|    0.6635 |     1.735 |     1.353 |     1.232 |
-#> |.....................|     1.608 |     1.213 |...........|...........|
-#> |    F| Forward Diff. |    -49.43 |    -3.533 |   -0.7907 |  0.002583 |
-#> |.....................|    -1.861 |  0.008122 |    -12.85 |    -17.77 |
-#> |.....................|     2.313 |    -14.52 |    -9.868 |    -10.18 |
-#> |.....................|    -13.34 |    -7.899 |...........|...........|
-#> |   22|     485.77865 |     1.012 |   -0.9786 |   -0.9368 |   -0.9660 |
-#> |.....................|   -0.9871 |   -0.9215 |   -0.7966 |   -0.7818 |
-#> |.....................|   -0.9271 |   -0.7864 |   -0.8231 |   -0.8237 |
-#> |.....................|   -0.7980 |   -0.8414 |...........|...........|
-#> |    U|     485.77865 |     101.2 |    -4.079 |   -0.9376 |    -2.399 |
-#> |.....................|    -4.087 |  -0.01100 |    0.7704 |   0.07163 |
-#> |.....................|    0.6629 |     1.746 |     1.359 |     1.238 |
-#> |.....................|     1.617 |     1.217 |...........|...........|
-#> |    X|     485.77865 |     101.2 |   0.01693 |    0.2814 |   0.09084 |
-#> |.....................|   0.01679 |    0.4972 |    0.7704 |   0.07163 |
-#> |.....................|    0.6629 |     1.746 |     1.359 |     1.238 |
-#> |.....................|     1.617 |     1.217 |...........|...........|
-#> |    F| Forward Diff. |     23.77 |    -2.587 |   -0.1355 |   -0.3176 |
-#> |.....................|    -1.913 |  0.006717 |    -13.39 |    -15.00 |
-#> |.....................|     2.211 |    -14.53 |    -9.747 |    -10.22 |
-#> |.....................|    -13.16 |    -7.915 |...........|...........|
-#> |   23|     485.42886 |     1.002 |   -0.9775 |   -0.9367 |   -0.9659 |
-#> |.....................|   -0.9862 |   -0.9215 |   -0.7907 |   -0.7751 |
-#> |.....................|   -0.9281 |   -0.7799 |   -0.8187 |   -0.8190 |
-#> |.....................|   -0.7921 |   -0.8378 |...........|...........|
-#> |    U|     485.42886 |     100.2 |    -4.077 |   -0.9376 |    -2.399 |
-#> |.....................|    -4.086 |  -0.01100 |    0.7725 |   0.07185 |
-#> |.....................|    0.6622 |     1.757 |     1.364 |     1.243 |
-#> |.....................|     1.626 |     1.221 |...........|...........|
-#> |    X|     485.42886 |     100.2 |   0.01695 |    0.2814 |   0.09085 |
-#> |.....................|   0.01680 |    0.4972 |    0.7725 |   0.07185 |
-#> |.....................|    0.6622 |     1.757 |     1.364 |     1.243 |
-#> |.....................|     1.626 |     1.221 |...........|...........|
-#> |    F| Forward Diff. |    -48.95 |    -3.431 |   -0.7980 |  0.007511 |
-#> |.....................|    -1.828 |  0.008340 |    -12.05 |    -16.59 |
-#> |.....................|     2.177 |    -14.27 |    -9.567 |    -9.843 |
-#> |.....................|    -12.98 |    -7.655 |...........|...........|
-#> |   24|     484.82183 |     1.012 |   -0.9759 |   -0.9364 |   -0.9658 |
-#> |.....................|   -0.9852 |   -0.9215 |   -0.7861 |   -0.7697 |
-#> |.....................|   -0.9290 |   -0.7723 |   -0.8141 |   -0.8141 |
-#> |.....................|   -0.7852 |   -0.8339 |...........|...........|
-#> |    U|     484.82183 |     101.2 |    -4.076 |   -0.9373 |    -2.398 |
-#> |.....................|    -4.085 |  -0.01100 |    0.7742 |   0.07203 |
-#> |.....................|    0.6616 |     1.769 |     1.370 |     1.249 |
-#> |.....................|     1.636 |     1.226 |...........|...........|
-#> |    X|     484.82183 |     101.2 |   0.01698 |    0.2814 |   0.09086 |
-#> |.....................|   0.01682 |    0.4972 |    0.7742 |   0.07203 |
-#> |.....................|    0.6616 |     1.769 |     1.370 |     1.249 |
-#> |.....................|     1.636 |     1.226 |...........|...........|
-#> |    F| Forward Diff. |     22.05 |    -2.460 |   -0.1372 |   -0.3150 |
-#> |.....................|    -1.875 |  0.006918 |    -12.51 |    -13.87 |
-#> |.....................|     2.059 |    -14.26 |    -9.441 |    -9.910 |
-#> |.....................|    -12.81 |    -7.688 |...........|...........|
-#> |   25|     484.49026 |     1.002 |   -0.9747 |   -0.9363 |   -0.9656 |
-#> |.....................|   -0.9843 |   -0.9215 |   -0.7802 |   -0.7632 |
-#> |.....................|   -0.9300 |   -0.7655 |   -0.8095 |   -0.8093 |
-#> |.....................|   -0.7791 |   -0.8302 |...........|...........|
-#> |    U|     484.49026 |     100.2 |    -4.075 |   -0.9372 |    -2.398 |
-#> |.....................|    -4.084 |  -0.01100 |    0.7764 |   0.07225 |
-#> |.....................|    0.6609 |     1.779 |     1.376 |     1.254 |
-#> |.....................|     1.645 |     1.230 |...........|...........|
-#> |    X|     484.49026 |     100.2 |   0.01700 |    0.2815 |   0.09087 |
-#> |.....................|   0.01684 |    0.4972 |    0.7764 |   0.07225 |
-#> |.....................|    0.6609 |     1.779 |     1.376 |     1.254 |
-#> |.....................|     1.645 |     1.230 |...........|...........|
-#> |    F| Forward Diff. |    -48.40 |    -3.314 |   -0.8046 |   0.01082 |
-#> |.....................|    -1.785 |  0.008564 |    -11.34 |    -13.90 |
-#> |.....................|     2.095 |    -13.95 |    -9.157 |    -9.483 |
-#> |.....................|    -12.66 |    -7.448 |...........|...........|
-#> |   26|     483.91316 |     1.012 |   -0.9731 |   -0.9360 |   -0.9656 |
-#> |.....................|   -0.9832 |   -0.9215 |   -0.7758 |   -0.7593 |
-#> |.....................|   -0.9309 |   -0.7575 |   -0.8048 |   -0.8042 |
-#> |.....................|   -0.7719 |   -0.8261 |...........|...........|
-#> |    U|     483.91316 |     101.2 |    -4.073 |   -0.9369 |    -2.398 |
-#> |.....................|    -4.083 |  -0.01100 |    0.7780 |   0.07238 |
-#> |.....................|    0.6603 |     1.792 |     1.382 |     1.260 |
-#> |.....................|     1.656 |     1.235 |...........|...........|
-#> |    X|     483.91316 |     101.2 |   0.01702 |    0.2815 |   0.09088 |
-#> |.....................|   0.01685 |    0.4972 |    0.7780 |   0.07238 |
-#> |.....................|    0.6603 |     1.792 |     1.382 |     1.260 |
-#> |.....................|     1.656 |     1.235 |...........|...........|
-#> |    F| Forward Diff. |     21.71 |    -2.295 |   -0.1241 |   -0.3190 |
-#> |.....................|    -1.824 |  0.007081 |    -13.14 |    -14.20 |
-#> |.....................|     1.713 |    -13.92 |    -9.049 |    -9.560 |
-#> |.....................|    -12.44 |    -7.439 |...........|...........|
-#> |   27|     483.53972 |     1.003 |   -0.9719 |   -0.9359 |   -0.9654 |
-#> |.....................|   -0.9822 |   -0.9215 |   -0.7695 |   -0.7529 |
-#> |.....................|   -0.9317 |   -0.7501 |   -0.8002 |   -0.7993 |
-#> |.....................|   -0.7653 |   -0.8222 |...........|...........|
-#> |    U|     483.53972 |     100.3 |    -4.072 |   -0.9368 |    -2.398 |
-#> |.....................|    -4.082 |  -0.01100 |    0.7803 |   0.07259 |
-#> |.....................|    0.6598 |     1.804 |     1.388 |     1.266 |
-#> |.....................|     1.666 |     1.239 |...........|...........|
-#> |    X|     483.53972 |     100.3 |   0.01705 |    0.2815 |   0.09089 |
-#> |.....................|   0.01687 |    0.4972 |    0.7803 |   0.07259 |
-#> |.....................|    0.6598 |     1.804 |     1.388 |     1.266 |
-#> |.....................|     1.666 |     1.239 |...........|...........|
-#> |    F| Forward Diff. |    -41.33 |    -3.086 |   -0.7421 |  -0.01550 |
-#> |.....................|    -1.732 |  0.008667 |    -12.24 |    -14.31 |
-#> |.....................|     1.879 |    -13.57 |    -8.704 |    -9.151 |
-#> |.....................|    -12.31 |    -7.231 |...........|...........|
-#> |   28|     483.02129 |     1.012 |   -0.9704 |   -0.9356 |   -0.9653 |
-#> |.....................|   -0.9811 |   -0.9215 |   -0.7639 |   -0.7482 |
-#> |.....................|   -0.9323 |   -0.7422 |   -0.7957 |   -0.7943 |
-#> |.....................|   -0.7582 |   -0.8182 |...........|...........|
-#> |    U|     483.02129 |     101.2 |    -4.070 |   -0.9365 |    -2.398 |
-#> |.....................|    -4.081 |  -0.01100 |    0.7823 |   0.07275 |
-#> |.....................|    0.6594 |     1.816 |     1.393 |     1.271 |
-#> |.....................|     1.676 |     1.244 |...........|...........|
-#> |    X|     483.02129 |     101.2 |   0.01707 |    0.2816 |   0.09090 |
-#> |.....................|   0.01689 |    0.4972 |    0.7823 |   0.07275 |
-#> |.....................|    0.6594 |     1.816 |     1.393 |     1.271 |
-#> |.....................|     1.676 |     1.244 |...........|...........|
-#> |    F| Forward Diff. |     24.99 |    -2.064 |  -0.07177 |   -0.3414 |
-#> |.....................|    -1.768 |  0.007186 |    -12.35 |    -13.09 |
-#> |.....................|     1.619 |    -13.63 |    -8.749 |    -9.199 |
-#> |.....................|    -12.40 |    -7.209 |...........|...........|
-#> |   29|     482.63111 |     1.003 |   -0.9692 |   -0.9355 |   -0.9651 |
-#> |.....................|   -0.9800 |   -0.9215 |   -0.7579 |   -0.7429 |
-#> |.....................|   -0.9329 |   -0.7344 |   -0.7911 |   -0.7893 |
-#> |.....................|   -0.7510 |   -0.8142 |...........|...........|
-#> |    U|     482.63111 |     100.3 |    -4.069 |   -0.9364 |    -2.398 |
-#> |.....................|    -4.080 |  -0.01100 |    0.7845 |   0.07293 |
-#> |.....................|    0.6589 |     1.829 |     1.399 |     1.277 |
-#> |.....................|     1.687 |     1.249 |...........|...........|
-#> |    X|     482.63111 |     100.3 |   0.01709 |    0.2816 |   0.09092 |
-#> |.....................|   0.01691 |    0.4972 |    0.7845 |   0.07293 |
-#> |.....................|    0.6589 |     1.829 |     1.399 |     1.277 |
-#> |.....................|     1.687 |     1.249 |...........|...........|
-#> |    F| Forward Diff. |    -36.55 |    -2.873 |   -0.6941 |  -0.03251 |
-#> |.....................|    -1.664 |  0.008820 |    -11.56 |    -13.31 |
-#> |.....................|     1.468 |    -13.22 |    -8.319 |    -8.815 |
-#> |.....................|    -11.93 |    -7.014 |...........|...........|
-#> |   30|     482.15860 |     1.013 |   -0.9679 |   -0.9352 |   -0.9650 |
-#> |.....................|   -0.9789 |   -0.9215 |   -0.7525 |   -0.7387 |
-#> |.....................|   -0.9332 |   -0.7261 |   -0.7866 |   -0.7843 |
-#> |.....................|   -0.7435 |   -0.8100 |...........|...........|
-#> |    U|      482.1586 |     101.3 |    -4.068 |   -0.9361 |    -2.398 |
-#> |.....................|    -4.079 |  -0.01100 |    0.7865 |   0.07307 |
-#> |.....................|    0.6587 |     1.842 |     1.405 |     1.283 |
-#> |.....................|     1.698 |     1.253 |...........|...........|
-#> |    X|      482.1586 |     101.3 |   0.01711 |    0.2817 |   0.09093 |
-#> |.....................|   0.01693 |    0.4972 |    0.7865 |   0.07307 |
-#> |.....................|    0.6587 |     1.842 |     1.405 |     1.283 |
-#> |.....................|     1.698 |     1.253 |...........|...........|
-#> |    F| Forward Diff. |     26.18 |    -1.853 |  -0.03641 |   -0.3540 |
-#> |.....................|    -1.697 |  0.007343 |    -10.35 |    -10.94 |
-#> |.....................|     1.762 |    -13.15 |    -8.194 |    -8.841 |
-#> |.....................|    -11.73 |    -7.013 |...........|...........|
-#> |   31|     481.77253 |     1.004 |   -0.9667 |   -0.9350 |   -0.9648 |
-#> |.....................|   -0.9778 |   -0.9215 |   -0.7477 |   -0.7350 |
-#> |.....................|   -0.9339 |   -0.7174 |   -0.7818 |   -0.7789 |
-#> |.....................|   -0.7358 |   -0.8055 |...........|...........|
-#> |    U|     481.77253 |     100.4 |    -4.067 |   -0.9360 |    -2.397 |
-#> |.....................|    -4.078 |  -0.01100 |    0.7882 |   0.07320 |
-#> |.....................|    0.6583 |     1.855 |     1.411 |     1.289 |
-#> |.....................|     1.709 |     1.259 |...........|...........|
-#> |    X|     481.77253 |     100.4 |   0.01713 |    0.2817 |   0.09095 |
-#> |.....................|   0.01695 |    0.4972 |    0.7882 |   0.07320 |
-#> |.....................|    0.6583 |     1.855 |     1.411 |     1.289 |
-#> |.....................|     1.709 |     1.259 |...........|...........|
-#> |    F| Forward Diff. |    -33.42 |    -2.468 |   -0.6588 |  -0.04495 |
-#> |.....................|    -1.582 |  0.009000 |    -9.278 |    -10.93 |
-#> |.....................|     2.073 |    -12.89 |    -7.995 |    -8.451 |
-#> |.....................|    -11.53 |    -6.784 |...........|...........|
-#> |   32|     481.33405 |     1.012 |   -0.9656 |   -0.9347 |   -0.9646 |
-#> |.....................|   -0.9766 |   -0.9215 |   -0.7446 |   -0.7329 |
-#> |.....................|   -0.9352 |   -0.7079 |   -0.7769 |   -0.7733 |
-#> |.....................|   -0.7275 |   -0.8008 |...........|...........|
-#> |    U|     481.33405 |     101.2 |    -4.066 |   -0.9357 |    -2.397 |
-#> |.....................|    -4.077 |  -0.01100 |    0.7894 |   0.07326 |
-#> |.....................|    0.6574 |     1.870 |     1.417 |     1.296 |
-#> |.....................|     1.721 |     1.264 |...........|...........|
-#> |    X|     481.33405 |     101.2 |   0.01715 |    0.2818 |   0.09096 |
-#> |.....................|   0.01697 |    0.4972 |    0.7894 |   0.07326 |
-#> |.....................|    0.6574 |     1.870 |     1.417 |     1.296 |
-#> |.....................|     1.721 |     1.264 |...........|...........|
-#> |    F| Forward Diff. |     23.32 |    -1.710 |  -0.03967 |   -0.3452 |
-#> |.....................|    -1.599 |  0.007614 |    -9.890 |    -10.44 |
-#> |.....................|     1.650 |    -12.78 |    -7.841 |    -8.441 |
-#> |.....................|    -11.31 |    -6.748 |...........|...........|
-#> |   33|     480.95912 |     1.004 |   -0.9646 |   -0.9346 |   -0.9644 |
-#> |.....................|   -0.9754 |   -0.9215 |   -0.7406 |   -0.7300 |
-#> |.....................|   -0.9364 |   -0.6985 |   -0.7720 |   -0.7677 |
-#> |.....................|   -0.7193 |   -0.7960 |...........|...........|
-#> |    U|     480.95912 |     100.4 |    -4.065 |   -0.9356 |    -2.397 |
-#> |.....................|    -4.075 |  -0.01100 |    0.7908 |   0.07336 |
-#> |.....................|    0.6566 |     1.885 |     1.424 |     1.302 |
-#> |.....................|     1.734 |     1.270 |...........|...........|
-#> |    X|     480.95912 |     100.4 |   0.01717 |    0.2818 |   0.09098 |
-#> |.....................|   0.01699 |    0.4972 |    0.7908 |   0.07336 |
-#> |.....................|    0.6566 |     1.885 |     1.424 |     1.302 |
-#> |.....................|     1.734 |     1.270 |...........|...........|
-#> |    F| Forward Diff. |    -30.38 |    -2.273 |   -0.6168 |  -0.05646 |
-#> |.....................|    -1.481 |  0.009185 |    -8.899 |    -11.86 |
-#> |.....................|     1.510 |    -12.49 |    -7.578 |    -8.069 |
-#> |.....................|    -11.13 |    -6.546 |...........|...........|
-#> |   34|     480.53887 |     1.012 |   -0.9637 |   -0.9342 |   -0.9642 |
-#> |.....................|   -0.9743 |   -0.9216 |   -0.7379 |   -0.7267 |
-#> |.....................|   -0.9369 |   -0.6888 |   -0.7673 |   -0.7623 |
-#> |.....................|   -0.7109 |   -0.7912 |...........|...........|
-#> |    U|     480.53887 |     101.2 |    -4.064 |   -0.9352 |    -2.397 |
-#> |.....................|    -4.074 |  -0.01100 |    0.7918 |   0.07347 |
-#> |.....................|    0.6562 |     1.901 |     1.429 |     1.308 |
-#> |.....................|     1.746 |     1.275 |...........|...........|
-#> |    X|     480.53887 |     101.2 |   0.01719 |    0.2819 |   0.09100 |
-#> |.....................|   0.01700 |    0.4972 |    0.7918 |   0.07347 |
-#> |.....................|    0.6562 |     1.901 |     1.429 |     1.308 |
-#> |.....................|     1.746 |     1.275 |...........|...........|
-#> |    F| Forward Diff. |     23.40 |    -1.545 | -0.009684 |   -0.3499 |
-#> |.....................|    -1.497 |  0.007817 |    -10.78 |    -11.16 |
-#> |.....................|     1.267 |    -12.36 |    -7.423 |    -8.042 |
-#> |.....................|    -10.90 |    -6.497 |...........|...........|
-#> |   35|     480.15983 |     1.005 |   -0.9631 |   -0.9341 |   -0.9640 |
-#> |.....................|   -0.9733 |   -0.9216 |   -0.7332 |   -0.7223 |
-#> |.....................|   -0.9371 |   -0.6793 |   -0.7629 |   -0.7571 |
-#> |.....................|   -0.7029 |   -0.7866 |...........|...........|
-#> |    U|     480.15983 |     100.5 |    -4.063 |   -0.9351 |    -2.397 |
-#> |.....................|    -4.073 |  -0.01100 |    0.7935 |   0.07362 |
-#> |.....................|    0.6561 |     1.916 |     1.435 |     1.314 |
-#> |.....................|     1.758 |     1.280 |...........|...........|
-#> |    X|     480.15983 |     100.5 |   0.01720 |    0.2819 |   0.09102 |
-#> |.....................|   0.01702 |    0.4972 |    0.7935 |   0.07362 |
-#> |.....................|    0.6561 |     1.916 |     1.435 |     1.314 |
-#> |.....................|     1.758 |     1.280 |...........|...........|
-#> |    F| Forward Diff. |    -28.57 |    -2.381 |   -0.5845 |  -0.05882 |
-#> |.....................|    -1.378 |  0.009420 |    -9.960 |    -11.12 |
-#> |.....................|     1.408 |    -12.08 |    -7.201 |    -7.708 |
-#> |.....................|    -10.66 |    -6.274 |...........|...........|
-#> |   36|     479.76525 |     1.013 |   -0.9621 |   -0.9338 |   -0.9638 |
-#> |.....................|   -0.9724 |   -0.9216 |   -0.7274 |   -0.7189 |
-#> |.....................|   -0.9370 |   -0.6698 |   -0.7590 |   -0.7523 |
-#> |.....................|   -0.6950 |   -0.7821 |...........|...........|
-#> |    U|     479.76525 |     101.3 |    -4.062 |   -0.9349 |    -2.396 |
-#> |.....................|    -4.072 |  -0.01100 |    0.7956 |   0.07373 |
-#> |.....................|    0.6562 |     1.931 |     1.440 |     1.320 |
-#> |.....................|     1.770 |     1.286 |...........|...........|
-#> |    X|     479.76525 |     101.3 |   0.01721 |    0.2819 |   0.09104 |
-#> |.....................|   0.01704 |    0.4972 |    0.7956 |   0.07373 |
-#> |.....................|    0.6562 |     1.931 |     1.440 |     1.320 |
-#> |.....................|     1.770 |     1.286 |...........|...........|
-#> |    F| Forward Diff. |     25.60 |    -1.145 |   0.04744 |   -0.3638 |
-#> |.....................|    -1.405 |  0.007969 |    -8.937 |    -9.159 |
-#> |.....................|     1.481 |    -11.97 |    -7.076 |    -7.721 |
-#> |.....................|    -10.46 |    -6.241 |...........|...........|
-#> |   37|     479.40619 |     1.005 |   -0.9617 |   -0.9337 |   -0.9635 |
-#> |.....................|   -0.9714 |   -0.9216 |   -0.7231 |   -0.7171 |
-#> |.....................|   -0.9376 |   -0.6597 |   -0.7546 |   -0.7470 |
-#> |.....................|   -0.6867 |   -0.7774 |...........|...........|
-#> |    U|     479.40619 |     100.5 |    -4.062 |   -0.9348 |    -2.396 |
-#> |.....................|    -4.071 |  -0.01100 |    0.7972 |   0.07380 |
-#> |.....................|    0.6558 |     1.947 |     1.445 |     1.326 |
-#> |.....................|     1.782 |     1.291 |...........|...........|
-#> |    X|     479.40619 |     100.5 |   0.01722 |    0.2820 |   0.09107 |
-#> |.....................|   0.01705 |    0.4972 |    0.7972 |   0.07380 |
-#> |.....................|    0.6558 |     1.947 |     1.445 |     1.326 |
-#> |.....................|     1.782 |     1.291 |...........|...........|
-#> |    F| Forward Diff. |    -26.68 |    -2.255 |   -0.5492 |  -0.06756 |
-#> |.....................|    -1.289 |  0.009576 |    -8.071 |    -10.65 |
-#> |.....................|     1.114 |    -11.68 |    -6.840 |    -7.373 |
-#> |.....................|    -10.30 |    -6.055 |...........|...........|
-#> |   38|     479.03445 |     1.012 |   -0.9610 |   -0.9335 |   -0.9633 |
-#> |.....................|   -0.9705 |   -0.9216 |   -0.7212 |   -0.7148 |
-#> |.....................|   -0.9376 |   -0.6492 |   -0.7503 |   -0.7416 |
-#> |.....................|   -0.6779 |   -0.7724 |...........|...........|
-#> |    U|     479.03445 |     101.2 |    -4.061 |   -0.9345 |    -2.396 |
-#> |.....................|    -4.071 |  -0.01100 |    0.7979 |   0.07387 |
-#> |.....................|    0.6558 |     1.963 |     1.451 |     1.332 |
-#> |.....................|     1.795 |     1.297 |...........|...........|
-#> |    X|     479.03445 |     101.2 |   0.01723 |    0.2820 |   0.09109 |
-#> |.....................|   0.01707 |    0.4972 |    0.7979 |   0.07387 |
-#> |.....................|    0.6558 |     1.963 |     1.451 |     1.332 |
-#> |.....................|     1.795 |     1.297 |...........|...........|
-#> |    F| Forward Diff. |     22.12 |    -1.081 |   0.03630 |   -0.3485 |
-#> |.....................|    -1.311 |  0.008233 |    -8.610 |    -8.856 |
-#> |.....................|     1.385 |    -11.53 |    -6.694 |    -7.351 |
-#> |.....................|    -10.05 |    -5.987 |...........|...........|
-#> |   39|     478.70046 |     1.005 |   -0.9607 |   -0.9334 |   -0.9629 |
-#> |.....................|   -0.9697 |   -0.9216 |   -0.7185 |   -0.7124 |
-#> |.....................|   -0.9378 |   -0.6386 |   -0.7461 |   -0.7363 |
-#> |.....................|   -0.6692 |   -0.7674 |...........|...........|
-#> |    U|     478.70046 |     100.5 |    -4.061 |   -0.9345 |    -2.396 |
-#> |.....................|    -4.070 |  -0.01100 |    0.7989 |   0.07395 |
-#> |.....................|    0.6557 |     1.980 |     1.456 |     1.338 |
-#> |.....................|     1.808 |     1.302 |...........|...........|
-#> |    X|     478.70046 |     100.5 |   0.01724 |    0.2820 |   0.09112 |
-#> |.....................|   0.01708 |    0.4972 |    0.7989 |   0.07395 |
-#> |.....................|    0.6557 |     1.980 |     1.456 |     1.338 |
-#> |.....................|     1.808 |     1.302 |...........|...........|
-#> |    F| Forward Diff. |    -26.51 |    -2.193 |   -0.5308 |  -0.05813 |
-#> |.....................|    -1.191 |  0.009843 |    -9.246 |    -10.25 |
-#> |.....................|     1.049 |    -11.25 |    -6.459 |    -7.012 |
-#> |.....................|    -9.842 |    -5.790 |...........|...........|
-#> |   40|     478.33460 |     1.012 |   -0.9602 |   -0.9332 |   -0.9627 |
-#> |.....................|   -0.9690 |   -0.9216 |   -0.7136 |   -0.7111 |
-#> |.....................|   -0.9376 |   -0.6278 |   -0.7425 |   -0.7314 |
-#> |.....................|   -0.6607 |   -0.7626 |...........|...........|
-#> |    U|      478.3346 |     101.2 |    -4.060 |   -0.9343 |    -2.395 |
-#> |.....................|    -4.069 |  -0.01100 |    0.8007 |   0.07400 |
-#> |.....................|    0.6558 |     1.997 |     1.461 |     1.344 |
-#> |.....................|     1.820 |     1.308 |...........|...........|
-#> |    X|      478.3346 |     101.2 |   0.01724 |    0.2821 |   0.09114 |
-#> |.....................|   0.01709 |    0.4972 |    0.8007 |   0.07400 |
-#> |.....................|    0.6558 |     1.997 |     1.461 |     1.344 |
-#> |.....................|     1.820 |     1.308 |...........|...........|
-#> |    F| Forward Diff. |     20.00 |    -1.246 |   0.04282 |   -0.3358 |
-#> |.....................|    -1.228 |  0.008460 |    -8.250 |    -8.533 |
-#> |.....................|     1.305 |    -11.09 |    -6.335 |    -6.999 |
-#> |.....................|    -9.637 |    -5.739 |...........|...........|
-#> |   41|     478.02904 |     1.005 |   -0.9595 |   -0.9333 |   -0.9623 |
-#> |.....................|   -0.9683 |   -0.9217 |   -0.7087 |   -0.7092 |
-#> |.....................|   -0.9377 |   -0.6173 |   -0.7388 |   -0.7264 |
-#> |.....................|   -0.6523 |   -0.7577 |...........|...........|
-#> |    U|     478.02904 |     100.5 |    -4.060 |   -0.9343 |    -2.395 |
-#> |.....................|    -4.068 |  -0.01100 |    0.8025 |   0.07406 |
-#> |.....................|    0.6557 |     2.014 |     1.466 |     1.350 |
-#> |.....................|     1.833 |     1.314 |...........|...........|
-#> |    X|     478.02904 |     100.5 |   0.01726 |    0.2820 |   0.09117 |
-#> |.....................|   0.01711 |    0.4972 |    0.8025 |   0.07406 |
-#> |.....................|    0.6557 |     2.014 |     1.466 |     1.350 |
-#> |.....................|     1.833 |     1.314 |...........|...........|
-#> |    F| Forward Diff. |    -28.91 |    -2.133 |   -0.5430 |  -0.03427 |
-#> |.....................|    -1.114 |   0.01012 |    -7.324 |    -9.914 |
-#> |.....................|    0.9278 |    -10.81 |    -6.119 |    -6.673 |
-#> |.....................|    -9.457 |    -5.557 |...........|...........|
-#> |   42|     477.67480 |     1.012 |   -0.9587 |   -0.9331 |   -0.9620 |
-#> |.....................|   -0.9677 |   -0.9217 |   -0.7077 |   -0.7075 |
-#> |.....................|   -0.9374 |   -0.6060 |   -0.7354 |   -0.7215 |
-#> |.....................|   -0.6433 |   -0.7527 |...........|...........|
-#> |    U|      477.6748 |     101.2 |    -4.059 |   -0.9342 |    -2.395 |
-#> |.....................|    -4.068 |  -0.01100 |    0.8028 |   0.07412 |
-#> |.....................|    0.6559 |     2.032 |     1.470 |     1.355 |
-#> |.....................|     1.846 |     1.319 |...........|...........|
-#> |    X|      477.6748 |     101.2 |   0.01727 |    0.2821 |   0.09120 |
-#> |.....................|   0.01712 |    0.4972 |    0.8028 |   0.07412 |
-#> |.....................|    0.6559 |     2.032 |     1.470 |     1.355 |
-#> |.....................|     1.846 |     1.319 |...........|...........|
-#> |    F| Forward Diff. |     17.58 |    -1.074 |   0.03251 |   -0.3151 |
-#> |.....................|    -1.162 |  0.008688 |    -9.226 |    -9.481 |
-#> |.....................|    0.9303 |    -10.65 |    -6.004 |    -6.660 |
-#> |.....................|    -9.223 |    -5.492 |...........|...........|
-#> |   43|     477.36674 |     1.005 |   -0.9586 |   -0.9332 |   -0.9617 |
-#> |.....................|   -0.9672 |   -0.9217 |   -0.7028 |   -0.7029 |
-#> |.....................|   -0.9362 |   -0.5954 |   -0.7323 |   -0.7170 |
-#> |.....................|   -0.6350 |   -0.7479 |...........|...........|
-#> |    U|     477.36674 |     100.5 |    -4.059 |   -0.9343 |    -2.394 |
-#> |.....................|    -4.067 |  -0.01100 |    0.8046 |   0.07427 |
-#> |.....................|    0.6567 |     2.048 |     1.474 |     1.361 |
-#> |.....................|     1.858 |     1.325 |...........|...........|
-#> |    X|     477.36674 |     100.5 |   0.01727 |    0.2821 |   0.09123 |
-#> |.....................|   0.01713 |    0.4972 |    0.8046 |   0.07427 |
-#> |.....................|    0.6567 |     2.048 |     1.474 |     1.361 |
-#> |.....................|     1.858 |     1.325 |...........|...........|
-#> |    F| Forward Diff. |    -26.86 |    -1.999 |   -0.5088 |  -0.02993 |
-#> |.....................|    -1.056 |   0.01029 |    -6.930 |    -7.943 |
-#> |.....................|     1.123 |    -10.40 |    -5.776 |    -6.354 |
-#> |.....................|    -9.032 |    -5.321 |...........|...........|
-#> |   44|     477.05158 |     1.012 |   -0.9583 |   -0.9331 |   -0.9614 |
