From 91c5db736a4d3f2290a0cc5698fb4e35ae7bda59 Mon Sep 17 00:00:00 2001
From: Johannes Ranke For comparison, the FOMC model is fitted as well, and the \(\chi^2\) error level is checked. We get a warning that the default optimisation algorithm 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 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). The following code defines example dataset L2 from the FOCUS kinetics report, p. 287: Again, the SFO model is fitted and the result is plotted. The residual plot can be obtained simply by adding the argument For comparison, the FOMC model is fitted as well, and the \(\chi^2\) error level is checked. Fitting the four parameter DFOP model further reduces the \(\chi^2\) error level. Here, the DFOP model is clearly the best-fit model for dataset L2 based on the chi^2 error level criterion. However, the failure to calculate the covariance matrix indicates that the parameter estimates correlate excessively. Therefore, the FOMC model may be preferred for this dataset. Here, the DFOP model is clearly the best-fit model for dataset L2 based on the chi^2 error level criterion. The following code defines example dataset L3 from the FOCUS kinetics report, p. 290. 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 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. 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. The following code defines example dataset L4 from the FOCUS kinetics report, p. 293: Fits of the SFO and FOMC models, plots and summaries are produced below: 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. 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. 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. 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. 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. Parent only: Currently, we only have benchmark information on one system, therefore only the mkin version is shown with the results below. Timings are in seconds, shorter is better. All results were obtained by serial, i.e. not using multiple computing cores. Benchmarks for all available error models are shown. Constant variance (t1) and two-component error model (t2) for four models fitted to two datasets, i.e. eight fits for each test. ‘dimethenamid_2018’: Update example code to use saemix ‘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 ‘vignettes/web_only/benchmarks.rmd’: Add the first benchmark data using my laptop system, therefore add the CPU when showing the benchmark results. ‘dimethenamid_2018’: Update example code to use saemix ‘CAKE_export’: Check for validity of the map argument, updates ‘saem()’: Slightly improve speed in the case that no analytical solution for saemix is implemented, activate a test of the respective code ‘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 ‘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 ‘plot.mkinfit’: Respect argument ‘maxabs’ for residual plots, and make it possible to give ylim as a list, for row layouts All plotting functions setting graphical parameters: Use on.exit() for resetting graphical parameters ‘nlme.mmkin’: An nlme method for mmkin row objects and an associated S3 class with print, plot, anova and endpoint methods Rename Add plots to Site built with pkgdown 2.0.2. Site built with pkgdown 2.0.3.Example evaluation of FOCUS Example Dataset D
Johannes Ranke
- Last change 31 January 2019 (rebuilt 2022-03-07)
+ Last change 31 January 2019 (rebuilt 2022-05-18)
Source: vignettes/FOCUS_D.rmd
FOCUS_D.rmd
summary(fit)
