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_D.html | 202 +++----- docs/articles/FOCUS_D_files/figure-html/plot-1.png | Bin 79834 -> 80361 bytes .../FOCUS_D_files/figure-html/plot_2-1.png | Bin 24334 -> 25051 bytes docs/articles/FOCUS_L.html | 293 +++++------ docs/articles/index.html | 163 +++--- docs/articles/mkin.html | 192 +++---- docs/articles/prebuilt/2022_cyan_pathway.html | 552 ++++++++++++--------- .../figure-html/unnamed-chunk-13-1.png | Bin 363434 -> 363589 bytes .../figure-html/unnamed-chunk-14-1.png | Bin 363895 -> 364310 bytes .../figure-html/unnamed-chunk-15-1.png | Bin 365048 -> 365199 bytes .../figure-html/unnamed-chunk-20-1.png | Bin 378042 -> 378245 bytes .../figure-html/unnamed-chunk-21-1.png | Bin 371436 -> 371558 bytes .../figure-html/unnamed-chunk-22-1.png | Bin 373322 -> 373392 bytes 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-
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Example evaluation of FOCUS Example Dataset -D

+ +
+
+

Example evaluation of FOCUS Example Dataset D

Johannes Ranke

Last change 31 January 2019 -(rebuilt 2023-10-30)

+(rebuilt 2023-11-16) Source: vignettes/FOCUS_D.rmd - - +
FOCUS_D.rmd
@@ -241,9 +200,9 @@ the mkinparplot function.

 summary(fit)
## mkin version used for fitting:    1.2.6 
-## R version used for fitting:       4.3.1 
-## Date of fit:     Mon Oct 30 09:40:58 2023 
-## Date of summary: Mon Oct 30 09:40:58 2023 
+## R version used for fitting:       4.3.2 
+## Date of fit:     Thu Nov 16 04:20:11 2023 
+## Date of summary: Thu Nov 16 04:20:11 2023 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent * parent
@@ -251,7 +210,7 @@ the mkinparplot function.

 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted using 401 model solutions performed in 0.123 s
+## Fitted using 401 model solutions performed in 0.051 s
 ## 
 ## Error model: Constant variance 
 ## 
@@ -367,32 +326,27 @@ the mkinparplot function.

 ##   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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- diff --git a/docs/articles/FOCUS_D_files/figure-html/plot-1.png b/docs/articles/FOCUS_D_files/figure-html/plot-1.png index f0b51c1f..c0832a1a 100644 Binary files a/docs/articles/FOCUS_D_files/figure-html/plot-1.png and b/docs/articles/FOCUS_D_files/figure-html/plot-1.png differ diff --git a/docs/articles/FOCUS_D_files/figure-html/plot_2-1.png b/docs/articles/FOCUS_D_files/figure-html/plot_2-1.png index f6180470..02cfcfb4 100644 Binary files a/docs/articles/FOCUS_D_files/figure-html/plot_2-1.png and b/docs/articles/FOCUS_D_files/figure-html/plot_2-1.png differ 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 -
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Example evaluation of FOCUS Laboratory Data L1 -to L3

+ +
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+

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
 
 
 
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Developed by Johannes Ranke.

 

 
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diff --git a/docs/articles/index.html b/docs/articles/index.html
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-Articles • mkinArticles • mkin
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Benchmark timings for saem.mmkin

         

       

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Developed by Johannes Ranke.

 

 
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diff --git a/docs/articles/mkin.html b/docs/articles/mkin.html
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--- a/docs/articles/mkin.html
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@@ -4,141 +4,104 @@
 
 
 
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 Short introduction to mkin • mkin
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Short introduction to mkin

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Short introduction to mkin

                         
Johannes
 Ranke

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

+(rebuilt 2023-11-16)
       
       Source: vignettes/mkin.rmd
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mkin.rmd

     

 
     
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diff --git a/docs/articles/prebuilt/2022_cyan_pathway.html b/docs/articles/prebuilt/2022_cyan_pathway.html
index c22b07e4..5325018a 100644
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+++ b/docs/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

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Testing hierarchical pathway kinetics with residue data on cyantraniliprole

                         
Johannes
 Ranke

             
             
Last change on 20 April 2023,
-last compiled on 30 October 2023

+last compiled on 16 November 2023
       
       Source: vignettes/prebuilt/2022_cyan_pathway.rmd
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2022_cyan_pathway.rmd

     

 
     
@@ -2209,9 +2168,9 @@ Hierarchical SFO path 1 fit with constant variance
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 10:03:13 2023 
-Date of summary: Mon Oct 30 11:18:26 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:27:41 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan/dt = - k_cyan * cyan
@@ -2224,7 +2183,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 1273.632 s
+Fitted in 421.347 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Constant variance 
@@ -2337,9 +2296,9 @@ Hierarchical SFO path 1 fit with two-component error
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 09:58:51 2023 
-Date of summary: Mon Oct 30 11:18:26 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:27:55 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan/dt = - k_cyan * cyan
@@ -2352,7 +2311,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 1011.299 s
+Fitted in 435.122 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Two-component variance function 
@@ -2467,9 +2426,9 @@ Hierarchical FOMC path 1 fit with constant variance
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 10:04:48 2023 
-Date of summary: Mon Oct 30 11:18:26 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:28:33 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan
@@ -2484,7 +2443,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 1368.338 s
+Fitted in 473.357 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Constant variance 
@@ -2612,9 +2571,9 @@ Hierarchical FOMC path 1 fit with two-component error
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 10:00:40 2023 
-Date of summary: Mon Oct 30 11:18:26 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:28:46 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan
@@ -2629,7 +2588,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 1120.168 s
+Fitted in 486.031 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Two-component variance function 
@@ -2750,9 +2709,9 @@ Hierarchical DFOP path 1 fit with constant variance
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 10:02:52 2023 
-Date of summary: Mon Oct 30 11:18:26 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:29:15 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -2771,7 +2730,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 1252.502 s
+Fitted in 514.477 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Constant variance 
@@ -2896,9 +2855,9 @@ Hierarchical DFOP path 1 fit with two-component error
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 10:12:10 2023 
-Date of summary: Mon Oct 30 11:18:26 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:31:58 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -2917,7 +2876,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 1809.832 s
+Fitted in 677.928 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Two-component variance function 
@@ -3042,9 +3001,9 @@ Hierarchical SFORB path 1 fit with constant variance
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 10:02:30 2023 
-Date of summary: Mon Oct 30 11:18:26 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:29:33 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound *
@@ -3062,7 +3021,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 1230.946 s
+Fitted in 532.937 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Constant variance 
@@ -3207,9 +3166,9 @@ Hierarchical SFORB path 1 fit with two-component error
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 10:09:13 2023 
-Date of summary: Mon Oct 30 11:18:26 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:31:58 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound *
@@ -3227,7 +3186,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 1633.433 s
+Fitted in 677.936 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Two-component variance function 
@@ -3372,14 +3331,142 @@ Hierarchical HS path 1 fit with constant variance
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 10:02:52 2023 
-Date of summary: Mon Oct 30 11:18:27 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:29:18 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
-d_cyan/dt = - ifelse(time 
-