-#> |.....................|   -0.9667 |   -0.9217 |   -0.6985 |   -0.7029 |
-#> |.....................|   -0.9357 |   -0.5841 |   -0.7296 |   -0.7125 |
-#> |.....................|   -0.6265 |   -0.7430 |...........|...........|
-#> |    U|     477.05158 |     101.2 |    -4.058 |   -0.9342 |    -2.394 |
-#> |.....................|    -4.067 |  -0.01100 |    0.8062 |   0.07427 |
-#> |.....................|    0.6570 |     2.066 |     1.477 |     1.366 |
-#> |.....................|     1.871 |     1.331 |...........|...........|
-#> |    X|     477.05158 |     101.2 |   0.01728 |    0.2821 |   0.09126 |
-#> |.....................|   0.01713 |    0.4972 |    0.8062 |   0.07427 |
-#> |.....................|    0.6570 |     2.066 |     1.477 |     1.366 |
-#> |.....................|     1.871 |     1.331 |...........|...........|
-#> |    F| Forward Diff. |     21.59 |   -0.9080 |    0.1072 |   -0.3377 |
-#> |.....................|    -1.120 |  0.008656 |    -8.076 |    -8.919 |
-#> |.....................|    0.8940 |    -10.23 |    -5.724 |    -6.385 |
-#> |.....................|    -8.830 |    -5.273 |...........|...........|
-#> |   45|     476.75116 |     1.006 |   -0.9582 |   -0.9333 |   -0.9610 |
-#> |.....................|   -0.9662 |   -0.9217 |   -0.6961 |   -0.7025 |
-#> |.....................|   -0.9353 |   -0.5723 |   -0.7265 |   -0.7076 |
-#> |.....................|   -0.6174 |   -0.7378 |...........|...........|
-#> |    U|     476.75116 |     100.6 |    -4.058 |   -0.9343 |    -2.394 |
-#> |.....................|    -4.066 |  -0.01100 |    0.8070 |   0.07428 |
-#> |.....................|    0.6573 |     2.085 |     1.481 |     1.371 |
-#> |.....................|     1.884 |     1.337 |...........|...........|
-#> |    X|     476.75116 |     100.6 |   0.01728 |    0.2820 |   0.09129 |
-#> |.....................|   0.01714 |    0.4972 |    0.8070 |   0.07428 |
-#> |.....................|    0.6573 |     2.085 |     1.481 |     1.371 |
-#> |.....................|     1.884 |     1.337 |...........|...........|
-#> |    F| Forward Diff. |    -19.26 |    -1.806 |   -0.3949 |  -0.06769 |
-#> |.....................|    -1.006 |   0.01017 |    -6.717 |    -7.715 |
-#> |.....................|     1.115 |    -9.949 |    -5.529 |    -6.080 |
-#> |.....................|    -8.599 |    -5.083 |...........|...........|
-#> |   46|     476.47529 |     1.013 |   -0.9577 |   -0.9333 |   -0.9608 |
-#> |.....................|   -0.9657 |   -0.9218 |   -0.6941 |   -0.7020 |
-#> |.....................|   -0.9354 |   -0.5606 |   -0.7233 |   -0.7027 |
-#> |.....................|   -0.6086 |   -0.7326 |...........|...........|
-#> |    U|     476.47529 |     101.3 |    -4.058 |   -0.9343 |    -2.393 |
-#> |.....................|    -4.066 |  -0.01100 |    0.8078 |   0.07430 |
-#> |.....................|    0.6573 |     2.103 |     1.485 |     1.377 |
-#> |.....................|     1.897 |     1.342 |...........|...........|
-#> |    X|     476.47529 |     101.3 |   0.01729 |    0.2820 |   0.09132 |
-#> |.....................|   0.01715 |    0.4972 |    0.8078 |   0.07430 |
-#> |.....................|    0.6573 |     2.103 |     1.485 |     1.377 |
-#> |.....................|     1.897 |     1.342 |...........|...........|
-#> |    F| Forward Diff. |     23.23 |   -0.7393 |    0.1467 |   -0.3435 |
-#> |.....................|    -1.063 |  0.008714 |    -6.650 |    -7.604 |
-#> |.....................|     1.072 |    -9.778 |    -5.421 |    -6.068 |
-#> |.....................|    -8.413 |    -5.023 |...........|...........|
-#> |   47|     476.20958 |     1.007 |   -0.9575 |   -0.9335 |   -0.9604 |
-#> |.....................|   -0.9651 |   -0.9218 |   -0.6949 |   -0.7035 |
-#> |.....................|   -0.9364 |   -0.5488 |   -0.7198 |   -0.6977 |
-#> |.....................|   -0.5996 |   -0.7274 |...........|...........|
-#> |    U|     476.20958 |     100.7 |    -4.058 |   -0.9345 |    -2.393 |
-#> |.....................|    -4.065 |  -0.01100 |    0.8075 |   0.07425 |
-#> |.....................|    0.6566 |     2.122 |     1.490 |     1.383 |
-#> |.....................|     1.910 |     1.349 |...........|...........|
-#> |    X|     476.20958 |     100.7 |   0.01729 |    0.2820 |   0.09135 |
-#> |.....................|   0.01716 |    0.4972 |    0.8075 |   0.07425 |
-#> |.....................|    0.6566 |     2.122 |     1.490 |     1.383 |
-#> |.....................|     1.910 |     1.349 |...........|...........|
-#> |    F| Forward Diff. |    -16.91 |    -1.652 |   -0.3580 |  -0.07063 |
-#> |.....................|   -0.9392 |   0.01022 |    -6.706 |    -7.708 |
-#> |.....................|    0.9788 |    -9.498 |    -5.202 |    -5.742 |
-#> |.....................|    -8.208 |    -4.851 |...........|...........|
-#> |   48|     475.96032 |     1.013 |   -0.9572 |   -0.9335 |   -0.9601 |
-#> |.....................|   -0.9647 |   -0.9218 |   -0.6944 |   -0.7034 |
-#> |.....................|   -0.9370 |   -0.5368 |   -0.7166 |   -0.6928 |
-#> |.....................|   -0.5905 |   -0.7221 |...........|...........|
-#> |    U|     475.96032 |     101.3 |    -4.057 |   -0.9346 |    -2.393 |
-#> |.....................|    -4.065 |  -0.01100 |    0.8077 |   0.07425 |
-#> |.....................|    0.6562 |     2.141 |     1.494 |     1.388 |
-#> |.....................|     1.924 |     1.355 |...........|...........|
-#> |    X|     475.96032 |     101.3 |   0.01730 |    0.2820 |   0.09138 |
-#> |.....................|   0.01717 |    0.4972 |    0.8077 |   0.07425 |
-#> |.....................|    0.6562 |     2.141 |     1.494 |     1.388 |
-#> |.....................|     1.924 |     1.355 |...........|...........|
-#> |    F| Forward Diff. |     22.21 |   -0.6469 |    0.1490 |   -0.3297 |
-#> |.....................|   -0.9912 |  0.008804 |    -6.697 |    -7.730 |
-#> |.....................|     1.011 |    -9.295 |    -5.014 |    -5.737 |
-#> |.....................|    -7.990 |    -4.768 |...........|...........|
-#> |   49|     475.69232 |     1.007 |   -0.9579 |   -0.9338 |   -0.9597 |
-#> |.....................|   -0.9645 |   -0.9219 |   -0.6939 |   -0.7032 |
-#> |.....................|   -0.9375 |   -0.5243 |   -0.7149 |   -0.6885 |
-#> |.....................|   -0.5813 |   -0.7168 |...........|...........|
-#> |    U|     475.69232 |     100.7 |    -4.058 |   -0.9348 |    -2.392 |
-#> |.....................|    -4.064 |  -0.01100 |    0.8078 |   0.07426 |
-#> |.....................|    0.6559 |     2.161 |     1.496 |     1.393 |
-#> |.....................|     1.937 |     1.361 |...........|...........|
-#> |    X|     475.69232 |     100.7 |   0.01729 |    0.2819 |   0.09141 |
-#> |.....................|   0.01717 |    0.4972 |    0.8078 |   0.07426 |
-#> |.....................|    0.6559 |     2.161 |     1.496 |     1.393 |
-#> |.....................|     1.937 |     1.361 |...........|...........|
-#> |    F| Forward Diff. |    -16.63 |    -1.703 |   -0.3428 |  -0.06069 |
-#> |.....................|   -0.9074 |   0.01024 |    -7.409 |    -9.759 |
-#> |.....................|    0.6668 |    -9.063 |    -4.970 |    -5.451 |
-#> |.....................|    -7.786 |    -4.607 |...........|...........|
-#> |   50|     475.41012 |     1.012 |   -0.9580 |   -0.9340 |   -0.9594 |
-#> |.....................|   -0.9645 |   -0.9219 |   -0.6912 |   -0.6928 |
-#> |.....................|   -0.9358 |   -0.5138 |   -0.7150 |   -0.6862 |
-#> |.....................|   -0.5743 |   -0.7128 |...........|...........|
-#> |    U|     475.41012 |     101.2 |    -4.058 |   -0.9351 |    -2.392 |
-#> |.....................|    -4.064 |  -0.01101 |    0.8088 |   0.07461 |
-#> |.....................|    0.6570 |     2.177 |     1.496 |     1.396 |
-#> |.....................|     1.948 |     1.365 |...........|...........|
-#> |    X|     475.41012 |     101.2 |   0.01728 |    0.2819 |   0.09144 |
-#> |.....................|   0.01717 |    0.4972 |    0.8088 |   0.07461 |
-#> |.....................|    0.6570 |     2.177 |     1.496 |     1.396 |
-#> |.....................|     1.948 |     1.365 |...........|...........|
-#> |    F| Forward Diff. |     17.88 |   -0.8521 |   0.09625 |   -0.2834 |
-#> |.....................|    -1.006 |  0.008928 |    -8.320 |    -8.272 |
-#> |.....................|    0.6841 |    -8.896 |    -4.958 |    -5.482 |
-#> |.....................|    -7.690 |    -4.565 |...........|...........|
-#> |   51|     475.17343 |     1.006 |   -0.9580 |   -0.9344 |   -0.9592 |
-#> |.....................|   -0.9643 |   -0.9219 |   -0.6806 |   -0.6840 |
-#> |.....................|   -0.9328 |   -0.5062 |   -0.7153 |   -0.6852 |
-#> |.....................|   -0.5694 |   -0.7102 |...........|...........|
-#> |    U|     475.17343 |     100.6 |    -4.058 |   -0.9354 |    -2.392 |
-#> |.....................|    -4.064 |  -0.01101 |    0.8127 |   0.07490 |
-#> |.....................|    0.6590 |     2.189 |     1.495 |     1.397 |
-#> |.....................|     1.955 |     1.368 |...........|...........|
-#> |    X|     475.17343 |     100.6 |   0.01728 |    0.2818 |   0.09146 |
-#> |.....................|   0.01718 |    0.4972 |    0.8127 |   0.07490 |
-#> |.....................|    0.6590 |     2.189 |     1.495 |     1.397 |
-#> |.....................|     1.955 |     1.368 |...........|...........|
-#> |    F| Forward Diff. |    -22.54 |    -1.885 |   -0.4332 | -0.003109 |
-#> |.....................|   -0.9120 |   0.01053 |    -7.129 |    -7.659 |
-#> |.....................|    0.8338 |    -8.700 |    -4.918 |    -5.365 |
-#> |.....................|    -7.558 |    -4.481 |...........|...........|
-#> |   52|     474.94312 |     1.012 |   -0.9570 |   -0.9345 |   -0.9591 |
-#> |.....................|   -0.9638 |   -0.9220 |   -0.6676 |   -0.6825 |
-#> |.....................|   -0.9307 |   -0.4984 |   -0.7146 |   -0.6834 |
-#> |.....................|   -0.5639 |   -0.7072 |...........|...........|
-#> |    U|     474.94312 |     101.2 |    -4.057 |   -0.9355 |    -2.392 |
-#> |.....................|    -4.064 |  -0.01101 |    0.8175 |   0.07495 |
-#> |.....................|    0.6604 |     2.202 |     1.496 |     1.399 |
-#> |.....................|     1.963 |     1.372 |...........|...........|
-#> |    X|     474.94312 |     101.2 |   0.01730 |    0.2818 |   0.09147 |
-#> |.....................|   0.01718 |    0.4972 |    0.8175 |   0.07495 |
-#> |.....................|    0.6604 |     2.202 |     1.496 |     1.399 |
-#> |.....................|     1.963 |     1.372 |...........|...........|
-#> |    F| Forward Diff. |     20.08 |   -0.5236 |    0.1181 |   -0.2986 |
-#> |.....................|   -0.9599 |  0.008866 |    -5.310 |    -6.088 |
-#> |.....................|    0.8565 |    -8.707 |    -4.867 |    -5.430 |
-#> |.....................|    -7.458 |    -4.464 |...........|...........|
-#> |   53|     474.70657 |     1.007 |   -0.9569 |   -0.9346 |   -0.9588 |
-#> |.....................|   -0.9629 |   -0.9220 |   -0.6640 |   -0.6851 |
-#> |.....................|   -0.9296 |   -0.4868 |   -0.7112 |   -0.6784 |
-#> |.....................|   -0.5553 |   -0.7021 |...........|...........|
-#> |    U|     474.70657 |     100.7 |    -4.057 |   -0.9356 |    -2.392 |
-#> |.....................|    -4.063 |  -0.01101 |    0.8188 |   0.07487 |
-#> |.....................|    0.6612 |     2.220 |     1.500 |     1.405 |
-#> |.....................|     1.976 |     1.378 |...........|...........|
-#> |    X|     474.70657 |     100.7 |   0.01730 |    0.2818 |   0.09149 |
-#> |.....................|   0.01720 |    0.4972 |    0.8188 |   0.07487 |
-#> |.....................|    0.6612 |     2.220 |     1.500 |     1.405 |
-#> |.....................|     1.976 |     1.378 |...........|...........|
-#> |    F| Forward Diff. |    -17.64 |    -1.502 |   -0.3627 |  -0.03824 |
-#> |.....................|   -0.7798 |   0.01049 |    -5.965 |    -8.154 |
-#> |.....................|    0.5631 |    -8.385 |    -4.675 |    -5.151 |
-#> |.....................|    -7.306 |    -4.317 |...........|...........|
-#> |   54|     474.46623 |     1.012 |   -0.9580 |   -0.9346 |   -0.9586 |
-#> |.....................|   -0.9630 |   -0.9221 |   -0.6659 |   -0.6813 |
-#> |.....................|   -0.9264 |   -0.4751 |   -0.7083 |   -0.6739 |
-#> |.....................|   -0.5464 |   -0.6970 |...........|...........|
-#> |    U|     474.46623 |     101.2 |    -4.058 |   -0.9356 |    -2.391 |
-#> |.....................|    -4.063 |  -0.01101 |    0.8181 |   0.07499 |
-#> |.....................|    0.6633 |     2.239 |     1.504 |     1.410 |
-#> |.....................|     1.989 |     1.384 |...........|...........|
-#> |    X|     474.46623 |     101.2 |   0.01728 |    0.2818 |   0.09151 |
-#> |.....................|   0.01720 |    0.4972 |    0.8181 |   0.07499 |
-#> |.....................|    0.6633 |     2.239 |     1.504 |     1.410 |
-#> |.....................|     1.989 |     1.384 |...........|...........|
-#> |    F| Forward Diff. |     15.93 |   -0.7754 |   0.09266 |   -0.2754 |
-#> |.....................|   -0.8835 |  0.009135 |    -6.026 |    -6.068 |
-#> |.....................|    0.8217 |    -8.210 |    -4.532 |    -5.141 |
-#> |.....................|    -7.011 |    -4.237 |...........|...........|
-#> |   55|     474.23394 |     1.006 |   -0.9577 |   -0.9351 |   -0.9581 |
-#> |.....................|   -0.9633 |   -0.9221 |   -0.6610 |   -0.6793 |
-#> |.....................|   -0.9234 |   -0.4633 |   -0.7068 |   -0.6694 |
-#> |.....................|   -0.5382 |   -0.6917 |...........|...........|
-#> |    U|     474.23394 |     100.6 |    -4.058 |   -0.9360 |    -2.391 |
-#> |.....................|    -4.063 |  -0.01101 |    0.8199 |   0.07506 |
-#> |.....................|    0.6654 |     2.257 |     1.506 |     1.415 |
-#> |.....................|     2.001 |     1.390 |...........|...........|
-#> |    X|     474.23394 |     100.6 |   0.01729 |    0.2817 |   0.09156 |
-#> |.....................|   0.01719 |    0.4972 |    0.8199 |   0.07506 |
-#> |.....................|    0.6654 |     2.257 |     1.506 |     1.415 |
-#> |.....................|     2.001 |     1.390 |...........|...........|
-#> |    F| Forward Diff. |    -20.30 |    -1.703 |   -0.3919 | -0.002629 |
-#> |.....................|   -0.8653 |   0.01064 |    -4.947 |    -7.765 |
-#> |.....................|    0.7818 |    -8.010 |    -4.437 |    -4.875 |
-#> |.....................|    -6.938 |    -4.094 |...........|...........|
-#> |   56|     473.98878 |     1.011 |   -0.9542 |   -0.9354 |   -0.9578 |
-#> |.....................|   -0.9619 |   -0.9222 |   -0.6621 |   -0.6770 |
-#> |.....................|   -0.9235 |   -0.4507 |   -0.7053 |   -0.6648 |
-#> |.....................|   -0.5298 |   -0.6863 |...........|...........|
-#> |    U|     473.98878 |     101.1 |    -4.054 |   -0.9363 |    -2.390 |
-#> |.....................|    -4.062 |  -0.01101 |    0.8195 |   0.07514 |
-#> |.....................|    0.6653 |     2.277 |     1.508 |     1.421 |
-#> |.....................|     2.013 |     1.396 |...........|...........|
-#> |    X|     473.98878 |     101.1 |   0.01735 |    0.2816 |   0.09159 |
-#> |.....................|   0.01722 |    0.4972 |    0.8195 |   0.07514 |
-#> |.....................|    0.6653 |     2.277 |     1.508 |     1.421 |
-#> |.....................|     2.013 |     1.396 |...........|...........|
-#> |   57|     473.76836 |     1.011 |   -0.9500 |   -0.9359 |   -0.9574 |
-#> |.....................|   -0.9601 |   -0.9223 |   -0.6653 |   -0.6763 |
-#> |.....................|   -0.9234 |   -0.4357 |   -0.7046 |   -0.6601 |
-#> |.....................|   -0.5205 |   -0.6802 |...........|...........|
-#> |    U|     473.76836 |     101.1 |    -4.050 |   -0.9368 |    -2.390 |
-#> |.....................|    -4.060 |  -0.01101 |    0.8183 |   0.07516 |
-#> |.....................|    0.6654 |     2.301 |     1.509 |     1.426 |
-#> |.....................|     2.027 |     1.403 |...........|...........|
-#> |    X|     473.76836 |     101.1 |   0.01742 |    0.2815 |   0.09163 |
-#> |.....................|   0.01725 |    0.4972 |    0.8183 |   0.07516 |
-#> |.....................|    0.6654 |     2.301 |     1.509 |     1.426 |
-#> |.....................|     2.027 |     1.403 |...........|...........|
-#> |   58|     472.96708 |     1.009 |   -0.9317 |   -0.9384 |   -0.9555 |
-#> |.....................|   -0.9527 |   -0.9228 |   -0.6791 |   -0.6735 |
-#> |.....................|   -0.9230 |   -0.3711 |   -0.7015 |   -0.6396 |
-#> |.....................|   -0.4802 |   -0.6537 |...........|...........|
-#> |    U|     472.96708 |     100.9 |    -4.032 |   -0.9391 |    -2.388 |
-#> |.....................|    -4.053 |  -0.01101 |    0.8133 |   0.07525 |
-#> |.....................|    0.6656 |     2.403 |     1.513 |     1.450 |
-#> |.....................|     2.087 |     1.433 |...........|...........|
-#> |    X|     472.96708 |     100.9 |   0.01774 |    0.2811 |   0.09180 |
-#> |.....................|   0.01737 |    0.4972 |    0.8133 |   0.07525 |
-#> |.....................|    0.6656 |     2.403 |     1.513 |     1.450 |
-#> |.....................|     2.087 |     1.433 |...........|...........|
-#> |   59|     472.23802 |     1.005 |   -0.8811 |   -0.9451 |   -0.9502 |
-#> |.....................|   -0.9323 |   -0.9240 |   -0.7172 |   -0.6658 |
-#> |.....................|   -0.9220 |   -0.1924 |   -0.6930 |   -0.5829 |
-#> |.....................|   -0.3688 |   -0.5805 |...........|...........|
-#> |    U|     472.23802 |     100.5 |    -3.981 |   -0.9455 |    -2.383 |
-#> |.....................|    -4.032 |  -0.01103 |    0.7994 |   0.07551 |
-#> |.....................|    0.6663 |     2.686 |     1.523 |     1.515 |
-#> |.....................|     2.251 |     1.518 |...........|...........|
-#> |    X|     472.23802 |     100.5 |   0.01866 |    0.2798 |   0.09228 |
-#> |.....................|   0.01773 |    0.4972 |    0.7994 |   0.07551 |
-#> |.....................|    0.6663 |     2.686 |     1.523 |     1.515 |
-#> |.....................|     2.251 |     1.518 |...........|...........|
-#> |    F| Forward Diff. |    -10.41 |     25.09 |    -1.964 |    0.8913 |
-#> |.....................|     4.956 |   0.02208 |    -7.724 |    -8.360 |
-#> |.....................|   0.01123 |    -2.619 |    -3.185 |    -1.886 |
-#> |.....................|    -3.376 |    -1.727 |...........|...........|
-#> |   60|     470.34942 |     1.020 |    -1.007 |   -0.9408 |   -0.9496 |
-#> |.....................|   -0.9429 |   -0.9259 |   -0.7397 |   -0.6282 |
-#> |.....................|   -0.9207 |   0.06578 |   -0.6693 |   -0.4998 |
-#> |.....................|   -0.2002 |   -0.4722 |...........|...........|
-#> |    U|     470.34942 |     102.0 |    -4.107 |   -0.9414 |    -2.382 |
-#> |.....................|    -4.043 |  -0.01105 |    0.7911 |   0.07677 |
-#> |.....................|    0.6672 |     3.094 |     1.553 |     1.610 |
-#> |.....................|     2.500 |     1.642 |...........|...........|
-#> |    X|     470.34942 |     102.0 |   0.01646 |    0.2806 |   0.09235 |
-#> |.....................|   0.01755 |    0.4972 |    0.7911 |   0.07677 |
-#> |.....................|    0.6672 |     3.094 |     1.553 |     1.610 |
-#> |.....................|     2.500 |     1.642 |...........|...........|
-#> |    F| Forward Diff. |     49.94 |    -17.10 |     1.872 |    -1.413 |
-#> |.....................|     4.684 |  0.005064 |    -7.591 |    -5.431 |
-#> |.....................|    0.2085 |    -2.165 |    -1.196 |   -0.1732 |
-#> |.....................|   -0.4074 |   -0.2957 |...........|...........|
-#> |   61|     480.76065 |    0.9913 |   -0.9789 |   -0.9482 |   -0.9314 |
-#> |.....................|    -1.207 |   -0.9279 |   -0.6546 |   -0.4866 |
-#> |.....................|   -0.9168 |    0.2296 |   -0.6593 |   -0.5083 |
-#> |.....................|   -0.1307 |   -0.4332 |...........|...........|
-#> |    U|     480.76065 |     99.13 |    -4.079 |   -0.9483 |    -2.364 |
-#> |.....................|    -4.307 |  -0.01107 |    0.8222 |   0.08152 |
-#> |.....................|    0.6698 |     3.353 |     1.566 |     1.601 |
-#> |.....................|     2.603 |     1.687 |...........|...........|
-#> |    X|     480.76065 |     99.13 |   0.01693 |    0.2792 |   0.09404 |
-#> |.....................|   0.01347 |    0.4972 |    0.8222 |   0.08152 |
-#> |.....................|    0.6698 |     3.353 |     1.566 |     1.601 |
-#> |.....................|     2.603 |     1.687 |...........|...........|
-#> |   62|     472.12595 |    0.9860 |   -0.9933 |   -0.9428 |   -0.9466 |
-#> |.....................|   -0.9755 |   -0.9261 |   -0.7254 |   -0.6089 |
-#> |.....................|   -0.9204 |   0.08558 |   -0.6674 |   -0.5007 |
-#> |.....................|   -0.1921 |   -0.4676 |...........|...........|
-#> |    U|     472.12595 |     98.60 |    -4.093 |   -0.9433 |    -2.379 |
-#> |.....................|    -4.076 |  -0.01105 |    0.7964 |   0.07742 |
-#> |.....................|    0.6674 |     3.125 |     1.556 |     1.609 |
-#> |.....................|     2.512 |     1.648 |...........|...........|
-#> |    X|     472.12595 |     98.60 |   0.01668 |    0.2802 |   0.09262 |
-#> |.....................|   0.01698 |    0.4972 |    0.7964 |   0.07742 |
-#> |.....................|    0.6674 |     3.125 |     1.556 |     1.609 |
-#> |.....................|     2.512 |     1.648 |...........|...........|
-#> |   63|     470.26696 |     1.005 |    -1.002 |   -0.9414 |   -0.9491 |
-#> |.....................|   -0.9444 |   -0.9259 |   -0.7373 |   -0.6265 |
-#> |.....................|   -0.9207 |   0.06646 |   -0.6689 |   -0.4998 |
-#> |.....................|   -0.2001 |   -0.4721 |...........|...........|
-#> |    U|     470.26696 |     100.5 |    -4.102 |   -0.9420 |    -2.382 |
-#> |.....................|    -4.044 |  -0.01105 |    0.7920 |   0.07683 |
-#> |.....................|    0.6672 |     3.095 |     1.554 |     1.610 |
-#> |.....................|     2.501 |     1.642 |...........|...........|
-#> |    X|     470.26696 |     100.5 |   0.01654 |    0.2805 |   0.09239 |
-#> |.....................|   0.01752 |    0.4972 |    0.7920 |   0.07683 |
-#> |.....................|    0.6672 |     3.095 |     1.554 |     1.610 |
-#> |.....................|     2.501 |     1.642 |...........|...........|
-#> |    F| Forward Diff. |    -57.97 |    -21.53 |    0.3336 |   -0.1964 |
-#> |.....................|     4.949 |   0.01388 |    -7.299 |    -5.475 |
-#> |.....................|    0.3363 |    -1.951 |    -1.200 |    0.1716 |
-#> |.....................|   -0.4705 |   -0.2755 |...........|...........|
-#> |   64|     469.85165 |     1.014 |   -0.9972 |   -0.9415 |   -0.9489 |
-#> |.....................|   -0.9548 |   -0.9260 |   -0.7307 |   -0.6235 |
-#> |.....................|   -0.9208 |   0.07069 |   -0.6682 |   -0.5004 |
-#> |.....................|   -0.1987 |   -0.4712 |...........|...........|
-#> |    U|     469.85165 |     101.4 |    -4.097 |   -0.9421 |    -2.382 |
-#> |.....................|    -4.055 |  -0.01105 |    0.7944 |   0.07693 |
-#> |.....................|    0.6671 |     3.101 |     1.555 |     1.610 |
-#> |.....................|     2.503 |     1.643 |...........|...........|
-#> |    X|     469.85165 |     101.4 |   0.01662 |    0.2805 |   0.09241 |
-#> |.....................|   0.01734 |    0.4972 |    0.7944 |   0.07693 |
-#> |.....................|    0.6671 |     3.101 |     1.555 |     1.610 |
-#> |.....................|     2.503 |     1.643 |...........|...........|
-#> |    F| Forward Diff. |     9.302 |    -15.01 |     1.055 |   -0.6015 |
-#> |.....................|     1.082 |  0.004567 |    -8.090 |    -5.650 |
-#> |.....................|   -0.2579 |    -2.336 |    -1.339 |  -0.08766 |
-#> |.....................|   -0.5208 |   -0.3062 |...........|...........|
-#> |   65|     469.69998 |     1.007 |   -0.9853 |   -0.9423 |   -0.9484 |
-#> |.....................|   -0.9564 |   -0.9260 |   -0.7231 |   -0.6186 |
-#> |.....................|   -0.9204 |   0.07309 |   -0.6671 |   -0.5006 |
-#> |.....................|   -0.1982 |   -0.4709 |...........|...........|
-#> |    U|     469.69998 |     100.7 |    -4.085 |   -0.9429 |    -2.381 |
-#> |.....................|    -4.056 |  -0.01105 |    0.7972 |   0.07709 |
-#> |.....................|    0.6674 |     3.105 |     1.556 |     1.610 |
-#> |.....................|     2.503 |     1.644 |...........|...........|
-#> |    X|     469.69998 |     100.7 |   0.01682 |    0.2803 |   0.09245 |
-#> |.....................|   0.01731 |    0.4972 |    0.7972 |   0.07709 |
-#> |.....................|    0.6674 |     3.105 |     1.556 |     1.610 |
-#> |.....................|     2.503 |     1.644 |...........|...........|
-#> |    F| Forward Diff. |    -36.86 |    -12.39 |    0.1028 |    0.1354 |
-#> |.....................|    0.7614 |  0.008951 |    -8.542 |    -6.076 |
-#> |.....................|   -0.2246 |    -2.313 |    -1.235 |    0.1010 |
-#> |.....................|   -0.5654 |   -0.2998 |...........|...........|
-#> |   66|     469.45579 |     1.013 |   -0.9821 |   -0.9425 |   -0.9491 |
-#> |.....................|   -0.9562 |   -0.9260 |   -0.7099 |   -0.6134 |
-#> |.....................|   -0.9182 |   0.07758 |   -0.6674 |   -0.5042 |
-#> |.....................|   -0.1996 |   -0.4719 |...........|...........|
-#> |    U|     469.45579 |     101.3 |    -4.082 |   -0.9430 |    -2.382 |
-#> |.....................|    -4.056 |  -0.01105 |    0.8020 |   0.07727 |
-#> |.....................|    0.6689 |     3.112 |     1.556 |     1.605 |
-#> |.....................|     2.501 |     1.643 |...........|...........|
-#> |    X|     469.45579 |     101.3 |   0.01687 |    0.2803 |   0.09239 |
-#> |.....................|   0.01731 |    0.4972 |    0.8020 |   0.07727 |
-#> |.....................|    0.6689 |     3.112 |     1.556 |     1.605 |
-#> |.....................|     2.501 |     1.643 |...........|...........|
-#> |    F| Forward Diff. |     7.383 |    -7.976 |    0.5709 |   -0.2773 |
-#> |.....................|    0.4749 |  0.005686 |    -7.013 |    -4.742 |
-#> |.....................|   -0.3037 |    -2.186 |    -1.089 |  -0.04880 |
-#> |.....................|   -0.5661 |   -0.3435 |...........|...........|
-#> |   67|     469.35718 |     1.007 |   -0.9760 |   -0.9430 |   -0.9493 |
-#> |.....................|   -0.9561 |   -0.9261 |   -0.6977 |   -0.6075 |
-#> |.....................|   -0.9166 |   0.08278 |   -0.6675 |   -0.5068 |
-#> |.....................|   -0.2001 |   -0.4722 |...........|...........|
-#> |    U|     469.35718 |     100.7 |    -4.076 |   -0.9435 |    -2.382 |
-#> |.....................|    -4.056 |  -0.01105 |    0.8065 |   0.07747 |
-#> |.....................|    0.6700 |     3.121 |     1.556 |     1.602 |
-#> |.....................|     2.501 |     1.642 |...........|...........|
-#> |    X|     469.35718 |     100.7 |   0.01698 |    0.2802 |   0.09237 |
-#> |.....................|   0.01732 |    0.4972 |    0.8065 |   0.07747 |
-#> |.....................|    0.6700 |     3.121 |     1.556 |     1.602 |
-#> |.....................|     2.501 |     1.642 |...........|...........|