## mkin version used for fitting: 1.1.0
-## R version used for fitting: 4.1.2
-## Date of fit: Mon Mar 7 13:15:58 2022
-## Date of summary: Mon Mar 7 13:15:59 2022
+## R version used for fitting: 4.2.0
+## Date of fit: Wed May 18 20:42:29 2022
+## Date of summary: Wed May 18 20:42:30 2022
##
## Equations:
## d_parent/dt = - k_parent * parent
@@ -201,7 +201,7 @@
##
## Model predictions using solution type analytical
##
-## Fitted using 401 model solutions performed in 0.165 s
+## Fitted using 401 model solutions performed in 0.144 s
##
## Error model: Constant variance
##
@@ -244,11 +244,11 @@
##
## 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
+## parent_0 1.000e+00 5.174e-01 -1.688e-01 -5.471e-01 -1.174e-06
+## log_k_parent 5.174e-01 1.000e+00 -3.263e-01 -5.426e-01 -8.492e-07
+## log_k_m1 -1.688e-01 -3.263e-01 1.000e+00 7.478e-01 8.220e-07
+## f_parent_qlogis -5.471e-01 -5.426e-01 7.478e-01 1.000e+00 1.307e-06
+## sigma -1.174e-06 -8.492e-07 8.220e-07 1.307e-06 1.000e+00
##
## Backtransformed parameters:
## Confidence intervals for internally transformed parameters are asymmetric.
@@ -334,7 +334,7 @@
diff --git a/docs/articles/FOCUS_L.html b/docs/articles/FOCUS_L.html
index d7412a56..5f41b6a3 100644
--- a/docs/articles/FOCUS_L.html
+++ b/docs/articles/FOCUS_L.html
@@ -105,7 +105,7 @@
Example evaluation of FOCUS Laboratory Data L1 to L3
Johannes Ranke
- Last change 17 November 2016 (rebuilt 2022-03-07)
+ Last change 17 November 2016 (rebuilt 2022-05-18)
Source: vignettes/FOCUS_L.rmd
FOCUS_L.rmd
m.L1.SFO <- mkinfit("SFO", FOCUS_2006_L1_mkin, quiet = TRUE)
summary(m.L1.SFO)
-## mkin version used for fitting: 1.1.0
-## R version used for fitting: 4.1.2
-## Date of fit: Mon Mar 7 13:16:01 2022
-## Date of summary: Mon Mar 7 13:16:01 2022
+## R version used for fitting: 4.2.0
+## Date of fit: Wed May 18 20:42:32 2022
+## Date of summary: Wed May 18 20:42:32 2022
##
## Equations:
## d_parent/dt = - k_parent * parent
##
## Model predictions using solution type analytical
##
-## Fitted using 133 model solutions performed in 0.032 s
+## Fitted using 133 model solutions performed in 0.031 s
##
## Error model: Constant variance
##
@@ -173,9 +173,9 @@
##
## 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
+## parent_0 1.000e+00 6.186e-01 -1.712e-09
+## log_k_parent 6.186e-01 1.000e+00 -3.237e-09
+## sigma -1.712e-09 -3.237e-09 1.000e+00
##
## Backtransformed parameters:
## Confidence intervals for internally transformed parameters are asymmetric.
@@ -225,29 +225,26 @@
-
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")
m.L1.FOMC <- mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet=TRUE)
+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
+## DT50 DT90 DT50back
+## parent 7.249 24.08 7.249## mkin version used for fitting: 1.1.0
-## R version used for fitting: 4.1.2
-## Date of fit: Mon Mar 7 13:16:02 2022
-## Date of summary: Mon Mar 7 13:16:02 2022
+## R version used for fitting: 4.2.0
+## Date of fit: Wed May 18 20:42:33 2022
+## Date of summary: Wed May 18 20:42:33 2022
##
## Equations:
## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
##
## Model predictions using solution type analytical
##
-## Fitted using 369 model solutions performed in 0.081 s
+## Fitted using 357 model solutions performed in 0.072 s
##
## Error model: Constant variance
##
@@ -268,39 +265,34 @@
## Fixed parameter values:
## None
##
-##
-## Warning(s):
-## Optimisation did not converge:
-## false convergence (8)
-##
## Results:
##
-## AIC BIC logLik
-## 95.88781 99.44929 -43.9439
+## AIC BIC logLik
+## 95.88804 99.44953 -43.94402
##
## 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
+## log_alpha 11.37 NaN NaN NaN
+## log_beta 13.72 NaN NaN NaN
+## sigma 2.78 0.4621 1.789 3.771
##
## Parameter correlation:
## parent_0 log_alpha log_beta sigma
-## parent_0 1.0000000 NaN NaN 0.0001671
+## parent_0 1.0000000 NaN NaN 0.0005548
## log_alpha NaN 1 NaN NaN
## log_beta NaN NaN 1 NaN
-## sigma 0.0001671 NaN NaN 1.0000000
+## sigma 0.0005548 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
+## parent_0 92.47 NA NA 89.720 95.220
+## alpha 87110.00 NA NA NA NA
+## beta 911100.00 NA NA NA NA
+## sigma 2.78 NA NA 1.789 3.771
##
## FOCUS Chi2 error levels in percent:
## err.min n.optim df
@@ -308,8 +300,8 @@
## parent 3.619 3 6
##
## Estimated disappearance times:
-## DT50 DT90 DT50back
-## parent 7.25 24.08 7.25
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.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.Laboratory Data L2
+
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,
@@ -329,7 +321,7 @@
SFO fit for L2
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")