-

+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 518.128 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 
+      102.8845        -3.4495        -4.9355        -5.6040         0.6468 
+  f_cyan_ilr_2 f_JCZ38_qlogis         log_k1         log_k2         log_tb 
+        1.2396         9.7220        -2.9079        -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          5.406        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       1.013       0.0000
+f_cyan_ilr_1    0.000        0.00        0.00       0.000       0.6367
+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          2.038           0.00 0.0000 0.0000 0.0000
+f_JCZ38_qlogis        0.000          10.33 0.0000 0.0000 0.0000
+log_k1                0.000           0.00 0.7006 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 0.6773
+
+Starting values for error model parameters:
+a.1 
+  1 
+
+Results:
+
+Likelihood computed by importance sampling
+   AIC  BIC logLik
+  2427 2419  -1194
+
+Optimised parameters:
+                      est.      lower      upper
+cyan_0            101.9660  1.005e+02  1.035e+02
+log_k_JCZ38        -3.4698 -4.716e+00 -2.224e+00
+log_k_J9Z38        -5.0947 -5.740e+00 -4.450e+00
+log_k_JSE76        -5.5977 -6.321e+00 -4.875e+00
+f_cyan_ilr_1        0.6595  3.734e-01  9.456e-01
+f_cyan_ilr_2        0.5905  1.664e-01  1.015e+00
+f_JCZ38_qlogis     25.8627 -4.224e+05  4.225e+05
+log_k1             -3.0884 -3.453e+00 -2.723e+00
+log_k2             -4.3877 -4.778e+00 -3.998e+00
+log_tb              2.3057  1.715e+00  2.896e+00
+a.1                 3.3228         NA         NA
+SD.log_k_JCZ38      1.4071         NA         NA
+SD.log_k_J9Z38      0.5774         NA         NA
+SD.log_k_JSE76      0.6214         NA         NA
+SD.f_cyan_ilr_1     0.3058         NA         NA
+SD.f_cyan_ilr_2     0.3470         NA         NA
+SD.f_JCZ38_qlogis   0.0644         NA         NA
+SD.log_k1           0.3994         NA         NA
+SD.log_k2           0.4373         NA         NA
+SD.log_tb           0.6419         NA         NA
+
+Correlation is not available
+
+Random effects:
+                    est. lower upper
+SD.log_k_JCZ38    1.4071    NA    NA
+SD.log_k_J9Z38    0.5774    NA    NA
+SD.log_k_JSE76    0.6214    NA    NA
+SD.f_cyan_ilr_1   0.3058    NA    NA
+SD.f_cyan_ilr_2   0.3470    NA    NA
+SD.f_JCZ38_qlogis 0.0644    NA    NA
+SD.log_k1         0.3994    NA    NA
+SD.log_k2         0.4373    NA    NA
+SD.log_tb         0.6419    NA    NA
+
+Variance model:
+     est. lower upper
+a.1 3.323    NA    NA
+
+Backtransformed parameters:
+                      est.     lower     upper
+cyan_0           1.020e+02 1.005e+02 1.035e+02
+k_JCZ38          3.112e-02 8.951e-03 1.082e-01
+k_J9Z38          6.129e-03 3.216e-03 1.168e-02
+k_JSE76          3.706e-03 1.798e-03 7.639e-03
+f_cyan_to_JCZ38  5.890e-01        NA        NA
+f_cyan_to_J9Z38  2.318e-01        NA        NA
+f_JCZ38_to_JSE76 1.000e+00 0.000e+00 1.000e+00
+k1               4.558e-02 3.164e-02 6.565e-02
+k2               1.243e-02 8.417e-03 1.835e-02
+tb               1.003e+01 5.557e+00 1.811e+01
+
+Resulting formation fractions:
+                   ff
+cyan_JCZ38  5.890e-01
+cyan_J9Z38  2.318e-01
+cyan_sink   1.793e-01
+JCZ38_JSE76 1.000e+00
+JCZ38_sink  5.861e-12
+
+Estimated disappearance times:
+        DT50   DT90 DT50back DT50_k1 DT50_k2
+cyan   29.02 158.51    47.72   15.21   55.77
+JCZ38  22.27  73.98       NA      NA      NA
+J9Z38 113.09 375.69       NA      NA      NA
+JSE76 187.01 621.23       NA      NA      NA
+
+

+

 

 

 
Pathway 2
@@ -3390,9 +3477,9 @@ Hierarchical FOMC path 2 fit with two-component error
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 10:32:26 2023 
-Date of summary: Mon Oct 30 11:18:27 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:40:28 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan
@@ -3407,7 +3494,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 1185.728 s
+Fitted in 499.317 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Two-component variance function 
@@ -3556,9 +3643,9 @@ Hierarchical DFOP path 2 fit with constant variance
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 10:34:49 2023 
-Date of summary: Mon Oct 30 11:18:27 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:41:25 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -3578,7 +3665,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 1329.843 s
+Fitted in 555.724 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Constant variance 
@@ -3747,9 +3834,9 @@ Hierarchical DFOP path 2 fit with two-component error
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 10:41:05 2023 
-Date of summary: Mon Oct 30 11:18:27 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:44:08 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -3769,7 +3856,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 1705.043 s
+Fitted in 718.988 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Two-component variance function 
@@ -3938,9 +4025,9 @@ Hierarchical SFORB path 2 fit with constant variance
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 10:35:39 2023 
-Date of summary: Mon Oct 30 11:18:27 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:41:22 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound *
@@ -3958,7 +4045,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 1379.466 s
+Fitted in 553.276 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Constant variance 
@@ -4134,9 +4221,9 @@ Hierarchical SFORB path 2 fit with two-component error
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 10:41:39 2023 
-Date of summary: Mon Oct 30 11:18:27 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:44:02 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound *
@@ -4154,7 +4241,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 1739.402 s
+Fitted in 713.14 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Two-component variance function 
@@ -4335,9 +4422,9 @@ error
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 11:12:56 2023 
-Date of summary: Mon Oct 30 11:18:27 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:57:07 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan/dt = - (alpha/beta) * 1/((time/beta) + 1) * cyan
@@ -4352,7 +4439,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 1872.856 s
+Fitted in 776.732 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Two-component variance function 
@@ -4478,9 +4565,9 @@ variance
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 11:17:06 2023 
-Date of summary: Mon Oct 30 11:18:27 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:58:51 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -4500,7 +4587,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 2122.961 s
+Fitted in 880.94 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Constant variance 
@@ -4577,12 +4664,12 @@ f_JSE76_qlogis     1.9658      NA     NA
 log_k1            -1.9503      NA     NA
 log_k2            -4.4745      NA     NA
 g_qlogis          -0.4967      NA     NA
-a.1                2.7461 2.59886 2.8932
+a.1                2.7461 2.59274 2.8994
 SD.log_k_JCZ38     1.3178 0.47602 2.1596
 SD.log_k_J9Z38     0.7022 0.15061 1.2538
-SD.log_k_JSE76     0.6566 0.15614 1.1570
+SD.log_k_JSE76     0.6566 0.15613 1.1570
 SD.f_cyan_ilr_1    0.3409 0.11666 0.5652
-SD.f_cyan_ilr_2    0.4385 0.09483 0.7821
+SD.f_cyan_ilr_2    0.4385 0.09482 0.7821
 SD.log_k1          0.7381 0.25599 1.2202
 SD.log_k2          0.5133 0.18152 0.8450
 SD.g_qlogis        0.9866 0.35681 1.6164
@@ -4593,16 +4680,16 @@ Random effects:
                   est.   lower  upper
 SD.log_k_JCZ38  1.3178 0.47602 2.1596
 SD.log_k_J9Z38  0.7022 0.15061 1.2538
-SD.log_k_JSE76  0.6566 0.15614 1.1570
+SD.log_k_JSE76  0.6566 0.15613 1.1570
 SD.f_cyan_ilr_1 0.3409 0.11666 0.5652
-SD.f_cyan_ilr_2 0.4385 0.09483 0.7821
+SD.f_cyan_ilr_2 0.4385 0.09482 0.7821
 SD.log_k1       0.7381 0.25599 1.2202
 SD.log_k2       0.5133 0.18152 0.8450
 SD.g_qlogis     0.9866 0.35681 1.6164
 