-#> |    F| Forward Diff. |    -28.34 |    -7.406 |  -0.07810 |    0.1748 |
-#> |.....................|    0.6873 |  0.009156 |    -6.696 |    -4.901 |
-#> |.....................|   -0.2913 |    -2.170 |    -1.086 |  -0.02443 |
-#> |.....................|   -0.6503 |   -0.3607 |...........|...........|
-#> |   68|     469.19639 |     1.012 |   -0.9749 |   -0.9431 |   -0.9497 |
-#> |.....................|   -0.9576 |   -0.9262 |   -0.6862 |   -0.6021 |
-#> |.....................|   -0.9137 |   0.09137 |   -0.6688 |   -0.5111 |
-#> |.....................|   -0.2009 |   -0.4726 |...........|...........|
-#> |    U|     469.19639 |     101.2 |    -4.075 |   -0.9436 |    -2.382 |
-#> |.....................|    -4.058 |  -0.01105 |    0.8107 |   0.07765 |
-#> |.....................|    0.6719 |     3.134 |     1.554 |     1.597 |
-#> |.....................|     2.499 |     1.642 |...........|...........|
-#> |    X|     469.19639 |     101.2 |   0.01699 |    0.2802 |   0.09233 |
-#> |.....................|   0.01729 |    0.4972 |    0.8107 |   0.07765 |
-#> |.....................|    0.6719 |     3.134 |     1.554 |     1.597 |
-#> |.....................|     2.499 |     1.642 |...........|...........|
-#> |    F| Forward Diff. |     4.760 |    -4.629 |    0.3091 |   -0.1325 |
-#> |.....................|  -0.04401 |  0.005819 |    -5.826 |    -2.903 |
-#> |.....................|   -0.1562 |    -2.130 |    -1.121 |   -0.2535 |
-#> |.....................|   -0.6922 |   -0.4141 |...........|...........|
-#> |   69|     469.12263 |     1.008 |   -0.9713 |   -0.9434 |   -0.9499 |
-#> |.....................|   -0.9575 |   -0.9262 |   -0.6727 |   -0.6012 |
-#> |.....................|   -0.9123 |   0.09974 |   -0.6678 |   -0.5134 |
-#> |.....................|   -0.2010 |   -0.4726 |...........|...........|
-#> |    U|     469.12263 |     100.8 |    -4.071 |   -0.9438 |    -2.383 |
-#> |.....................|    -4.058 |  -0.01105 |    0.8156 |   0.07768 |
-#> |.....................|    0.6728 |     3.147 |     1.555 |     1.595 |
-#> |.....................|     2.499 |     1.642 |...........|...........|
-#> |    X|     469.12263 |     100.8 |   0.01706 |    0.2801 |   0.09232 |
-#> |.....................|   0.01729 |    0.4972 |    0.8156 |   0.07768 |
-#> |.....................|    0.6728 |     3.147 |     1.555 |     1.595 |
-#> |.....................|     2.499 |     1.642 |...........|...........|
-#> |    F| Forward Diff. |    -20.86 |    -4.532 |   -0.1251 |    0.1663 |
-#> |.....................|    0.1284 |  0.008177 |    -5.101 |    -3.487 |
-#> |.....................|   -0.2183 |    -2.137 |    -1.171 |   -0.2991 |
-#> |.....................|   -0.6817 |   -0.4261 |...........|...........|
-#> |   70|     469.02483 |     1.011 |   -0.9711 |   -0.9434 |   -0.9500 |
-#> |.....................|   -0.9569 |   -0.9263 |   -0.6616 |   -0.6038 |
-#> |.....................|   -0.9105 |    0.1111 |   -0.6656 |   -0.5157 |
-#> |.....................|   -0.2026 |   -0.4730 |...........|...........|
-#> |    U|     469.02483 |     101.1 |    -4.071 |   -0.9439 |    -2.383 |
-#> |.....................|    -4.057 |  -0.01105 |    0.8196 |   0.07759 |
-#> |.....................|    0.6741 |     3.165 |     1.558 |     1.592 |
-#> |.....................|     2.497 |     1.641 |...........|...........|
-#> |    X|     469.02483 |     101.1 |   0.01706 |    0.2801 |   0.09230 |
-#> |.....................|   0.01730 |    0.4972 |    0.8196 |   0.07759 |
-#> |.....................|    0.6741 |     3.165 |     1.558 |     1.592 |
-#> |.....................|     2.497 |     1.641 |...........|...........|
-#> |    F| Forward Diff. |     4.786 |    -2.589 |    0.2046 |   -0.1061 |
-#> |.....................|    0.1383 |  0.006373 |    -4.080 |    -2.588 |
-#> |.....................|   -0.1418 |    -1.956 |   -0.9118 |   -0.4226 |
-#> |.....................|   -0.7530 |   -0.4429 |...........|...........|
-#> |   71|     468.97618 |     1.009 |   -0.9710 |   -0.9439 |   -0.9494 |
-#> |.....................|   -0.9625 |   -0.9265 |   -0.6573 |   -0.5998 |
-#> |.....................|   -0.9085 |    0.1255 |   -0.6648 |   -0.5157 |
-#> |.....................|   -0.2015 |   -0.4719 |...........|...........|
-#> |    U|     468.97618 |     100.9 |    -4.071 |   -0.9443 |    -2.382 |
-#> |.....................|    -4.063 |  -0.01106 |    0.8212 |   0.07773 |
-#> |.....................|    0.6755 |     3.188 |     1.559 |     1.592 |
-#> |.....................|     2.498 |     1.643 |...........|...........|
-#> |    X|     468.97618 |     100.9 |   0.01706 |    0.2800 |   0.09236 |
-#> |.....................|   0.01721 |    0.4972 |    0.8212 |   0.07773 |
-#> |.....................|    0.6755 |     3.188 |     1.559 |     1.592 |
-#> |.....................|     2.498 |     1.643 |...........|...........|
-#> |    F| Forward Diff. |    -11.25 |    -3.431 |  -0.02518 |    0.1501 |
-#> |.....................|    -1.529 |  0.005347 |    -4.655 |    -3.448 |
-#> |.....................|   -0.3102 |    -2.013 |   -0.8937 |   -0.3742 |
-#> |.....................|   -0.7403 |   -0.4511 |...........|...........|
-#> |   72|     468.91299 |     1.010 |   -0.9702 |   -0.9444 |   -0.9496 |
-#> |.....................|   -0.9534 |   -0.9266 |   -0.6524 |   -0.5929 |
-#> |.....................|   -0.9051 |    0.1362 |   -0.6665 |   -0.5172 |
-#> |.....................|   -0.2029 |   -0.4725 |...........|...........|
-#> |    U|     468.91299 |     101.0 |    -4.070 |   -0.9448 |    -2.382 |
-#> |.....................|    -4.053 |  -0.01106 |    0.8230 |   0.07796 |
-#> |.....................|    0.6777 |     3.205 |     1.557 |     1.590 |
-#> |.....................|     2.496 |     1.642 |...........|...........|
-#> |    X|     468.91299 |     101.0 |   0.01707 |    0.2799 |   0.09234 |
-#> |.....................|   0.01736 |    0.4972 |    0.8230 |   0.07796 |
-#> |.....................|    0.6777 |     3.205 |     1.557 |     1.590 |
-#> |.....................|     2.496 |     1.642 |...........|...........|
-#> |    F| Forward Diff. |    -8.129 |    -2.859 |  -0.02802 | -0.004107 |
-#> |.....................|     1.281 |  0.009120 |    -4.291 |    -2.058 |
-#> |.....................|   -0.1551 |    -2.052 |    -1.121 |   -0.5699 |
-#> |.....................|   -0.7547 |   -0.4743 |...........|...........|
-#> |   73|     471.25018 |     1.036 |   -0.9607 |   -0.9443 |   -0.9496 |
-#> |.....................|   -0.9576 |   -0.9266 |   -0.6382 |   -0.5860 |
-#> |.....................|   -0.9046 |    0.1430 |   -0.6628 |   -0.5153 |
-#> |.....................|   -0.2004 |   -0.4709 |...........|...........|
-#> |    U|     471.25018 |     103.6 |    -4.061 |   -0.9447 |    -2.382 |
-#> |.....................|    -4.058 |  -0.01106 |    0.8282 |   0.07819 |
-#> |.....................|    0.6781 |     3.216 |     1.562 |     1.593 |
-#> |.....................|     2.500 |     1.644 |...........|...........|
-#> |    X|     471.25018 |     103.6 |   0.01724 |    0.2800 |   0.09234 |
-#> |.....................|   0.01729 |    0.4972 |    0.8282 |   0.07819 |
-#> |.....................|    0.6781 |     3.216 |     1.562 |     1.593 |
-#> |.....................|     2.500 |     1.644 |...........|...........|
-#> |   74|     468.90555 |     1.012 |   -0.9692 |   -0.9444 |   -0.9496 |
-#> |.....................|   -0.9538 |   -0.9266 |   -0.6510 |   -0.5922 |
-#> |.....................|   -0.9050 |    0.1369 |   -0.6661 |   -0.5170 |
-#> |.....................|   -0.2027 |   -0.4723 |...........|...........|
-#> |    U|     468.90555 |     101.2 |    -4.069 |   -0.9448 |    -2.382 |
-#> |.....................|    -4.054 |  -0.01106 |    0.8235 |   0.07798 |
-#> |.....................|    0.6778 |     3.206 |     1.557 |     1.591 |
-#> |.....................|     2.497 |     1.642 |...........|...........|
-#> |    X|     468.90555 |     101.2 |   0.01709 |    0.2799 |   0.09234 |
-#> |.....................|   0.01736 |    0.4972 |    0.8235 |   0.07798 |
-#> |.....................|    0.6778 |     3.206 |     1.557 |     1.591 |
-#> |.....................|     2.497 |     1.642 |...........|...........|
-#> |    F| Forward Diff. |     11.48 |    -1.027 |    0.1960 |   -0.1655 |
-#> |.....................|    0.9827 |  0.007474 |    -3.960 |    -2.226 |
-#> |.....................|   -0.2199 |    -2.046 |    -1.158 |   -0.6171 |
-#> |.....................|   -0.7493 |   -0.4797 |...........|...........|
-#> |   75|     468.88608 |     1.010 |   -0.9691 |   -0.9444 |   -0.9495 |
-#> |.....................|   -0.9542 |   -0.9266 |   -0.6497 |   -0.5917 |
-#> |.....................|   -0.9044 |    0.1391 |   -0.6659 |   -0.5166 |
-#> |.....................|   -0.2026 |   -0.4722 |...........|...........|
-#> |    U|     468.88608 |     101.0 |    -4.069 |   -0.9448 |    -2.382 |
-#> |.....................|    -4.054 |  -0.01106 |    0.8240 |   0.07799 |
-#> |.....................|    0.6782 |     3.210 |     1.558 |     1.591 |
-#> |.....................|     2.497 |     1.642 |...........|...........|
-#> |    X|     468.88608 |     101.0 |   0.01709 |    0.2799 |   0.09235 |
-#> |.....................|   0.01735 |    0.4972 |    0.8240 |   0.07799 |
-#> |.....................|    0.6782 |     3.210 |     1.558 |     1.591 |
-#> |.....................|     2.497 |     1.642 |...........|...........|
-#> |    F| Forward Diff. |    -2.784 |    -1.944 |  0.009889 |  -0.02065 |
-#> |.....................|    0.9781 |  0.008521 |    -3.685 |    -1.489 |
-#> |.....................|  -0.08345 |    -1.963 |   -0.9408 |   -0.4978 |
-#> |.....................|   -0.7271 |   -0.4658 |...........|...........|
-#> |   76|     468.87604 |     1.012 |   -0.9680 |   -0.9444 |   -0.9495 |
-#> |.....................|   -0.9547 |   -0.9266 |   -0.6476 |   -0.5909 |
-#> |.....................|   -0.9043 |    0.1402 |   -0.6654 |   -0.5163 |
-#> |.....................|   -0.2021 |   -0.4719 |...........|...........|
-#> |    U|     468.87604 |     101.2 |    -4.068 |   -0.9448 |    -2.382 |
-#> |.....................|    -4.055 |  -0.01106 |    0.8248 |   0.07802 |
-#> |.....................|    0.6783 |     3.211 |     1.558 |     1.591 |
-#> |.....................|     2.498 |     1.643 |...........|...........|
-#> |    X|     468.87604 |     101.2 |   0.01711 |    0.2799 |   0.09235 |
-#> |.....................|   0.01734 |    0.4972 |    0.8248 |   0.07802 |
-#> |.....................|    0.6783 |     3.211 |     1.558 |     1.591 |
-#> |.....................|     2.498 |     1.643 |...........|...........|
-#> |    F| Forward Diff. |     9.309 |   -0.5261 |    0.1314 |   -0.1053 |
-#> |.....................|    0.6891 |  0.007435 |    -3.809 |    -2.129 |
-#> |.....................|   -0.2297 |    -2.013 |    -1.108 |   -0.5855 |
-#> |.....................|   -0.7533 |   -0.4780 |...........|...........|
-#> |   77|     468.85962 |     1.010 |   -0.9680 |   -0.9444 |   -0.9495 |
-#> |.....................|   -0.9550 |   -0.9266 |   -0.6462 |   -0.5907 |
-#> |.....................|   -0.9037 |    0.1428 |   -0.6653 |   -0.5160 |
-#> |.....................|   -0.2020 |   -0.4717 |...........|...........|
-#> |    U|     468.85962 |     101.0 |    -4.068 |   -0.9448 |    -2.382 |
-#> |.....................|    -4.055 |  -0.01106 |    0.8253 |   0.07803 |
-#> |.....................|    0.6787 |     3.215 |     1.558 |     1.592 |
-#> |.....................|     2.498 |     1.643 |...........|...........|
-#> |    X|     468.85962 |     101.0 |   0.01711 |    0.2799 |   0.09235 |
-#> |.....................|   0.01734 |    0.4972 |    0.8253 |   0.07803 |
-#> |.....................|    0.6787 |     3.215 |     1.558 |     1.592 |
-#> |.....................|     2.498 |     1.643 |...........|...........|
-#> |    F| Forward Diff. |    -1.556 |    -1.258 | -0.007590 |  0.001179 |
-#> |.....................|    0.7035 |  0.008243 |    -4.446 |    -2.277 |
-#> |.....................|   -0.2406 |    -1.984 |    -1.075 |   -0.5476 |
-#> |.....................|   -0.7588 |   -0.4741 |...........|...........|
-#> |   78|     468.84535 |     1.011 |   -0.9673 |   -0.9444 |   -0.9495 |
-#> |.....................|   -0.9554 |   -0.9266 |   -0.6436 |   -0.5895 |
-#> |.....................|   -0.9036 |    0.1439 |   -0.6647 |   -0.5157 |
-#> |.....................|   -0.2016 |   -0.4714 |...........|...........|
-#> |    U|     468.84535 |     101.1 |    -4.067 |   -0.9448 |    -2.382 |
-#> |.....................|    -4.055 |  -0.01106 |    0.8262 |   0.07807 |
-#> |.....................|    0.6788 |     3.217 |     1.559 |     1.592 |
-#> |.....................|     2.498 |     1.643 |...........|...........|
-#> |    X|     468.84535 |     101.1 |   0.01712 |    0.2799 |   0.09235 |
-#> |.....................|   0.01733 |    0.4972 |    0.8262 |   0.07807 |
-#> |.....................|    0.6788 |     3.217 |     1.559 |     1.592 |
-#> |.....................|     2.498 |     1.643 |...........|...........|
-#> |    F| Forward Diff. |     5.130 |   -0.4165 |   0.05789 |  -0.04298 |
-#> |.....................|    0.5152 |  0.007618 |    -4.342 |    -2.024 |
-#> |.....................|   -0.2412 |    -1.936 |   -0.8986 |   -0.4874 |
-#> |.....................|   -0.7551 |   -0.4761 |...........|...........|
-#> |   79|     468.83559 |     1.009 |   -0.9672 |   -0.9445 |   -0.9494 |
-#> |.....................|   -0.9556 |   -0.9266 |   -0.6414 |   -0.5890 |
-#> |.....................|   -0.9032 |    0.1455 |   -0.6647 |   -0.5153 |
-#> |.....................|   -0.2012 |   -0.4711 |...........|...........|
-#> |    U|     468.83559 |     100.9 |    -4.067 |   -0.9449 |    -2.382 |
-#> |.....................|    -4.056 |  -0.01106 |    0.8270 |   0.07809 |
-#> |.....................|    0.6790 |     3.220 |     1.559 |     1.593 |
-#> |.....................|     2.499 |     1.643 |...........|...........|
-#> |    X|     468.83559 |     100.9 |   0.01713 |    0.2799 |   0.09236 |
-#> |.....................|   0.01733 |    0.4972 |    0.8270 |   0.07809 |
-#> |.....................|    0.6790 |     3.220 |     1.559 |     1.593 |
-#> |.....................|     2.499 |     1.643 |...........|...........|
-#> |    F| Forward Diff. |    -7.676 |    -1.212 |   -0.1115 |   0.08612 |
-#> |.....................|    0.5488 |  0.008589 |    -2.761 |    -2.165 |
-#> |.....................|   -0.2456 |    -1.924 |   -0.8622 |   -0.4413 |
-#> |.....................|   -0.7592 |   -0.4720 |...........|...........|
-#> |   80|     468.82320 |     1.011 |   -0.9670 |   -0.9445 |   -0.9494 |
-#> |.....................|   -0.9559 |   -0.9267 |   -0.6401 |   -0.5885 |
-#> |.....................|   -0.9025 |    0.1478 |   -0.6651 |   -0.5152 |
-#> |.....................|   -0.2008 |   -0.4708 |...........|...........|
-#> |    U|      468.8232 |     101.1 |    -4.067 |   -0.9449 |    -2.382 |
-#> |.....................|    -4.056 |  -0.01106 |    0.8275 |   0.07810 |
-#> |.....................|    0.6795 |     3.223 |     1.559 |     1.593 |
-#> |.....................|     2.499 |     1.644 |...........|...........|
-#> |    X|      468.8232 |     101.1 |   0.01713 |    0.2799 |   0.09236 |
-#> |.....................|   0.01732 |    0.4972 |    0.8275 |   0.07810 |
-#> |.....................|    0.6795 |     3.223 |     1.559 |     1.593 |
-#> |.....................|     2.499 |     1.644 |...........|...........|
-#> |    F| Forward Diff. |     5.440 |   -0.1810 |   0.05193 |  -0.03082 |
-#> |.....................|    0.3483 |  0.007438 |    -3.541 |    -1.923 |
-#> |.....................|   -0.2409 |    -1.947 |    -1.058 |   -0.5469 |
-#> |.....................|   -0.7518 |   -0.4735 |...........|...........|
-#> |   81|     468.81154 |     1.010 |   -0.9671 |   -0.9445 |   -0.9493 |
-#> |.....................|   -0.9562 |   -0.9267 |   -0.6389 |   -0.5880 |
-#> |.....................|   -0.9017 |    0.1505 |   -0.6652 |   -0.5150 |
-#> |.....................|   -0.2005 |   -0.4704 |...........|...........|
-#> |    U|     468.81154 |     101.0 |    -4.067 |   -0.9449 |    -2.382 |
-#> |.....................|    -4.056 |  -0.01106 |    0.8279 |   0.07812 |
-#> |.....................|    0.6800 |     3.228 |     1.559 |     1.593 |
-#> |.....................|     2.500 |     1.644 |...........|...........|
-#> |    X|     468.81154 |     101.0 |   0.01713 |    0.2799 |   0.09237 |
-#> |.....................|   0.01732 |    0.4972 |    0.8279 |   0.07812 |
-#> |.....................|    0.6800 |     3.228 |     1.559 |     1.593 |
-#> |.....................|     2.500 |     1.644 |...........|...........|
-#> |    F| Forward Diff. |    -2.875 |   -0.7736 |  -0.05343 |   0.05244 |
-#> |.....................|    0.3113 |  0.007978 |    -4.161 |    -2.012 |
-#> |.....................|   -0.2433 |    -1.896 |   -0.8853 |   -0.4539 |
-#> |.....................|   -0.7524 |   -0.4694 |...........|...........|
-#> |   82|     468.80001 |     1.011 |   -0.9668 |   -0.9445 |   -0.9493 |
-#> |.....................|   -0.9563 |   -0.9267 |   -0.6364 |   -0.5873 |
-#> |.....................|   -0.9013 |    0.1522 |   -0.6651 |   -0.5147 |
-#> |.....................|   -0.2001 |   -0.4701 |...........|...........|
-#> |    U|     468.80001 |     101.1 |    -4.067 |   -0.9449 |    -2.382 |
-#> |.....................|    -4.056 |  -0.01106 |    0.8288 |   0.07814 |
-#> |.....................|    0.6803 |     3.230 |     1.559 |     1.593 |
-#> |.....................|     2.501 |     1.645 |...........|...........|
-#> |    X|     468.80001 |     101.1 |   0.01713 |    0.2799 |   0.09237 |
-#> |.....................|   0.01731 |    0.4972 |    0.8288 |   0.07814 |
-#> |.....................|    0.6803 |     3.230 |     1.559 |     1.593 |
-#> |.....................|     2.501 |     1.645 |...........|...........|
-#> |    F| Forward Diff. |     6.046 |   0.03721 |   0.05257 |  -0.02595 |
-#> |.....................|    0.1943 |  0.007238 |    -2.985 |    -2.233 |
-#> |.....................|   -0.3122 |    -1.891 |   -0.9609 |   -0.5652 |
-#> |.....................|   -0.8019 |   -0.4712 |...........|...........|
-#> |   83|     468.79133 |     1.009 |   -0.9669 |   -0.9445 |   -0.9492 |
-#> |.....................|   -0.9565 |   -0.9267 |   -0.6348 |   -0.5869 |
-#> |.....................|   -0.9006 |    0.1543 |   -0.6654 |   -0.5144 |
-#> |.....................|   -0.1996 |   -0.4698 |...........|...........|
-#> |    U|     468.79133 |     100.9 |    -4.067 |   -0.9449 |    -2.382 |
-#> |.....................|    -4.056 |  -0.01106 |    0.8294 |   0.07816 |
-#> |.....................|    0.6807 |     3.234 |     1.558 |     1.594 |
-#> |.....................|     2.501 |     1.645 |...........|...........|
-#> |    X|     468.79133 |     100.9 |   0.01713 |    0.2799 |   0.09237 |
-#> |.....................|   0.01731 |    0.4972 |    0.8294 |   0.07816 |
-#> |.....................|    0.6807 |     3.234 |     1.558 |     1.594 |
-#> |.....................|     2.501 |     1.645 |...........|...........|
-#> |    F| Forward Diff. |    -7.226 |   -0.9038 |   -0.1166 |    0.1039 |
-#> |.....................|    0.2475 |  0.008246 |    -3.388 |    -1.948 |
-#> |.....................|   -0.2420 |    -1.872 |   -0.8620 |   -0.4291 |
-#> |.....................|   -0.7186 |   -0.4561 |...........|...........|
-#> |   84|     468.77848 |     1.011 |   -0.9668 |   -0.9446 |   -0.9492 |
-#> |.....................|   -0.9568 |   -0.9267 |   -0.6338 |   -0.5863 |
-#> |.....................|   -0.8997 |    0.1569 |   -0.6658 |   -0.5142 |
-#> |.....................|   -0.1992 |   -0.4695 |...........|...........|
-#> |    U|     468.77848 |     101.1 |    -4.067 |   -0.9450 |    -2.382 |
-#> |.....................|    -4.057 |  -0.01106 |    0.8298 |   0.07818 |
-#> |.....................|    0.6814 |     3.238 |     1.558 |     1.594 |
-#> |.....................|     2.502 |     1.645 |...........|...........|
-#> |    X|     468.77848 |     101.1 |   0.01713 |    0.2799 |   0.09238 |
-#> |.....................|   0.01730 |    0.4972 |    0.8298 |   0.07818 |
-#> |.....................|    0.6814 |     3.238 |     1.558 |     1.594 |
-#> |.....................|     2.502 |     1.645 |...........|...........|
-#> |    F| Forward Diff. |     2.503 |   -0.1762 |  0.005994 |   0.01651 |
-#> |.....................|   0.06327 |  0.007339 |    -4.407 |    -2.185 |
-#> |.....................|   -0.3133 |    -1.836 |   -0.8110 |   -0.4803 |
-#> |.....................|   -0.7946 |   -0.4665 |...........|...........|
-#> |   85|     468.76805 |     1.010 |   -0.9668 |   -0.9446 |   -0.9492 |
-#> |.....................|   -0.9569 |   -0.9267 |   -0.6312 |   -0.5853 |
-#> |.....................|   -0.8993 |    0.1583 |   -0.6657 |   -0.5139 |
-#> |.....................|   -0.1987 |   -0.4691 |...........|...........|
-#> |    U|     468.76805 |     101.0 |    -4.067 |   -0.9450 |    -2.382 |
-#> |.....................|    -4.057 |  -0.01106 |    0.8307 |   0.07821 |
-#> |.....................|    0.6816 |     3.240 |     1.558 |     1.594 |
-#> |.....................|     2.503 |     1.646 |...........|...........|
-#> |    X|     468.76805 |     101.0 |   0.01713 |    0.2799 |   0.09238 |
-#> |.....................|   0.01730 |    0.4972 |    0.8307 |   0.07821 |
-#> |.....................|    0.6816 |     3.240 |     1.558 |     1.594 |
-#> |.....................|     2.503 |     1.646 |...........|...........|
-#> |    F| Forward Diff. |    -5.980 |   -0.7098 |   -0.1045 |    0.1001 |
-#> |.....................|    0.1097 |  0.008007 |    -2.998 |    -1.799 |
-#> |.....................|   -0.2421 |    -1.902 |    -1.021 |   -0.4929 |
-#> |.....................|   -0.7234 |   -0.4545 |...........|...........|
-#> |   86|     468.76178 |     1.012 |   -0.9666 |   -0.9446 |   -0.9492 |
-#> |.....................|   -0.9569 |   -0.9268 |   -0.6296 |   -0.5849 |
-#> |.....................|   -0.8987 |    0.1602 |   -0.6657 |   -0.5136 |
-#> |.....................|   -0.1982 |   -0.4689 |...........|...........|
-#> |    U|     468.76178 |     101.2 |    -4.067 |   -0.9450 |    -2.382 |
-#> |.....................|    -4.057 |  -0.01106 |    0.8313 |   0.07822 |
-#> |.....................|    0.6820 |     3.243 |     1.558 |     1.595 |
-#> |.....................|     2.503 |     1.646 |...........|...........|
-#> |    X|     468.76178 |     101.2 |   0.01714 |    0.2799 |   0.09238 |
-#> |.....................|   0.01730 |    0.4972 |    0.8313 |   0.07822 |
-#> |.....................|    0.6820 |     3.243 |     1.558 |     1.595 |
-#> |.....................|     2.503 |     1.646 |...........|...........|
-#> |    F| Forward Diff. |     9.381 |    0.4945 |   0.08709 |  -0.04347 |
-#> |.....................|  -0.04178 |  0.006758 |    -3.785 |    -1.947 |
-#> |.....................|   -0.3007 |    -1.819 |   -0.8940 |   -0.4901 |
-#> |.....................|   -0.7836 |   -0.4662 |...........|...........|
-#> |   87|     468.74724 |     1.010 |   -0.9668 |   -0.9447 |   -0.9491 |
-#> |.....................|   -0.9570 |   -0.9268 |   -0.6284 |   -0.5849 |
-#> |.....................|   -0.8978 |    0.1628 |   -0.6658 |   -0.5134 |
-#> |.....................|   -0.1979 |   -0.4686 |...........|...........|
-#> |    U|     468.74724 |     101.0 |    -4.067 |   -0.9451 |    -2.382 |
-#> |.....................|    -4.057 |  -0.01106 |    0.8318 |   0.07822 |
-#> |.....................|    0.6827 |     3.247 |     1.558 |     1.595 |
-#> |.....................|     2.504 |     1.646 |...........|...........|
-#> |    X|     468.74724 |     101.0 |   0.01713 |    0.2799 |   0.09239 |
-#> |.....................|   0.01730 |    0.4972 |    0.8318 |   0.07822 |
-#> |.....................|    0.6827 |     3.247 |     1.558 |     1.595 |
-#> |.....................|     2.504 |     1.646 |...........|...........|
-#> |    F| Forward Diff. |    -1.251 |   -0.3146 |  -0.04610 |   0.05724 |
-#> |.....................|   0.02086 |  0.007590 |    -4.230 |    -2.098 |
-#> |.....................|   -0.3136 |    -1.833 |   -0.9365 |   -0.5244 |
-#> |.....................|   -0.7857 |   -0.4618 |...........|...........|
-#> |   88|     468.73570 |     1.011 |   -0.9666 |   -0.9446 |   -0.9492 |
-#> |.....................|   -0.9570 |   -0.9268 |   -0.6257 |   -0.5836 |
-#> |.....................|   -0.8976 |    0.1639 |   -0.6652 |   -0.5131 |
-#> |.....................|   -0.1974 |   -0.4683 |...........|...........|
-#> |    U|      468.7357 |     101.1 |    -4.067 |   -0.9450 |    -2.382 |
-#> |.....................|    -4.057 |  -0.01106 |    0.8327 |   0.07827 |
-#> |.....................|    0.6828 |     3.249 |     1.559 |     1.595 |
-#> |.....................|     2.504 |     1.647 |...........|...........|
-#> |    X|      468.7357 |     101.1 |   0.01714 |    0.2799 |   0.09238 |
-#> |.....................|   0.01730 |    0.4972 |    0.8327 |   0.07827 |
-#> |.....................|    0.6828 |     3.249 |     1.559 |     1.595 |
-#> |.....................|     2.504 |     1.647 |...........|...........|
-#> |    F| Forward Diff. |     4.473 |    0.2106 |   0.02342 |  0.003517 |
-#> |.....................|  -0.03354 |  0.007130 |    -3.431 |    -1.904 |
-#> |.....................|   -0.3114 |    -1.829 |   -0.9161 |   -0.5352 |
-#> |.....................|   -0.7806 |   -0.4641 |...........|...........|
-#> |   89|     468.73562 |     1.009 |   -0.9667 |   -0.9447 |   -0.9491 |
-#> |.....................|   -0.9570 |   -0.9268 |   -0.6239 |   -0.5826 |
-#> |.....................|   -0.8973 |    0.1651 |   -0.6648 |   -0.5128 |
-#> |.....................|   -0.1970 |   -0.4681 |...........|...........|
-#> |    U|     468.73562 |     100.9 |    -4.067 |   -0.9450 |    -2.382 |
-#> |.....................|    -4.057 |  -0.01106 |    0.8334 |   0.07830 |
-#> |.....................|    0.6830 |     3.251 |     1.559 |     1.596 |
-#> |.....................|     2.505 |     1.647 |...........|...........|
-#> |    X|     468.73562 |     100.9 |   0.01713 |    0.2799 |   0.09238 |
-#> |.....................|   0.01730 |    0.4972 |    0.8334 |   0.07830 |
-#> |.....................|    0.6830 |     3.251 |     1.559 |     1.596 |
-#> |.....................|     2.505 |     1.647 |...........|...........|
-#> |    C| Central Diff. |    -12.26 |    -1.176 |   -0.2138 |    0.1217 |
-#> |.....................|  -0.02157 |  0.008077 |    -2.776 |    -1.301 |
-#> |.....................|   -0.1367 |    -1.738 |   -0.7465 |   -0.4531 |
-#> |.....................|   -0.7359 |   -0.4611 |...........|...........|
-#> |   90|     468.72331 |     1.010 |   -0.9665 |   -0.9446 |   -0.9492 |
-#> |.....................|   -0.9570 |   -0.9268 |   -0.6235 |   -0.5825 |
-#> |.....................|   -0.8973 |    0.1654 |   -0.6647 |   -0.5127 |
-#> |.....................|   -0.1969 |   -0.4680 |...........|...........|
-#> |    U|     468.72331 |     101.0 |    -4.067 |   -0.9450 |    -2.382 |
-#> |.....................|    -4.057 |  -0.01106 |    0.8335 |   0.07831 |
-#> |.....................|    0.6830 |     3.251 |     1.559 |     1.596 |
-#> |.....................|     2.505 |     1.647 |...........|...........|