FOMC fit for L2
+
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: 1.1.0
-## R version used for fitting: 4.1.2
-## Date of fit: Mon Mar 7 13:16:03 2022
-## Date of summary: Mon Mar 7 13:16:03 2022
+## R version used for fitting: 4.2.0
+## Date of fit: Wed May 18 20:42:33 2022
+## Date of summary: Wed May 18 20:42:33 2022
##
## Equations:
## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
##
## Model predictions using solution type analytical
##
-## Fitted using 239 model solutions performed in 0.049 s
+## Fitted using 239 model solutions performed in 0.044 s
##
## Error model: Constant variance
##
@@ -394,10 +386,10 @@
##
## 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
+## parent_0 1.000e+00 -1.151e-01 -2.085e-01 -7.637e-09
+## log_alpha -1.151e-01 1.000e+00 9.741e-01 -1.617e-07
+## log_beta -2.085e-01 9.741e-01 1.000e+00 -1.387e-07
+## sigma -7.637e-09 -1.617e-07 -1.387e-07 1.000e+00
##
## Backtransformed parameters:
## Confidence intervals for internally transformed parameters are asymmetric.
@@ -423,17 +415,17 @@
DFOP fit for L2
+
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: 1.1.0
-## R version used for fitting: 4.1.2
-## Date of fit: Mon Mar 7 13:16:03 2022
-## Date of summary: Mon Mar 7 13:16:03 2022
+## R version used for fitting: 4.2.0
+## Date of fit: Wed May 18 20:42:34 2022
+## Date of summary: Wed May 18 20:42:34 2022
##
## Equations:
## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -442,7 +434,7 @@
##
## Model predictions using solution type analytical
##
-## Fitted using 581 model solutions performed in 0.132 s
+## Fitted using 581 model solutions performed in 0.121 s
##
## Error model: Constant variance
##
@@ -473,18 +465,18 @@
## 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_k1 3.113 1.845e+03 -4360.0000 4367.0000
## 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
+## parent_0 1.000e+00 6.784e-07 -5.188e-10 2.665e-01 -5.800e-10
+## log_k1 6.784e-07 1.000e+00 1.114e-04 -2.191e-04 -1.029e-05
+## log_k2 -5.188e-10 1.114e-04 1.000e+00 -7.903e-01 5.080e-09
+## g_qlogis 2.665e-01 -2.191e-04 -7.903e-01 1.000e+00 -7.991e-09
+## sigma -5.800e-10 -1.029e-05 5.080e-09 -7.991e-09 1.000e+00
##
## Backtransformed parameters:
## Confidence intervals for internally transformed parameters are asymmetric.
@@ -492,7 +484,7 @@
## 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
+## k1 22.4800 5.544e-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
@@ -504,15 +496,15 @@
##
## Estimated disappearance times:
## DT50 DT90 DT50back DT50_k1 DT50_k2
-## parent 0.5335 5.311 1.599 0.03084 2.058
Laboratory Data L3
+
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))
@@ -521,7 +513,7 @@
Fit multiple models
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)
@@ -534,12 +526,12 @@
+
summary(mm.L3[["DFOP", 1]])