 Variance model:
      est. lower upper
-a.1 2.746 2.599 2.893
+a.1 2.746 2.593 2.899
 
 Backtransformed parameters:
                       est. lower upper
@@ -4644,9 +4731,9 @@ error
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 11:17:59 2023 
-Date of summary: Mon Oct 30 11:18:27 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:58:58 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -4666,7 +4753,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 2175.807 s
+Fitted in 887.853 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Two-component variance function 
@@ -4810,9 +4897,9 @@ variance
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 11:17:04 2023 
-Date of summary: Mon Oct 30 11:18:27 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:58:49 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound *
@@ -4830,7 +4917,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 2121.218 s
+Fitted in 878.878 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Constant variance 
@@ -4981,9 +5068,9 @@ error
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 11:18:24 2023 
-Date of summary: Mon Oct 30 11:18:27 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:59:10 2023 
+Date of summary: Thu Nov 16 04:59:11 2023 
 
 Equations:
 d_cyan_free/dt = - k_cyan_free * cyan_free - k_cyan_free_bound *
@@ -5001,7 +5088,7 @@ Data:
 
 Model predictions using solution type deSolve 
 
-Fitted in 2200.603 s
+Fitted in 899.539 s
 Using 300, 100 iterations and 10 chains
 
 Variance model: Two-component variance function 
@@ -5150,23 +5237,23 @@ JSE76  25.44  84.51       NA           NA           NA
 

 
Session info
 

-
R version 4.3.1 (2023-06-16)
+
R version 4.3.2 (2023-10-31)
 Platform: x86_64-pc-linux-gnu (64-bit)
-Running under: Ubuntu 22.04.3 LTS
+Running under: Debian GNU/Linux 12 (bookworm)
 
 Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0 
-LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
+BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 
+LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0
 
 locale:
- [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
- [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
- [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
+ [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=en_US.UTF-8 LC_IDENTIFICATION=C       
+[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C       
 
-time zone: Europe/Zurich
+time zone: Europe/Berlin
 tzcode source: system (glibc)
 
 attached base packages:
@@ -5174,62 +5261,55 @@ attached base packages:
 [8] base     
 
 other attached packages:
-[1] saemix_3.2 npde_3.3   knitr_1.44 mkin_1.2.6
+[1] saemix_3.2 npde_3.3   knitr_1.42 mkin_1.2.6
 
 loaded via a namespace (and not attached):
- [1] sass_0.4.7        utf8_1.2.3        generics_0.1.3    stringi_1.7.12   
- [5] lattice_0.21-9    digest_0.6.33     magrittr_2.0.3    evaluate_0.22    
- [9] grid_4.3.1        fastmap_1.1.1     cellranger_1.1.0  rprojroot_2.0.3  
-[13] jsonlite_1.8.7    processx_3.8.2    pkgbuild_1.4.2    deSolve_1.35     
-[17] mclust_6.0.0      ps_1.7.5          gridExtra_2.3     purrr_1.0.1      
-[21] fansi_1.0.4       scales_1.2.1      codetools_0.2-19  textshaping_0.3.6
-[25] jquerylib_0.1.4   cli_3.6.1         crayon_1.5.2      rlang_1.1.1      
-[29] munsell_0.5.0     cachem_1.0.8      yaml_2.3.7        inline_0.3.19    
-[33] tools_4.3.1       memoise_2.0.1     dplyr_1.1.2       colorspace_2.1-0 
-[37] ggplot2_3.4.2     vctrs_0.6.3       R6_2.5.1          zoo_1.8-12       
-[41] lifecycle_1.0.3   stringr_1.5.0     fs_1.6.3          MASS_7.3-60      
-[45] ragg_1.2.5        callr_3.7.3       pkgconfig_2.0.3   desc_1.4.2       
-[49] pkgdown_2.0.7     bslib_0.5.1       pillar_1.9.0      gtable_0.3.3     
-[53] glue_1.6.2        systemfonts_1.0.4 xfun_0.40         tibble_3.2.1     
-[57] lmtest_0.9-40     tidyselect_1.2.0  rstudioapi_0.15.0 htmltools_0.5.6.1
-[61] nlme_3.1-163      rmarkdown_2.23    compiler_4.3.1    prettyunits_1.2.0
-[65] readxl_1.4.2     