-#> |    X|     468.72331 |     101.0 |   0.01714 |    0.2799 |   0.09238 |
-#> |.....................|   0.01730 |    0.4972 |    0.8335 |   0.07831 |
-#> |.....................|    0.6830 |     3.251 |     1.559 |     1.596 |
-#> |.....................|     2.505 |     1.647 |...........|...........|
-#> |    F| Forward Diff. |   -0.3583 |  -0.08989 |  -0.03828 |   0.04946 |
-#> |.....................|  0.006154 |  0.007526 |    -3.405 |    -1.898 |
-#> |.....................|   -0.3214 |    -1.836 |   -0.8751 |   -0.5118 |
-#> |.....................|   -0.7778 |   -0.4622 |...........|...........|
-#> |   91|     468.71715 |     1.011 |   -0.9665 |   -0.9446 |   -0.9492 |
-#> |.....................|   -0.9570 |   -0.9268 |   -0.6223 |   -0.5817 |
-#> |.....................|   -0.8972 |    0.1661 |   -0.6643 |   -0.5125 |
-#> |.....................|   -0.1966 |   -0.4678 |...........|...........|
-#> |    U|     468.71715 |     101.1 |    -4.067 |   -0.9450 |    -2.382 |
-#> |.....................|    -4.057 |  -0.01106 |    0.8340 |   0.07833 |
-#> |.....................|    0.6831 |     3.252 |     1.560 |     1.596 |
-#> |.....................|     2.506 |     1.647 |...........|...........|
-#> |    X|     468.71715 |     101.1 |   0.01714 |    0.2799 |   0.09238 |
-#> |.....................|   0.01730 |    0.4972 |    0.8340 |   0.07833 |
-#> |.....................|    0.6831 |     3.252 |     1.560 |     1.596 |
-#> |.....................|     2.506 |     1.647 |...........|...........|
-#> |   92|     468.70862 |     1.011 |   -0.9665 |   -0.9446 |   -0.9492 |
-#> |.....................|   -0.9570 |   -0.9268 |   -0.6204 |   -0.5807 |
-#> |.....................|   -0.8970 |    0.1671 |   -0.6639 |   -0.5123 |
-#> |.....................|   -0.1962 |   -0.4676 |...........|...........|
-#> |    U|     468.70862 |     101.1 |    -4.066 |   -0.9450 |    -2.382 |
-#> |.....................|    -4.057 |  -0.01106 |    0.8347 |   0.07836 |
-#> |.....................|    0.6832 |     3.254 |     1.560 |     1.596 |
-#> |.....................|     2.506 |     1.648 |...........|...........|
-#> |    X|     468.70862 |     101.1 |   0.01714 |    0.2799 |   0.09238 |
-#> |.....................|   0.01730 |    0.4972 |    0.8347 |   0.07836 |
-#> |.....................|    0.6832 |     3.254 |     1.560 |     1.596 |
-#> |.....................|     2.506 |     1.648 |...........|...........|
-#> |   93|     468.69301 |     1.011 |   -0.9664 |   -0.9446 |   -0.9493 |
-#> |.....................|   -0.9570 |   -0.9268 |   -0.6166 |   -0.5786 |
-#> |.....................|   -0.8967 |    0.1691 |   -0.6629 |   -0.5117 |
-#> |.....................|   -0.1953 |   -0.4671 |...........|...........|
-#> |    U|     468.69301 |     101.1 |    -4.066 |   -0.9449 |    -2.382 |
-#> |.....................|    -4.057 |  -0.01106 |    0.8361 |   0.07843 |
-#> |.....................|    0.6834 |     3.257 |     1.562 |     1.597 |
-#> |.....................|     2.508 |     1.648 |...........|...........|
-#> |    X|     468.69301 |     101.1 |   0.01714 |    0.2799 |   0.09237 |
-#> |.....................|   0.01730 |    0.4972 |    0.8361 |   0.07843 |
-#> |.....................|    0.6834 |     3.257 |     1.562 |     1.597 |
-#> |.....................|     2.508 |     1.648 |...........|...........|
-#> |    F| Forward Diff. |     5.000 |    0.4463 |   0.03173 | -0.005614 |
-#> |.....................|  -0.04729 |  0.007073 |    -3.041 |    -1.513 |
-#> |.....................|   -0.3269 |    -1.766 |   -0.6347 |   -0.4208 |
-#> |.....................|   -0.7611 |   -0.4631 |...........|...........|
-#> |   94|     468.66018 |     1.011 |   -0.9666 |   -0.9442 |   -0.9484 |
-#> |.....................|   -0.9562 |   -0.9269 |   -0.6101 |   -0.5828 |
-#> |.....................|   -0.8947 |    0.1828 |   -0.6704 |   -0.5138 |
-#> |.....................|   -0.1918 |   -0.4639 |...........|...........|
-#> |    U|     468.66018 |     101.1 |    -4.067 |   -0.9446 |    -2.381 |
-#> |.....................|    -4.056 |  -0.01106 |    0.8385 |   0.07829 |
-#> |.....................|    0.6847 |     3.279 |     1.552 |     1.594 |
-#> |.....................|     2.513 |     1.652 |...........|...........|
-#> |    X|     468.66018 |     101.1 |   0.01714 |    0.2800 |   0.09245 |
-#> |.....................|   0.01731 |    0.4972 |    0.8385 |   0.07829 |
-#> |.....................|    0.6847 |     3.279 |     1.552 |     1.594 |
-#> |.....................|     2.513 |     1.652 |...........|...........|
-#> |   95|     468.61872 |     1.011 |   -0.9669 |   -0.9434 |   -0.9467 |
-#> |.....................|   -0.9547 |   -0.9271 |   -0.5984 |   -0.5914 |
-#> |.....................|   -0.8911 |    0.2086 |   -0.6849 |   -0.5181 |
-#> |.....................|   -0.1852 |   -0.4581 |...........|...........|
-#> |    U|     468.61872 |     101.1 |    -4.067 |   -0.9439 |    -2.379 |
-#> |.....................|    -4.055 |  -0.01106 |    0.8427 |   0.07801 |
-#> |.....................|    0.6872 |     3.320 |     1.534 |     1.589 |
-#> |.....................|     2.523 |     1.658 |...........|...........|
-#> |    X|     468.61872 |     101.1 |   0.01713 |    0.2801 |   0.09261 |
-#> |.....................|   0.01734 |    0.4972 |    0.8427 |   0.07801 |
-#> |.....................|    0.6872 |     3.320 |     1.534 |     1.589 |
-#> |.....................|     2.523 |     1.658 |...........|...........|
-#> |    F| Forward Diff. |     3.484 |    0.5384 |   0.08463 |   0.09865 |
-#> |.....................|    0.7055 |  0.007848 |    -2.909 |    -1.559 |
-#> |.....................|   -0.2162 |    -1.642 |    -1.728 |   -0.7121 |
-#> |.....................|   -0.5947 |   -0.3648 |...........|...........|
-#> |   96|     468.58548 |     1.008 |   -0.9690 |   -0.9515 |   -0.9524 |
-#> |.....................|   -0.9418 |   -0.9281 |   -0.5713 |   -0.6320 |
-#> |.....................|   -0.8823 |    0.2961 |   -0.6589 |   -0.5284 |
-#> |.....................|   -0.1884 |   -0.4503 |...........|...........|
-#> |    U|     468.58548 |     100.8 |    -4.069 |   -0.9515 |    -2.385 |
-#> |.....................|    -4.042 |  -0.01107 |    0.8526 |   0.07665 |
-#> |.....................|    0.6931 |     3.458 |     1.567 |     1.578 |
-#> |.....................|     2.518 |     1.667 |...........|...........|
-#> |    X|     468.58548 |     100.8 |   0.01709 |    0.2786 |   0.09208 |
-#> |.....................|   0.01757 |    0.4972 |    0.8526 |   0.07665 |
-#> |.....................|    0.6931 |     3.458 |     1.567 |     1.578 |
-#> |.....................|     2.518 |     1.667 |...........|...........|
-#> |    F| Forward Diff. |    -20.63 |    -1.258 |   -0.4941 |   -0.2790 |
-#> |.....................|     5.133 |   0.01399 |    -2.360 |    -3.936 |
-#> |.....................|  -0.04374 |    -1.146 |   -0.2901 |    -1.004 |
-#> |.....................|   -0.6864 |   -0.2503 |...........|...........|
-#> |   97|     468.42330 |     1.011 |   -0.9777 |   -0.9596 |   -0.9476 |
-#> |.....................|   -0.9583 |   -0.9295 |   -0.5827 |   -0.6211 |
-#> |.....................|   -0.8760 |    0.3979 |   -0.6632 |   -0.5247 |
-#> |.....................|   -0.1834 |   -0.4404 |...........|...........|
-#> |    U|      468.4233 |     101.1 |    -4.078 |   -0.9591 |    -2.380 |
-#> |.....................|    -4.058 |  -0.01109 |    0.8485 |   0.07701 |
-#> |.....................|    0.6974 |     3.619 |     1.561 |     1.582 |
-#> |.....................|     2.525 |     1.679 |...........|...........|
-#> |    X|      468.4233 |     101.1 |   0.01695 |    0.2771 |   0.09253 |
-#> |.....................|   0.01728 |    0.4972 |    0.8485 |   0.07701 |
-#> |.....................|    0.6974 |     3.619 |     1.561 |     1.582 |
-#> |.....................|     2.525 |     1.679 |...........|...........|
-#> |    F| Forward Diff. |    -2.203 |    -3.445 |   -0.3661 |   -0.1876 |
-#> |.....................|   -0.3413 |  0.004713 |    -2.617 |    -2.520 |
-#> |.....................|   0.09908 |   -0.8887 |   -0.1336 |   -0.9981 |
-#> |.....................|   -0.6593 |   -0.1712 |...........|...........|
-#> |   98|     468.44544 |     1.015 |   -0.9711 |   -0.9083 |   -0.9392 |
-#> |.....................|   -0.9571 |   -0.9308 |   -0.5728 |   -0.6140 |
-#> |.....................|   -0.9111 |    0.4459 |   -0.6774 |   -0.4582 |
-#> |.....................|   -0.1728 |   -0.4486 |...........|...........|
-#> |    U|     468.44544 |     101.5 |    -4.071 |   -0.9109 |    -2.372 |
-#> |.....................|    -4.057 |  -0.01110 |    0.8520 |   0.07725 |
-#> |.....................|    0.6737 |     3.695 |     1.543 |     1.658 |
-#> |.....................|     2.541 |     1.669 |...........|...........|
-#> |    X|     468.44544 |     101.5 |   0.01706 |    0.2868 |   0.09331 |
-#> |.....................|   0.01730 |    0.4972 |    0.8520 |   0.07725 |
-#> |.....................|    0.6737 |     3.695 |     1.543 |     1.658 |
-#> |.....................|     2.541 |     1.669 |...........|...........|
-#> |   99|     468.45245 |     1.016 |   -0.9696 |   -0.9377 |   -0.9438 |
-#> |.....................|   -0.9573 |   -0.9300 |   -0.5745 |   -0.6143 |
-#> |.....................|   -0.8908 |    0.4193 |   -0.6689 |   -0.4955 |
-#> |.....................|   -0.1780 |   -0.4435 |...........|...........|
-#> |    U|     468.45245 |     101.6 |    -4.070 |   -0.9385 |    -2.376 |
-#> |.....................|    -4.057 |  -0.01109 |    0.8514 |   0.07724 |
-#> |.....................|    0.6874 |     3.653 |     1.554 |     1.615 |
-#> |.....................|     2.533 |     1.675 |...........|...........|
-#> |    X|     468.45245 |     101.6 |   0.01708 |    0.2812 |   0.09288 |
-#> |.....................|   0.01730 |    0.4972 |    0.8514 |   0.07724 |
-#> |.....................|    0.6874 |     3.653 |     1.554 |     1.615 |
-#> |.....................|     2.533 |     1.675 |...........|...........|
-#> |  100|     468.50368 |     1.017 |   -0.9688 |   -0.9537 |   -0.9463 |
-#> |.....................|   -0.9573 |   -0.9296 |   -0.5755 |   -0.6144 |
-#> |.....................|   -0.8797 |    0.4047 |   -0.6643 |   -0.5158 |
-#> |.....................|   -0.1808 |   -0.4408 |...........|...........|
-#> |    U|     468.50368 |     101.7 |    -4.069 |   -0.9536 |    -2.379 |
-#> |.....................|    -4.057 |  -0.01109 |    0.8511 |   0.07724 |
-#> |.....................|    0.6949 |     3.630 |     1.560 |     1.592 |
-#> |.....................|     2.529 |     1.678 |...........|...........|
-#> |    X|     468.50368 |     101.7 |   0.01710 |    0.2782 |   0.09265 |
-#> |.....................|   0.01729 |    0.4972 |    0.8511 |   0.07724 |
-#> |.....................|    0.6949 |     3.630 |     1.560 |     1.592 |
-#> |.....................|     2.529 |     1.678 |...........|...........|
-#> |  101|     468.41664 |     1.014 |   -0.9744 |   -0.9593 |   -0.9474 |
-#> |.....................|   -0.9580 |   -0.9295 |   -0.5802 |   -0.6187 |
-#> |.....................|   -0.8761 |    0.3987 |   -0.6631 |   -0.5237 |
-#> |.....................|   -0.1828 |   -0.4402 |...........|...........|
-#> |    U|     468.41664 |     101.4 |    -4.074 |   -0.9588 |    -2.380 |
-#> |.....................|    -4.058 |  -0.01109 |    0.8494 |   0.07709 |
-#> |.....................|    0.6973 |     3.620 |     1.561 |     1.583 |
-#> |.....................|     2.526 |     1.679 |...........|...........|
-#> |    X|     468.41664 |     101.4 |   0.01700 |    0.2771 |   0.09254 |
-#> |.....................|   0.01728 |    0.4972 |    0.8494 |   0.07709 |
-#> |.....................|    0.6973 |     3.620 |     1.561 |     1.583 |
-#> |.....................|     2.526 |     1.679 |...........|...........|
-#> |    F| Forward Diff. |     15.72 |  -0.02243 |   -0.2559 |   -0.2642 |
-#> |.....................|   -0.4515 |  0.003975 |    -3.178 |    -2.839 |
-#> |.....................|  -0.02889 |   -0.8526 |   -0.3239 |    -1.069 |
-#> |.....................|   -0.6251 |   -0.1666 |...........|...........|
-#> |  102|     468.39161 |     1.011 |   -0.9744 |   -0.9571 |   -0.9468 |
-#> |.....................|   -0.9580 |   -0.9295 |   -0.5795 |   -0.6181 |
-#> |.....................|   -0.8777 |    0.4014 |   -0.6637 |   -0.5208 |
-#> |.....................|   -0.1824 |   -0.4404 |...........|...........|
-#> |    U|     468.39161 |     101.1 |    -4.074 |   -0.9567 |    -2.380 |
-#> |.....................|    -4.058 |  -0.01109 |    0.8496 |   0.07711 |
-#> |.....................|    0.6962 |     3.624 |     1.561 |     1.586 |
-#> |.....................|     2.527 |     1.679 |...........|...........|
-#> |    X|     468.39161 |     101.1 |   0.01700 |    0.2775 |   0.09260 |
-#> |.....................|   0.01728 |    0.4972 |    0.8496 |   0.07711 |
-#> |.....................|    0.6962 |     3.624 |     1.561 |     1.586 |
-#> |.....................|     2.527 |     1.679 |...........|...........|
-#> |    F| Forward Diff. |   -0.3129 |    -1.347 |   -0.3359 |  -0.08922 |
-#> |.....................|   -0.3284 |  0.005471 |    -2.643 |    -3.028 |
-#> |.....................|  -0.08821 |   -0.8778 |   -0.3083 |   -0.9349 |
-#> |.....................|   -0.6501 |   -0.1781 |...........|...........|
-#> |  103|     468.37315 |     1.012 |   -0.9728 |   -0.9567 |   -0.9467 |
-#> |.....................|   -0.9576 |   -0.9295 |   -0.5763 |   -0.6144 |
-#> |.....................|   -0.8776 |    0.4024 |   -0.6633 |   -0.5197 |
-#> |.....................|   -0.1816 |   -0.4402 |...........|...........|
-#> |    U|     468.37315 |     101.2 |    -4.073 |   -0.9564 |    -2.379 |
-#> |.....................|    -4.058 |  -0.01109 |    0.8508 |   0.07724 |
-#> |.....................|    0.6963 |     3.626 |     1.561 |     1.588 |
-#> |.....................|     2.528 |     1.679 |...........|...........|
-#> |    X|     468.37315 |     101.2 |   0.01703 |    0.2776 |   0.09261 |
-#> |.....................|   0.01729 |    0.4972 |    0.8508 |   0.07724 |
-#> |.....................|    0.6963 |     3.626 |     1.561 |     1.588 |
-#> |.....................|     2.528 |     1.679 |...........|...........|
-#> |    F| Forward Diff. |     3.643 |  -0.05906 |   -0.3284 |  -0.08464 |
-#> |.....................|   -0.2659 |  0.005628 |    -2.441 |    -2.741 |
-#> |.....................|   -0.1033 |   -0.8597 |   -0.2783 |   -0.9091 |
-#> |.....................|   -0.6423 |   -0.1835 |...........|...........|
-#> |  104|     468.35774 |     1.011 |   -0.9727 |   -0.9524 |   -0.9471 |
-#> |.....................|   -0.9577 |   -0.9297 |   -0.5762 |   -0.6128 |
-#> |.....................|   -0.8791 |    0.4096 |   -0.6644 |   -0.5136 |
-#> |.....................|   -0.1797 |   -0.4410 |...........|...........|
-#> |    U|     468.35774 |     101.1 |    -4.073 |   -0.9523 |    -2.380 |
-#> |.....................|    -4.058 |  -0.01109 |    0.8508 |   0.07729 |
-#> |.....................|    0.6953 |     3.637 |     1.560 |     1.595 |
-#> |.....................|     2.531 |     1.678 |...........|...........|
-#> |    X|     468.35774 |     101.1 |   0.01703 |    0.2784 |   0.09257 |
-#> |.....................|   0.01729 |    0.4972 |    0.8508 |   0.07729 |
-#> |.....................|    0.6953 |     3.637 |     1.560 |     1.595 |
-#> |.....................|     2.531 |     1.678 |...........|...........|
-#> |    F| Forward Diff. |    -4.235 |   -0.7549 |   -0.2072 |  -0.03117 |
-#> |.....................|   -0.2512 |  0.006470 |    -2.488 |    -2.805 |
-#> |.....................|   -0.1485 |   -0.7903 |   -0.1532 |   -0.6368 |
-#> |.....................|   -0.5813 |   -0.1871 |...........|...........|
-#> |  105|     468.34230 |     1.012 |   -0.9728 |   -0.9537 |   -0.9473 |
-#> |.....................|   -0.9580 |   -0.9300 |   -0.5748 |   -0.6111 |
-#> |.....................|   -0.8817 |    0.4177 |   -0.6661 |   -0.5086 |
-#> |.....................|   -0.1765 |   -0.4413 |...........|...........|
-#> |    U|      468.3423 |     101.2 |    -4.073 |   -0.9535 |    -2.380 |
-#> |.....................|    -4.058 |  -0.01109 |    0.8513 |   0.07735 |
-#> |.....................|    0.6935 |     3.650 |     1.558 |     1.600 |
-#> |.....................|     2.535 |     1.678 |...........|...........|
-#> |    X|      468.3423 |     101.2 |   0.01703 |    0.2782 |   0.09256 |
-#> |.....................|   0.01728 |    0.4972 |    0.8513 |   0.07735 |
-#> |.....................|    0.6935 |     3.650 |     1.558 |     1.600 |
-#> |.....................|     2.535 |     1.678 |...........|...........|
-#> |    F| Forward Diff. |     5.528 |    0.1613 |   -0.1518 |   -0.1427 |
-#> |.....................|   -0.4211 |  0.005662 |    -2.339 |    -2.549 |
-#> |.....................|   -0.1833 |   -0.8387 |   -0.3838 |   -0.5791 |
-#> |.....................|   -0.5586 |   -0.2081 |...........|...........|
-#> |  106|     468.32828 |     1.011 |   -0.9730 |   -0.9582 |   -0.9446 |
-#> |.....................|   -0.9579 |   -0.9303 |   -0.5739 |   -0.6081 |
-#> |.....................|   -0.8827 |    0.4247 |   -0.6653 |   -0.5110 |
-#> |.....................|   -0.1721 |   -0.4394 |...........|...........|
-#> |    U|     468.32828 |     101.1 |    -4.073 |   -0.9578 |    -2.377 |
-#> |.....................|    -4.058 |  -0.01110 |    0.8517 |   0.07745 |
-#> |.....................|    0.6929 |     3.661 |     1.559 |     1.598 |
-#> |.....................|     2.542 |     1.680 |...........|...........|
-#> |    X|     468.32828 |     101.1 |   0.01703 |    0.2773 |   0.09281 |
-#> |.....................|   0.01729 |    0.4972 |    0.8517 |   0.07745 |
-#> |.....................|    0.6929 |     3.661 |     1.559 |     1.598 |
-#> |.....................|     2.542 |     1.680 |...........|...........|
-#> |    F| Forward Diff. |    -1.625 |   -0.2716 |   -0.4478 |   0.07059 |
-#> |.....................|   -0.3746 |  0.006164 |    -2.097 |    -1.611 |
-#> |.....................|  -0.05708 |   -0.8042 |   -0.2658 |   -0.6338 |
-#> |.....................|   -0.5023 |   -0.1867 |...........|...........|
-#> |  107|     468.31633 |     1.012 |   -0.9727 |   -0.9524 |   -0.9447 |
-#> |.....................|   -0.9580 |   -0.9305 |   -0.5707 |   -0.6067 |
-#> |.....................|   -0.8839 |    0.4327 |   -0.6650 |   -0.5105 |
-#> |.....................|   -0.1703 |   -0.4382 |...........|...........|
-#> |    U|     468.31633 |     101.2 |    -4.073 |   -0.9523 |    -2.377 |
-#> |.....................|    -4.058 |  -0.01110 |    0.8528 |   0.07749 |
-#> |.....................|    0.6921 |     3.674 |     1.559 |     1.598 |
-#> |.....................|     2.545 |     1.681 |...........|...........|
-#> |    X|     468.31633 |     101.2 |   0.01703 |    0.2784 |   0.09280 |
-#> |.....................|   0.01728 |    0.4972 |    0.8528 |   0.07749 |
-#> |.....................|    0.6921 |     3.674 |     1.559 |     1.598 |
-#> |.....................|     2.545 |     1.681 |...........|...........|
-#> |    F| Forward Diff. |     8.853 |    0.6395 |  -0.04718 |  -0.01095 |
-#> |.....................|   -0.5142 |  0.005281 |    -1.984 |    -1.469 |
-#> |.....................|  -0.06825 |   -0.7616 |   -0.1275 |   -0.5767 |
-#> |.....................|   -0.4529 |   -0.1729 |...........|...........|
-#> |  108|     468.30195 |     1.011 |   -0.9730 |   -0.9497 |   -0.9482 |
-#> |.....................|   -0.9586 |   -0.9308 |   -0.5675 |   -0.6075 |
-#> |.....................|   -0.8868 |    0.4402 |   -0.6670 |   -0.5066 |
-#> |.....................|   -0.1704 |   -0.4381 |...........|...........|
-#> |    U|     468.30195 |     101.1 |    -4.073 |   -0.9498 |    -2.381 |
-#> |.....................|    -4.059 |  -0.01110 |    0.8540 |   0.07747 |
-#> |.....................|    0.6901 |     3.686 |     1.556 |     1.603 |
-#> |.....................|     2.544 |     1.681 |...........|...........|
-#> |    X|     468.30195 |     101.1 |   0.01703 |    0.2789 |   0.09247 |
-#> |.....................|   0.01727 |    0.4972 |    0.8540 |   0.07747 |
-#> |.....................|    0.6901 |     3.686 |     1.556 |     1.603 |
-#> |.....................|     2.544 |     1.681 |...........|...........|
-#> |    F| Forward Diff. |    -1.407 |   -0.4624 |  -0.02880 |   -0.1214 |
-#> |.....................|   -0.5499 |  0.005628 |    -1.325 |    -1.518 |
-#> |.....................|   -0.1161 |   -0.7707 |   -0.3300 |   -0.4912 |
-#> |.....................|   -0.4772 |   -0.1931 |...........|...........|
-#> |  109|     468.29210 |     1.012 |   -0.9733 |   -0.9523 |   -0.9459 |
-#> |.....................|   -0.9581 |   -0.9311 |   -0.5658 |   -0.6073 |
-#> |.....................|   -0.8878 |    0.4488 |   -0.6682 |   -0.5015 |
-#> |.....................|   -0.1697 |   -0.4385 |...........|...........|
-#> |    U|      468.2921 |     101.2 |    -4.073 |   -0.9523 |    -2.379 |
-#> |.....................|    -4.058 |  -0.01111 |    0.8546 |   0.07747 |
-#> |.....................|    0.6894 |     3.699 |     1.555 |     1.608 |
-#> |.....................|     2.546 |     1.681 |...........|...........|
-#> |    X|      468.2921 |     101.2 |   0.01702 |    0.2784 |   0.09269 |
-#> |.....................|   0.01728 |    0.4972 |    0.8546 |   0.07747 |
-#> |.....................|    0.6894 |     3.699 |     1.555 |     1.608 |
-#> |.....................|     2.546 |     1.681 |...........|...........|
-#> |  110|     468.28540 |     1.012 |   -0.9739 |   -0.9554 |   -0.9432 |
-#> |.....................|   -0.9581 |   -0.9314 |   -0.5648 |   -0.6081 |
-#> |.....................|   -0.8889 |    0.4579 |   -0.6697 |   -0.4962 |
-#> |.....................|   -0.1692 |   -0.4390 |...........|...........|
-#> |    U|      468.2854 |     101.2 |    -4.074 |   -0.9551 |    -2.376 |
-#> |.....................|    -4.058 |  -0.01111 |    0.8550 |   0.07745 |
-#> |.....................|    0.6886 |     3.714 |     1.553 |     1.615 |
-#> |.....................|     2.546 |     1.680 |...........|...........|
-#> |    X|      468.2854 |     101.2 |   0.01701 |    0.2779 |   0.09293 |
-#> |.....................|   0.01728 |    0.4972 |    0.8550 |   0.07745 |
-#> |.....................|    0.6886 |     3.714 |     1.553 |     1.615 |
-#> |.....................|     2.546 |     1.680 |...........|...........|
-#> |    F| Forward Diff. |     3.644 |   0.03668 |   -0.1986 |   0.05251 |
-#> |.....................|   -0.5265 |  0.006364 |    -2.013 |    -2.999 |
-#> |.....................|   -0.3077 |   -0.7577 |   -0.4283 |   -0.2217 |
-#> |.....................|   -0.4457 |   -0.1968 |...........|...........|
-#> |  111|     468.26285 |     1.012 |   -0.9738 |   -0.9546 |   -0.9455 |
-#> |.....................|   -0.9580 |   -0.9321 |   -0.5638 |   -0.6053 |
-#> |.....................|   -0.8894 |    0.4796 |   -0.6701 |   -0.4937 |
-#> |.....................|   -0.1665 |   -0.4375 |...........|...........|
-#> |    U|     468.26285 |     101.2 |    -4.074 |   -0.9544 |    -2.378 |
-#> |.....................|    -4.058 |  -0.01112 |    0.8554 |   0.07754 |
-#> |.....................|    0.6883 |     3.748 |     1.552 |     1.617 |
-#> |.....................|     2.550 |     1.682 |...........|...........|
-#> |    X|     468.26285 |     101.2 |   0.01701 |    0.2780 |   0.09272 |
-#> |.....................|   0.01728 |    0.4972 |    0.8554 |   0.07754 |
-#> |.....................|    0.6883 |     3.748 |     1.552 |     1.617 |
-#> |.....................|     2.550 |     1.682 |...........|...........|
-#> |  112|     468.24808 |     1.012 |   -0.9737 |   -0.9538 |   -0.9478 |
-#> |.....................|   -0.9581 |   -0.9328 |   -0.5632 |   -0.6032 |
-#> |.....................|   -0.8900 |    0.5018 |   -0.6707 |   -0.4913 |
-#> |.....................|   -0.1639 |   -0.4361 |...........|...........|
-#> |    U|     468.24808 |     101.2 |    -4.074 |   -0.9537 |    -2.380 |
-#> |.....................|    -4.058 |  -0.01113 |    0.8556 |   0.07761 |
-#> |.....................|    0.6879 |     3.783 |     1.552 |     1.620 |
-#> |.....................|     2.554 |     1.684 |...........|...........|
-#> |    X|     468.24808 |     101.2 |   0.01701 |    0.2781 |   0.09251 |
-#> |.....................|   0.01728 |    0.4972 |    0.8556 |   0.07761 |
-#> |.....................|    0.6879 |     3.783 |     1.552 |     1.620 |
-#> |.....................|     2.554 |     1.684 |...........|...........|
-#> |    F| Forward Diff. |     7.572 |    0.7442 |   -0.1004 |   -0.2485 |
-#> |.....................|   -0.5511 |  0.005645 |    -1.896 |    -1.976 |
-#> |.....................|   -0.3421 |   -0.6164 |   -0.3384 |   -0.1002 |
-#> |.....................|   -0.3637 |   -0.1858 |...........|...........|
-#> |  113|     468.24925 |     1.009 |   -0.9744 |   -0.9459 |   -0.9275 |
-#> |.....................|   -0.9570 |   -0.9342 |   -0.5606 |   -0.6003 |
-#> |.....................|   -0.8814 |    0.5390 |   -0.6664 |   -0.4916 |
-#> |.....................|   -0.1575 |   -0.4319 |...........|...........|
-#> |    U|     468.24925 |     100.9 |    -4.074 |   -0.9463 |    -2.360 |
-#> |.....................|    -4.057 |  -0.01114 |    0.8565 |   0.07771 |
-#> |.....................|    0.6937 |     3.842 |     1.557 |     1.620 |
-#> |.....................|     2.563 |     1.689 |...........|...........|
-#> |    X|     468.24925 |     100.9 |   0.01700 |    0.2796 |   0.09441 |
-#> |.....................|   0.01730 |    0.4972 |    0.8565 |   0.07771 |
-#> |.....................|    0.6937 |     3.842 |     1.557 |     1.620 |
-#> |.....................|     2.563 |     1.689 |...........|...........|
-#> |  114|     468.25666 |     1.009 |   -0.9742 |   -0.9500 |   -0.9379 |
-#> |.....................|   -0.9574 |   -0.9335 |   -0.5615 |   -0.6013 |
-#> |.....................|   -0.8858 |    0.5198 |   -0.6685 |   -0.4914 |
-#> |.....................|   -0.1608 |   -0.4340 |...........|...........|
-#> |    U|     468.25666 |     100.9 |    -4.074 |   -0.9501 |    -2.371 |
-#> |.....................|    -4.057 |  -0.01113 |    0.8562 |   0.07768 |
-#> |.....................|    0.6908 |     3.812 |     1.554 |     1.620 |
-#> |.....................|     2.559 |     1.686 |...........|...........|
-#> |    X|     468.25666 |     100.9 |   0.01701 |    0.2789 |   0.09342 |
-#> |.....................|   0.01729 |    0.4972 |    0.8562 |   0.07768 |
-#> |.....................|    0.6908 |     3.812 |     1.554 |     1.620 |
-#> |.....................|     2.559 |     1.686 |...........|...........|
-#> |  115|     468.26483 |     1.009 |   -0.9741 |   -0.9524 |   -0.9439 |
-#> |.....................|   -0.9577 |   -0.9331 |   -0.5620 |   -0.6018 |
-#> |.....................|   -0.8883 |    0.5089 |   -0.6697 |   -0.4913 |
-#> |.....................|   -0.1626 |   -0.4352 |...........|...........|
-#> |    U|     468.26483 |     100.9 |    -4.074 |   -0.9523 |    -2.377 |
-#> |.....................|    -4.058 |  -0.01113 |    0.8560 |   0.07766 |
-#> |.....................|    0.6891 |     3.794 |     1.553 |     1.620 |
