From 95178837d3f91e84837628446b5fd468179af2b9 Mon Sep 17 00:00:00 2001
From: Johannes Ranke
experimental_data_for_UBA.Rd
The 12 datasets were extracted from active substance evaluation dossiers published + by EFSA. Kinetic evaluations shown for these datasets are intended to illustrate + and advance error model specifications. The fact that these data and some + results are shown here do not imply a license to use them in the context of + pesticide registrations, as the use of the data may be constrained by + data protection regulations.
+ +experimental_data_for_UBA_2019
+
+ A list containing twelve datasets as an R6 class defined by mkinds
,
+ each containing, among others, the following components
title
The name of the dataset, e.g. Soil 1
data
A data frame with the data in the form expected by mkinfit
Ranke (2019) Documentation of results obtained for the error model expertise + written for the German Umweltbundesamt.
+ + +++# Model definitions +sfo_sfo <- mkinmod( + parent = mkinsub("SFO", to = "A1"), + A1 = mkinsub("SFO"), + use_of_ff = "max" +)#>+dfop_sfo <- mkinmod( + parent = mkinsub("DFOP", to = "A1"), + A1 = mkinsub("SFO"), + use_of_ff = "max" +)#>+sfo_sfo_sfo <- mkinmod( + parent = mkinsub("SFO", to = "A1"), + A1 = mkinsub("SFO", to = "A2"), + A2 = mkinsub("SFO"), + use_of_ff = "max" +)#>+dfop_sfo_sfo <- mkinmod( + parent = mkinsub("DFOP", to = "A1"), + A1 = mkinsub("SFO", to = "A2"), + A2 = mkinsub("SFO"), + use_of_ff = "max" +)#>d_1_2 <- lapply(experimental_data_for_UBA_2019[1:2], function(x) x$data) +names(d_1_2) <- paste("Soil", 1:2) + + +f_1_2_tc <- mmkin(list("DFOP-SFO-SFO" = dfop_sfo_sfo), d_1_2, error_model = "tc") + +plot(f_1_2_tc, resplot = "errmod")+
Function to plot the confidence intervals obtained using mkinfit
Function to plot squared residuals and the error model for an mkin object
Synthetic datasets for one parent compound with two metabolites
Experimental datasets used for development and testing of error models
If the error model is "const", the error model algorithm is ignored, + because no special algorithm is needed and unweighted (also known as + ordinary) least squares fitting can be applied.
+The default algorithm "d_3" will directly minimize the negative + log-likelihood and - independently - also use the three step algorithm + described below. The fit with the higher likelihood is returned.
+The algorithm "direct" will directly minimize the negative + log-likelihood.
+The algorithm "twostep" will minimize the negative log-likelihood + after an initial unweighted leas squares optimisation step.
+The algorithm "threestep" starts with unweighted least squares, + then optimizes only the error model using the degradation model + parameters found, and then minimizes the negative log-likelihood + with free degradation and error model parameters.
+The algorithm "fourstep" starts with unweighted least squares, + then optimizes only the error model using the degradation model + parameters found, then optimizes the degradation model again + with fixed error model parameters, and finally minimizes the negative + log-likelihood with free degradation and error model parameters.
+The algorithm "IRLS" starts with unweighted least squares, + and then iterates optimization of the error model parameters and subsequent + optimization of the degradation model using those error model parameters, + until the error model parameters converge.
Tolerance for the convergence criterion calculated from the error model + parameters in IRLS fits.
Maximum number of iterations in IRLS fits.