+ [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     cellranger_1.1.0  rprojroot_2.0.3  
+[13] jsonlite_1.8.4    processx_3.8.1    pkgbuild_1.4.0    deSolve_1.35     
+[17] DBI_1.1.3         mclust_6.0.0      ps_1.7.5          gridExtra_2.3    
+[21] purrr_1.0.1       fansi_1.0.4       scales_1.2.1      codetools_0.2-19 
+[25] textshaping_0.3.6 jquerylib_0.1.4   cli_3.6.1         crayon_1.5.2     
+[29] rlang_1.1.1       munsell_0.5.0     cachem_1.0.8      yaml_2.3.7       
+[33] inline_0.3.19     tools_4.3.2       memoise_2.0.1     dplyr_1.1.2      
+[37] colorspace_2.1-0  ggplot2_3.4.2     vctrs_0.6.2       R6_2.5.1         
+[41] zoo_1.8-12        lifecycle_1.0.3   stringr_1.5.0     fs_1.6.2         
+[45] MASS_7.3-60       ragg_1.2.5        callr_3.7.3       pkgconfig_2.0.3  
+[49] desc_1.4.2        pkgdown_2.0.7     bslib_0.4.2       pillar_1.9.0     
+[53] gtable_0.3.3      glue_1.6.2        systemfonts_1.0.4 highr_0.10       
+[57] xfun_0.39         tibble_3.2.1      lmtest_0.9-40     tidyselect_1.2.0 
+[61] htmltools_0.5.5   nlme_3.1-163      rmarkdown_2.21    compiler_4.3.2   
+[65] prettyunits_1.1.1 readxl_1.4.2     

 

 

 
Hardware info
 

-
CPU model: Intel(R) Xeon(R) Gold 6134 CPU @ 3.20GHz

-
MemTotal:       247605564 kB

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

+
MemTotal:       64927712 kB

 

 

-  

-
-  
-
+  
 

 
 
 
-      

+    

   

 
Developed by Johannes Ranke.

 

 
-

+

   

 
Site built with pkgdown 2.0.7.

 

 
-      

+    

 

 
   
 
-
   
 
   
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diff --git a/docs/articles/prebuilt/2022_dmta_parent.html b/docs/articles/prebuilt/2022_dmta_parent.html
index 9fdf75f7..952d028e 100644
--- a/docs/articles/prebuilt/2022_dmta_parent.html
+++ b/docs/articles/prebuilt/2022_dmta_parent.html
@@ -4,145 +4,104 @@
 
 
 
-
+
+
 Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P • mkin
-
-
-
+
+
+
 
-
-
+
 
 
 
-
+
+    Skip to contents
     
 
-    

-      

-  

-    

-      
Testing hierarchical parent degradation kinetics
-with residue data on dimethenamid and dimethenamid-P

+

+  

+      
Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P

                         
Johannes
 Ranke

             
             
Last change on 5 January
-2023, last compiled on 30 October 2023

+2023, last compiled on 16 November 2023
       
       Source: vignettes/prebuilt/2022_dmta_parent.rmd
-      
-
+      
2022_dmta_parent.rmd

     

 
     
@@ -1290,9 +1249,9 @@ Plot of the final NLHM DFOP fit
 summary(f_saem_dfop_tc_no_ranef_k2)
saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 11:19:13 2023 
-Date of summary: Mon Oct 30 11:19:14 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:59:35 2023 
+Date of summary: Thu Nov 16 04:59:35 2023 
 
 Equations:
 d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -1304,7 +1263,7 @@ Data:
 
 Model predictions using solution type analytical 
 
-Fitted in 8.975 s
+Fitted in 4.4 s
 Using 300, 100 iterations and 9 chains
 
 Variance model: Two-component variance function 
@@ -1466,9 +1425,9 @@ Hierarchical mkin fit of the SFO model with error model const
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 11:18:56 2023 
-Date of summary: Mon Oct 30 11:21:30 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:59:26 2023 
+Date of summary: Thu Nov 16 05:00:43 2023 
 
 Equations:
 d_DMTA/dt = - k_DMTA * DMTA
@@ -1478,7 +1437,7 @@ Data:
 
 Model predictions using solution type analytical 
 
-Fitted in 1.899 s
+Fitted in 0.788 s
 Using 300, 100 iterations and 9 chains
 
 Variance model: Constant variance 
@@ -1538,9 +1497,9 @@ Hierarchical mkin fit of the SFO model with error model tc
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 11:19:00 2023 
-Date of summary: Mon Oct 30 11:21:30 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:59:28 2023 
+Date of summary: Thu Nov 16 05:00:43 2023 
 
 Equations:
 d_DMTA/dt = - k_DMTA * DMTA
@@ -1550,7 +1509,7 @@ Data:
 
 Model predictions using solution type analytical 
 
-Fitted in 5.364 s
+Fitted in 2.428 s
 Using 300, 100 iterations and 9 chains
 
 Variance model: Two-component variance function 
@@ -1612,9 +1571,9 @@ Hierarchical mkin fit of the FOMC model with error model const
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 11:18:57 2023 
-Date of summary: Mon Oct 30 11:21:30 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:59:27 2023 
+Date of summary: Thu Nov 16 05:00:43 2023 
 
 Equations:
 d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA
@@ -1624,7 +1583,7 @@ Data:
 
 Model predictions using solution type analytical 
 
-Fitted in 2.944 s
+Fitted in 1.28 s
 Using 300, 100 iterations and 9 chains
 
 Variance model: Constant variance 
@@ -1689,9 +1648,9 @@ Hierarchical mkin fit of the FOMC model with error model tc
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 11:19:01 2023 
-Date of summary: Mon Oct 30 11:21:30 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:59:28 2023 
+Date of summary: Thu Nov 16 05:00:43 2023 
 
 Equations:
 d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA
@@ -1701,7 +1660,7 @@ Data:
 
 Model predictions using solution type analytical 
 
-Fitted in 6.228 s
+Fitted in 2.793 s
 Using 300, 100 iterations and 9 chains
 
 Variance model: Two-component variance function 
@@ -1768,9 +1727,9 @@ Hierarchical mkin fit of the DFOP model with error model const
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 11:18:57 2023 
-Date of summary: Mon Oct 30 11:21:30 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:59:27 2023 
+Date of summary: Thu Nov 16 05:00:43 2023 
 
 Equations:
 d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -1782,7 +1741,7 @@ Data:
 
 Model predictions using solution type analytical 
 
-Fitted in 3.231 s
+Fitted in 1.752 s
 Using 300, 100 iterations and 9 chains
 
 Variance model: Constant variance 
@@ -1852,9 +1811,9 @@ Hierarchical mkin fit of the DFOP model with error model tc
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 11:19:01 2023 
-Date of summary: Mon Oct 30 11:21:30 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:59:29 2023 
+Date of summary: Thu Nov 16 05:00:43 2023 
 
 Equations:
 d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -1866,7 +1825,7 @@ Data:
 
 Model predictions using solution type analytical 
 
-Fitted in 6.71 s
+Fitted in 3.186 s
 Using 300, 100 iterations and 9 chains
 
 Variance model: Two-component variance function 
@@ -1938,27 +1897,166 @@ Hierarchical mkin fit of the HS model with error model const
 

 saemix version used for fitting:      3.2 
 mkin version used for pre-fitting:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 11:18:59 2023 
-Date of summary: Mon Oct 30 11:21:30 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:59:28 2023 
+Date of summary: Thu Nov 16 05:00:43 2023 
 