-## mkin version used for fitting: 1.1.0
-## R version used for fitting: 4.1.2
-## Date of fit: Mon Mar 7 13:16:04 2022
-## Date of summary: Mon Mar 7 13:16:04 2022
+## R version used for fitting: 4.2.0
+## Date of fit: Wed May 18 20:42:34 2022
+## Date of summary: Wed May 18 20:42:35 2022
##
## Equations:
## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
@@ -548,7 +540,7 @@
##
## Model predictions using solution type analytical
##
-## Fitted using 376 model solutions performed in 0.08 s
+## Fitted using 376 model solutions performed in 0.073 s
##
## Error model: Constant variance
##
@@ -586,11 +578,11 @@
##
## 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
+## parent_0 1.000e+00 1.732e-01 2.282e-02 4.009e-01 -9.632e-08
+## log_k1 1.732e-01 1.000e+00 4.945e-01 -5.809e-01 7.145e-07
+## log_k2 2.282e-02 4.945e-01 1.000e+00 -6.812e-01 1.021e-06
+## g_qlogis 4.009e-01 -5.809e-01 -6.812e-01 1.000e+00 -7.925e-07
+## sigma -9.632e-08 7.145e-07 1.021e-06 -7.925e-07 1.000e+00
##
## Backtransformed parameters:
## Confidence intervals for internally transformed parameters are asymmetric.
@@ -622,7 +614,7 @@
## 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)
Laboratory Data L4
+
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)
+
# 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),
@@ -647,19 +639,19 @@
plot(mm.L4)
+
summary(mm.L4[["SFO", 1]], data = FALSE)
-## mkin version used for fitting: 1.1.0
-## R version used for fitting: 4.1.2
-## Date of fit: Mon Mar 7 13:16:04 2022
-## Date of summary: Mon Mar 7 13:16:05 2022
+## R version used for fitting: 4.2.0
+## Date of fit: Wed May 18 20:42:35 2022
+## Date of summary: Wed May 18 20:42:35 2022
##
## Equations:
## d_parent/dt = - k_parent * parent
##
## Model predictions using solution type analytical
##
-## Fitted using 142 model solutions performed in 0.029 s
+## Fitted using 142 model solutions performed in 0.027 s
##
## Error model: Constant variance
##
@@ -691,9 +683,9 @@
##
## 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
+## parent_0 1.000e+00 5.938e-01 3.440e-07
+## log_k_parent 5.938e-01 1.000e+00 5.885e-07
+## sigma 3.440e-07 5.885e-07 1.000e+00
##
## Backtransformed parameters:
## Confidence intervals for internally transformed parameters are asymmetric.
@@ -712,19 +704,19 @@
## Estimated disappearance times:
## DT50 DT90
## parent 106 352
+
summary(mm.L4[["FOMC", 1]], data = FALSE)
## mkin version used for fitting: 1.1.0
-## R version used for fitting: 4.1.2
-## Date of fit: Mon Mar 7 13:16:04 2022
-## Date of summary: Mon Mar 7 13:16:05 2022
+## R version used for fitting: 4.2.0
+## Date of fit: Wed May 18 20:42:35 2022
+## Date of summary: Wed May 18 20:42:35 2022
##
## Equations:
## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
##
## Model predictions using solution type analytical
##
-## Fitted using 224 model solutions performed in 0.045 s
+## Fitted using 224 model solutions performed in 0.041 s
##
## Error model: Constant variance
##
@@ -759,10 +751,10 @@
##
## 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
+## parent_0 1.000e+00 -4.696e-01 -5.543e-01 -2.563e-07
+## log_alpha -4.696e-01 1.000e+00 9.889e-01 4.066e-08
+## log_beta -5.543e-01 9.889e-01 1.000e+00 6.818e-08
+## sigma -2.563e-07 4.066e-08 6.818e-08 1.000e+00
##
## Backtransformed parameters:
## Confidence intervals for internally transformed parameters are asymmetric.
@@ -811,7 +803,7 @@
diff --git a/docs/articles/FOCUS_L_files/figure-html/unnamed-chunk-6-1.png b/docs/articles/FOCUS_L_files/figure-html/unnamed-chunk-6-1.png
index b6130527..b56e91e1 100644
Binary files a/docs/articles/FOCUS_L_files/figure-html/unnamed-chunk-6-1.png and b/docs/articles/FOCUS_L_files/figure-html/unnamed-chunk-6-1.png differ
diff --git a/docs/articles/index.html b/docs/articles/index.html