Should a trace of the parameter values be listed?
diff --git a/docs/reference/mkinmod.html b/docs/reference/mkinmod.html index 51be5465..2c5f056e 100644 --- a/docs/reference/mkinmod.html +++ b/docs/reference/mkinmod.html @@ -68,7 +68,7 @@ For the definition of model types and their parameters, the equations given @@ -234,7 +234,7 @@ For the definition of model types and their parameters, the equations given SFO_SFO <- mkinmod( parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"), verbose = TRUE)# Use shorthand notation for parent only degradation fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE) -summary(fit)#> mkin version used for fitting: 0.9.49.4 +summary(fit)#> mkin version used for fitting: 0.9.49.5 #> R version used for fitting: 3.6.0 -#> Date of fit: Wed May 8 20:50:50 2019 -#> Date of summary: Wed May 8 20:50:50 2019 +#> Date of fit: Tue Jun 4 15:01:15 2019 +#> Date of summary: Tue Jun 4 15:01:15 2019 #> #> Equations: #> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent #> #> Model predictions using solution type analytical #> -#> Fitted using 222 model solutions performed in 0.456 s +#> Fitted using 222 model solutions performed in 0.461 s #> #> Error model: #> Constant variance @@ -443,7 +480,7 @@ Per default, parameters in the kinetic models are internally transformed in m1 = mkinsub("SFO"))#># Fit the model to the FOCUS example dataset D using defaults print(system.time(fit <- mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "eigen", quiet = TRUE)))#> Warning: Observations with value of zero were removed from the data#> User System verstrichen -#> 1.488 0.000 1.488coef(fit)#> NULLendpoints(fit)#> $ff +#> 1.521 0.000 1.526coef(fit)#> NULLendpoints(fit)#> $ff #> parent_sink parent_m1 m1_sink #> 0.485524 0.514476 1.000000 #> @@ -515,7 +552,7 @@ Per default, parameters in the kinetic models are internally transformed in #> Sum of squared residuals at call 126: 371.2134 #> Sum of squared residuals at call 135: 371.2134 #> Negative log-likelihood at call 145: 97.22429#>#> User System verstrichen -#> 1.086 0.000 1.087coef(fit.deSolve)#> NULLendpoints(fit.deSolve)#> $ff +#> 1.093 0.000 1.093coef(fit.deSolve)#> NULLendpoints(fit.deSolve)#> $ff #> parent_sink parent_m1 m1_sink #> 0.485524 0.514476 1.000000 #> @@ -545,10 +582,10 @@ Per default, parameters in the kinetic models are internally transformed in fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D, parms.ini = fit.SFORB$bparms.ode, quiet = TRUE)#> Warning: Observations with value of zero were removed from the data# Weighted fits, including IRLS SFO_SFO.ff <- mkinmod(parent = mkinsub("SFO", "m1"), - m1 = mkinsub("SFO"), use_of_ff = "max")#>f.noweight <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE)#> Warning: Observations with value of zero were removed from the datasummary(f.noweight)#>f.noweight <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE)#> Warning: Observations with value of zero were removed from the datasummary(f.noweight)#> mkin version used for fitting: 0.9.49.5 #> R version used for fitting: 3.6.0 -#> Date of fit: Wed May 8 20:51:06 2019 -#> Date of summary: Wed May 8 20:51:06 2019 +#> Date of fit: Tue Jun 4 15:01:31 2019 +#> Date of summary: Tue Jun 4 15:01:31 2019 