 Equations:
-d_DMTA/dt = - ifelse(time 
-

+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 2.28 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:  1.2.6 
-R version used for fitting:         4.3.1 
-Date of fit:     Mon Oct 30 11:19:02 2023 
-Date of summary: Mon Oct 30 11:21:30 2023 
+R version used for fitting:         4.3.2 
+Date of fit:     Thu Nov 16 04:59:29 2023 
+Date of summary: Thu Nov 16 05:00:43 2023 
 
 Equations:
-d_DMTA/dt = - ifelse(time 
-

-

+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 3.658 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    97.76571 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
@@ -2007,23 +2105,23 @@ Convergence plot for the NLHM HS fit with two-component error
 

 
Session info
 

-
R version 4.3.1 (2023-06-16)
+
R version 4.3.2 (2023-10-31)
 Platform: x86_64-pc-linux-gnu (64-bit)
-Running under: Ubuntu 22.04.3 LTS
+Running under: Debian GNU/Linux 12 (bookworm)
 
 Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0 
-LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
+BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 
+LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0
 
 locale:
- [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
- [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
- [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
+ [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=en_US.UTF-8 LC_IDENTIFICATION=C       
+[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C       
 
-time zone: Europe/Zurich
+time zone: Europe/Berlin
 tzcode source: system (glibc)
 
 attached base packages:
@@ -2031,59 +2129,52 @@ attached base packages:
 [8] base     
 
 other attached packages:
-[1] saemix_3.2 npde_3.3   knitr_1.44 mkin_1.2.6
+[1] saemix_3.2 npde_3.3   knitr_1.42 mkin_1.2.6
 
 loaded via a namespace (and not attached):
- [1] sass_0.4.7        utf8_1.2.3        generics_0.1.3    stringi_1.7.12   
- [5] lattice_0.21-9    digest_0.6.33     magrittr_2.0.3    evaluate_0.22    
- [9] grid_4.3.1        fastmap_1.1.1     rprojroot_2.0.3   jsonlite_1.8.7   
-[13] mclust_6.0.0      gridExtra_2.3     purrr_1.0.1       fansi_1.0.4      
-[17] scales_1.2.1      codetools_0.2-19  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_4.3.1       memoise_2.0.1     dplyr_1.1.2      
-[29] colorspace_2.1-0  ggplot2_3.4.2     vctrs_0.6.3       R6_2.5.1         
-[33] zoo_1.8-12        lifecycle_1.0.3   stringr_1.5.0     fs_1.6.3         
-[37] MASS_7.3-60       ragg_1.2.5        pkgconfig_2.0.3   desc_1.4.2       
-[41] pkgdown_2.0.7     bslib_0.5.1       pillar_1.9.0      gtable_0.3.3     
-[45] glue_1.6.2        systemfonts_1.0.4 xfun_0.40         tibble_3.2.1     
-[49] lmtest_0.9-40     tidyselect_1.2.0  rstudioapi_0.15.0 htmltools_0.5.6.1
-[53] nlme_3.1-163      rmarkdown_2.23    compiler_4.3.1   

+ [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       memoise_2.0.1    
+[29] dplyr_1.1.2       colorspace_2.1-0  ggplot2_3.4.2     vctrs_0.6.2      
+[33] R6_2.5.1          zoo_1.8-12        lifecycle_1.0.3   stringr_1.5.0    
+[37] fs_1.6.2          MASS_7.3-60       ragg_1.2.5        pkgconfig_2.0.3  
+[41] desc_1.4.2        pkgdown_2.0.7     bslib_0.4.2       pillar_1.9.0     
+[45] gtable_0.3.3      glue_1.6.2        systemfonts_1.0.4 highr_0.10       
+[49] xfun_0.39         tibble_3.2.1      lmtest_0.9-40     tidyselect_1.2.0 
+[53] htmltools_0.5.5   nlme_3.1-163      rmarkdown_2.21    compiler_4.3.2   

 

 

 
Hardware info
 

-
CPU model: Intel(R) Xeon(R) Gold 6134 CPU @ 3.20GHz

-
MemTotal:       247605564 kB

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

+
MemTotal:       64927712 kB

 

 

-  
-
-  
-
+  
 
 
 
 
-      

+    

   

 
Developed by Johannes Ranke.

 

 
-

+

   

 
Site built with pkgdown 2.0.7.

 

 
-      

+    

 
 
   
 
-
   
 
   
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diff --git a/docs/articles/prebuilt/2022_dmta_pathway.html b/docs/articles/prebuilt/2022_dmta_pathway.html
index 2c3f326a..9a0e181d 100644
--- a/docs/articles/prebuilt/2022_dmta_pathway.html
+++ b/docs/articles/prebuilt/2022_dmta_pathway.html
@@ -4,145 +4,104 @@
 
 
 
-
+
+
 Testing hierarchical pathway kinetics with residue data on dimethenamid and dimethenamid-P • mkin
-
-
-
+
+
+
 
-
-
+
 
 
 
-
+
+    Skip to contents
     
 
-    

-      

-  

-    

-      
Testing hierarchical pathway kinetics with
-residue data on dimethenamid and dimethenamid-P

+
+

+  

+      
Testing hierarchical pathway kinetics with residue data on dimethenamid and dimethenamid-P

                         
Johannes
 Ranke

             
             
Last change on 20 April 2023,
-last compiled on 30 October 2023

+last compiled on 16 November 2023
       
       Source: vignettes/prebuilt/2022_dmta_pathway.rmd
-      
-
+      
2022_dmta_pathway.rmd

     

 
     
@@ -1979,23 +1938,23 @@ error
 
Session info
 

-
R version 4.3.1 (2023-06-16)
+
R version 4.3.2 (2023-10-31)
 Platform: x86_64-pc-linux-gnu (64-bit)
-Running under: Ubuntu 22.04.3 LTS
+Running under: Debian GNU/Linux 12 (bookworm)
 
 Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0 
-LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
+BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 
+LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0
 
 locale:
- [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
- [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
- [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
+ [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=en_US.UTF-8 LC_IDENTIFICATION=C       
+[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C       
 