index f340896b..89eb092b 100644
--- a/docs/articles/index.html
+++ b/docs/articles/index.html
@@ -112,7 +112,7 @@
Introduction to mkin
Johannes Ranke
- Last change 15 February 2021 (rebuilt 2022-03-07)
+ Last change 15 February 2021 (rebuilt 2022-05-18)
Source: vignettes/mkin.rmd
mkin.rmd
Calculation of time weighted average concentrations with mkin
Johannes Ranke
- Last change 18 September 2019 (rebuilt 2022-03-07)
+ Last change 18 September 2019 (rebuilt 2022-05-18)
Source: vignettes/twa.rmd
twa.rmd
Example evaluation of FOCUS dataset Z
Johannes Ranke
- Last change 16 January 2018 (rebuilt 2022-03-07)
+ Last change 16 January 2018 (rebuilt 2022-05-18)
Source: vignettes/web_only/FOCUS_Z.rmd
FOCUS_Z.rmd
-## 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
+## Z0_0 96.838397 1.994270 48.5583 4.0284e-42 92.826435 100.850359
+## k_Z0 2.215406 0.118459 18.7018 1.0416e-23 1.989466 2.467005
+## k_Z1 0.478300 0.028257 16.9267 6.2409e-22 0.424702 0.538662
+## k_Z2 0.451616 0.042137 10.7178 1.6305e-14 0.374328 0.544863
+## k_Z3 0.058693 0.015245 3.8499 1.7803e-04 0.034805 0.098976
+## f_Z2_to_Z3 0.471509 0.058352 8.0804 9.6622e-11 0.357739 0.588317
## sigma 3.984431 0.383402 10.3923 4.5575e-14 3.213126 4.755736
+
endpoints(m.Z.FOCUS)
+## Z1 1.44919 4.8141
+## Z2 1.53481 5.0985
+## Z3 11.80971 39.2310## $ff
## Z2_Z3 Z2_sink
-## 0.4715 0.5285
+## 0.47151 0.52849
##
## $distimes
## DT50 DT90
## Z0 0.31288 1.0394
-## Z1 1.44917 4.8141
-## Z2 1.53478 5.0984
-## Z3 11.80986 39.2315
+
Z.mkin.1 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
Z1 = mkinsub("SFO", "Z2", sink = FALSE),
Z2 = mkinsub("SFO", "Z3"),
Z3 = mkinsub("SFORB"))
-## Temporary DLL for differentials generated and loaded
+
m.Z.mkin.1 <- mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE)
-## Warning in mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE): Observations with
## value of zero were removed from the data
+
plot_sep(m.Z.mkin.1)
+
summary(m.Z.mkin.1, data = FALSE)$cov.unscaled
## NULL
+
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
+
@@ -398,7 +398,7 @@
diff --git a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png
index bc6efaf7..229bae82 100644
Binary files a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png and b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_10-1.png differ
diff --git a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11-1.png
index 55c1b645..e13ad9aa 100644
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diff --git a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11a-1.png
index 8e63cd04..ae160414 100644
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diff --git a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_11b-1.png
index 3902e059..23e270d1 100644
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diff --git a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png
index d95cac25..77965455 100644
Binary files a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png and b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_5-1.png differ
diff --git a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png
index cb333a1c..250d0df5 100644
Binary files a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png and b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_6-1.png differ
diff --git a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png
index db807f14..5a01c03e 100644
Binary files a/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png and b/docs/articles/web_only/FOCUS_Z_files/figure-html/FOCUS_2006_Z_fits_9-1.png differ
diff --git a/docs/articles/web_only/NAFTA_examples.html b/docs/articles/web_only/NAFTA_examples.html
index 996e5d49..df1e06db 100644
--- a/docs/articles/web_only/NAFTA_examples.html
+++ b/docs/articles/web_only/NAFTA_examples.html