-#> |.....................|     2.556 |     1.685 |...........|...........|
-#> |    X|     468.26483 |     100.9 |   0.01701 |    0.2784 |   0.09287 |
-#> |.....................|   0.01729 |    0.4972 |    0.8560 |   0.07766 |
-#> |.....................|    0.6891 |     3.794 |     1.553 |     1.620 |
-#> |.....................|     2.556 |     1.685 |...........|...........|
-#> |  116|     468.25961 |     1.009 |   -0.9740 |   -0.9538 |   -0.9477 |
-#> |.....................|   -0.9579 |   -0.9328 |   -0.5624 |   -0.6023 |
-#> |.....................|   -0.8898 |    0.5020 |   -0.6705 |   -0.4913 |
-#> |.....................|   -0.1637 |   -0.4360 |...........|...........|
-#> |    U|     468.25961 |     100.9 |    -4.074 |   -0.9536 |    -2.380 |
-#> |.....................|    -4.058 |  -0.01113 |    0.8558 |   0.07764 |
-#> |.....................|    0.6880 |     3.783 |     1.552 |     1.620 |
-#> |.....................|     2.554 |     1.684 |...........|...........|
-#> |    X|     468.25961 |     100.9 |   0.01701 |    0.2782 |   0.09252 |
-#> |.....................|   0.01729 |    0.4972 |    0.8558 |   0.07764 |
-#> |.....................|    0.6880 |     3.783 |     1.552 |     1.620 |
-#> |.....................|     2.554 |     1.684 |...........|...........|
-#> |  117|     468.24351 |     1.011 |   -0.9738 |   -0.9538 |   -0.9477 |
-#> |.....................|   -0.9580 |   -0.9328 |   -0.5629 |   -0.6029 |
-#> |.....................|   -0.8899 |    0.5019 |   -0.6706 |   -0.4913 |
-#> |.....................|   -0.1638 |   -0.4360 |...........|...........|
-#> |    U|     468.24351 |     101.1 |    -4.074 |   -0.9537 |    -2.380 |
-#> |.....................|    -4.058 |  -0.01113 |    0.8557 |   0.07762 |
-#> |.....................|    0.6880 |     3.783 |     1.552 |     1.620 |
-#> |.....................|     2.554 |     1.684 |...........|...........|
-#> |    X|     468.24351 |     101.1 |   0.01701 |    0.2781 |   0.09252 |
-#> |.....................|   0.01728 |    0.4972 |    0.8557 |   0.07762 |
-#> |.....................|    0.6880 |     3.783 |     1.552 |     1.620 |
-#> |.....................|     2.554 |     1.684 |...........|...........|
-#> |    F| Forward Diff. |   -0.7570 |  -0.04882 |   -0.1901 |   -0.1704 |
-#> |.....................|   -0.4436 |  0.006358 |    -1.944 |    -2.069 |
-#> |.....................|   -0.3547 |   -0.6277 |   -0.2411 |  -0.07768 |
-#> |.....................|   -0.3909 |   -0.1932 |...........|...........|
-#> |  118|     468.24096 |     1.012 |   -0.9738 |   -0.9538 |   -0.9477 |
-#> |.....................|   -0.9579 |   -0.9328 |   -0.5622 |   -0.6021 |
-#> |.....................|   -0.8898 |    0.5021 |   -0.6705 |   -0.4913 |
-#> |.....................|   -0.1637 |   -0.4360 |...........|...........|
-#> |    U|     468.24096 |     101.2 |    -4.074 |   -0.9536 |    -2.380 |
-#> |.....................|    -4.058 |  -0.01113 |    0.8559 |   0.07765 |
-#> |.....................|    0.6881 |     3.784 |     1.552 |     1.620 |
-#> |.....................|     2.554 |     1.684 |...........|...........|
-#> |    X|     468.24096 |     101.2 |   0.01701 |    0.2782 |   0.09252 |
-#> |.....................|   0.01729 |    0.4972 |    0.8559 |   0.07765 |
-#> |.....................|    0.6881 |     3.784 |     1.552 |     1.620 |
-#> |.....................|     2.554 |     1.684 |...........|...........|
-#> |    F| Forward Diff. |     1.456 |    0.1549 |   -0.1619 |   -0.1892 |
-#> |.....................|   -0.4078 |  0.006267 |    -1.860 |    -2.735 |
-#> |.....................|   -0.3543 |   -0.6265 |   -0.1851 |  -0.08656 |
-#> |.....................|   -0.3612 |   -0.1856 |...........|...........|
-#> |  119|     468.23716 |     1.012 |   -0.9738 |   -0.9536 |   -0.9467 |
-#> |.....................|   -0.9576 |   -0.9329 |   -0.5614 |   -0.6008 |
-#> |.....................|   -0.8898 |    0.5037 |   -0.6704 |   -0.4911 |
-#> |.....................|   -0.1638 |   -0.4357 |...........|...........|
-#> |    U|     468.23716 |     101.2 |    -4.074 |   -0.9534 |    -2.379 |
-#> |.....................|    -4.058 |  -0.01113 |    0.8562 |   0.07769 |
-#> |.....................|    0.6881 |     3.786 |     1.552 |     1.620 |
-#> |.....................|     2.554 |     1.684 |...........|...........|
-#> |    X|     468.23716 |     101.2 |   0.01701 |    0.2782 |   0.09261 |
-#> |.....................|   0.01729 |    0.4972 |    0.8562 |   0.07769 |
-#> |.....................|    0.6881 |     3.786 |     1.552 |     1.620 |
-#> |.....................|     2.554 |     1.684 |...........|...........|
-#> |    F| Forward Diff. |     2.250 |    0.2329 |   -0.1405 |   -0.1467 |
-#> |.....................|   -0.3393 |  0.006453 |    -1.023 |    -1.889 |
-#> |.....................|   -0.3583 |   -0.6239 |   -0.2353 |  -0.09107 |
-#> |.....................|   -0.3636 |   -0.1837 |...........|...........|
-#> |  120|     468.26529 |     1.008 |   -0.9742 |   -0.9534 |   -0.9465 |
-#> |.....................|   -0.9571 |   -0.9329 |   -0.5599 |   -0.5980 |
-#> |.....................|   -0.8893 |    0.5046 |   -0.6700 |   -0.4910 |
-#> |.....................|   -0.1633 |   -0.4354 |...........|...........|
-#> |    U|     468.26529 |     100.8 |    -4.074 |   -0.9532 |    -2.379 |
-#> |.....................|    -4.057 |  -0.01113 |    0.8568 |   0.07778 |
-#> |.....................|    0.6884 |     3.788 |     1.553 |     1.621 |
-#> |.....................|     2.555 |     1.685 |...........|...........|
-#> |    X|     468.26529 |     100.8 |   0.01701 |    0.2782 |   0.09263 |
-#> |.....................|   0.01730 |    0.4972 |    0.8568 |   0.07778 |
-#> |.....................|    0.6884 |     3.788 |     1.553 |     1.621 |
-#> |.....................|     2.555 |     1.685 |...........|...........|
-#> |  121|     468.23604 |     1.011 |   -0.9739 |   -0.9535 |   -0.9467 |
-#> |.....................|   -0.9575 |   -0.9329 |   -0.5612 |   -0.6003 |
-#> |.....................|   -0.8897 |    0.5039 |   -0.6703 |   -0.4911 |
-#> |.....................|   -0.1637 |   -0.4357 |...........|...........|
-#> |    U|     468.23604 |     101.1 |    -4.074 |   -0.9534 |    -2.379 |
-#> |.....................|    -4.058 |  -0.01113 |    0.8563 |   0.07771 |
-#> |.....................|    0.6881 |     3.786 |     1.552 |     1.620 |
-#> |.....................|     2.554 |     1.684 |...........|...........|
-#> |    X|     468.23604 |     101.1 |   0.01701 |    0.2782 |   0.09261 |
-#> |.....................|   0.01729 |    0.4972 |    0.8563 |   0.07771 |
-#> |.....................|    0.6881 |     3.786 |     1.552 |     1.620 |
-#> |.....................|     2.554 |     1.684 |...........|...........|
-#> |    F| Forward Diff. |    -2.188 |   -0.1927 |   -0.1868 |   -0.1045 |
-#> |.....................|   -0.2665 |  0.006857 |    -1.024 |    -1.172 |
-#> |.....................|   -0.2153 |   -0.6125 |   -0.1502 |  -0.07921 |
-#> |.....................|   -0.3902 |   -0.1918 |...........|...........|
-#> |  122|     468.23464 |     1.012 |   -0.9738 |   -0.9534 |   -0.9465 |
-#> |.....................|   -0.9574 |   -0.9329 |   -0.5609 |   -0.6000 |
-#> |.....................|   -0.8895 |    0.5043 |   -0.6702 |   -0.4911 |
-#> |.....................|   -0.1635 |   -0.4356 |...........|...........|
-#> |    U|     468.23464 |     101.2 |    -4.074 |   -0.9533 |    -2.379 |
-#> |.....................|    -4.057 |  -0.01113 |    0.8564 |   0.07772 |
-#> |.....................|    0.6883 |     3.787 |     1.552 |     1.620 |
-#> |.....................|     2.555 |     1.684 |...........|...........|
-#> |    X|     468.23464 |     101.2 |   0.01701 |    0.2782 |   0.09263 |
-#> |.....................|   0.01729 |    0.4972 |    0.8564 |   0.07772 |
-#> |.....................|    0.6883 |     3.787 |     1.552 |     1.620 |
-#> |.....................|     2.555 |     1.684 |...........|...........|
-#> |    F| Forward Diff. |     1.857 |    0.1925 |   -0.1360 |   -0.1332 |
-#> |.....................|   -0.2859 |  0.006578 |   -0.9819 |    -1.076 |
-#> |.....................|   -0.2136 |   -0.6087 |   -0.2154 |  -0.09459 |
-#> |.....................|   -0.3609 |   -0.1836 |...........|...........|
-#> |  123|     468.23346 |     1.011 |   -0.9739 |   -0.9532 |   -0.9463 |
-#> |.....................|   -0.9574 |   -0.9329 |   -0.5607 |   -0.5998 |
-#> |.....................|   -0.8893 |    0.5049 |   -0.6701 |   -0.4911 |
-#> |.....................|   -0.1633 |   -0.4355 |...........|...........|
-#> |    U|     468.23346 |     101.1 |    -4.074 |   -0.9531 |    -2.379 |
-#> |.....................|    -4.057 |  -0.01113 |    0.8565 |   0.07772 |
-#> |.....................|    0.6884 |     3.788 |     1.552 |     1.621 |
-#> |.....................|     2.555 |     1.684 |...........|...........|
-#> |    X|     468.23346 |     101.1 |   0.01701 |    0.2783 |   0.09265 |
-#> |.....................|   0.01729 |    0.4972 |    0.8565 |   0.07772 |
-#> |.....................|    0.6884 |     3.788 |     1.552 |     1.621 |
-#> |.....................|     2.555 |     1.684 |...........|...........|
-#> |    F| Forward Diff. |    -1.112 |  -0.08635 |   -0.1600 |  -0.09176 |
-#> |.....................|   -0.2402 |  0.006873 |   -0.9941 |    -1.084 |
-#> |.....................|   -0.2133 |   -0.6080 |   -0.2006 |  -0.08423 |
-#> |.....................|   -0.3853 |   -0.1906 |...........|...........|
-#> |  124|     468.23209 |     1.012 |   -0.9738 |   -0.9531 |   -0.9461 |
-#> |.....................|   -0.9573 |   -0.9329 |   -0.5604 |   -0.5995 |
-#> |.....................|   -0.8891 |    0.5054 |   -0.6700 |   -0.4910 |
-#> |.....................|   -0.1631 |   -0.4354 |...........|...........|
-#> |    U|     468.23209 |     101.2 |    -4.074 |   -0.9530 |    -2.379 |
-#> |.....................|    -4.057 |  -0.01113 |    0.8566 |   0.07774 |
-#> |.....................|    0.6885 |     3.789 |     1.553 |     1.621 |
-#> |.....................|     2.555 |     1.685 |...........|...........|
-#> |    X|     468.23209 |     101.2 |   0.01701 |    0.2783 |   0.09266 |
-#> |.....................|   0.01730 |    0.4972 |    0.8566 |   0.07774 |
-#> |.....................|    0.6885 |     3.789 |     1.553 |     1.621 |
-#> |.....................|     2.555 |     1.685 |...........|...........|
-#> |  125|     468.23061 |     1.012 |   -0.9738 |   -0.9526 |   -0.9453 |
-#> |.....................|   -0.9573 |   -0.9330 |   -0.5604 |   -0.5995 |
-#> |.....................|   -0.8885 |    0.5071 |   -0.6698 |   -0.4911 |
-#> |.....................|   -0.1626 |   -0.4353 |...........|...........|
-#> |    U|     468.23061 |     101.2 |    -4.074 |   -0.9525 |    -2.378 |
-#> |.....................|    -4.057 |  -0.01113 |    0.8566 |   0.07773 |
-#> |.....................|    0.6889 |     3.791 |     1.553 |     1.620 |
-#> |.....................|     2.556 |     1.685 |...........|...........|
-#> |    X|     468.23061 |     101.2 |   0.01701 |    0.2784 |   0.09274 |
-#> |.....................|   0.01730 |    0.4972 |    0.8566 |   0.07773 |
-#> |.....................|    0.6889 |     3.791 |     1.553 |     1.620 |
-#> |.....................|     2.556 |     1.685 |...........|...........|
-#> |  126|     468.22552 |     1.012 |   -0.9738 |   -0.9506 |   -0.9419 |
-#> |.....................|   -0.9573 |   -0.9333 |   -0.5606 |   -0.5998 |
-#> |.....................|   -0.8861 |    0.5138 |   -0.6689 |   -0.4912 |
-#> |.....................|   -0.1606 |   -0.4347 |...........|...........|
-#> |    U|     468.22552 |     101.2 |    -4.074 |   -0.9506 |    -2.375 |
-#> |.....................|    -4.057 |  -0.01113 |    0.8565 |   0.07773 |
-#> |.....................|    0.6906 |     3.802 |     1.554 |     1.620 |
-#> |.....................|     2.559 |     1.685 |...........|...........|
-#> |    X|     468.22552 |     101.2 |   0.01701 |    0.2788 |   0.09305 |
-#> |.....................|   0.01730 |    0.4972 |    0.8565 |   0.07773 |
-#> |.....................|    0.6906 |     3.802 |     1.554 |     1.620 |
-#> |.....................|     2.559 |     1.685 |...........|...........|
-#> |  127|     468.21689 |     1.012 |   -0.9737 |   -0.9426 |   -0.9286 |
-#> |.....................|   -0.9574 |   -0.9344 |   -0.5614 |   -0.6009 |
-#> |.....................|   -0.8763 |    0.5405 |   -0.6653 |   -0.4919 |
-#> |.....................|   -0.1525 |   -0.4325 |...........|...........|
-#> |    U|     468.21689 |     101.2 |    -4.074 |   -0.9431 |    -2.361 |
-#> |.....................|    -4.057 |  -0.01114 |    0.8562 |   0.07769 |
-#> |.....................|    0.6972 |     3.844 |     1.558 |     1.620 |
-#> |.....................|     2.571 |     1.688 |...........|...........|
-#> |    X|     468.21689 |     101.2 |   0.01701 |    0.2803 |   0.09430 |
-#> |.....................|   0.01729 |    0.4972 |    0.8562 |   0.07769 |
-#> |.....................|    0.6972 |     3.844 |     1.558 |     1.620 |
-#> |.....................|     2.571 |     1.688 |...........|...........|
-#> |    F| Forward Diff. |     1.525 |    0.5842 |    0.4183 |    0.9468 |
-#> |.....................|   -0.5439 |  0.008618 |    -1.874 |    -1.936 |
-#> |.....................|   -0.2463 |   -0.5498 |   0.04440 |   -0.1490 |
-#> |.....................|   -0.2038 |   -0.1015 |...........|...........|
-#> |  128|     468.19158 |     1.011 |   -0.9737 |   -0.9504 |   -0.9293 |
-#> |.....................|   -0.9577 |   -0.9362 |   -0.5600 |   -0.6009 |
-#> |.....................|   -0.8523 |    0.5756 |   -0.6644 |   -0.4878 |
-#> |.....................|   -0.1417 |   -0.4298 |...........|...........|
-#> |    U|     468.19158 |     101.1 |    -4.074 |   -0.9504 |    -2.362 |
-#> |.....................|    -4.058 |  -0.01116 |    0.8567 |   0.07769 |
-#> |.....................|    0.7134 |     3.900 |     1.560 |     1.624 |
-#> |.....................|     2.587 |     1.691 |...........|...........|
-#> |    X|     468.19158 |     101.1 |   0.01701 |    0.2788 |   0.09423 |
-#> |.....................|   0.01729 |    0.4972 |    0.8567 |   0.07769 |
-#> |.....................|    0.7134 |     3.900 |     1.560 |     1.624 |
-#> |.....................|     2.587 |     1.691 |...........|...........|
-#> |    F| Forward Diff. |    -7.990 |    0.8226 |  -0.02734 |    0.9308 |
-#> |.....................|   -0.6358 |  0.008756 |    -3.089 |    -2.706 |
-#> |.....................|  -0.08468 |   -0.5047 |    0.1760 |  -0.08785 |
-#> |.....................|  -0.06839 |  -0.06706 |...........|...........|
-#> |  129|     468.16872 |     1.012 |   -0.9746 |   -0.9536 |   -0.9297 |
-#> |.....................|   -0.9583 |   -0.9383 |   -0.5551 |   -0.6021 |
-#> |.....................|   -0.8428 |    0.6190 |   -0.6652 |   -0.4874 |
-#> |.....................|   -0.1424 |   -0.4276 |...........|...........|
-#> |    U|     468.16872 |     101.2 |    -4.075 |   -0.9534 |    -2.362 |
-#> |.....................|    -4.058 |  -0.01118 |    0.8585 |   0.07765 |
-#> |.....................|    0.7198 |     3.968 |     1.559 |     1.625 |
-#> |.....................|     2.586 |     1.694 |...........|...........|
-#> |    X|     468.16872 |     101.2 |   0.01700 |    0.2782 |   0.09420 |
-#> |.....................|   0.01728 |    0.4972 |    0.8585 |   0.07765 |
-#> |.....................|    0.7198 |     3.968 |     1.559 |     1.625 |
-#> |.....................|     2.586 |     1.694 |...........|...........|
-#> |    F| Forward Diff. |     1.949 |     1.224 |  -0.09904 |    0.8335 |
-#> |.....................|   -0.8902 |  0.008091 |    -1.732 |    -1.975 |
-#> |.....................|  -0.02618 |   -0.4349 |    0.2067 |   -0.1419 |
-#> |.....................|  -0.09587 |  -0.05531 |...........|...........|
-#> |  130|     468.14579 |     1.011 |   -0.9759 |   -0.9465 |   -0.9356 |
-#> |.....................|   -0.9575 |   -0.9407 |   -0.5519 |   -0.5999 |
-#> |.....................|   -0.8420 |    0.6626 |   -0.6664 |   -0.4855 |
-#> |.....................|   -0.1418 |   -0.4273 |...........|...........|
-#> |    U|     468.14579 |     101.1 |    -4.076 |   -0.9467 |    -2.368 |
-#> |.....................|    -4.057 |  -0.01121 |    0.8597 |   0.07772 |
-#> |.....................|    0.7204 |     4.037 |     1.557 |     1.627 |
-#> |.....................|     2.587 |     1.694 |...........|...........|
-#> |    X|     468.14579 |     101.1 |   0.01698 |    0.2795 |   0.09364 |
-#> |.....................|   0.01729 |    0.4972 |    0.8597 |   0.07772 |
-#> |.....................|    0.7204 |     4.037 |     1.557 |     1.627 |
-#> |.....................|     2.587 |     1.694 |...........|...........|
-#> |    F| Forward Diff. |    -9.402 |   -0.5832 |    0.1847 |    0.5188 |
-#> |.....................|   -0.4155 |  0.008564 |    -1.671 |    -1.980 |
-#> |.....................|  -0.03632 |   -0.3649 |    0.3304 |  -0.09551 |
-#> |.....................|   -0.1039 |  -0.08698 |...........|...........|
-#> |  131|     468.12514 |     1.011 |   -0.9763 |   -0.9445 |   -0.9403 |
-#> |.....................|   -0.9555 |   -0.9442 |   -0.5537 |   -0.5953 |
-#> |.....................|   -0.8391 |    0.7059 |   -0.6668 |   -0.4805 |
-#> |.....................|   -0.1376 |   -0.4223 |...........|...........|
-#> |    U|     468.12514 |     101.1 |    -4.076 |   -0.9449 |    -2.373 |
-#> |.....................|    -4.056 |  -0.01125 |    0.8590 |   0.07788 |
-#> |.....................|    0.7223 |     4.106 |     1.557 |     1.633 |
-#> |.....................|     2.593 |     1.700 |...........|...........|
-#> |    X|     468.12514 |     101.1 |   0.01697 |    0.2799 |   0.09320 |
-#> |.....................|   0.01733 |    0.4972 |    0.8590 |   0.07788 |
-#> |.....................|    0.7223 |     4.106 |     1.557 |     1.633 |
-#> |.....................|     2.593 |     1.700 |...........|...........|
-#> |    F| Forward Diff. |    -5.823 |   -0.4010 |    0.3316 |    0.1628 |
-#> |.....................|    0.2993 |  0.008766 |    -1.373 |    -1.049 |
-#> |.....................|  0.008284 |   -0.3402 |    0.4029 |   0.04088 |
-#> |.....................|  -0.03436 |  -0.04680 |...........|...........|
-#> |  132|     468.10920 |     1.012 |   -0.9773 |   -0.9503 |   -0.9395 |
-#> |.....................|   -0.9556 |   -0.9476 |   -0.5516 |   -0.5942 |
-#> |.....................|   -0.8420 |    0.7499 |   -0.6684 |   -0.4836 |
-#> |.....................|   -0.1347 |   -0.4216 |...........|...........|
-#> |    U|      468.1092 |     101.2 |    -4.077 |   -0.9504 |    -2.372 |
-#> |.....................|    -4.056 |  -0.01129 |    0.8598 |   0.07791 |
-#> |.....................|    0.7204 |     4.175 |     1.555 |     1.629 |
-#> |.....................|     2.597 |     1.700 |...........|...........|
-#> |    X|      468.1092 |     101.2 |   0.01695 |    0.2788 |   0.09328 |
-#> |.....................|   0.01732 |    0.4972 |    0.8598 |   0.07791 |
-#> |.....................|    0.7204 |     4.175 |     1.555 |     1.629 |
-#> |.....................|     2.597 |     1.700 |...........|...........|
-#> |    F| Forward Diff. |    0.4262 |  -0.09925 |    0.1213 |    0.1364 |
-#> |.....................|    0.2200 |  0.008054 |   -0.8480 |   -0.9224 |
-#> |.....................|  0.002683 |   -0.2932 |    0.3866 |  -0.06974 |
-#> |.....................|   0.01820 |  -0.05063 |...........|...........|
-#> |  133|     468.09766 |     1.011 |   -0.9774 |   -0.9506 |   -0.9392 |
-#> |.....................|   -0.9564 |   -0.9508 |   -0.5497 |   -0.5929 |
-#> |.....................|   -0.8318 |    0.7901 |   -0.6724 |   -0.4776 |
-#> |.....................|   -0.1474 |   -0.4133 |...........|...........|
-#> |    U|     468.09766 |     101.1 |    -4.077 |   -0.9507 |    -2.372 |
-#> |.....................|    -4.056 |  -0.01132 |    0.8605 |   0.07796 |
-#> |.....................|    0.7273 |     4.239 |     1.550 |     1.636 |
-#> |.....................|     2.578 |     1.710 |...........|...........|
-#> |    X|     468.09766 |     101.1 |   0.01695 |    0.2788 |   0.09331 |
-#> |.....................|   0.01731 |    0.4972 |    0.8605 |   0.07796 |
-#> |.....................|    0.7273 |     4.239 |     1.550 |     1.636 |
-#> |.....................|     2.578 |     1.710 |...........|...........|
-#> |    F| Forward Diff. |    -1.610 |   0.04645 |   0.08092 |    0.1870 |
-#> |.....................|   -0.1143 |  0.008788 |   -0.7906 |   -0.9380 |
-#> |.....................|   0.03576 |   -0.2567 |    0.2790 |   0.04583 |
-#> |.....................|   -0.1853 |   0.03622 |...........|...........|
-#> |  134|     468.08577 |     1.011 |   -0.9779 |   -0.9521 |   -0.9394 |
-#> |.....................|   -0.9569 |   -0.9550 |   -0.5484 |   -0.5900 |
-#> |.....................|   -0.8316 |    0.8332 |   -0.6752 |   -0.4781 |
-#> |.....................|   -0.1428 |   -0.4231 |...........|...........|
-#> |    U|     468.08577 |     101.1 |    -4.078 |   -0.9520 |    -2.372 |
-#> |.....................|    -4.057 |  -0.01137 |    0.8610 |   0.07805 |
-#> |.....................|    0.7274 |     4.307 |     1.546 |     1.635 |
-#> |.....................|     2.585 |     1.699 |...........|...........|
-#> |    X|     468.08577 |     101.1 |   0.01694 |    0.2785 |   0.09329 |
-#> |.....................|   0.01730 |    0.4972 |    0.8610 |   0.07805 |
-#> |.....................|    0.7274 |     4.307 |     1.546 |     1.635 |
-#> |.....................|     2.585 |     1.699 |...........|...........|
-#> |    F| Forward Diff. |    -2.835 |  -0.08271 |   0.01028 |    0.1502 |
-#> |.....................|   -0.2859 |  0.008536 |   -0.7298 |   -0.7597 |
-#> |.....................|   0.09519 |   -0.2281 |    0.1720 |  -0.01715 |
-#> |.....................|   -0.1386 |   -0.1062 |...........|...........|
-#> |  135|     468.06947 |     1.011 |   -0.9795 |   -0.9573 |   -0.9407 |
-#> |.....................|   -0.9575 |   -0.9652 |   -0.5443 |   -0.5834 |
-#> |.....................|   -0.8515 |    0.9153 |   -0.6785 |   -0.4834 |
-#> |.....................|   -0.1291 |   -0.4003 |...........|...........|
-#> |    U|     468.06947 |     101.1 |    -4.080 |   -0.9569 |    -2.373 |
-#> |.....................|    -4.057 |  -0.01148 |    0.8625 |   0.07827 |
-#> |.....................|    0.7139 |     4.437 |     1.542 |     1.629 |
-#> |.....................|     2.605 |     1.725 |...........|...........|
-#> |    X|     468.06947 |     101.1 |   0.01692 |    0.2775 |   0.09316 |
-#> |.....................|   0.01729 |    0.4971 |    0.8625 |   0.07827 |
-#> |.....................|    0.7139 |     4.437 |     1.542 |     1.629 |
-#> |.....................|     2.605 |     1.725 |...........|...........|
-#> |    F| Forward Diff. |    -3.887 |   -0.6407 |   -0.1939 |   0.08469 |
-#> |.....................|   -0.4208 |  0.006503 |    -1.301 |    -1.072 |
-#> |.....................|   -0.1255 |   -0.1861 |    0.1431 |  -0.06050 |
-#> |.....................|   0.01658 |    0.1111 |...........|...........|
-#> |  136|     468.05012 |     1.012 |   -0.9812 |   -0.9547 |   -0.9420 |
-#> |.....................|   -0.9570 |   -0.9873 |   -0.5356 |   -0.5736 |
-#> |.....................|   -0.8556 |     1.092 |   -0.6884 |   -0.4796 |
-#> |.....................|   -0.1211 |   -0.3873 |...........|...........|
-#> |    U|     468.05012 |     101.2 |    -4.081 |   -0.9544 |    -2.375 |
-#> |.....................|    -4.057 |  -0.01172 |    0.8656 |   0.07860 |
-#> |.....................|    0.7112 |     4.716 |     1.529 |     1.634 |
-#> |.....................|     2.617 |     1.740 |...........|...........|
-#> |    X|     468.05012 |     101.2 |   0.01689 |    0.2780 |   0.09305 |
-#> |.....................|   0.01730 |    0.4971 |    0.8656 |   0.07860 |
-#> |.....................|    0.7112 |     4.716 |     1.529 |     1.634 |
-#> |.....................|     2.617 |     1.740 |...........|...........|
-#> |    F| Forward Diff. |     2.331 |   -0.3124 |   0.04539 |  -0.09325 |
-#> |.....................|   -0.3359 |  0.005628 |   -0.9294 |   -0.4404 |
-#> |.....................|   -0.1788 |   -0.1003 |   -0.1180 |  -0.02636 |
-#> |.....................|   0.09915 |    0.1820 |...........|...........|
-#> |  137|     468.05341 |     1.012 |   -0.9836 |   -0.9687 |   -0.9317 |
-#> |.....................|   -0.9507 |    -1.013 |   -0.5235 |   -0.5660 |
-#> |.....................|   -0.8472 |     1.268 |   -0.6904 |   -0.4754 |
-#> |.....................|   -0.1200 |   -0.3857 |...........|...........|
-#> |    U|     468.05341 |     101.2 |    -4.084 |   -0.9676 |    -2.364 |
-#> |.....................|    -4.051 |  -0.01201 |    0.8700 |   0.07886 |
-#> |.....................|    0.7168 |     4.995 |     1.527 |     1.639 |
-#> |.....................|     2.619 |     1.742 |...........|...........|
-#> |    X|     468.05341 |     101.2 |   0.01685 |    0.2754 |   0.09401 |
-#> |.....................|   0.01741 |    0.4970 |    0.8700 |   0.07886 |
-#> |.....................|    0.7168 |     4.995 |     1.527 |     1.639 |
-#> |.....................|     2.619 |     1.742 |...........|...........|
-#> |  138|     468.05012 |     1.012 |   -0.9812 |   -0.9547 |   -0.9420 |
-#> |.....................|   -0.9570 |   -0.9873 |   -0.5356 |   -0.5736 |
-#> |.....................|   -0.8556 |     1.092 |   -0.6884 |   -0.4796 |
-#> |.....................|   -0.1211 |   -0.3873 |...........|...........|
-#> |    U|     468.05012 |     101.2 |    -4.081 |   -0.9544 |    -2.375 |
-#> |.....................|    -4.057 |  -0.01172 |    0.8656 |   0.07860 |
-#> |.....................|    0.7112 |     4.716 |     1.529 |     1.634 |
-#> |.....................|     2.617 |     1.740 |...........|...........|
-#> |    X|     468.05012 |     101.2 |   0.01689 |    0.2780 |   0.09305 |
-#> |.....................|   0.01730 |    0.4971 |    0.8656 |   0.07860 |
-#> |.....................|    0.7112 |     4.716 |     1.529 |     1.634 |
-#> |.....................|     2.617 |     1.740 |...........|...........|
-#> calculating covariance matrix
-#> done
-#> Calculating residuals/tables
-#> done
-AIC(f_nlmixr_dfop_sfo_saem$nm, f_nlmixr_dfop_sfo_focei$nm)
-#> Calculating -2LL by Gaussian quadrature (nnodes=3,nsd=1.6)
-#> 
-#>                            df       AIC
-#> f_nlmixr_dfop_sfo_saem$nm  16 1105.3725
-#> f_nlmixr_dfop_sfo_focei$nm 14  810.3271
-summary(f_nlmixr_dfop_sfo_sfo, data = TRUE)
-#> Error in h(simpleError(msg, call)): error in evaluating the argument 'object' in selecting a method for function 'summary': object 'f_nlmixr_dfop_sfo_sfo' not found
-# }
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.2.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/summary.saem.mmkin.html b/docs/dev/reference/summary.saem.mmkin.html
deleted file mode 100644
index e434ad8d..00000000
--- a/docs/dev/reference/summary.saem.mmkin.html
+++ /dev/null
@@ -1,677 +0,0 @@
-
-Summary method for class "saem.mmkin" — summary.saem.mmkin • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Summary method for class "saem.mmkin"
      