-time zone: Europe/Zurich
+time zone: Europe/Berlin
 tzcode source: system (glibc)
 
 attached base packages:
@@ -2003,61 +1962,54 @@ attached base packages:
 [8] base     
 
 other attached packages:
-[1] saemix_3.2 npde_3.3   knitr_1.44 mkin_1.2.6
+[1] saemix_3.2 npde_3.3   knitr_1.42 mkin_1.2.6
 
 loaded via a namespace (and not attached):
- [1] sass_0.4.7        utf8_1.2.3        generics_0.1.3    stringi_1.7.12   
- [5] lattice_0.21-9    digest_0.6.33     magrittr_2.0.3    evaluate_0.22    
- [9] grid_4.3.1        fastmap_1.1.1     rprojroot_2.0.3   jsonlite_1.8.7   
-[13] processx_3.8.2    pkgbuild_1.4.2    deSolve_1.35      mclust_6.0.0     
-[17] ps_1.7.5          gridExtra_2.3     purrr_1.0.1       fansi_1.0.4      
-[21] scales_1.2.1      codetools_0.2-19  textshaping_0.3.6 jquerylib_0.1.4  
-[25] cli_3.6.1         crayon_1.5.2      rlang_1.1.1       munsell_0.5.0    
-[29] cachem_1.0.8      yaml_2.3.7        inline_0.3.19     tools_4.3.1      
-[33] memoise_2.0.1     dplyr_1.1.2       colorspace_2.1-0  ggplot2_3.4.2    
-[37] vctrs_0.6.3       R6_2.5.1          zoo_1.8-12        lifecycle_1.0.3  
-[41] stringr_1.5.0     fs_1.6.3          MASS_7.3-60       ragg_1.2.5       
-[45] callr_3.7.3       pkgconfig_2.0.3   desc_1.4.2        pkgdown_2.0.7    
-[49] bslib_0.5.1       pillar_1.9.0      gtable_0.3.3      glue_1.6.2       
-[53] systemfonts_1.0.4 xfun_0.40         tibble_3.2.1      lmtest_0.9-40    
-[57] tidyselect_1.2.0  rstudioapi_0.15.0 htmltools_0.5.6.1 nlme_3.1-163     
-[61] rmarkdown_2.23    compiler_4.3.1    prettyunits_1.2.0

+ [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] processx_3.8.1    pkgbuild_1.4.0    deSolve_1.35      DBI_1.1.3        
+[17] mclust_6.0.0      ps_1.7.5          gridExtra_2.3     purrr_1.0.1      
+[21] fansi_1.0.4       scales_1.2.1      codetools_0.2-19  textshaping_0.3.6
+[25] jquerylib_0.1.4   cli_3.6.1         crayon_1.5.2      rlang_1.1.1      
+[29] munsell_0.5.0     cachem_1.0.8      yaml_2.3.7        inline_0.3.19    
+[33] tools_4.3.2       memoise_2.0.1     dplyr_1.1.2       colorspace_2.1-0 
+[37] ggplot2_3.4.2     vctrs_0.6.2       R6_2.5.1          zoo_1.8-12       
+[41] lifecycle_1.0.3   stringr_1.5.0     fs_1.6.2          MASS_7.3-60      
+[45] ragg_1.2.5        callr_3.7.3       pkgconfig_2.0.3   desc_1.4.2       
+[49] pkgdown_2.0.7     bslib_0.4.2       pillar_1.9.0      gtable_0.3.3     
+[53] glue_1.6.2        systemfonts_1.0.4 highr_0.10        xfun_0.39        
+[57] tibble_3.2.1      lmtest_0.9-40     tidyselect_1.2.0  htmltools_0.5.5  
+[61] nlme_3.1-163      rmarkdown_2.21    compiler_4.3.2    prettyunits_1.1.1

 

 

 
Hardware info
 

-
CPU model: Intel(R) Xeon(R) Gold 6134 CPU @ 3.20GHz

-
MemTotal:       247605564 kB

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

+
MemTotal:       64927712 kB

 

 

-  

-
-  
 
-

 
 
-
-      

+    

   

 
Developed by Johannes Ranke.

 

 
-

+

   

 
Site built with pkgdown 2.0.7.

 

 
-      

+    

 

 
   
 
-
   
 
   
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diff --git a/docs/articles/prebuilt/2023_mesotrione_parent.html b/docs/articles/prebuilt/2023_mesotrione_parent.html
index 8f166a73..77f9bada 100644
--- a/docs/articles/prebuilt/2023_mesotrione_parent.html
+++ b/docs/articles/prebuilt/2023_mesotrione_parent.html
@@ -4,145 +4,104 @@
 
 
 
-
+
+
 Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione • mkin
-
-
-
+
+
+
 
-
-
+
 
 
 
-
+
+    Skip to contents
     
 
-    

-      

-  

-    

-      
Testing covariate modelling in hierarchical
-parent degradation kinetics with residue data on mesotrione

+
+

+  

+      
Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione

                         
Johannes
 Ranke

             
             
Last change on 4 August 2023,
-last compiled on 13 Oktober 2023

+last compiled on 16 November 2023
       
       Source: vignettes/prebuilt/2023_mesotrione_parent.rmd
-      
-
+      
2023_mesotrione_parent.rmd

     

 
     
@@ -2480,7 +2439,7 @@ further refined to make them fully identifiable.

 

 
Session info
 

-
R version 4.3.1 (2023-06-16)
+
R version 4.3.2 (2023-10-31)
 Platform: x86_64-pc-linux-gnu (64-bit)
 Running under: Debian GNU/Linux 12 (bookworm)
 
@@ -2509,19 +2468,18 @@ other attached packages:
 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_4.3.1        fastmap_1.1.1     cellranger_1.1.0  rprojroot_2.0.3  
-[13] jsonlite_1.8.4    DBI_1.1.3         mclust_6.0.0      gridExtra_2.3    
-[17] purrr_1.0.1       fansi_1.0.4       scales_1.2.1      codetools_0.2-19 
-[21] textshaping_0.3.6 jquerylib_0.1.4   cli_3.6.1         rlang_1.1.1      
-[25] munsell_0.5.0     cachem_1.0.8      yaml_2.3.7        tools_4.3.1      
-[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   nlme_3.1-162      rmarkdown_2.21   
-[57] compiler_4.3.1    readxl_1.4.2     

+ [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   

 

 

 
Hardware info
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MemTotal:       64928100 kB

 

 

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diff --git a/docs/articles/twa.html b/docs/articles/twa.html
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--- a/docs/articles/twa.html
+++ b/docs/articles/twa.html
@@ -4,145 +4,104 @@
 
 
 
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Calculation of time weighted average
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+

+  

+      
Calculation of time weighted average concentrations with mkin

                         
Johannes
 Ranke

             
             
Last change 18 September 2019
-(rebuilt 2023-10-30)

+(rebuilt 2023-11-16)
       
       Source: vignettes/twa.rmd
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+      
twa.rmd

     

 
     
@@ -214,32 +173,27 @@ 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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diff --git a/docs/articles/web_only/FOCUS_Z.html b/docs/articles/web_only/FOCUS_Z.html
index f19f59ad..7fd597d2 100644
--- a/docs/articles/web_only/FOCUS_Z.html
+++ b/docs/articles/web_only/FOCUS_Z.html
@@ -4,144 +4,104 @@
 
 
 
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Example evaluation of FOCUS dataset Z

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Example evaluation of FOCUS dataset Z

                         
Johannes
 Ranke

             
             