@@ -43,7 +43,7 @@
Functions and data
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
## Warning in mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE): Optimisation did not converge:
+## false convergence (8)
plot_sep(m.Z.mkin.3)
Evaluation of example datasets from Attachment 1 to the US EPA SOP for the NAFTA guidance
Johannes Ranke
- 26 February 2019 (rebuilt 2022-03-02)
+ 26 February 2019 (rebuilt 2022-05-18)
Source: vignettes/web_only/NAFTA_examples.rmd
NAFTA_examples.rmd
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
@@ -482,8 +477,8 @@
## 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
+## k2 0.0389 2.24e-04 0.0255 0.0592
+## g 0.5256 5.00e-01 0.0000 1.0000
## sigma 1.5957 2.50e-04 0.9135 2.2779
##
##
@@ -500,7 +495,7 @@
Example on page 10
-
+
p10 <- nafta(NAFTA_SOP_Attachment[["p10"]])
## Warning in sqrt(diag(covar)): NaNs produced
@@ -508,10 +503,10 @@
## doubtful## Warning in sqrt(1/diag(V)): 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(p10)
+
print(p10)
## Sums of squares:
## SFO IORE DFOP
@@ -537,8 +532,8 @@
## $DFOP
## Estimate Pr(>t) Lower Upper
## parent_0 101.7315 1.41e-09 91.6534 111.8097
-## k1 0.0495 6.58e-03 0.0303 0.0809
-## k2 0.0495 2.60e-03 0.0410 0.0598
+## k1 0.0495 6.32e-03 0.0241 0.1018
+## k2 0.0495 2.41e-03 0.0272 0.0901
## g 0.4487 5.00e-01 NA NA
## sigma 8.0152 2.50e-04 4.5886 11.4418
##
@@ -560,14 +555,14 @@
Example on page 11
-
+
p11 <- nafta(NAFTA_SOP_Attachment[["p11"]])
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
-## The half-life obtained from the IORE model may be used
+
plot(p11)
+
print(p11)
+## [1] 41148171## Sums of squares:
## SFO IORE DFOP
@@ -594,7 +589,7 @@
## Estimate Pr(>t) Lower Upper
## parent_0 1.05e+02 9.47e-13 99.9990 109.1224
## k1 4.41e-02 5.95e-03 0.0296 0.0658
-## k2 9.94e-13 5.00e-01 0.0000 Inf
+## k2 9.93e-13 5.00e-01 0.0000 Inf
## g 3.22e-01 1.45e-03 0.2814 0.3650
## sigma 3.22e+00 3.52e-04 1.8410 4.5906
##
@@ -606,7 +601,7 @@
## DFOP 3.07e+11 1.93e+12 6.98e+11
##
## Representative half-life:
-## [1] 41148170
Example on page 12, upper panel
-
+
p12a <- nafta(NAFTA_SOP_Attachment[["p12a"]])
-## Warning in summary.mkinfit(x): Could not calculate correlation; no covariance
+## matrix
+
+## Warning in summary.mkinfit(x): Could not calculate correlation; no covariance
## matrix
-## Warning in sqrt(diag(covar)): NaNs produced
-## Warning in sqrt(diag(covar_notrans)): NaNs produced
-## Warning in sqrt(1/diag(V)): NaNs produced
## Warning in cov2cor(ans$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
@@ -655,12 +648,12 @@
## sigma 3.965 NA NA NA
##
## $DFOP
-## Estimate Pr(>t) Lower Upper
-## parent_0 100.521 2.74e-10 92.2366 108.805
-## k1 0.124 2.53e-05 0.0908 0.170
-## k2 0.124 2.52e-02 0.0456 0.339
-## g 0.793 NaN NA NA
-## sigma 7.048 2.50e-04 4.0349 10.061
+## Estimate Pr(>t) Lower Upper
+## parent_0 100.521 NA NA NA
+## k1 0.124 NA NA NA
+## k2 0.124 NA NA NA
+## g 0.793 NA NA NA
+## sigma 7.048 NA NA NA
##
##
## DTx values:
@@ -675,18 +668,17 @@
Example on page 12, lower panel
-
+
p12b <- nafta(NAFTA_SOP_Attachment[["p12b"]])
## Warning in qt(alpha/2, rdf): NaNs produced
-## Warning in qt(1 - alpha/2, rdf): NaNs produced
## Warning in sqrt(diag(covar_notrans)): NaNs produced
## Warning in pt(abs(tval), rdf, lower.tail = FALSE): NaNs produced
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
-## The half-life obtained from the IORE model may be used
+
plot(p12b)
+
print(p12b)
## Sums of squares:
## SFO IORE DFOP
@@ -730,14 +722,18 @@
Example on page 13
-
+
p13 <- nafta(NAFTA_SOP_Attachment[["p13"]])
+## Warning in sqrt(diag(covar)): NaNs produced
+## Warning in sqrt(1/diag(V)): NaNs produced
## Warning in cov2cor(ans$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(p13)
+
print(p13)
## Sums of squares:
## SFO IORE DFOP
@@ -763,9 +759,9 @@