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -556,7 +593,7 @@ Per default, parameters in the kinetic models are internally transformed in #> #> Model predictions using solution type deSolve #> -#> Fitted using 421 model solutions performed in 1.082 s +#> Fitted using 421 model solutions performed in 1.096 s #> #> Error model: #> Constant variance @@ -663,10 +700,10 @@ Per default, parameters in the kinetic models are internally transformed in #> 100 m1 31.04 31.98163 -9.416e-01 #> 100 m1 33.13 31.98163 1.148e+00 #> 120 m1 25.15 28.78984 -3.640e+00 -#> 120 m1 33.31 28.78984 4.520e+00f.obs <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, error_model = "obs", quiet = TRUE)#> Warning: Observations with value of zero were removed from the datasummary(f.obs)#> mkin version used for fitting: 0.9.49.4 +#> 120 m1 33.31 28.78984 4.520e+00f.obs <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, error_model = "obs", quiet = TRUE)#> Warning: Observations with value of zero were removed from the datasummary(f.obs)#> mkin version used for fitting: 0.9.49.5 #> R version used for fitting: 3.6.0 -#> Date of fit: Wed May 8 20:51:08 2019 -#> Date of summary: Wed May 8 20:51:08 2019 +#> Date of fit: Tue Jun 4 15:01:34 2019 +#> Date of summary: Tue Jun 4 15:01:34 2019 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -674,19 +711,19 @@ Per default, parameters in the kinetic models are internally transformed in #> #> Model predictions using solution type deSolve #> -#> Fitted using 758 model solutions performed in 1.971 s +#> Fitted using 979 model solutions performed in 2.603 s #> #> Error model: #> Variance unique to each observed variable #> #> Starting values for parameters to be optimised: -#> value type -#> parent_0 100.7500 state -#> k_parent 0.1000 deparm -#> k_m1 0.1001 deparm -#> f_parent_to_m1 0.5000 deparm -#> sigma_parent 3.0000 error -#> sigma_m1 3.0000 error +#> value type +#> parent_0 100.750000 state +#> k_parent 0.100000 deparm +#> k_m1 0.100100 deparm +#> f_parent_to_m1 0.500000 deparm +#> sigma_parent 3.398909 error +#> sigma_m1 2.857157 error #> #> Starting values for the transformed parameters actually optimised: #> value lower upper @@ -694,8 +731,8 @@ Per default, parameters in the kinetic models are internally transformed in #> log_k_parent -2.302585 -Inf Inf #> log_k_m1 -2.301586 -Inf Inf #> f_parent_ilr_1 0.000000 -Inf Inf -#> sigma_parent 3.000000 0 Inf -#> sigma_m1 3.000000 0 Inf +#> sigma_parent 3.398909 0 Inf +#> sigma_m1 2.857157 0 Inf #> #> Fixed parameter values: #> value type @@ -715,14 +752,14 @@ Per default, parameters in the kinetic models are internally transformed in #> parent_0 1.00000 0.51078 -0.19133 -0.59997 0.035670 #> log_k_parent 0.51078 1.00000 -0.37458 -0.59239 0.069833 #> log_k_m1 -0.19133 -0.37458 1.00000 0.74398 -0.026158 -#> f_parent_ilr_1 -0.59997 -0.59239 0.74398 1.00000 -0.041368 +#> f_parent_ilr_1 -0.59997 -0.59239 0.74398 1.00000 -0.041369 #> sigma_parent 0.03567 0.06983 -0.02616 -0.04137 1.000000 -#> sigma_m1 -0.03385 -0.06627 0.02482 0.03925 -0.004628 +#> sigma_m1 -0.03385 -0.06627 0.02482 0.03926 -0.004628 #> sigma_m1 #> parent_0 -0.033847 #> log_k_parent -0.066265 -#> log_k_m1 0.024821 -#> f_parent_ilr_1 0.039255 +#> log_k_m1 0.024823 +#> f_parent_ilr_1 