Last change 16 January 2018
-(rebuilt 2023-10-30)

+(rebuilt 2023-11-16)
       
       Source: vignettes/web_only/FOCUS_Z.rmd
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@@ -472,34 +432,27 @@ Studies on Pesticides in EU Registration. 1.1 ed. 
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diff --git a/docs/articles/web_only/NAFTA_examples.html b/docs/articles/web_only/NAFTA_examples.html
index 1c5be845..57b2ed1c 100644
--- a/docs/articles/web_only/NAFTA_examples.html
+++ b/docs/articles/web_only/NAFTA_examples.html
@@ -4,145 +4,104 @@
 
 
 
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+
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Evaluation of example datasets from Attachment 1
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+      
Evaluation of example datasets from Attachment 1 to the US EPA SOP for the NAFTA guidance

                         
Johannes
 Ranke

             
             
26 February 2019 (rebuilt
-2023-10-30)

+2023-11-16)
       
       Source: vignettes/web_only/NAFTA_examples.rmd
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NAFTA_examples.rmd

     

 
     
@@ -1079,34 +1038,27 @@ Pesticide Degradation.” 
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index 7c4af88b..17c2f8d8 100644
--- a/docs/articles/web_only/benchmarks.html
+++ b/docs/articles/web_only/benchmarks.html
@@ -4,144 +4,104 @@
 
 
 
-
+
+
 Benchmark timings for mkin • mkin
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Benchmark timings for mkin

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Benchmark timings for mkin

                         
Johannes
 Ranke

             
             
Last change 17 February 2023
-(rebuilt 2023-11-02)

+(rebuilt 2023-11-16)
       
       Source: vignettes/web_only/benchmarks.rmd
-      
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+      
benchmarks.rmd

     

 
     
@@ -465,8 +425,8 @@ models fitted to two datasets, i.e. eight fits for each test.

 Ryzen 9 7950X
 4.3.2
 1.2.6
-1.400
-2.012
+1.408
+2.041
 
 
 
@@ -736,9 +696,9 @@ for each test.

 Ryzen 9 7950X
 4.3.2
 1.2.6
-0.790
-2.212
-1.173
+0.795
+2.228
+1.178
 
 
 
@@ -1092,45 +1052,38 @@ dataset, i.e. one fit for each test.

 Ryzen 9 7950X
 4.3.2
 1.2.6
-0.432
-0.551
-0.580
-1.322
-0.746
-0.996
+0.439
+0.557
+0.585
+1.338
+0.749
+0.999
 
 
 
 

 

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diff --git a/docs/articles/web_only/compiled_models.html b/docs/articles/web_only/compiled_models.html
index 1aa88e05..210ddaf7 100644
--- a/docs/articles/web_only/compiled_models.html
+++ b/docs/articles/web_only/compiled_models.html
@@ -4,144 +4,103 @@
 
 
 
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 Performance benefit by using compiled model definitions in mkin • mkin
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Performance benefit by using compiled model
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Performance benefit by using compiled model definitions in mkin

                         
Johannes
 Ranke

             
-            
2023-10-30

+            
2023-11-16

       
       Source: vignettes/web_only/compiled_models.rmd
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+      
compiled_models.rmd

     

 
     
@@ -216,10 +175,10 @@ solution is also implemented, which is included in the tests below.

   print("R package rbenchmark is not available")
 }

 
##                    test replications relative elapsed
-## 4            analytical            1    1.000   0.213
-## 3     deSolve, compiled            1    1.418   0.302
-## 2      Eigenvalue based            1    2.000   0.426
-## 1 deSolve, not compiled            1   23.535   5.013

+## 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

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

 
@@ -250,44 +209,37 @@ compiled code is available.

 }

 
## Temporary DLL for differentials generated and loaded

 
##                    test replications relative elapsed
-## 2     deSolve, compiled            1    1.000   0.492
-## 1 deSolve, not compiled            1   20.398  10.036

-
Here we get a performance benefit of a factor of 20 using the version
+## 2     deSolve, compiled            1    1.000   0.181
+## 1 deSolve, not compiled            1   23.646   4.280

+
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 4.3.1 (2023-06-16)
+
## R version 4.3.2 (2023-10-31)
 ## Platform: x86_64-pc-linux-gnu (64-bit)
-## Running under: Ubuntu 22.04.3 LTS

-
## CPU model: Intel(R) Xeon(R) Gold 6134 CPU @ 3.20GHz

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

 
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diff --git a/docs/articles/web_only/dimethenamid_2018.html b/docs/articles/web_only/dimethenamid_2018.html
index 1cffd561..4221ba07 100644
--- a/docs/articles/web_only/dimethenamid_2018.html
+++ b/docs/articles/web_only/dimethenamid_2018.html
@@ -4,145 +4,104 @@
 
 
 
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 Example evaluations of the dimethenamid data from 2018 • mkin
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Example evaluations of the dimethenamid data
-from 2018

+
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Example evaluations of the dimethenamid data from 2018

                         
Johannes
 Ranke

             
             
Last change 1 July 2022,
-built on 30 Oct 2023

+built on 16 Nov 2023
       
       Source: vignettes/web_only/dimethenamid_2018.rmd
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@@ -225,12 +184,12 @@ 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", ]))

+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", ]))
+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 @@ -242,7 +201,7 @@ 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 @@ -254,7 +213,7 @@ 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 @@ -344,7 +303,7 @@ 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)

@@ -361,17 +320,8 @@ 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)
-
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
-
-saemix_control <- saemixControl(nbiter.saemix = c(800, 300), nb.chains = 15,
+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)
@@ -379,7 +329,7 @@ Attaching package: 'saemix'
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")

@@ -387,19 +337,19 @@ 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:
@@ -435,14 +385,14 @@ 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:
@@ -484,7 +434,7 @@ 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,
@@ -492,7 +442,7 @@ 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)

@@ -506,7 +456,7 @@ 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(
@@ -530,7 +480,7 @@ 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)
@@ -550,7 +500,7 @@ 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"),
@@ -561,7 +511,7 @@ 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)

 
@@ -624,48 +574,48 @@ satisfactory precision.