## $DFOP
## Estimate Pr(>t) Lower Upper
## parent_0 92.73500 NA 8.95e+01 95.92118
-## k1 0.00258 NA 4.14e-04 0.01611
-## k2 0.00258 NA 1.74e-03 0.00383
-## g 0.16452 NA 0.00e+00 1.00000
+## k1 0.00258 NA 4.24e-04 0.01573
+## k2 0.00258 NA 1.76e-03 0.00379
+## g 0.16452 NA NA NA
## sigma 3.41172 NA 2.02e+00 4.79960
##
##
@@ -782,7 +778,7 @@
DT50 not observed in the study and DFOP problems in PestDF
-
+
p14 <- nafta(NAFTA_SOP_Attachment[["p14"]])
## Warning in sqrt(diag(covar)): NaNs produced
@@ -790,10 +786,10 @@
## doubtful## Warning in sqrt(1/diag(V)): NaNs produced
## The SFO model is rejected as S_SFO is equal or higher than the critical value S_c
-## The half-life obtained from the IORE model may be used
+
plot(p14)
+
print(p14)
@@ -838,14 +834,18 @@
## Sums of squares:
## SFO IORE DFOP
@@ -820,7 +816,7 @@
## Estimate Pr(>t) Lower Upper
## parent_0 1.00e+02 2.96e-28 99.40280 101.2768
## k1 9.53e-03 1.20e-01 0.00638 0.0143
-## k2 6.08e-12 5.00e-01 0.00000 Inf
+## k2 5.03e-12 5.00e-01 0.00000 Inf
## g 3.98e-01 2.19e-01 0.30481 0.4998
## sigma 1.17e+00 7.68e-06 0.77406 1.5610
##
@@ -829,7 +825,7 @@
## DT50 DT90 DT50_rep
## SFO 2.48e+02 8.25e+02 2.48e+02
## IORE 4.34e+02 2.22e+04 6.70e+03
-## DFOP 3.05e+10 2.95e+11 1.14e+11
+## DFOP 3.69e+10 3.57e+11 1.38e+11
##
## Representative half-life:
## [1] 6697.44
N is less than 1 and DFOP fraction parameter is below zero
-
+
p15a <- nafta(NAFTA_SOP_Attachment[["p15a"]])
+## Warning in sqrt(diag(covar)): NaNs produced
+## Warning in sqrt(1/diag(V)): NaNs produced
## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is
+## doubtful
## 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
@@ -871,9 +871,9 @@
## $DFOP
## Estimate Pr(>t) Lower Upper
## parent_0 97.96751 2.85e-13 94.21913 101.7159
-## k1 0.00952 6.28e-02 0.00250 0.0363
-## k2 0.00952 1.27e-04 0.00646 0.0140
-## g 0.21241 5.00e-01 0.00000 1.0000
+## k1 0.00952 6.28e-02 0.00260 0.0349
+## k2 0.00952 1.27e-04 0.00652 0.0139
+## g 0.21241 5.00e-01 NA NA
## sigma 4.18778 2.50e-04 2.39747 5.9781
##
##
@@ -885,18 +885,14 @@
##
## Representative half-life:
## [1] 41.33
+
p15b <- nafta(NAFTA_SOP_Attachment[["p15b"]])
-## Warning in sqrt(diag(covar)): NaNs produced
-## Warning in sqrt(1/diag(V)): NaNs produced
## Warning in cov2cor(ans$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
@@ -916,15 +912,15 @@
## 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
+## N_parent 0.00 5.00e-01 -1.07695 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
+## k1 4.86e-03 NA 8.62e-04 2.74e-02
## k2 4.86e-03 NA 3.21e-03 7.35e-03
-## g 1.88e-01 NA NA NA
+## g 1.88e-01 NA 0.00e+00 1.00e+00
## sigma 2.76e+00 NA 1.58e+00 3.94e+00
##
##
@@ -941,16 +937,16 @@
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
@@ -1026,7 +1022,7 @@
diff --git a/docs/articles/web_only/NAFTA_examples_files/figure-html/p10-1.png b/docs/articles/web_only/NAFTA_examples_files/figure-html/p10-1.png
index 75611a70..a53c48b2 100644
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diff --git a/docs/articles/web_only/NAFTA_examples_files/figure-html/p15a-1.png b/docs/articles/web_only/NAFTA_examples_files/figure-html/p15a-1.png
index b6faeff9..fb211a8e 100644
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diff --git a/docs/articles/web_only/NAFTA_examples_files/figure-html/p15b-1.png b/docs/articles/web_only/NAFTA_examples_files/figure-html/p15b-1.png
index 6b9ba98c..9aedbf16 100644
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diff --git a/docs/articles/web_only/NAFTA_examples_files/figure-html/p5b-1.png b/docs/articles/web_only/NAFTA_examples_files/figure-html/p5b-1.png
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diff --git a/docs/articles/web_only/NAFTA_examples_files/figure-html/p6-1.png b/docs/articles/web_only/NAFTA_examples_files/figure-html/p6-1.png