-    Source: R/summary.saem.mmkin.R
-    
-    
      
-
-    
      
-    
      Lists model equations, initial parameter values, optimised parameters
-for fixed effects (population), random effects (deviations from the
-population mean) and residual error model, as well as the resulting
-endpoints such as formation fractions and DT50 values. Optionally
-(default is FALSE), the data are listed in full.
      
-    
      
-
-    
      
-    
      # S3 method for saem.mmkin
-summary(
-  object,
-  data = FALSE,
-  verbose = FALSE,
-  covariates = NULL,
-  covariate_quantile = 0.5,
-  distimes = TRUE,
-  ...
-)
-
-# S3 method for summary.saem.mmkin
-print(x, digits = max(3, getOption("digits") - 3), verbose = x$verbose, ...)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      an object of class saem.mmkin
      
-
-
-
      data
      
-
      logical, indicating whether the full data should be included in
-the summary.
      
-
-
-
      verbose
      
-
      Should the summary be verbose?
      
-
-
-
      covariates
      
-
      Numeric vector with covariate values for all variables in
-any covariate models in the object. If given, it overrides 'covariate_quantile'.
      
-
-
-
      covariate_quantile
      
-
      This argument only has an effect if the fitted
-object has covariate models. If so, the default is to show endpoints
-for the median of the covariate values (50th percentile).
      
-
-
-
      distimes
      
-
      logical, indicating whether DT50 and DT90 values should be
-included.
      
-
-
-
      ...
      
-
      optional arguments passed to methods like print.
      
-
-
-
      x
      
-
      an object of class summary.saem.mmkin
      
-
-
-
      digits
      
-
      Number of digits to use for printing
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      The summary function returns a list based on the saemix::SaemixObject
      
-
-
-
      obtained in the fit, with at least the following additional components
      
-
      saemixversion, mkinversion, Rversion
      
-
      The saemix, mkin and R versions used
      
-
-
      date.fit, date.summary
      
-
      The dates where the fit and the summary were
-produced
      
-
-
      diffs
      
-
      The differential equations used in the degradation model
      
-
-
      use_of_ff
      
-
      Was maximum or minimum use made of formation fractions
      
-
-
      data
      
-
      The data
      
-
-
      confint_trans
      
-
      Transformed parameters as used in the optimisation, with confidence intervals
      
-
-
      confint_back
      
-
      Backtransformed parameters, with confidence intervals if available
      
-
-
      confint_errmod
      
-
      Error model parameters with confidence intervals
      
-
-
      ff
      
-
      The estimated formation fractions derived from the fitted
-model.
      
-
-
      distimes
      
-
      The DT50 and DT90 values for each observed variable.
      
-
-
      SFORB
      
-
      If applicable, eigenvalues of SFORB components of the model.
      
-
-
      The print method is called for its side effect, i.e. printing the summary.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke for the mkin specific parts
-saemix authors for the parts inherited from saemix.
      
-    
      
-
-    
      
-    
      Examples
      
-    
      # Generate five datasets following DFOP-SFO kinetics
-sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "m1"),
- m1 = mkinsub("SFO"), quiet = TRUE)
-set.seed(1234)
-k1_in <- rlnorm(5, log(0.1), 0.3)
-k2_in <- rlnorm(5, log(0.02), 0.3)
-g_in <- plogis(rnorm(5, qlogis(0.5), 0.3))
-f_parent_to_m1_in <- plogis(rnorm(5, qlogis(0.3), 0.3))
-k_m1_in <- rlnorm(5, log(0.02), 0.3)
-
-pred_dfop_sfo <- function(k1, k2, g, f_parent_to_m1, k_m1) {
-  mkinpredict(dfop_sfo,
-    c(k1 = k1, k2 = k2, g = g, f_parent_to_m1 = f_parent_to_m1, k_m1 = k_m1),
-    c(parent = 100, m1 = 0),
-    sampling_times)
-}
-
-ds_mean_dfop_sfo <- lapply(1:5, function(i) {
-  mkinpredict(dfop_sfo,
-    c(k1 = k1_in[i], k2 = k2_in[i], g = g_in[i],
-      f_parent_to_m1 = f_parent_to_m1_in[i], k_m1 = k_m1_in[i]),
-    c(parent = 100, m1 = 0),
-    sampling_times)
-})
-names(ds_mean_dfop_sfo) <- paste("ds", 1:5)
-
-ds_syn_dfop_sfo <- lapply(ds_mean_dfop_sfo, function(ds) {
-  add_err(ds,
-    sdfunc = function(value) sqrt(1^2 + value^2 * 0.07^2),
-    n = 1)[[1]]
-})
-
-# \dontrun{
-# Evaluate using mmkin and saem
-f_mmkin_dfop_sfo <- mmkin(list(dfop_sfo), ds_syn_dfop_sfo,
-  quiet = TRUE, error_model = "tc", cores = 5)
-f_saem_dfop_sfo <- saem(f_mmkin_dfop_sfo)
-print(f_saem_dfop_sfo)
-#> Kinetic nonlinear mixed-effects model fit by SAEM
-#> Structural model:
-#> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-#>            time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-#>            * parent
-#> d_m1/dt = + f_parent_to_m1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)
-#>            * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-#>            exp(-k2 * time))) * parent - k_m1 * m1
-#> 
-#> Data:
-#> 171 observations of 2 variable(s) grouped in 5 datasets
-#> 
-#> Likelihood computed by importance sampling
-#>     AIC   BIC logLik
-#>   810.8 805.4 -391.4
-#> 
-#> Fitted parameters:
-#>                     estimate     lower     upper
-#> parent_0           100.86947  97.81542 103.92353
-#> log_k_m1            -4.06947  -4.16944  -3.96950
-#> f_parent_qlogis     -0.93256  -1.34200  -0.52312
-#> log_k1              -2.37017  -2.72660  -2.01375
-#> log_k2              -4.06264  -4.21344  -3.91184
-#> g_qlogis            -0.02174  -0.45898   0.41549
-#> a.1                  0.87598   0.67275   1.07922
-#> b.1                  0.07949   0.06389   0.09509
-#> SD.parent_0          0.19170 -30.36286  30.74626
-#> SD.log_k_m1          0.01883  -0.28736   0.32502
-#> SD.f_parent_qlogis   0.44300   0.16391   0.72209
-#> SD.log_k1            0.35320   0.09661   0.60978
-#> SD.log_k2            0.13707   0.02359   0.25056
-#> SD.g_qlogis          0.37478   0.04490   0.70467
-illparms(f_saem_dfop_sfo)
-#> [1] "sd(parent_0)" "sd(log_k_m1)"
-f_saem_dfop_sfo_2 <- update(f_saem_dfop_sfo,
-  no_random_effect = c("parent_0", "log_k_m1"))
-illparms(f_saem_dfop_sfo_2)
-intervals(f_saem_dfop_sfo_2)
-#> Approximate 95% confidence intervals
-#> 
-#>  Fixed effects:
-#>                      lower         est.        upper
-#> parent_0       98.36731429 101.42508066 104.48284703
-#> k_m1            0.01513234   0.01670094   0.01843214
-#> f_parent_to_m1  0.20221431   0.27608850   0.36461630
-#> k1              0.06915073   0.09759718   0.13774560
-#> k2              0.01487068   0.01740389   0.02036863
-#> g               0.37365671   0.48384821   0.59563299
-#> 
-#>  Random effects:
-#>                          lower      est.     upper
-#> sd(f_parent_qlogis) 0.16439770 0.4427585 0.7211193
-#> sd(log_k1)          0.08304243 0.3345213 0.5860002
-#> sd(log_k2)          0.03146410 0.1490210 0.2665779
-#> sd(g_qlogis)        0.06216385 0.4023430 0.7425221
-#> 
-#>  
-#>          lower       est.      upper
-#> a.1 0.67696663 0.87777355 1.07858048
-#> b.1 0.06363957 0.07878001 0.09392044
-summary(f_saem_dfop_sfo_2, data = TRUE)
-#> saemix version used for fitting:      3.2 
-#> mkin version used for pre-fitting:  1.2.3 
-#> R version used for fitting:         4.2.3 
-#> Date of fit:     Sun Apr 16 08:34:58 2023 
-#> Date of summary: Sun Apr 16 08:34:58 2023 
-#> 
-#> Equations:
-#> d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-#>            time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
-#>            * parent
-#> d_m1/dt = + f_parent_to_m1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)
-#>            * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
-#>            exp(-k2 * time))) * parent - k_m1 * m1
-#> 
-#> Data:
-#> 171 observations of 2 variable(s) grouped in 5 datasets
-#> 
-#> Model predictions using solution type analytical 
-#> 
-#> Fitted in 9.384 s
-#> Using 300, 100 iterations and 10 chains
-#> 
-#> Variance model: Two-component variance function 
-#> 
-#> Starting values for degradation parameters:
-#>        parent_0        log_k_m1 f_parent_qlogis          log_k1          log_k2 
-#>       101.65645        -4.05368        -0.94311        -2.35943        -4.07006 
-#>        g_qlogis 
-#>        -0.01132 
-#> 
-#> Fixed degradation parameter values:
-#> None
-#> 
-#> Starting values for random effects (square root of initial entries in omega):
-#>                 parent_0 log_k_m1 f_parent_qlogis log_k1 log_k2 g_qlogis
-#> parent_0           6.742   0.0000          0.0000 0.0000 0.0000    0.000
-#> log_k_m1           0.000   0.2236          0.0000 0.0000 0.0000    0.000
-#> f_parent_qlogis    0.000   0.0000          0.5572 0.0000 0.0000    0.000
-#> log_k1             0.000   0.0000          0.0000 0.8031 0.0000    0.000
-#> log_k2             0.000   0.0000          0.0000 0.0000 0.2931    0.000
-#> g_qlogis           0.000   0.0000          0.0000 0.0000 0.0000    0.807
-#> 
-#> Starting values for error model parameters:
-#> a.1 b.1 
-#>   1   1 
-#> 
-#> Results:
-#> 
-#> Likelihood computed by importance sampling
-#>   AIC   BIC logLik
-#>   807 802.3 -391.5
-#> 
-#> Optimised parameters:
-#>                         est.    lower     upper
-#> parent_0           101.42508 98.36731 104.48285
-#> log_k_m1            -4.09229 -4.19092  -3.99366
-#> f_parent_qlogis     -0.96395 -1.37251  -0.55538
-#> log_k1              -2.32691 -2.67147  -1.98235
-#> log_k2              -4.05106 -4.20836  -3.89376
-#> g_qlogis            -0.06463 -0.51656   0.38730
-#> a.1                  0.87777  0.67697   1.07858
-#> b.1                  0.07878  0.06364   0.09392
-#> SD.f_parent_qlogis   0.44276  0.16440   0.72112
-#> SD.log_k1            0.33452  0.08304   0.58600
-#> SD.log_k2            0.14902  0.03146   0.26658
-#> SD.g_qlogis          0.40234  0.06216   0.74252
-#> 
-#> Correlation: 
-#>                 parnt_0 lg_k_m1 f_prnt_ log_k1  log_k2 
-#> log_k_m1        -0.4693                                
-#> f_parent_qlogis -0.2378  0.2595                        
-#> log_k1           0.1720 -0.1593 -0.0669                
-#> log_k2           0.0179  0.0594  0.0035  0.1995        
-#> g_qlogis         0.1073 -0.1060 -0.0322 -0.2299 -0.3168
-#> 
-#> Random effects:
-#>                      est.   lower  upper
-#> SD.f_parent_qlogis 0.4428 0.16440 0.7211
-#> SD.log_k1          0.3345 0.08304 0.5860
-#> SD.log_k2          0.1490 0.03146 0.2666
-#> SD.g_qlogis        0.4023 0.06216 0.7425
-#> 
-#> Variance model:
-#>        est.   lower   upper
-#> a.1 0.87777 0.67697 1.07858
-#> b.1 0.07878 0.06364 0.09392
-#> 
-#> Backtransformed parameters:
-#>                    est.    lower     upper
-#> parent_0       101.4251 98.36731 104.48285
-#> k_m1             0.0167  0.01513   0.01843
-#> f_parent_to_m1   0.2761  0.20221   0.36462
-#> k1               0.0976  0.06915   0.13775
-#> k2               0.0174  0.01487   0.02037
-#> g                0.4838  0.37366   0.59563
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_m1   0.2761
-#> parent_sink 0.7239
-#> 
-#> Estimated disappearance times:
-#>         DT50   DT90 DT50back DT50_k1 DT50_k2
-#> parent 15.54  94.33     28.4   7.102   39.83
-#> m1     41.50 137.87       NA      NA      NA
-#> 
-#> Data:
-#>    ds   name time observed predicted  residual    std standardized
-#>  ds 1 parent    0     89.8 1.014e+02 -11.62508 8.0383     -1.44620
-#>  ds 1 parent    0    104.1 1.014e+02   2.67492 8.0383      0.33277
-#>  ds 1 parent    1     88.7 9.650e+01  -7.80311 7.6530     -1.01961
-#>  ds 1 parent    1     95.5 9.650e+01  -1.00311 7.6530     -0.13107
-#>  ds 1 parent    3     81.8 8.753e+01  -5.72638 6.9510     -0.82382
-#>  ds 1 parent    3     94.5 8.753e+01   6.97362 6.9510      1.00326
-#>  ds 1 parent    7     71.5 7.254e+01  -1.04133 5.7818     -0.18010
-#>  ds 1 parent    7     70.3 7.254e+01  -2.24133 5.7818     -0.38765
-#>  ds 1 parent   14     54.2 5.349e+01   0.71029 4.3044      0.16502
-#>  ds 1 parent   14     49.6 5.349e+01  -3.88971 4.3044     -0.90366
-#>  ds 1 parent   28     31.5 3.167e+01  -0.16616 2.6446     -0.06283
-#>  ds 1 parent   28     28.8 3.167e+01  -2.86616 2.6446     -1.08379
-#>  ds 1 parent   60     12.1 1.279e+01  -0.69287 1.3365     -0.51843
-#>  ds 1 parent   60     13.6 1.279e+01   0.80713 1.3365      0.60392
-#>  ds 1 parent   90      6.2 6.397e+00  -0.19718 1.0122     -0.19481
-#>  ds 1 parent   90      8.3 6.397e+00   1.90282 1.0122      1.87996
-#>  ds 1 parent  120      2.2 3.323e+00  -1.12320 0.9160     -1.22623
-#>  ds 1 parent  120      2.4 3.323e+00  -0.92320 0.9160     -1.00788
-#>  ds 1     m1    1      0.3 1.179e+00  -0.87919 0.8827     -0.99605
-#>  ds 1     m1    1      0.2 1.179e+00  -0.97919 0.8827     -1.10935
-#>  ds 1     m1    3      2.2 3.273e+00  -1.07272 0.9149     -1.17256
-#>  ds 1     m1    3      3.0 3.273e+00  -0.27272 0.9149     -0.29811
-#>  ds 1     m1    7      6.5 6.559e+00  -0.05872 1.0186     -0.05765
-#>  ds 1     m1    7      5.0 6.559e+00  -1.55872 1.0186     -1.53032
-#>  ds 1     m1   14     10.2 1.016e+01   0.03787 1.1880      0.03188
-#>  ds 1     m1   14      9.5 1.016e+01  -0.66213 1.1880     -0.55734
-#>  ds 1     m1   28     12.2 1.268e+01  -0.47913 1.3297     -0.36032
-#>  ds 1     m1   28     13.4 1.268e+01   0.72087 1.3297      0.54211
-#>  ds 1     m1   60     11.8 1.078e+01   1.02493 1.2211      0.83936
-#>  ds 1     m1   60     13.2 1.078e+01   2.42493 1.2211      1.98588
-#>  ds 1     m1   90      6.6 7.705e+00  -1.10464 1.0672     -1.03509
-#>  ds 1     m1   90      9.3 7.705e+00   1.59536 1.0672      1.49491
-#>  ds 1     m1  120      3.5 5.236e+00  -1.73617 0.9699     -1.79010
-#>  ds 1     m1  120      5.4 5.236e+00   0.16383 0.9699      0.16892
-#>  ds 2 parent    0    118.0 1.014e+02  16.57492 8.0383      2.06198
-#>  ds 2 parent    0     99.8 1.014e+02  -1.62508 8.0383     -0.20217
-#>  ds 2 parent    1     90.2 9.599e+01  -5.79045 7.6129     -0.76061
-#>  ds 2 parent    1     94.6 9.599e+01  -1.39045 7.6129     -0.18264
-#>  ds 2 parent    3     96.1 8.652e+01   9.57931 6.8724      1.39388
-#>  ds 2 parent    3     78.4 8.652e+01  -8.12069 6.8724     -1.18164
-#>  ds 2 parent    7     77.9 7.197e+01   5.93429 5.7370      1.03439
-#>  ds 2 parent    7     77.7 7.197e+01   5.73429 5.7370      0.99953
-#>  ds 2 parent   14     56.0 5.555e+01   0.44657 4.4637      0.10005
-#>  ds 2 parent   14     54.7 5.555e+01  -0.85343 4.4637     -0.19120
-#>  ds 2 parent   28     36.6 3.853e+01  -1.93170 3.1599     -0.61132
-#>  ds 2 parent   28     36.8 3.853e+01  -1.73170 3.1599     -0.54803
-#>  ds 2 parent   60     22.1 2.110e+01   1.00360 1.8795      0.53396
-#>  ds 2 parent   60     24.7 2.110e+01   3.60360 1.8795      1.91728
-#>  ds 2 parent   90     12.4 1.250e+01  -0.09712 1.3190     -0.07363
-#>  ds 2 parent   90     10.8 1.250e+01  -1.69712 1.3190     -1.28667
-#>  ds 2 parent  120      6.8 7.419e+00  -0.61913 1.0546     -0.58709
-#>  ds 2 parent  120      7.9 7.419e+00   0.48087 1.0546      0.45599
-#>  ds 2     m1    1      1.3 1.422e+00  -0.12194 0.8849     -0.13781
-#>  ds 2     m1    3      3.7 3.831e+00  -0.13149 0.9282     -0.14166
-#>  ds 2     m1    3      4.7 3.831e+00   0.86851 0.9282      0.93567
-#>  ds 2     m1    7      8.1 7.292e+00   0.80812 1.0490      0.77034
-#>  ds 2     m1    7      7.9 7.292e+00   0.60812 1.0490      0.57969
-#>  ds 2     m1   14     10.1 1.055e+01  -0.45332 1.2090     -0.37495
-#>  ds 2     m1   14     10.3 1.055e+01  -0.25332 1.2090     -0.20953
-#>  ds 2     m1   28     10.7 1.230e+01  -1.59960 1.3074     -1.22347
-#>  ds 2     m1   28     12.2 1.230e+01  -0.09960 1.3074     -0.07618
-#>  ds 2     m1   60     10.7 1.065e+01   0.05342 1.2141      0.04400
-#>  ds 2     m1   60     12.5 1.065e+01   1.85342 1.2141      1.52661
-#>  ds 2     m1   90      9.1 8.196e+00   0.90368 1.0897      0.82930
-#>  ds 2     m1   90      7.4 8.196e+00  -0.79632 1.0897     -0.73078
-#>  ds 2     m1  120      6.1 5.997e+00   0.10252 0.9969      0.10284
-#>  ds 2     m1  120      4.5 5.997e+00  -1.49748 0.9969     -1.50220
-#>  ds 3 parent    0    106.2 1.014e+02   4.77492 8.0383      0.59402
-#>  ds 3 parent    0    106.9 1.014e+02   5.47492 8.0383      0.68110
-#>  ds 3 parent    1    107.4 9.390e+01  13.49935 7.4494      1.81214
-#>  ds 3 parent    1     96.1 9.390e+01   2.19935 7.4494      0.29524
-#>  ds 3 parent    3     79.4 8.152e+01  -2.12307 6.4821     -0.32753
-#>  ds 3 parent    3     82.6 8.152e+01   1.07693 6.4821      0.16614
-#>  ds 3 parent    7     63.9 6.446e+01  -0.55834 5.1533     -0.10834
-#>  ds 3 parent    7     62.4 6.446e+01  -2.05834 5.1533     -0.39942
-#>  ds 3 parent   14     51.0 4.826e+01   2.74073 3.9019      0.70241
-#>  ds 3 parent   14     47.1 4.826e+01  -1.15927 3.9019     -0.29711
-#>  ds 3 parent   28     36.1 3.424e+01   1.86399 2.8364      0.65718
-#>  ds 3 parent   28     36.6 3.424e+01   2.36399 2.8364      0.83346
-#>  ds 3 parent   60     20.1 1.968e+01   0.42172 1.7815      0.23672
-#>  ds 3 parent   60     19.8 1.968e+01   0.12172 1.7815      0.06833
-#>  ds 3 parent   90     11.3 1.195e+01  -0.64633 1.2869     -0.50222
-#>  ds 3 parent   90     10.7 1.195e+01  -1.24633 1.2869     -0.96844
-#>  ds 3 parent  120      8.2 7.255e+00   0.94532 1.0474      0.90251
-#>  ds 3 parent  120      7.3 7.255e+00   0.04532 1.0474      0.04327
-#>  ds 3     m1    0      0.8 2.956e-11   0.80000 0.8778      0.91140
-#>  ds 3     m1    1      1.8 1.758e+00   0.04187 0.8886      0.04712
-#>  ds 3     m1    1      2.3 1.758e+00   0.54187 0.8886      0.60978
-#>  ds 3     m1    3      4.2 4.567e+00  -0.36697 0.9486     -0.38683
-#>  ds 3     m1    3      4.1 4.567e+00  -0.46697 0.9486     -0.49224
-#>  ds 3     m1    7      6.8 8.151e+00  -1.35124 1.0876     -1.24242
-#>  ds 3     m1    7     10.1 8.151e+00   1.94876 1.0876      1.79182
-#>  ds 3     m1   14     11.4 1.083e+01   0.57098 1.2240      0.46647
-#>  ds 3     m1   14     12.8 1.083e+01   1.97098 1.2240      1.61022
-#>  ds 3     m1   28     11.5 1.147e+01   0.03175 1.2597      0.02520
-#>  ds 3     m1   28     10.6 1.147e+01  -0.86825 1.2597     -0.68928
-#>  ds 3     m1   60      7.5 9.298e+00  -1.79834 1.1433     -1.57298
-#>  ds 3     m1   60      8.6 9.298e+00  -0.69834 1.1433     -0.61083
-#>  ds 3     m1   90      7.3 7.038e+00   0.26249 1.0382      0.25283
-#>  ds 3     m1   90      8.1 7.038e+00   1.06249 1.0382      1.02340
-#>  ds 3     m1  120      5.3 5.116e+00   0.18417 0.9659      0.19068
-#>  ds 3     m1  120      3.8 5.116e+00  -1.31583 0.9659     -1.36232
-#>  ds 4 parent    0    104.7 1.014e+02   3.27492 8.0383      0.40741
-#>  ds 4 parent    0     88.3 1.014e+02 -13.12508 8.0383     -1.63281
-#>  ds 4 parent    1     94.2 9.781e+01  -3.61183 7.7555     -0.46572
-#>  ds 4 parent    1     94.6 9.781e+01  -3.21183 7.7555     -0.41414
-#>  ds 4 parent    3     78.1 9.110e+01 -13.00467 7.2307     -1.79853
-#>  ds 4 parent    3     96.5 9.110e+01   5.39533 7.2307      0.74617
-#>  ds 4 parent    7     76.2 7.951e+01  -3.30511 6.3246     -0.52258
-#>  ds 4 parent    7     77.8 7.951e+01  -1.70511 6.3246     -0.26960
-#>  ds 4 parent   14     70.8 6.376e+01   7.03783 5.0993      1.38016
-#>  ds 4 parent   14     67.3 6.376e+01   3.53783 5.0993      0.69379
-#>  ds 4 parent   28     43.1 4.340e+01  -0.30456 3.5303     -0.08627
-#>  ds 4 parent   28     45.1 4.340e+01   1.69544 3.5303      0.48026
-#>  ds 4 parent   60     21.3 2.142e+01  -0.12077 1.9022     -0.06349
-#>  ds 4 parent   60     23.5 2.142e+01   2.07923 1.9022      1.09308
-#>  ds 4 parent   90     11.8 1.207e+01  -0.26813 1.2940     -0.20721
-#>  ds 4 parent   90     12.1 1.207e+01   0.03187 1.2940      0.02463
-#>  ds 4 parent  120      7.0 6.954e+00   0.04554 1.0347      0.04402
-#>  ds 4 parent  120      6.2 6.954e+00  -0.75446 1.0347     -0.72914
-#>  ds 4     m1    0      1.6 1.990e-13   1.60000 0.8778      1.82279
-#>  ds 4     m1    1      0.9 7.305e-01   0.16949 0.8797      0.19267
-#>  ds 4     m1    3      3.7 2.051e+00   1.64896 0.8925      1.84753
-#>  ds 4     m1    3      2.0 2.051e+00  -0.05104 0.8925     -0.05719
-#>  ds 4     m1    7      3.6 4.204e+00  -0.60375 0.9382     -0.64354
-#>  ds 4     m1    7      3.8 4.204e+00  -0.40375 0.9382     -0.43036
-#>  ds 4     m1   14      7.1 6.760e+00   0.34021 1.0267      0.33137
-#>  ds 4     m1   14      6.6 6.760e+00  -0.15979 1.0267     -0.15563
-#>  ds 4     m1   28      9.5 9.011e+00   0.48856 1.1289      0.43277
-#>  ds 4     m1   28      9.3 9.011e+00   0.28856 1.1289      0.25561
-#>  ds 4     m1   60      8.3 8.611e+00  -0.31077 1.1093     -0.28014
-#>  ds 4     m1   60      9.0 8.611e+00   0.38923 1.1093      0.35086
-#>  ds 4     m1   90      6.6 6.678e+00  -0.07753 1.0233     -0.07576
-#>  ds 4     m1   90      7.7 6.678e+00   1.02247 1.0233      0.99915
-#>  ds 4     m1  120      3.7 4.847e+00  -1.14679 0.9572     -1.19804
-#>  ds 4     m1  120      3.5 4.847e+00  -1.34679 0.9572     -1.40698
-#>  ds 5 parent    0    110.4 1.014e+02   8.97492 8.0383      1.11651
-#>  ds 5 parent    0    112.1 1.014e+02  10.67492 8.0383      1.32800
-#>  ds 5 parent    1     93.5 9.466e+01  -1.16118 7.5089     -0.15464
-#>  ds 5 parent    1     91.0 9.466e+01  -3.66118 7.5089     -0.48758
-#>  ds 5 parent    3     71.0 8.302e+01 -12.01844 6.5988     -1.82130
-#>  ds 5 parent    3     89.7 8.302e+01   6.68156 6.5988      1.01254
-#>  ds 5 parent    7     60.4 6.563e+01  -5.22574 5.2440     -0.99652
-#>  ds 5 parent    7     59.1 6.563e+01  -6.52574 5.2440     -1.24442
-#>  ds 5 parent   14     56.5 4.727e+01   9.22621 3.8263      2.41128
-#>  ds 5 parent   14     47.0 4.727e+01  -0.27379 3.8263     -0.07156
-#>  ds 5 parent   28     30.2 3.103e+01  -0.83405 2.5977     -0.32108
-#>  ds 5 parent   28     23.9 3.103e+01  -7.13405 2.5977     -2.74634
-#>  ds 5 parent   60     17.0 1.800e+01  -0.99696 1.6675     -0.59787
-#>  ds 5 parent   60     18.7 1.800e+01   0.70304 1.6675      0.42161
-#>  ds 5 parent   90     11.3 1.167e+01  -0.36809 1.2710     -0.28961
-#>  ds 5 parent   90     11.9 1.167e+01   0.23191 1.2710      0.18246
-#>  ds 5 parent  120      9.0 7.595e+00   1.40496 1.0623      1.32256
-#>  ds 5 parent  120      8.1 7.595e+00   0.50496 1.0623      0.47535
-#>  ds 5     m1    0      0.7 0.000e+00   0.70000 0.8778      0.79747
-#>  ds 5     m1    1      3.0 3.158e+00  -0.15799 0.9123     -0.17317
-#>  ds 5     m1    1      2.6 3.158e+00  -0.55799 0.9123     -0.61160
-#>  ds 5     m1    3      5.1 8.443e+00  -3.34286 1.1013     -3.03535
-#>  ds 5     m1    3      7.5 8.443e+00  -0.94286 1.1013     -0.85613
-#>  ds 5     m1    7     16.5 1.580e+01   0.69781 1.5232      0.45811
-#>  ds 5     m1    7     19.0 1.580e+01   3.19781 1.5232      2.09935
-#>  ds 5     m1   14     22.9 2.216e+01   0.73604 1.9543      0.37663
-#>  ds 5     m1   14     23.2 2.216e+01   1.03604 1.9543      0.53014
-#>  ds 5     m1   28     22.2 2.423e+01  -2.03128 2.1011     -0.96678
-#>  ds 5     m1   28     24.4 2.423e+01   0.16872 2.1011      0.08030
-#>  ds 5     m1   60     15.5 1.876e+01  -3.25610 1.7187     -1.89455
-#>  ds 5     m1   60     19.8 1.876e+01   1.04390 1.7187      0.60739
-#>  ds 5     m1   90     14.9 1.366e+01   1.23585 1.3890      0.88976
-#>  ds 5     m1   90     14.2 1.366e+01   0.53585 1.3890      0.38579
-#>  ds 5     m1  120     10.9 9.761e+00   1.13911 1.1670      0.97613
-#>  ds 5     m1  120     10.4 9.761e+00   0.63911 1.1670      0.54767
-# Add a correlation between random effects of g and k2
-cov_model_3 <- f_saem_dfop_sfo_2$so@model@covariance.model
-cov_model_3["log_k2", "g_qlogis"] <- 1
-cov_model_3["g_qlogis", "log_k2"] <- 1
-f_saem_dfop_sfo_3 <- update(f_saem_dfop_sfo,
-  covariance.model = cov_model_3)
-intervals(f_saem_dfop_sfo_3)
-#> Approximate 95% confidence intervals
-#> 
-#>  Fixed effects:
-#>                      lower         est.        upper
-#> parent_0       98.39888363 101.48951337 104.58014311
-#> k_m1            0.01508704   0.01665986   0.01839665
-#> f_parent_to_m1  0.20141557   0.27540583   0.36418131
-#> k1              0.07708759   0.10430866   0.14114200
-#> k2              0.01476621   0.01786384   0.02161129
-#> g               0.33679867   0.45083525   0.57028162
-#> 
-#>  Random effects:
-#>                             lower       est.      upper
-#> sd(f_parent_qlogis)    0.38085375  0.4441841  0.5075145
-#> sd(log_k1)             0.04774819  0.2660384  0.4843286
-#> sd(log_k2)            -0.63842736  0.1977024  1.0338321
-#> sd(g_qlogis)           0.22711289  0.4502227  0.6733326
-#> corr(log_k2,g_qlogis) -0.83271473 -0.6176939 -0.4026730
-#> 
-#>  
-#>          lower       est.      upper
-#> a.1 0.67347568 0.87437392 1.07527216
-#> b.1 0.06393032 0.07912417 0.09431802
-# The correlation does not improve the fit judged by AIC and BIC, although
-# the likelihood is higher with the additional parameter
-anova(f_saem_dfop_sfo, f_saem_dfop_sfo_2, f_saem_dfop_sfo_3)
-#> Data: 171 observations of 2 variable(s) grouped in 5 datasets
-#> 
-#>                   npar    AIC    BIC     Lik
-#> f_saem_dfop_sfo_2   12 806.96 802.27 -391.48
-#> f_saem_dfop_sfo_3   13 807.99 802.91 -391.00
-#> f_saem_dfop_sfo     14 810.83 805.36 -391.42
-# }
-
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/summary_listing.html b/docs/dev/reference/summary_listing.html
deleted file mode 100644
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-
-Display the output of a summary function according to the output format — summary_listing • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Display the output of a summary function according to the output format
      
-    Source: R/summary_listing.R
-    
-    
      
-
-    
      
-    
      This function is intended for use in a R markdown code chunk with the chunk
-option results = "asis".
      