0.039256 #> sigma_parent -0.004628 #> sigma_m1 1.000000 #> @@ -786,17 +823,17 @@ Per default, parameters in the kinetic models are internally transformed in #> 21 m1 46.44 41.65115 4.789e+00 #> 35 m1 41.22 43.29465 -2.075e+00 #> 35 m1 37.95 43.29465 -5.345e+00 -#> 50 m1 41.19 41.19948 -9.481e-03 +#> 50 m1 41.19 41.19948 -9.479e-03 #> 50 m1 40.01 41.19948 -1.189e+00 -#> 75 m1 40.09 36.44036 3.650e+00 -#> 75 m1 33.85 36.44036 -2.590e+00 -#> 100 m1 31.04 31.98774 -9.477e-01 -#> 100 m1 33.13 31.98774 1.142e+00 -#> 120 m1 25.15 28.80430 -3.654e+00 -#> 120 m1 33.31 28.80430 4.506e+00f.tc <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, error_model = "tc", quiet = TRUE)#> Warning: Observations with value of zero were removed from the datasummary(f.tc)#> mkin version used for fitting: 0.9.49.4 +#> 75 m1 40.09 36.44035 3.650e+00 +#> 75 m1 33.85 36.44035 -2.590e+00 +#> 100 m1 31.04 31.98773 -9.477e-01 +#> 100 m1 33.13 31.98773 1.142e+00 +#> 120 m1 25.15 28.80429 -3.654e+00 +#> 120 m1 33.31 28.80429 4.506e+00f.tc <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, error_model = "tc", quiet = TRUE)#> Warning: Observations with value of zero were removed from the datasummary(f.tc)#> mkin version used for fitting: 0.9.49.5 #> R version used for fitting: 3.6.0 -#> Date of fit: Wed May 8 20:51:11 2019 -#> Date of summary: Wed May 8 20:51:11 2019 +#> Date of fit: Tue Jun 4 15:01:43 2019 +#> Date of summary: Tue Jun 4 15:01:43 2019 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -804,28 +841,28 @@ Per default, parameters in the kinetic models are internally transformed in #> #> Model predictions using solution type deSolve #> -#> Fitted using 821 model solutions performed in 3.29 s +#> Fitted using 2289 model solutions performed in 9.499 s #> #> Error model: #> Two-component variance function #> #> Starting values for parameters to be optimised: -#> value type -#> parent_0 100.7500 state -#> k_parent 0.1000 deparm -#> k_m1 0.1001 deparm -#> f_parent_to_m1 0.5000 deparm -#> sigma_low 0.1000 error -#> rsd_high 0.1000 error +#> value type +#> parent_0 1.007500e+02 state +#> k_parent 1.000000e-01 deparm +#> k_m1 1.001000e-01 deparm +#> f_parent_to_m1 5.000000e-01 deparm +#> sigma_low 5.641148e-03 error +#> rsd_high 8.430766e-02 error #> #> Starting values for the transformed parameters actually optimised: -#> value lower upper -#> parent_0 100.750000 -Inf Inf -#> log_k_parent -2.302585 -Inf Inf -#> log_k_m1 -2.301586 -Inf Inf -#> f_parent_ilr_1 0.000000 -Inf Inf -#> sigma_low 0.100000 0 Inf -#> rsd_high 0.100000 0 Inf +#> value lower upper +#> parent_0 100.750000000 -Inf Inf +#> log_k_parent -2.302585093 -Inf Inf +#> log_k_m1 -2.301585593 -Inf Inf +#> f_parent_ilr_1 0.000000000 -Inf Inf +#> sigma_low 0.005641148 0 Inf +#> rsd_high 0.084307660 0 Inf #> #> Fixed parameter values: #> value type @@ -856,7 +893,7 @@ Per default, parameters in the kinetic models are internally transformed in #> Estimate t value Pr(>t) Lower Upper #> parent_0 1.007e+02 38.4300 1.180e-28 95.400000 1.061e+02 #> k_parent 1.006e-01 112.8000 1.718e-43 0.098760 1.024e-01 -#> k_m1 5.167e-03 10.9500 1.172e-12 0.004290 6.223e-03 +#> k_m1 5.167e-03 10.9500 1.171e-12 0.004290 6.223e-03 #> f_parent_to_m1 5.084e-01 26.0100 2.146e-23 0.468600 