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diff --git a/docs/articles/web_only/NAFTA_examples_files/figure-html/p7-1.png b/docs/articles/web_only/NAFTA_examples_files/figure-html/p7-1.png
index d64ea98d..10225504 100644
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diff --git a/docs/articles/web_only/benchmarks.html b/docs/articles/web_only/benchmarks.html
index 2eea3cb2..058d43fa 100644
--- a/docs/articles/web_only/benchmarks.html
+++ b/docs/articles/web_only/benchmarks.html
@@ -43,7 +43,7 @@
Functions and data
Benchmark timings for mkin
Johannes Ranke
- Last change 13 May 2020 (rebuilt 2022-03-02)
+ Last change 13 May 2020 (rebuilt 2022-05-18)
Source: vignettes/web_only/benchmarks.rmd
benchmarks.rmd
FOCUS_C <- FOCUS_2006_C
-FOCUS_D <- subset(FOCUS_2006_D, value != 0)
+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"]]
@@ -179,74 +179,83 @@
Results
-Parent only
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.error_model = "obs"
.error_model = "obs"
.References
-
-
-
-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
-
-
-
-
-Ranke J, Meinecke S (2019) Error Models for the Kinetic Evaluation of Chemical Degradation Data Environments 6 (12) 124 doi:10.3390/environments6120124
-
-
-
+
-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
-
-
+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
+
+Ranke J, Meinecke S (2019) Error Models for the Kinetic Evaluation of Chemical Degradation Data Environments 6 (12) 124 doi:10.3390/environments6120124
+ 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
+ mkin 1.1.1
-mkin 1.0.5 (2021-09-15)
-mkin 1.0.4 (2021-04-20)
mkin 1.0.3 (2021-02-15)
-mkin 0.9.49.10 (2020-04-18)
test_FOMC_ill-defined.R
as it is too platform dependentmkin 0.9.45.2 (2017-07-24)
twa
to max_twa_parent
to avoid conflict with twa
from my pfm
packagemkin 0.9.45.1 (2016-12-20)
New features
-twa
function, calculating maximum time weighted average concentrations for the parent (SFO, FOMC and DFOP).twa
function, calculating maximum time weighted average concentrations for the parent (SFO, FOMC and DFOP).mkin 0.9.43 (2016-06-28)
@@ -352,8 +348,7 @@
mkin 0.9.42 (2016-03-25)
Major changes
-from_max_mean
to mkinfit
, for fitting only the decline from the maximum observed value for models with a single observed variablefrom_max_mean
to mkinfit
, for fitting only the decline from the maximum observed value for models with a single observed variableMinor changes
compiled_models
vignetteBug fixes
print.summary.mkinfit()
: Avoid an error that occurred when printing summaries generated with mkin versions before 0.9-36print.summary.mkinfit()
: Avoid an error that occurred when printing summaries generated with mkin versions before 0.9-36mkin 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.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.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.mkin 0.9-39 (2015-06-26)
@@ -399,8 +391,7 @@
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.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.mkin 0.9-38 (2015-06-24)
@@ -412,8 +403,7 @@
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.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.Bug fixes
mkinparplot()
: Avoid warnings that occurred when not all confidence intervals were available in the summary of the fitmkin 0.9-31 (2014-07-14)
Bug fixes
-mkinerrmin()
used by the summary function.mkinerrmin()
used by the summary function.mkin 0.9-30 (2014-07-11)
New features
-mkinmod()
.mkinmod()
.
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
+ doi:10.1021/jf00103a026Ranke J and Meinecke S (2019) Error Models for the Kinetic Evaluation of Chemical Degradation Data. Environments 6(12) 124 -doi: 10.3390/environments6120124 +doi:10.3390/environments6120124 .