-    
      
-
-    
      
-    
      summary_listing(object, caption = NULL, label = NULL, clearpage = TRUE)
-
-tex_listing(object, caption = NULL, label = NULL, clearpage = TRUE)
-
-html_listing(object, caption = NULL)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      The object for which the summary is to be listed
      
-
-
-
      caption
      
-
      An optional caption
      
-
-
-
      label
      
-
      An optional label, ignored in html output
      
-
-
-
      clearpage
      
-
      Should a new page be started after the listing? Ignored in html output
      
-
-
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/synthetic_data_for_UBA_2014-1.png b/docs/dev/reference/synthetic_data_for_UBA_2014-1.png
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diff --git a/docs/dev/reference/synthetic_data_for_UBA_2014.html b/docs/dev/reference/synthetic_data_for_UBA_2014.html
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-
-Synthetic datasets for one parent compound with two metabolites — synthetic_data_for_UBA_2014 • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Synthetic datasets for one parent compound with two metabolites
      
-    
-    
-    
      
-
-    
      
-    
      The 12 datasets were generated using four different models and three different
- variance components. The four models are either the SFO or the DFOP model with either
- two sequential or two parallel metabolites.
      
-
      Variance component 'a' is based on a normal distribution with standard deviation of 3,
- Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7.
- Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the
- minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07
- for the increase of the standard deviation with y. Note that this is a simplified version
- of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the
- measured values approximates lognormal distribution for high values, whereas we are using
- normally distributed error components all along.
      
-
      Initial concentrations for metabolites and all values where adding the variance component resulted
- in a value below the assumed limit of detection of 0.1 were set to NA.
      
-
      As an example, the first dataset has the title SFO_lin_a and is based on the SFO model
- with two sequential metabolites (linear pathway), with added variance component 'a'.
      
-
      Compare also the code in the example section to see the degradation models.
      
-    
      
-
-    
      
-    
      synthetic_data_for_UBA_2014
      
-    
      
-
-    
      
-    
      Format
      
-    
      A list containing twelve datasets as an R6 class defined by mkinds,
-  each containing, among others, the following components
      title
      
-
      The name of the dataset, e.g. SFO_lin_a
      
-
-    
      data
      
-
      A data frame with the data in the form expected by mkinfit
      
-
-  
-
      
-    
      
-    
      Source
      
-    
      Ranke (2014) Prüfung und Validierung von Modellierungssoftware als Alternative
-  zu ModelMaker 4.0, Umweltbundesamt Projektnummer 27452
      
-
      Rocke, David M. und Lorenzato, Stefan (1995) A two-component model for
-  measurement error in analytical chemistry. Technometrics 37(2), 176-184.
      
-    
      
-
-    
      
-    
      Examples
      
-    
      # \dontrun{
-# The data have been generated using the following kinetic models
-m_synth_SFO_lin <- mkinmod(parent = list(type = "SFO", to = "M1"),
-                           M1 = list(type = "SFO", to = "M2"),
-                           M2 = list(type = "SFO"), use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-
-
-m_synth_SFO_par <- mkinmod(parent = list(type = "SFO", to = c("M1", "M2"),
-                                         sink = FALSE),
-                           M1 = list(type = "SFO"),
-                           M2 = list(type = "SFO"), use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-
-m_synth_DFOP_lin <- mkinmod(parent = list(type = "DFOP", to = "M1"),
-                            M1 = list(type = "SFO", to = "M2"),
-                            M2 = list(type = "SFO"), use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-
-m_synth_DFOP_par <- mkinmod(parent = list(type = "DFOP", to = c("M1", "M2"),
-                                          sink = FALSE),
-                            M1 = list(type = "SFO"),
-                            M2 = list(type = "SFO"), use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-
-# The model predictions without intentional error were generated as follows
-sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
-
-d_synth_SFO_lin <- mkinpredict(m_synth_SFO_lin,
-                               c(k_parent = 0.7, f_parent_to_M1 = 0.8,
-                                 k_M1 = 0.3, f_M1_to_M2 = 0.7,
-                                 k_M2 = 0.02),
-                               c(parent = 100, M1 = 0, M2 = 0),
-                               sampling_times)
-
-d_synth_DFOP_lin <- mkinpredict(m_synth_DFOP_lin,
-                                c(k1 = 0.2, k2 = 0.02, g = 0.5,
-                                  f_parent_to_M1 = 0.5, k_M1 = 0.3,
-                                  f_M1_to_M2 = 0.7, k_M2 = 0.02),
-                                 c(parent = 100, M1 = 0, M2 = 0),
-                                 sampling_times)
-
-d_synth_SFO_par <- mkinpredict(m_synth_SFO_par,
-                               c(k_parent = 0.2,
-                                 f_parent_to_M1 = 0.8, k_M1 = 0.01,
-                                 f_parent_to_M2 = 0.2, k_M2 = 0.02),
-                                 c(parent = 100, M1 = 0, M2 = 0),
-                                 sampling_times)
-
-d_synth_DFOP_par <- mkinpredict(m_synth_DFOP_par,
-                               c(k1 = 0.3, k2 = 0.02, g = 0.7,
-                                 f_parent_to_M1 = 0.6, k_M1 = 0.04,
-                                 f_parent_to_M2 = 0.4, k_M2 = 0.01),
-                                 c(parent = 100, M1 = 0, M2 = 0),
-                                 sampling_times)
-
-# Construct names for datasets with errors
-d_synth_names = paste0("d_synth_", c("SFO_lin", "SFO_par",
-                                     "DFOP_lin", "DFOP_par"))
-
-# Original function used or adding errors. The add_err function now published
-# with this package is a slightly generalised version where the names of
-# secondary compartments that should have an initial value of zero (M1 and M2
-# in this case) are not hardcoded any more.
-# add_err = function(d, sdfunc, LOD = 0.1, reps = 2, seed = 123456789)
-# {
-#   set.seed(seed)
-#   d_long = mkin_wide_to_long(d, time = "time")
-#   d_rep = data.frame(lapply(d_long, rep, each = 2))
-#   d_rep$value = rnorm(length(d_rep$value), d_rep$value, sdfunc(d_rep$value))
-#
-#   d_rep[d_rep$time == 0 & d_rep$name %in% c("M1", "M2"), "value"] <- 0
-#   d_NA <- transform(d_rep, value = ifelse(value < LOD, NA, value))
-#   d_NA$value <- round(d_NA$value, 1)
-#   return(d_NA)
-# }
-
-# The following is the simplified version of the two-component model of Rocke
-# and Lorenzato (1995)
-sdfunc_twocomp = function(value, sd_low, rsd_high) {
-  sqrt(sd_low^2 + value^2 * rsd_high^2)
-}
-
-# Add the errors.
-for (d_synth_name in d_synth_names)
-{
-  d_synth = get(d_synth_name)
-  assign(paste0(d_synth_name, "_a"), add_err(d_synth, function(value) 3))
-  assign(paste0(d_synth_name, "_b"), add_err(d_synth, function(value) 7))
-  assign(paste0(d_synth_name, "_c"), add_err(d_synth,
-                           function(value) sdfunc_twocomp(value, 0.5, 0.07)))
-
-}
-
-d_synth_err_names = c(
-  paste(rep(d_synth_names, each = 3), letters[1:3], sep = "_")
-)
-
-# This is just one example of an evaluation using the kinetic model used for
-# the generation of the data
-  fit <- mkinfit(m_synth_SFO_lin, synthetic_data_for_UBA_2014[[1]]$data,
-                 quiet = TRUE)
-  plot_sep(fit)
-
-  summary(fit)
-#> mkin version used for fitting:    1.2.3 
-#> R version used for fitting:       4.2.3 
-#> Date of fit:     Sun Apr 16 08:35:08 2023 
-#> Date of summary: Sun Apr 16 08:35:08 2023 
-#> 
-#> Equations:
-#> d_parent/dt = - k_parent * parent
-#> d_M1/dt = + f_parent_to_M1 * k_parent * parent - k_M1 * M1
-#> d_M2/dt = + f_M1_to_M2 * k_M1 * M1 - k_M2 * M2
-#> 
-#> Model predictions using solution type deSolve 
-#> 
-#> Fitted using 833 model solutions performed in 0.166 s
-#> 
-#> Error model: Constant variance 
-#> 
-#> Error model algorithm: OLS 
-#> 
-#> Starting values for parameters to be optimised:
-#>                   value   type
-#> parent_0       101.3500  state
-#> k_parent         0.1000 deparm
-#> k_M1             0.1001 deparm
-#> k_M2             0.1002 deparm
-#> f_parent_to_M1   0.5000 deparm
-#> f_M1_to_M2       0.5000 deparm
-#> 
-#> Starting values for the transformed parameters actually optimised:
-#>                      value lower upper
-#> parent_0        101.350000  -Inf   Inf
-#> log_k_parent     -2.302585  -Inf   Inf
-#> log_k_M1         -2.301586  -Inf   Inf
-#> log_k_M2         -2.300587  -Inf   Inf
-#> f_parent_qlogis   0.000000  -Inf   Inf
-#> f_M1_qlogis       0.000000  -Inf   Inf
-#> 
-#> Fixed parameter values:
-#>      value  type
-#> M1_0     0 state
-#> M2_0     0 state
-#> 
-#> Results:
-#> 
-#>        AIC      BIC    logLik
-#>   188.7274 200.3723 -87.36368
-#> 
-#> Optimised, transformed parameters with symmetric confidence intervals:
-#>                 Estimate Std. Error   Lower    Upper
-#> parent_0        102.1000    1.57000 98.8600 105.3000
-#> log_k_parent     -0.3020    0.03885 -0.3812  -0.2229
-#> log_k_M1         -1.2070    0.07123 -1.3520  -1.0620
-#> log_k_M2         -3.9010    0.06571 -4.0350  -3.7670
-#> f_parent_qlogis   1.2010    0.23530  0.7216   1.6800
-#> f_M1_qlogis       0.9589    0.24890  0.4520   1.4660
-#> sigma             2.2730    0.25740  1.7490   2.7970
-#> 
-#> Parameter correlation:
-#>                   parent_0 log_k_parent   log_k_M1   log_k_M2 f_parent_qlogis
-#> parent_0         1.000e+00    3.933e-01 -1.605e-01  2.819e-02      -4.624e-01
-#> log_k_parent     3.933e-01    1.000e+00 -4.082e-01  7.166e-02      -5.682e-01
-#> log_k_M1        -1.605e-01   -4.082e-01  1.000e+00 -3.929e-01       7.478e-01
-#> log_k_M2         2.819e-02    7.166e-02 -3.929e-01  1.000e+00      -2.658e-01
-#> f_parent_qlogis -4.624e-01   -5.682e-01  7.478e-01 -2.658e-01       1.000e+00
-#> f_M1_qlogis      1.614e-01    4.102e-01 -8.109e-01  5.419e-01      -8.605e-01
-#> sigma           -2.900e-08   -8.030e-09 -2.741e-08  3.938e-08      -2.681e-08
-#>                 f_M1_qlogis      sigma
-#> parent_0          1.614e-01 -2.900e-08
-#> log_k_parent      4.102e-01 -8.030e-09
-#> log_k_M1         -8.109e-01 -2.741e-08
-#> log_k_M2          5.419e-01  3.938e-08
-#> f_parent_qlogis  -8.605e-01 -2.681e-08
-#> f_M1_qlogis       1.000e+00  4.971e-08
-#> sigma             4.971e-08  1.000e+00
-#> 
-#> Backtransformed parameters:
-#> Confidence intervals for internally transformed parameters are asymmetric.
-#> t-test (unrealistically) based on the assumption of normal distribution
-#> for estimators of untransformed parameters.
-#>                 Estimate t value    Pr(>t)    Lower     Upper
-#> parent_0       102.10000  65.000 7.281e-36 98.86000 105.30000
-#> k_parent         0.73930  25.740 2.948e-23  0.68310   0.80020
-#> k_M1             0.29920  14.040 1.577e-15  0.25880   0.34590
-#> k_M2             0.02023  15.220 1.653e-16  0.01769   0.02312
-#> f_parent_to_M1   0.76870  18.370 7.295e-19  0.67300   0.84290
-#> f_M1_to_M2       0.72290  14.500 6.418e-16  0.61110   0.81240
-#> sigma            2.27300   8.832 2.161e-10  1.74900   2.79700
-#> 
-#> FOCUS Chi2 error levels in percent:
-#>          err.min n.optim df
-#> All data   8.454       6 17
-#> parent     8.660       2  6
-#> M1        10.583       2  5
-#> M2         3.586       2  6
-#> 
-#> Resulting formation fractions:
-#>                 ff
-#> parent_M1   0.7687
-#> parent_sink 0.2313
-#> M1_M2       0.7229
-#> M1_sink     0.2771
-#> 
-#> Estimated disappearance times:
-#>           DT50    DT90
-#> parent  0.9376   3.114
-#> M1      2.3170   7.697
-#> M2     34.2689 113.839
-#> 
-#> Data:
-#>  time variable observed  predicted residual
-#>     0   parent    101.5  1.021e+02 -0.56248
-#>     0   parent    101.2  1.021e+02 -0.86248
-#>     1   parent     53.9  4.873e+01  5.17118
-#>     1   parent     47.5  4.873e+01 -1.22882
-#>     3   parent     10.4  1.111e+01 -0.70773
-#>     3   parent      7.6  1.111e+01 -3.50773
-#>     7   parent      1.1  5.772e-01  0.52283
-#>     7   parent      0.3  5.772e-01 -0.27717
-#>    14   parent      3.5  3.264e-03  3.49674
-#>    28   parent      3.2  1.045e-07  3.20000
-#>    90   parent      0.6  9.530e-10  0.60000
-#>   120   parent      3.5 -5.940e-10  3.50000
-#>     1       M1     36.4  3.479e+01  1.61088
-#>     1       M1     37.4  3.479e+01  2.61088
-#>     3       M1     34.3  3.937e+01 -5.07027
-#>     3       M1     39.8  3.937e+01  0.42973
-#>     7       M1     15.1  1.549e+01 -0.38715
-#>     7       M1     17.8  1.549e+01  2.31285
-#>    14       M1      5.8  1.995e+00  3.80469
-#>    14       M1      1.2  1.995e+00 -0.79531
-#>    60       M1      0.5  2.111e-06  0.50000
-#>    90       M1      3.2 -9.670e-10  3.20000
-#>   120       M1      1.5  7.670e-10  1.50000
-#>   120       M1      0.6  7.670e-10  0.60000
-#>     1       M2      4.8  4.455e+00  0.34517
-#>     3       M2     20.9  2.153e+01 -0.62527
-#>     3       M2     19.3  2.153e+01 -2.22527
-#>     7       M2     42.0  4.192e+01  0.07941
-#>     7       M2     43.1  4.192e+01  1.17941
-#>    14       M2     49.4  4.557e+01  3.83353
-#>    14       M2     44.3  4.557e+01 -1.26647
-#>    28       M2     34.6  3.547e+01 -0.87275
-#>    28       M2     33.0  3.547e+01 -2.47275
-#>    60       M2     18.8  1.858e+01  0.21837
-#>    60       M2     17.6  1.858e+01 -0.98163
-#>    90       M2     10.6  1.013e+01  0.47130
-#>    90       M2     10.8  1.013e+01  0.67130
-#>   120       M2      9.8  5.521e+00  4.27893
-#>   120       M2      3.3  5.521e+00 -2.22107
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/test_data_from_UBA_2014-1.png b/docs/dev/reference/test_data_from_UBA_2014-1.png
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diff --git a/docs/dev/reference/test_data_from_UBA_2014.html b/docs/dev/reference/test_data_from_UBA_2014.html
deleted file mode 100644
index 8b0194f6..00000000
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+++ /dev/null
@@ -1,236 +0,0 @@
-
-Three experimental datasets from two water sediment systems and one soil — test_data_from_UBA_2014 • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Three experimental datasets from two water sediment systems and one soil
      
-    
-    
-    
      
-
-    
      
-    
      The datasets were used for the comparative validation of several kinetic evaluation
- software packages (Ranke, 2014).
      
-    
      
-
-    
      
-    
      test_data_from_UBA_2014
      
-    
      
-
-    
      
-    
      Format
      
-    
      A list containing three datasets as an R6 class defined by mkinds.
-  Each dataset has, among others, the following components
      title
      
-
      The name of the dataset, e.g. UBA_2014_WS_river
      
-
-    
      data
      
-
      A data frame with the data in the form expected by mkinfit
      
-
-  
-
      
-    
      
-    
      Source
      
-    
      Ranke (2014) Prüfung und Validierung von Modellierungssoftware als Alternative
-  zu ModelMaker 4.0, Umweltbundesamt Projektnummer 27452
      
-    
      
-
-    
      
-    
      Examples
      
-    
        # \dontrun{
-  # This is a level P-II evaluation of the dataset according to the FOCUS kinetics
-  # guidance. Due to the strong correlation of the parameter estimates, the
-  # covariance matrix is not returned. Note that level P-II evaluations are
-  # generally considered deprecated due to the frequent occurrence of such
-  # large parameter correlations, among other reasons (e.g. the adequacy of the
-  # model).
-  m_ws <- mkinmod(parent_w = mkinsub("SFO", "parent_s"),
-                  parent_s = mkinsub("SFO", "parent_w"))
-#> Temporary DLL for differentials generated and loaded
-  f_river <- mkinfit(m_ws, test_data_from_UBA_2014[[1]]$data, quiet = TRUE)
-#> Warning: Observations with value of zero were removed from the data
-  plot_sep(f_river)
-
-
-  summary(f_river)$bpar
-#> Warning: Could not calculate correlation; no covariance matrix
-#>                           Estimate se_notrans t value Pr(>t) Lower Upper
-#> parent_w_0             95.91998118         NA      NA     NA    NA    NA
-#> k_parent_w              0.41145375         NA      NA     NA    NA    NA
-#> k_parent_s              0.04663944         NA      NA     NA    NA    NA
-#> f_parent_w_to_parent_s  0.12467894         NA      NA     NA    NA    NA
-#> f_parent_s_to_parent_w  0.50000000         NA      NA     NA    NA    NA
-#> sigma                   3.13612618         NA      NA     NA    NA    NA
-  mkinerrmin(f_river)
-#>            err.min n.optim df
-#> All data 0.1090929       5  6
-#> parent_w 0.0817436       3  3
-#> parent_s 0.1619965       2  3
-
-  # This is the evaluation used for the validation of software packages
-  # in the expertise from 2014
-  m_soil <- mkinmod(parent = mkinsub("SFO", c("M1", "M2")),
-                    M1 = mkinsub("SFO", "M3"),
-                    M2 = mkinsub("SFO", "M3"),
-                    M3 = mkinsub("SFO"),
-                    use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-
-  f_soil <- mkinfit(m_soil, test_data_from_UBA_2014[[3]]$data, quiet = TRUE)
-#> Warning: Observations with value of zero were removed from the data
-  plot_sep(f_soil, lpos = c("topright", "topright", "topright", "bottomright"))
-
-  summary(f_soil)$bpar
-#>                   Estimate  se_notrans    t value       Pr(>t)        Lower
-#> parent_0       76.55425650 0.859186399 89.1008710 1.113861e-26 74.755959418
-#> k_parent        0.12081956 0.004601918 26.2541722 1.077359e-16  0.111561575
-#> k_M1            0.84258615 0.806160102  1.0451846 1.545268e-01  0.113779609
-#> k_M2            0.04210880 0.017083034  2.4649483 1.170188e-02  0.018013857
-#> k_M3            0.01122918 0.007245856  1.5497385 6.885052e-02  0.002909431
-#> f_parent_to_M1  0.32240200 0.240783943  1.3389680 9.819076e-02           NA
-#> f_parent_to_M2  0.16099855 0.033691952  4.7785464 6.531136e-05           NA
-#> f_M1_to_M3      0.27921507 0.269423780  1.0363416 1.565267e-01  0.022978205
-#> f_M2_to_M3      0.55641252 0.595119966  0.9349586 1.807707e-01  0.008002509
-#> sigma           1.14005399 0.149696423  7.6157731 1.727024e-07  0.826735778
-#>                      Upper
-#> parent_0       78.35255358
-#> k_parent        0.13084582
-#> k_M1            6.23970702
-#> k_M2            0.09843260
-#> k_M3            0.04333992
-#> f_parent_to_M1          NA
-#> f_parent_to_M2          NA
-#> f_M1_to_M3      0.86450775
-#> f_M2_to_M3      0.99489895
-#> sigma           1.45337221
-  mkinerrmin(f_soil)
-#>             err.min n.optim df
-#> All data 0.09649963       9 20
-#> parent   0.04721283       2  6
-#> M1       0.26551208       2  5
-#> M2       0.20327575       2  5
-#> M3       0.05196550       3  4
-  # }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.7.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/tex_listing.html b/docs/dev/reference/tex_listing.html
deleted file mode 100644
index 03bd83f2..00000000
--- a/docs/dev/reference/tex_listing.html
+++ /dev/null
@@ -1,143 +0,0 @@
-
-Wrap the output of a summary function in tex listing environment — tex_listing • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Wrap the output of a summary function in tex listing environment
      
-    Source: R/tex_listing.R
-    
-    
      
-
-    
      
-    
      This function can be used in a R markdown code chunk with the chunk
-option results = "asis".
      
-    
      
-
-    
      
-    
      tex_listing(object, caption = NULL, label = NULL, clearpage = TRUE)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      The object for which the summary is to be listed
      
-
-
-
      caption
      
-
      An optional caption
      
-
-
-
      label
      
-
      An optional label
      
-
-
-
      clearpage
      
-
      Should a new page be started after the listing?
      
-
-
      
-
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.6.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/tffm0.html b/docs/dev/reference/tffm0.html
deleted file mode 100644
index 8988b5a2..00000000
--- a/docs/dev/reference/tffm0.html
+++ /dev/null
@@ -1,158 +0,0 @@
-
-Transform formation fractions as in the first published mkin version — tffm0 • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Transform formation fractions as in the first published mkin version
      
-    Source: R/tffm0.R
-    
-    
      
-
-    
      
-    
      The transformed fractions can be restricted between 0 and 1 in model
-optimisations. Therefore this transformation was used originally in mkin. It
-was later replaced by the ilr transformation because the ilr transformed
-fractions can assumed to follow normal distribution. As the ilr
-transformation is not available in RxODE and can therefore not be used in
-the nlmixr modelling language, this transformation is currently used for
-translating mkin models with formation fractions to more than one target
-compartment for fitting with nlmixr in nlmixr_model. However,
-this implementation cannot be used there, as it is not accessible
-from RxODE.
      
-    
      
-
-    
      
-    
      tffm0(ff)
-
-invtffm0(ff_trans)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      ff
      
-
      Vector of untransformed formation fractions. The sum
-must be smaller or equal to one
      
-
      ff_trans
      
-
      Vector of transformed formation fractions that can be
-restricted to the interval from 0 to 1
      
-
      
-    
      
-    
      Value
      
-    
      A vector of the transformed formation fractions
-A vector of backtransformed formation fractions for natural use in degradation models
      
-    
      
-
-    
      
-    
      Examples
      
-    
      ff_example <- c(
-  0.10983681, 0.09035905, 0.08399383
-)
-ff_example_trans <- tffm0(ff_example)
-invtffm0(ff_example_trans)
-#> [1] 0.10983681 0.09035905 0.08399383
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
-
-
      
-  
      Site built with pkgdown 2.0.2.
      
-
      
-
-      
      
-
-  
-
-
-  
-
-  
-
diff --git a/docs/dev/reference/transform_odeparms.html b/docs/dev/reference/transform_odeparms.html
deleted file mode 100644
index 4cb2e575..00000000
--- a/docs/dev/reference/transform_odeparms.html
+++ /dev/null
@@ -1,336 +0,0 @@
-
-Functions to transform and backtransform kinetic parameters for fitting — transform_odeparms • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Functions to transform and backtransform kinetic parameters for fitting
      
-    Source: R/transform_odeparms.R
-    
-    
      
-
-    
      
-    
      The transformations are intended to map parameters that should only take on
-restricted values to the full scale of real numbers. For kinetic rate
-constants and other parameters that can only take on positive values, a
-simple log transformation is used. For compositional parameters, such as the
-formations fractions that should always sum up to 1 and can not be negative,
-the ilr transformation is used.
      
-    
      
-
-    
      
-    
      transform_odeparms(
-  parms,
-  mkinmod,
-  transform_rates = TRUE,
-  transform_fractions = TRUE
-)
-
-backtransform_odeparms(
-  transparms,
-  mkinmod,
-  transform_rates = TRUE,
-  transform_fractions = TRUE
-)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      parms
      
-
      Parameters of kinetic models as used in the differential
-equations.
      
-
-
-
      mkinmod
      
-
      The kinetic model of class mkinmod, containing
-the names of the model variables that are needed for grouping the
-formation fractions before ilr transformation, the parameter
-names and the information if the pathway to sink is included in the model.
      
-
-
-
      transform_rates
      
-
      Boolean specifying if kinetic rate constants should
-be transformed in the model specification used in the fitting for better
-compliance with the assumption of normal distribution of the estimator. If
-TRUE, also alpha and beta parameters of the FOMC model are
-log-transformed, as well as k1 and k2 rate constants for the DFOP and HS
-models and the break point tb of the HS model.
      
-
-
-
      transform_fractions
      
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      Boolean specifying if formation fractions
-constants should be transformed in the model specification used in the
-fitting for better compliance with the assumption of normal distribution
-of the estimator. The default (TRUE) is to do transformations.
-The g parameter of the DFOP model is also seen as a fraction.
-If a single fraction is transformed (g parameter of DFOP or only a single
-target variable e.g. a single metabolite plus a pathway to sink), a
-logistic transformation is used stats::qlogis(). In other cases, i.e. if
-two or more formation fractions need to be transformed whose sum cannot
-exceed one, the ilr transformation is used.
      
-
-
-
      transparms
      
-
      Transformed parameters of kinetic models as used in the
-fitting procedure.
      
-
-
      
-    
      
-    
      Value
      
-    
-
-
      A vector of transformed or backtransformed parameters
      
-    
      
-    
      
-    
      Details
      
-    
      The transformation of sets of formation fractions is fragile, as it supposes
-the same ordering of the components in forward and backward transformation.
-This is no problem for the internal use in mkinfit.
      
-    
      
-    
      
-    
      Author
      
-    
      Johannes Ranke
      
-    
      
-
-    
      
-    
      Examples
      
-    
      
-SFO_SFO <- mkinmod(
-  parent = list(type = "SFO", to = "m1", sink = TRUE),
-  m1 = list(type = "SFO"), use_of_ff = "min")
-#> Temporary DLL for differentials generated and loaded
-
-# Fit the model to the FOCUS example dataset D using defaults
-FOCUS_D <- subset(FOCUS_2006_D, value != 0) # remove zero values to avoid warning
-fit <- mkinfit(SFO_SFO, FOCUS_D, quiet = TRUE)
-fit.s <- summary(fit)
-# Transformed and backtransformed parameters
-print(fit.s$par, 3)
-#>                   Estimate Std. Error Lower  Upper
-#> parent_0             99.60     1.5702 96.40 102.79
-#> log_k_parent_sink    -3.04     0.0763 -3.19  -2.88
-#> log_k_parent_m1      -2.98     0.0403 -3.06  -2.90
-#> log_k_m1_sink        -5.25     0.1332 -5.52  -4.98
-#> sigma                 3.13     0.3585  2.40   3.85
-print(fit.s$bpar, 3)
-#>               Estimate se_notrans t value   Pr(>t)    Lower    Upper
-#> parent_0      99.59848    1.57022   63.43 2.30e-36 96.40384 102.7931
-#> k_parent_sink  0.04792    0.00365   13.11 6.13e-15  0.04103   0.0560
-#> k_parent_m1    0.05078    0.00205   24.80 3.27e-23  0.04678   0.0551
-#> k_m1_sink      0.00526    0.00070    7.51 6.16e-09  0.00401   0.0069
-#> sigma          3.12550    0.35852    8.72 2.24e-10  2.39609   3.8549
-
-# \dontrun{
-# Compare to the version without transforming rate parameters (does not work
-# with analytical solution, we get NA values for m1 in predictions)
-fit.2 <- mkinfit(SFO_SFO, FOCUS_D, transform_rates = FALSE,
-  solution_type = "deSolve", quiet = TRUE)
-fit.2.s <- summary(fit.2)
-print(fit.2.s$par, 3)
-#>               Estimate Std. Error    Lower    Upper
-#> parent_0      99.59848    1.57022 96.40384 1.03e+02
-#> k_parent_sink  0.04792    0.00365  0.04049 5.54e-02
-#> k_parent_m1    0.05078    0.00205  0.04661 5.49e-02
-#> k_m1_sink      0.00526    0.00070  0.00384 6.69e-03
-#> sigma          3.12550    0.35852  2.39609 3.85e+00
-print(fit.2.s$bpar, 3)
-#>               Estimate se_notrans t value   Pr(>t)    Lower    Upper
-#> parent_0      99.59848    1.57022   63.43 2.30e-36 96.40384 1.03e+02
-#> k_parent_sink  0.04792    0.00365   13.11 6.13e-15  0.04049 5.54e-02
-#> k_parent_m1    0.05078    0.00205   24.80 3.27e-23  0.04661 5.49e-02
-#> k_m1_sink      0.00526    0.00070    7.51 6.16e-09  0.00384 6.69e-03
-#> sigma          3.12550    0.35852    8.72 2.24e-10  2.39609 3.85e+00
-# }
-
-initials <- fit$start$value
-names(initials) <- rownames(fit$start)
-transformed <- fit$start_transformed$value
-names(transformed) <- rownames(fit$start_transformed)
-transform_odeparms(initials, SFO_SFO)
-#>          parent_0 log_k_parent_sink   log_k_parent_m1     log_k_m1_sink 
-#>        100.750000         -2.302585         -2.301586         -2.300587 
-backtransform_odeparms(transformed, SFO_SFO)
-#>      parent_0 k_parent_sink   k_parent_m1     k_m1_sink 
-#>      100.7500        0.1000        0.1001        0.1002 
-
-# \dontrun{
-# The case of formation fractions (this is now the default)
-SFO_SFO.ff <- mkinmod(
-  parent = list(type = "SFO", to = "m1", sink = TRUE),
-  m1 = list(type = "SFO"),
-  use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-
-fit.ff <- mkinfit(SFO_SFO.ff, FOCUS_D, quiet = TRUE)
-fit.ff.s <- summary(fit.ff)
-print(fit.ff.s$par, 3)
-#>                 Estimate Std. Error  Lower  Upper
-#> parent_0         99.5985     1.5702 96.404 102.79
-#> log_k_parent     -2.3157     0.0409 -2.399  -2.23
-#> log_k_m1         -5.2475     0.1332 -5.518  -4.98
-#> f_parent_qlogis   0.0579     0.0893 -0.124   0.24
-#> sigma             3.1255     0.3585  2.396   3.85
-print(fit.ff.s$bpar, 3)
-#>                Estimate se_notrans t value   Pr(>t)    Lower    Upper
-#> parent_0       99.59848    1.57022   63.43 2.30e-36 96.40383 102.7931
-#> k_parent        0.09870    0.00403   24.47 4.96e-23  0.09082   0.1073
-#> k_m1            0.00526    0.00070    7.51 6.16e-09  0.00401   0.0069
-#> f_parent_to_m1  0.51448    0.02230   23.07 3.10e-22  0.46912   0.5596
-#> sigma           3.12550    0.35852    8.72 2.24e-10  2.39609   3.8549
-initials <- c("f_parent_to_m1" = 0.5)
-transformed <- transform_odeparms(initials, SFO_SFO.ff)
-backtransform_odeparms(transformed, SFO_SFO.ff)
-#> f_parent_to_m1 
-#>            0.5 
-
-# And without sink
-SFO_SFO.ff.2 <- mkinmod(
-  parent = list(type = "SFO", to = "m1", sink = FALSE),
-  m1 = list(type = "SFO"),
-  use_of_ff = "max")
-#> Temporary DLL for differentials generated and loaded
-
-
-fit.ff.2 <- mkinfit(SFO_SFO.ff.2, FOCUS_D, quiet = TRUE)
-fit.ff.2.s <- summary(fit.ff.2)
-print(fit.ff.2.s$par, 3)
-#>              Estimate Std. Error Lower Upper
-#> parent_0        84.79      3.012 78.67 90.91
-#> log_k_parent    -2.76      0.082 -2.92 -2.59
-#> log_k_m1        -4.21      0.123 -4.46 -3.96
-#> sigma            8.22      0.943  6.31 10.14
-print(fit.ff.2.s$bpar, 3)
-#>          Estimate se_notrans t value   Pr(>t)   Lower  Upper
-#> parent_0  84.7916    3.01203   28.15 1.92e-25 78.6704 90.913
-#> k_parent   0.0635    0.00521   12.19 2.91e-14  0.0538  0.075
-#> k_m1       0.0148    0.00182    8.13 8.81e-10  0.0115  0.019
-#> sigma      8.2229    0.94323    8.72 1.73e-10  6.3060 10.140
-# }
-
-
      
-    
      
-  
      
-  
-
      
-
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-      
      
-  
      Developed by Johannes Ranke.
      