 
Session Info
 

-
+
-
R version 4.3.1 (2023-06-16)
+
R version 4.3.2 (2023-10-31)
 Platform: x86_64-pc-linux-gnu (64-bit)
-Running under: Ubuntu 22.04.3 LTS
+Running under: Debian GNU/Linux 12 (bookworm)
 
 Matrix products: default
-BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0 
-LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
+BLAS:   /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.11.0 
+LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.11.0
 
 locale:
- [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
- [3] LC_TIME=C                  LC_COLLATE=en_US.UTF-8    
- [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
- [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
+ [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=en_US.UTF-8 LC_IDENTIFICATION=C       
+[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C       
 
-time zone: Europe/Zurich
+time zone: Europe/Berlin
 tzcode source: system (glibc)
 
 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_1.44  
+[1] saemix_3.2   npde_3.3     nlme_3.1-163 mkin_1.2.6   knitr_1.42  
 
 loaded via a namespace (and not attached):
- [1] sass_0.4.7        utf8_1.2.3        generics_0.1.3    stringi_1.7.12   
- [5] lattice_0.21-9    digest_0.6.33     magrittr_2.0.3    evaluate_0.22    
- [9] grid_4.3.1        fastmap_1.1.1     rprojroot_2.0.3   jsonlite_1.8.7   
-[13] mclust_6.0.0      gridExtra_2.3     purrr_1.0.1       fansi_1.0.4      
-[17] scales_1.2.1      codetools_0.2-19  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_4.3.1       parallel_4.3.1    memoise_2.0.1    
-[29] dplyr_1.1.2       colorspace_2.1-0  ggplot2_3.4.2     vctrs_0.6.3      
-[33] R6_2.5.1          zoo_1.8-12        lifecycle_1.0.3   stringr_1.5.0    
-[37] fs_1.6.3          MASS_7.3-60       ragg_1.2.5        pkgconfig_2.0.3  
-[41] desc_1.4.2        pkgdown_2.0.7     bslib_0.5.1       pillar_1.9.0     
-[45] gtable_0.3.3      glue_1.6.2        systemfonts_1.0.4 xfun_0.40        
-[49] tibble_3.2.1      lmtest_0.9-40     tidyselect_1.2.0  rstudioapi_0.15.0
-[53] htmltools_0.5.6.1 rmarkdown_2.23    compiler_4.3.1   

+ [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   

 

 

 
References
@@ -690,34 +640,27 @@ November 2017.” 
-
-        
-

-
+  
 

 
 
 
-      
 
   
 
-
   
 
   
diff --git a/docs/articles/web_only/multistart.html b/docs/articles/web_only/multistart.html
index dff087e4..4438adc3 100644
--- a/docs/articles/web_only/multistart.html
+++ b/docs/articles/web_only/multistart.html
@@ -4,144 +4,104 @@
 
-
+
+Short demo of the multistart method • mkin
-
-
-
+
+
+
-
-
+
-
+
+    Skip to contents
     
 
-    

-      

-  

-    

-      
Short demo of the multistart method

+

+  

+      
Short demo of the multistart method

                         
Johannes
 Ranke

             
             
Last change 20 April 2023
-(rebuilt 2023-10-30)

+(rebuilt 2023-11-16)
       
       Source: vignettes/web_only/multistart.rmd
-      
-
+      
multistart.rmd

     

 
     
@@ -207,32 +167,27 @@ 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.

-  

-
-  
-
+  
 

 
 
 
-      

+    

   

 
Developed by Johannes Ranke.

 

 
-

+

   

 
Site built with pkgdown 2.0.7.

 

 
-      

+    

 

 
   
 
-
   
 
   
diff --git a/docs/articles/web_only/multistart_files/figure-html/unnamed-chunk-3-1.png b/docs/articles/web_only/multistart_files/figure-html/unnamed-chunk-3-1.png
index 8be6ba61..f41dc889 100644
Binary files a/docs/articles/web_only/multistart_files/figure-html/unnamed-chunk-3-1.png and b/docs/articles/web_only/multistart_files/figure-html/unnamed-chunk-3-1.png differ
diff --git a/docs/articles/web_only/multistart_files/figure-html/unnamed-chunk-4-1.png b/docs/articles/web_only/multistart_files/figure-html/unnamed-chunk-4-1.png
index bc518c0c..9e206791 100644
Binary files a/docs/articles/web_only/multistart_files/figure-html/unnamed-chunk-4-1.png and b/docs/articles/web_only/multistart_files/figure-html/unnamed-chunk-4-1.png differ
diff --git a/docs/articles/web_only/multistart_files/figure-html/unnamed-chunk-5-1.png b/docs/articles/web_only/multistart_files/figure-html/unnamed-chunk-5-1.png
index 9ecdf4c9..c8e918cd 100644
Binary files a/docs/articles/web_only/multistart_files/figure-html/unnamed-chunk-5-1.png and b/docs/articles/web_only/multistart_files/figure-html/unnamed-chunk-5-1.png differ
diff --git a/docs/articles/web_only/saem_benchmarks.html b/docs/articles/web_only/saem_benchmarks.html
index 9180773e..91e41a5b 100644
--- a/docs/articles/web_only/saem_benchmarks.html
+++ b/docs/articles/web_only/saem_benchmarks.html
@@ -4,144 +4,104 @@
 
 
 
-
+
+
 Benchmark timings for saem.mmkin • mkin
-
-
-
+
+
+
 
-
-
+
 
 
 
-
+
+    Skip to contents
     
 
-    

-      

-  

-    

-      
Benchmark timings for saem.mmkin

+
+

+  

+      
Benchmark timings for saem.mmkin

                         
Johannes
 Ranke

             
             
Last change 17 February 2023
-(rebuilt 2023-11-02)

+(rebuilt 2023-11-16)
       
       Source: vignettes/web_only/saem_benchmarks.rmd
-      
-
+      
saem_benchmarks.rmd

     

 
     
@@ -193,7 +153,7 @@ explanation of the following preprocessing.

 
 anova(
   sfo_const, dfop_const, sforb_const, hs_const,
-  sfo_tc, dfop_tc, sforb_tc, hs_tc) |> kable(, digits = 1)

+  sfo_tc, dfop_tc, sforb_tc, hs_tc) |> kable(, digits = 1)

 

 

 Degradation model
 
 
 
 
 
 
 
 
 

@@ -440,10 +400,10 @@ systems. All trademarks belong to their respective owners.

-
-
-
-
+
+
+
+

 

 
 Linux
 1.2.6
 3.21.1261.9712.3592.4241.1352.0252.4062.478
 

 
 

@@ -555,10 +515,10 @@ systems. All trademarks belong to their respective owners.

 Linux
 1.2.6
 3.2
-2.116
-3.246
-3.602
-3.036
+2.161
+3.325
+3.669
+3.153
 
 
 
@@ -654,8 +614,8 @@ systems. All trademarks belong to their respective owners.

 Linux
 1.2.6
 3.2
-11.712
-290.532
+12.007
+286.757
 
 
 
@@ -741,40 +701,33 @@ systems. All trademarks belong to their respective owners.

 Linux
 1.2.6
 3.2
-479.161
+480.577
 
 
 
 

 

-  

-
-  
 
-

 
 
-
-      

+    

   

 
Developed by Johannes Ranke.

 

 
-

+

   

 
Site built with pkgdown 2.0.7.

 

 
-      

+    

 

 
   
 
-
   
 
   
-- 
cgit v1.2.1