5.481e-01 #> sigma_low 3.050e-03 0.6314 2.661e-01 -0.006786 1.289e-02 #> rsd_high 7.928e-02 8.4170 6.418e-10 0.060100 9.847e-02 @@ -879,18 +916,18 @@ Per default, parameters in the kinetic models are internally transformed in #> #> Data: #> time variable observed predicted residual -#> 0 parent 99.46 100.73433 -1.274329 -#> 0 parent 102.04 100.73433 1.305671 -#> 1 parent 93.50 91.09750 2.402495 -#> 1 parent 92.50 91.09750 1.402495 -#> 3 parent 63.23 74.50140 -11.271403 -#> 3 parent 68.99 74.50140 -5.511403 -#> 7 parent 52.32 49.82880 2.491205 -#> 7 parent 55.13 49.82880 5.301205 -#> 14 parent 27.27 24.64809 2.621909 -#> 14 parent 26.64 24.64809 1.991909 -#> 21 parent 11.50 12.19231 -0.692315 -#> 21 parent 11.64 12.19231 -0.552315 +#> 0 parent 99.46 100.73434 -1.274339 +#> 0 parent 102.04 100.73434 1.305661 +#> 1 parent 93.50 91.09751 2.402486 +#> 1 parent 92.50 91.09751 1.402486 +#> 3 parent 63.23 74.50141 -11.271410 +#> 3 parent 68.99 74.50141 -5.511410 +#> 7 parent 52.32 49.82880 2.491201 +#> 7 parent 55.13 49.82880 5.301201 +#> 14 parent 27.27 24.64809 2.621908 +#> 14 parent 26.64 24.64809 1.991908 +#> 21 parent 11.50 12.19232 -0.692315 +#> 21 parent 11.64 12.19232 -0.552315 #> 35 parent 2.85 2.98327 -0.133266 #> 35 parent 2.91 2.98327 -0.073266 #> 50 parent 0.69 0.66013 0.029874 @@ -899,24 +936,24 @@ Per default, parameters in the kinetic models are internally transformed in #> 75 parent 0.06 0.05344 0.006562 #> 1 m1 4.84 4.88645 -0.046451 #> 1 m1 5.64 4.88645 0.753549 -#> 3 m1 12.91 13.22867 -0.318668 -#> 3 m1 12.96 13.22867 -0.268668 -#> 7 m1 22.97 25.36416 -2.394164 -#> 7 m1 24.47 25.36416 -0.894164 -#> 14 m1 41.69 37.00974 4.680265 -#> 14 m1 33.21 37.00974 -3.799735 -#> 21 m1 44.37 41.90133 2.468670 -#> 21 m1 46.44 41.90133 4.538670 -#> 35 m1 41.22 43.45691 -2.236914 -#> 35 m1 37.95 43.45691 -5.506914 -#> 50 m1 41.19 41.34199 -0.151988 -#> 50 m1 40.01 41.34199 -1.331988 -#> 75 m1 40.09 36.61471 3.475290 -#> 75 m1 33.85 36.61471 -2.764710 -#> 100 m1 31.04 32.20083 -1.160830 -#> 100 m1 33.13 32.20083 0.929170 -#> 120 m1 25.15 29.04131 -3.891312 -#> 120 m1 33.31 29.04131 4.268688+#> 3 m1 12.91 13.22867 -0.318669 +#> 3 m1 12.96 13.22867 -0.268669 +#> 7 m1 22.97 25.36417 -2.394166 +#> 7 m1 24.47 25.36417 -0.894166 +#> 14 m1 41.69 37.00974 4.680263 +#> 14 m1 33.21 37.00974 -3.799737 +#> 21 m1 44.37 41.90133 2.468669 +#> 21 m1 46.44 41.90133 4.538669 +#> 35 m1 41.22 43.45691 -2.236913 +#> 35 m1 37.95 43.45691 -5.506913 +#> 50 m1 41.19 41.34199 -0.151985 +#> 50 m1 40.01 41.34199 -1.331985 +#> 75 m1 40.09 36.61471 3.475295 +#> 75 m1 33.85 36.61471 -2.764705 +#> 100 m1 31.04 32.20082 -1.160823 +#> 100 m1 33.13 32.20082 0.929177 +#> 120 m1 25.15 29.04130 -3.891304 +#> 120 m1 33.31 29.04130 4.268696
# One parent compound, one metabolite, both single first order, path from -# parent to sink included -SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1", full = "Parent"), +diff --git a/docs/reference/plot.mmkin-1.png b/docs/reference/plot.mmkin-1.png index 03d334f7..8cf969c9 100644 Binary files a/docs/reference/plot.mmkin-1.png and b/docs/reference/plot.mmkin-1.png differ diff --git a/docs/reference/plot.mmkin-2.png b/docs/reference/plot.mmkin-2.png index 25ed01cc..45d67b55 100644 Binary files