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      Site built with pkgdown 2.0.7.
      
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-
-Update an mkinfit model with different arguments — update.mkinfit • mkin
-    
-
-    
      
-      
      
-
-      
-
-      
      
-  
      
-    
      
-    
      Update an mkinfit model with different arguments
      
-    Source: R/update.mkinfit.R
-    
-    
      
-
-    
      
-    
      This function will return an updated mkinfit object. The fitted degradation
-model parameters from the old fit are used as starting values for the
-updated fit. Values specified as 'parms.ini' and/or 'state.ini' will
-override these starting values.
      
-    
      
-
-    
      
-    
      # S3 method for mkinfit
-update(object, ..., evaluate = TRUE)
      
-    
      
-
-    
      
-    
      Arguments
      
-    
      object
      
-
      An mkinfit object to be updated
      
-
-
-
      ...
      
-
      Arguments to mkinfit that should replace
-the arguments from the original call. Arguments set to NULL will
-remove arguments given in the original call
      
-
-
-
      evaluate
      
-
      Should the call be evaluated or returned as a call
      
-
-
      
-
-    
      
-    
      Examples
      
-    
      # \dontrun{
-fit <- mkinfit("SFO", subset(FOCUS_2006_D, value != 0), quiet = TRUE)
-parms(fit)
-#>    parent_0    k_parent       sigma 
-#> 99.44423885  0.09793574  3.39632469 
-plot_err(fit)
-
-fit_2 <- update(fit, error_model = "tc")
-parms(fit_2)
-#>     parent_0     k_parent    sigma_low     rsd_high 
-#> 1.008549e+02 1.005665e-01 3.752222e-03 6.763434e-02 
-plot_err(fit_2)
-
-# }
-
      
-    
      
-  
      
-  
-
      
-
-
-      
      
-  
      Developed by Johannes Ranke.
      
-
      
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-  
      Site built with pkgdown 2.0.7.
      
-
      
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-/* Docsearch -------------------------------------------------------------- */
-/*
-  Source: https://github.com/algolia/docsearch/
-  License: MIT
-*/
-
-.algolia-autocomplete {
-  display: block;
-  -webkit-box-flex: 1;
-  -ms-flex: 1;
-  flex: 1
-}
-
-.algolia-autocomplete .ds-dropdown-menu {
-  width: 100%;
-  min-width: none;
-  max-width: none;
-  padding: .75rem 0;
-  background-color: #fff;
-  background-clip: padding-box;
-  border: 1px solid rgba(0, 0, 0, .1);
-  box-shadow: 0 .5rem 1rem rgba(0, 0, 0, .175);
-}
-
-@media (min-width:768px) {
-  .algolia-autocomplete .ds-dropdown-menu {
-      width: 175%
-  }
-}
-
-.algolia-autocomplete .ds-dropdown-menu::before {
-  display: none
-}
-
-.algolia-autocomplete .ds-dropdown-menu [class^=ds-dataset-] {
-  padding: 0;
-  background-color: rgb(255,255,255);
-  border: 0;
-  max-height: 80vh;
-}
-
-.algolia-autocomplete .ds-dropdown-menu .ds-suggestions {
-  margin-top: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion {
-  padding: 0;
-  overflow: visible
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--category-header {
-  padding: .125rem 1rem;
-  margin-top: 0;
-  font-size: 1.3em;
-  font-weight: 500;
-  color: #00008B;
-  border-bottom: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--wrapper {
-    float: none;
-    padding-top: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--subcategory-column {
-  float: none;
-  width: auto;
-  padding: 0;
-  text-align: left
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--content {
-  float: none;
-  width: auto;
-  padding: 0
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--content::before {
-  display: none
-}
-
-.algolia-autocomplete .ds-suggestion:not(:first-child) .algolia-docsearch-suggestion--category-header {
-  padding-top: .75rem;
-  margin-top: .75rem;
-  border-top: 1px solid rgba(0, 0, 0, .1)
-}
-
-.algolia-autocomplete .ds-suggestion .algolia-docsearch-suggestion--subcategory-column {
-  display: block;
-  padding: .1rem 1rem;
-  margin-bottom: 0.1;
-  font-size: 1.0em;
-  font-weight: 400
-  /* display: none */
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--title {
-  display: block;
-  padding: .25rem 1rem;
-  margin-bottom: 0;
-  font-size: 0.9em;
-  font-weight: 400
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--text {
-  padding: 0 1rem .5rem;
-  margin-top: -.25rem;
-  font-size: 0.8em;
-  font-weight: 400;
-  line-height: 1.25
-}
-
-.algolia-autocomplete .algolia-docsearch-footer {
-  width: 110px;
-  height: 20px;
-  z-index: 3;
-  margin-top: 10.66667px;
-  float: right;
-  font-size: 0;
-  line-height: 0;
-}
-
-.algolia-autocomplete .algolia-docsearch-footer--logo {
-  background-image: url("data:image/svg+xml;utf8,");
-  background-repeat: no-repeat;
-  background-position: 50%;
-  background-size: 100%;
-  overflow: hidden;
-  text-indent: -9000px;
-  width: 100%;
-  height: 100%;
-  display: block;
-  transform: translate(-8px);
-}
-
-.algolia-autocomplete .algolia-docsearch-suggestion--highlight {
-  color: #FF8C00;
-  background: rgba(232, 189, 54, 0.1)
-}
-
-
-.algolia-autocomplete .algolia-docsearch-suggestion--text .algolia-docsearch-suggestion--highlight {
-  box-shadow: inset 0 -2px 0 0 rgba(105, 105, 105, .5)
-}
-
-.algolia-autocomplete .ds-suggestion.ds-cursor .algolia-docsearch-suggestion--content {
-  background-color: rgba(192, 192, 192, .15)
-}
diff --git a/docs/docsearch.js b/docs/docsearch.js
deleted file mode 100644
index b35504cd..00000000
--- a/docs/docsearch.js
+++ /dev/null
@@ -1,85 +0,0 @@
-$(function() {
-
-  // register a handler to move the focus to the search bar
-  // upon pressing shift + "/" (i.e. "?")
-  $(document).on('keydown', function(e) {
-    if (e.shiftKey && e.keyCode == 191) {
-      e.preventDefault();
-      $("#search-input").focus();
-    }
-  });
-
-  $(document).ready(function() {
-    // do keyword highlighting
-    /* modified from https://jsfiddle.net/julmot/bL6bb5oo/ */
-    var mark = function() {
-
-      var referrer = document.URL ;
-      var paramKey = "q" ;
-
-      if (referrer.indexOf("?") !== -1) {
-        var qs = referrer.substr(referrer.indexOf('?') + 1);
-        var qs_noanchor = qs.split('#')[0];
-        var qsa = qs_noanchor.split('&');
-        var keyword = "";
-
-        for (var i = 0; i < qsa.length; i++) {
-          var currentParam = qsa[i].split('=');
-
-          if (currentParam.length !== 2) {
-            continue;
-          }
-
-          if (currentParam[0] == paramKey) {
-            keyword = decodeURIComponent(currentParam[1].replace(/\+/g, "%20"));
-          }
-        }
-
-        if (keyword !== "") {
-          $(".contents").unmark({
-            done: function() {
-              $(".contents").mark(keyword);
-            }
-          });
-        }
-      }
-    };
-
-    mark();
-  });
-});
-
-/* Search term highlighting ------------------------------*/
-
-function matchedWords(hit) {
-  var words = [];
-
-  var hierarchy = hit._highlightResult.hierarchy;
-  // loop to fetch from lvl0, lvl1, etc.
-  for (var idx in hierarchy) {
-    words = words.concat(hierarchy[idx].matchedWords);
-  }
-
-  var content = hit._highlightResult.content;
-  if (content) {
-    words = words.concat(content.matchedWords);
-  }
-
-  // return unique words
-  var words_uniq = [...new Set(words)];
-  return words_uniq;
-}
-
-function updateHitURL(hit) {
-
-  var words = matchedWords(hit);
-  var url = "";
-
-  if (hit.anchor) {
-    url = hit.url_without_anchor + '?q=' + escape(words.join(" ")) + '#' + hit.anchor;
-  } else {
-    url = hit.url + '?q=' + escape(words.join(" "));
-  }
-
-  return url;
-}
diff --git a/docs/index.html b/docs/index.html
index 1a3b4f81..ef4fc650 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -7,8 +7,10 @@
 
 Kinetic Evaluation of Chemical Degradation Data • mkin
 
-
-
+
+
+
+
 
 
 
diff --git a/docs/katex-auto.js b/docs/katex-auto.js
new file mode 100644
index 00000000..20651d9f
--- /dev/null
+++ b/docs/katex-auto.js
@@ -0,0 +1,14 @@
+// https://github.com/jgm/pandoc/blob/29fa97ab96b8e2d62d48326e1b949a71dc41f47a/src/Text/Pandoc/Writers/HTML.hs#L332-L345
+document.addEventListener("DOMContentLoaded", function () {
+  var mathElements = document.getElementsByClassName("math");
+  var macros = [];
+  for (var i = 0; i < mathElements.length; i++) {
+    var texText = mathElements[i].firstChild;
+    if (mathElements[i].tagName == "SPAN") {
+      katex.render(texText.data, mathElements[i], {
+        displayMode: mathElements[i].classList.contains("display"),
+        throwOnError: false,
+        macros: macros,
+        fleqn: false
+      });
+    }}});
diff --git a/docs/lightswitch.js b/docs/lightswitch.js
new file mode 100644
index 00000000..9467125a
--- /dev/null
+++ b/docs/lightswitch.js
@@ -0,0 +1,85 @@
+
+/*!
+ * Color mode toggler for Bootstrap's docs (https://getbootstrap.com/)
+ * Copyright 2011-2023 The Bootstrap Authors
+ * Licensed under the Creative Commons Attribution 3.0 Unported License.
+ * Updates for {pkgdown} by the {bslib} authors, also licensed under CC-BY-3.0.
+ */
+
+const getStoredTheme = () => localStorage.getItem('theme')
+const setStoredTheme = theme => localStorage.setItem('theme', theme)
+
+const getPreferredTheme = () => {
+  const storedTheme = getStoredTheme()
+  if (storedTheme) {
+    return storedTheme
+  }
+
+  return window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light'
+}
+
+const setTheme = theme => {
+  if (theme === 'auto') {
+    document.documentElement.setAttribute('data-bs-theme', (window.matchMedia('(prefers-color-scheme: dark)').matches ? 'dark' : 'light'))
+  } else {
+    document.documentElement.setAttribute('data-bs-theme', theme)
+  }
+}
+
+function bsSetupThemeToggle () {
+  'use strict'
+
+  const showActiveTheme = (theme, focus = false) => {
+    var activeLabel, activeIcon;
+
+    document.querySelectorAll('[data-bs-theme-value]').forEach(element => {
+      const buttonTheme = element.getAttribute('data-bs-theme-value')
+      const isActive = buttonTheme == theme
+      
+      element.classList.toggle('active', isActive)
+      element.setAttribute('aria-pressed', isActive)
+
+      if (isActive) {
+        activeLabel = element.textContent;
+        activeIcon = element.querySelector('span').classList.value;
+      }
+    })
+
+    const themeSwitcher = document.querySelector('#dropdown-lightswitch')
+    if (!themeSwitcher) {
+      return
+    }
+
+    themeSwitcher.setAttribute('aria-label', activeLabel)
+    themeSwitcher.querySelector('span').classList.value = activeIcon;
+
+    if (focus) {
+      themeSwitcher.focus()
+    }
+  }
+
+  window.matchMedia('(prefers-color-scheme: dark)').addEventListener('change', () => {
+    const storedTheme = getStoredTheme()
+    if (storedTheme !== 'light' && storedTheme !== 'dark') {
+      setTheme(getPreferredTheme())
+    }
+  })
+
+  window.addEventListener('DOMContentLoaded', () => {
+    showActiveTheme(getPreferredTheme())
+
+    document
+      .querySelectorAll('[data-bs-theme-value]')
+      .forEach(toggle => {
+        toggle.addEventListener('click', () => {
+          const theme = toggle.getAttribute('data-bs-theme-value')
+          setTheme(theme)
+          setStoredTheme(theme)
+          showActiveTheme(theme, true)
+        })
+      })
+  })
+}
+
+setTheme(getPreferredTheme());
+bsSetupThemeToggle();
diff --git a/docs/news/index.html b/docs/news/index.html
index 44de0536..c1837d9d 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -1,5 +1,5 @@
 
-Changelog • mkin
+Changelog • mkin
     Skip to contents
 
 
@@ -61,7 +61,10 @@
 
     
      
 
      mkin 1.2.9
      
-
      • ’R/create_deg_func.R: Make sure that no reversible reactions are specified in the case of two observed variables, as this is not supported
        • 
+
        • ‘R/plot.mixed.R’: Support more than 25 datasets
          • 
+
        • ‘R/mkinfit.R’: Support passing the observed data as a ‘tibble’
          • 
+
        • ‘R/parplot.R’: Support multistart objects with covariate models and filter negative values of scaled parameters (with a warning) for plotting.
          • 
+
        • ’R/create_deg_func.R: Make sure that no reversible reactions are specified in the case of two observed variables, as this is not supported
          • 
 
      
     
      
 
      mkin 1.2.8 (unreleased)
      
diff --git a/docs/pkgdown.css b/docs/pkgdown.css
deleted file mode 100644
index 80ea5b83..00000000
--- a/docs/pkgdown.css
+++ /dev/null
@@ -1,384 +0,0 @@
-/* Sticky footer */
-
-/**
- * Basic idea: https://philipwalton.github.io/solved-by-flexbox/demos/sticky-footer/
- * Details: https://github.com/philipwalton/solved-by-flexbox/blob/master/assets/css/components/site.css
- *
- * .Site -> body > .container
- * .Site-content -> body > .container .row
- * .footer -> footer
- *
- * Key idea seems to be to ensure that .container and __all its parents__
- * have height set to 100%
- *
- */
-
-html, body {
-  height: 100%;
-}
-
-body {
-  position: relative;
-}
-
-body > .container {
-  display: flex;
-  height: 100%;
-  flex-direction: column;
-}
-
-body > .container .row {
-  flex: 1 0 auto;
-}
-
-footer {
-  margin-top: 45px;
-  padding: 35px 0 36px;
-  border-top: 1px solid #e5e5e5;
-  color: #666;
-  display: flex;
-  flex-shrink: 0;
-}
-footer p {
-  margin-bottom: 0;
-}
-footer div {
-  flex: 1;
-}
-footer .pkgdown {
-  text-align: right;
-}
-footer p {
-  margin-bottom: 0;
-}
-
-img.icon {
-  float: right;
-}
-
-/* Ensure in-page images don't run outside their container */
-.contents img {
-  max-width: 100%;
-  height: auto;
-}
-
-/* Fix bug in bootstrap (only seen in firefox) */
-summary {
-  display: list-item;
-}
-
-/* Typographic tweaking ---------------------------------*/
-
-.contents .page-header {
-  margin-top: calc(-60px + 1em);
-}
-
-dd {
-  margin-left: 3em;
-}
-
-/* Section anchors ---------------------------------*/
-
-a.anchor {
-  display: none;
-  margin-left: 5px;
-  width: 20px;
-  height: 20px;
-
-  background-image: url(./link.svg);
-  background-repeat: no-repeat;
-  background-size: 20px 20px;
-  background-position: center center;
-}
-
-h1:hover .anchor,
-h2:hover .anchor,
-h3:hover .anchor,
-h4:hover .anchor,
-h5:hover .anchor,
-h6:hover .anchor {
-  display: inline-block;
-}
-
-/* Fixes for fixed navbar --------------------------*/
-
-.contents h1, .contents h2, .contents h3, .contents h4 {
-  padding-top: 60px;
-  margin-top: -40px;
-}
-
-/* Navbar submenu --------------------------*/
-
-.dropdown-submenu {
-  position: relative;
-}
-
-.dropdown-submenu>.dropdown-menu {
-  top: 0;
-  left: 100%;
-  margin-top: -6px;
-  margin-left: -1px;
-  border-radius: 0 6px 6px 6px;
-}
-
-.dropdown-submenu:hover>.dropdown-menu {
-  display: block;
-}
-
-.dropdown-submenu>a:after {
-  display: block;
-  content: " ";
-  float: right;
-  width: 0;
-  height: 0;
-  border-color: transparent;
-  border-style: solid;
-  border-width: 5px 0 5px 5px;
-  border-left-color: #cccccc;
-  margin-top: 5px;
-  margin-right: -10px;
-}
-
-.dropdown-submenu:hover>a:after {
-  border-left-color: #ffffff;
-}
-
-.dropdown-submenu.pull-left {
-  float: none;
-}
-
-.dropdown-submenu.pull-left>.dropdown-menu {
-  left: -100%;
-  margin-left: 10px;
-  border-radius: 6px 0 6px 6px;
-}
-
-/* Sidebar --------------------------*/
-
-#pkgdown-sidebar {
-  margin-top: 30px;
-  position: -webkit-sticky;
-  position: sticky;
-  top: 70px;
-}
-
-#pkgdown-sidebar h2 {
-  font-size: 1.5em;
-  margin-top: 1em;
-}
-
-#pkgdown-sidebar h2:first-child {
-  margin-top: 0;
-}
-
-#pkgdown-sidebar .list-unstyled li {
-  margin-bottom: 0.5em;
-}
-
-/* bootstrap-toc tweaks ------------------------------------------------------*/
-
-/* All levels of nav */
-
-nav[data-toggle='toc'] .nav > li > a {
-  padding: 4px 20px 4px 6px;
-  font-size: 1.5rem;
-  font-weight: 400;
-  color: inherit;
-}
-
-nav[data-toggle='toc'] .nav > li > a:hover,
-nav[data-toggle='toc'] .nav > li > a:focus {
-  padding-left: 5px;
-  color: inherit;
-  border-left: 1px solid #878787;
-}
-
-nav[data-toggle='toc'] .nav > .active > a,
-nav[data-toggle='toc'] .nav > .active:hover > a,
-nav[data-toggle='toc'] .nav > .active:focus > a {
-  padding-left: 5px;
-  font-size: 1.5rem;
-  font-weight: 400;
-  color: inherit;
-  border-left: 2px solid #878787;
-}
-
-/* Nav: second level (shown on .active) */
-
-nav[data-toggle='toc'] .nav .nav {
-  display: none; /* Hide by default, but at >768px, show it */
-  padding-bottom: 10px;
-}
-
-nav[data-toggle='toc'] .nav .nav > li > a {
-  padding-left: 16px;
-  font-size: 1.35rem;
-}
-
-nav[data-toggle='toc'] .nav .nav > li > a:hover,
-nav[data-toggle='toc'] .nav .nav > li > a:focus {
-  padding-left: 15px;
-}
-
-nav[data-toggle='toc'] .nav .nav > .active > a,
-nav[data-toggle='toc'] .nav .nav > .active:hover > a,
-nav[data-toggle='toc'] .nav .nav > .active:focus > a {
-  padding-left: 15px;
-  font-weight: 500;
-  font-size: 1.35rem;
-}
-
-/* orcid ------------------------------------------------------------------- */
-
-.orcid {
-  font-size: 16px;
-  color: #A6CE39;
-  /* margins are required by official ORCID trademark and display guidelines */
-  margin-left:4px;
-  margin-right:4px;
-  vertical-align: middle;
-}
-
-/* Reference index & topics ----------------------------------------------- */
-
-.ref-index th {font-weight: normal;}
-
-.ref-index td {vertical-align: top; min-width: 100px}
-.ref-index .icon {width: 40px;}
-.ref-index .alias {width: 40%;}
-.ref-index-icons .alias {width: calc(40% - 40px);}
-.ref-index .title {width: 60%;}
-
-.ref-arguments th {text-align: right; padding-right: 10px;}
-.ref-arguments th, .ref-arguments td {vertical-align: top; min-width: 100px}
-.ref-arguments .name {width: 20%;}
-.ref-arguments .desc {width: 80%;}
-
-/* Nice scrolling for wide elements --------------------------------------- */
-
-table {
-  display: block;
-  overflow: auto;
-}
-
-/* Syntax highlighting ---------------------------------------------------- */
-
-pre, code, pre code {
-  background-color: #f8f8f8;
-  color: #333;
-}
-pre, pre code {
-  white-space: pre-wrap;
-  word-break: break-all;
-  overflow-wrap: break-word;
-}
-
-pre {
-  border: 1px solid #eee;
-}
-
-pre .img, pre .r-plt {
-  margin: 5px 0;
-}
-
-pre .img img, pre .r-plt img {
-  background-color: #fff;
-}
-
-code a, pre a {
-  color: #375f84;
-}
-
-a.sourceLine:hover {
-  text-decoration: none;
-}
-
-.fl      {color: #1514b5;}
-.fu      {color: #000000;} /* function */
-.ch,.st  {color: #036a07;} /* string */
-.kw      {color: #264D66;} /* keyword */
-.co      {color: #888888;} /* comment */
-
-.error   {font-weight: bolder;}
-.warning {font-weight: bolder;}
-
-/* Clipboard --------------------------*/
-
-.hasCopyButton {
-  position: relative;
-}
-
-.btn-copy-ex {
-  position: absolute;
-  right: 0;
-  top: 0;
-  visibility: hidden;
-}
-
-.hasCopyButton:hover button.btn-copy-ex {
-  visibility: visible;
-}
-
-/* headroom.js ------------------------ */
-
-.headroom {
-  will-change: transform;
-  transition: transform 200ms linear;
-}
-.headroom--pinned {
-  transform: translateY(0%);
-}
-.headroom--unpinned {
-  transform: translateY(-100%);
-}
-
-/* mark.js ----------------------------*/
-
-mark {
-  background-color: rgba(255, 255, 51, 0.5);
-  border-bottom: 2px solid rgba(255, 153, 51, 0.3);
-  padding: 1px;
-}
-
-/* vertical spacing after htmlwidgets */
-.html-widget {
-  margin-bottom: 10px;
-}
-
-/* fontawesome ------------------------ */
-
-.fab {
-    font-family: "Font Awesome 5 Brands" !important;
-}
-
-/* don't display links in code chunks when printing */
-/* source: https://stackoverflow.com/a/10781533 */
-@media print {
-  code a:link:after, code a:visited:after {
-    content: "";
-  }
-}
-
-/* Section anchors ---------------------------------
-   Added in pandoc 2.11: https://github.com/jgm/pandoc-templates/commit/9904bf71
-*/
-
-div.csl-bib-body { }
-div.csl-entry {
-  clear: both;
-}
-.hanging-indent div.csl-entry {
-  margin-left:2em;
-  text-indent:-2em;
-}
-div.csl-left-margin {
-  min-width:2em;
-  float:left;
-}
-div.csl-right-inline {
-  margin-left:2em;
-  padding-left:1em;
-}
-div.csl-indent {
-  margin-left: 2em;
-}
diff --git a/docs/pkgdown.js b/docs/pkgdown.js
index 5fccd9c0..1a99c65f 100644
--- a/docs/pkgdown.js
+++ b/docs/pkgdown.js
@@ -30,10 +30,10 @@
   /* Clipboard --------------------------*/
 
   function changeTooltipMessage(element, msg) {
-    var tooltipOriginalTitle=element.getAttribute('data-original-title');
-    element.setAttribute('data-original-title', msg);
+    var tooltipOriginalTitle=element.getAttribute('data-bs-original-title');
+    element.setAttribute('data-bs-original-title', msg);
     $(element).tooltip('show');
-    element.setAttribute('data-original-title', tooltipOriginalTitle);
+    element.setAttribute('data-bs-original-title', tooltipOriginalTitle);
   }
 
   if(ClipboardJS.isSupported()) {
@@ -60,7 +60,7 @@
         e.clearSelection();
       });
 
-      clipboard.on('error', function() {
+      clipboard.on('error', function(e) {
         changeTooltipMessage(e.trigger,'Press Ctrl+C or Command+C to copy');
       });
 
@@ -153,4 +153,10 @@ async function searchFuse(query, callback) {
   });
 })(window.jQuery || window.$)
 
-
+document.addEventListener('keydown', function(event) {
+  // Check if the pressed key is '/'
+  if (event.key === '/') {
+    event.preventDefault();  // Prevent any default action associated with the '/' key
+    document.getElementById('search-input').focus();  // Set focus to the search input
+  }
+});
diff --git a/docs/pkgdown.yml b/docs/pkgdown.yml
index 90d79efb..ad6c5809 100644
--- a/docs/pkgdown.yml
+++ b/docs/pkgdown.yml
@@ -1,24 +1,23 @@
 pandoc: 2.17.1.1
-pkgdown: 2.0.7
+pkgdown: 2.1.1
 pkgdown_sha: ~
 articles:
+  prebuilt/2022_cyan_pathway: prebuilt/2022_cyan_pathway.html
+  prebuilt/2022_dmta_parent: prebuilt/2022_dmta_parent.html
+  prebuilt/2022_dmta_pathway: prebuilt/2022_dmta_pathway.html
+  prebuilt/2023_mesotrione_parent: prebuilt/2023_mesotrione_parent.html
+  web_only/benchmarks: web_only/benchmarks.html
+  web_only/compiled_models: web_only/compiled_models.html
+  web_only/dimethenamid_2018: web_only/dimethenamid_2018.html
   FOCUS_D: FOCUS_D.html
   FOCUS_L: FOCUS_L.html
+  web_only/FOCUS_Z: web_only/FOCUS_Z.html
   mkin: mkin.html
-  2022_cyan_pathway: prebuilt/2022_cyan_pathway.html
-  2022_dmta_parent: prebuilt/2022_dmta_parent.html
-  2022_dmta_pathway: prebuilt/2022_dmta_pathway.html
-  2023_mesotrione_parent: prebuilt/2023_mesotrione_parent.html
+  web_only/multistart: web_only/multistart.html
+  web_only/NAFTA_examples: web_only/NAFTA_examples.html
+  web_only/saem_benchmarks: web_only/saem_benchmarks.html
   twa: twa.html
-  FOCUS_Z: web_only/FOCUS_Z.html
-  NAFTA_examples: web_only/NAFTA_examples.html
-  benchmarks: web_only/benchmarks.html
-  compiled_models: web_only/compiled_models.html
-  dimethenamid_2018: web_only/dimethenamid_2018.html
-  multistart: web_only/multistart.html
-  saem_benchmarks: web_only/saem_benchmarks.html
-last_built: 2023-11-16T03:09Z
+last_built: 2025-02-13T13:50Z
 urls:
   reference: https://pkgdown.jrwb.de/mkin/reference
   article: https://pkgdown.jrwb.de/mkin/articles
-
diff --git a/docs/reference/AIC.mmkin.html b/docs/reference/AIC.mmkin.html
index ede8eb3d..516e6009 100644
--- a/docs/reference/AIC.mmkin.html
+++ b/docs/reference/AIC.mmkin.html
@@ -1,76 +1,63 @@
 
-Calculate the AIC for a column of an mmkin object — AIC.mmkin • mkin
+Calculate the AIC for a column of an mmkin object — AIC.mmkin • mkin
     Skip to contents
-    
 
-    
      • 
     
      
-  
      
 
 
     
      
-  
      Developed by Johannes Ranke.
      
+  
      Developed by Johannes Ranke.
      
 
      
 
 
      
-  
      Site built with pkgdown 2.0.7.
      
+  
      Site built with pkgdown 2.1.1.
      - - + + diff --git a/docs/reference/CAKE_export.html b/docs/reference/CAKE_export.html index a9aac1ef..3dd5cafe 100644 --- a/docs/reference/CAKE_export.html +++ b/docs/reference/CAKE_export.html @@ -1,76 +1,63 @@ -Export a list of datasets format to a CAKE study file — CAKE_export • mkin +Export a list of datasets format to a CAKE study file — CAKE_export • mkin Skip to contents - -
      -

      Developed by Johannes Ranke.

      +

      Developed by Johannes Ranke.

      -

      Site built with pkgdown 2.0.7.

      +

      Site built with pkgdown 2.1.1.

      - - + + diff --git a/docs/reference/ilr.html b/docs/reference/ilr.html index 04a8ab76..7aa6379f 100644 --- a/docs/reference/ilr.html +++ b/docs/reference/ilr.html @@ -1,76 +1,63 @@ -Function to perform isometric log-ratio transformation — ilr • mkin +Function to perform isometric log-ratio transformation — ilr • mkin Skip to contents - -