a/docs/reference/plot.mmkin-2.png and b/docs/reference/plot.mmkin-2.png differ diff --git a/docs/reference/plot.mmkin-3.png b/docs/reference/plot.mmkin-3.png index 7f32afe2..47cd7eec 100644 Binary files a/docs/reference/plot.mmkin-3.png and b/docs/reference/plot.mmkin-3.png differ diff --git a/docs/reference/plot.mmkin-4.png b/docs/reference/plot.mmkin-4.png index b03dffb2..44037bb4 100644 Binary files a/docs/reference/plot.mmkin-4.png and b/docs/reference/plot.mmkin-4.png differ diff --git a/docs/reference/plot.mmkin.html b/docs/reference/plot.mmkin.html index 3037ca24..0b626d1b 100644 --- a/docs/reference/plot.mmkin.html +++ b/docs/reference/plot.mmkin.html @@ -67,7 +67,7 @@ If the current plot device is a tikz device, @@ -197,8 +197,8 @@ If the current plot device is a tikz device,# One parent compound, one metabolite, both single first order, path from +# parent to sink included +SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1", full = "Parent"), m1 = mkinsub("SFO", full = "Metabolite M1" ))#>#> Warning: Observations with value of zero were removed from the dataplot(fit)# Show the observed variables separately plot(fit, sep_obs = TRUE, lpos = c("topright", "bottomright"))@@ -306,7 +306,7 @@ plot_sep(fit, sep_obs = TRUE, show_residuals = TRUE, show_errmin = TRUE, …diff --git a/docs/reference/print.mkinds.html b/docs/reference/print.mkinds.html index 2cc112aa..7c401533 100644 --- a/docs/reference/print.mkinds.html +++ b/docs/reference/print.mkinds.html @@ -63,7 +63,7 @@ @@ -165,7 +165,7 @@ diff --git a/docs/reference/print.mkinmod.html b/docs/reference/print.mkinmod.html index d09b629e..4ca7631b 100644 --- a/docs/reference/print.mkinmod.html +++ b/docs/reference/print.mkinmod.html @@ -63,7 +63,7 @@ @@ -186,7 +186,7 @@ diff --git a/docs/reference/print.nafta.html b/docs/reference/print.nafta.html index 28847afe..10afb77d 100644 --- a/docs/reference/print.nafta.html +++ b/docs/reference/print.nafta.html @@ -65,7 +65,7 @@ @@ -177,7 +177,7 @@ diff --git a/docs/reference/schaefer07_complex_case-1.png b/docs/reference/schaefer07_complex_case-1.png index 49967dc9..34356613 100644 Binary files a/docs/reference/schaefer07_complex_case-1.png and b/docs/reference/schaefer07_complex_case-1.png differ diff --git a/docs/reference/schaefer07_complex_case.html b/docs/reference/schaefer07_complex_case.html index 09f6d1e2..50e07d37 100644 --- a/docs/reference/schaefer07_complex_case.html +++ b/docs/reference/schaefer07_complex_case.html @@ -65,7 +65,7 @@ @@ -216,7 +216,7 @@ diff --git a/docs/reference/sigma_twocomp.html b/docs/reference/sigma_twocomp.html index 265c7d1f..b73b81f4 100644 --- a/docs/reference/sigma_twocomp.html +++ b/docs/reference/sigma_twocomp.html @@ -68,7 +68,7 @@ This is the error model used for example by Werner et al. (1978). The model @@ -195,7 +195,7 @@ This is the error model used for example by Werner et al. (1978). The model diff --git a/docs/reference/summary.mkinfit.html b/docs/reference/summary.mkinfit.html index b3151da1..ffe1edb1 100644 --- a/docs/reference/summary.mkinfit.html +++ b/docs/reference/summary.mkinfit.html @@ -66,7 +66,7 @@ @@ -209,10 +209,10 @@# Only use one core not to offend CRAN checks fits <- mmkin(c("FOMC", "HS"), list("FOCUS B" = FOCUS_2006_B, "FOCUS C" = FOCUS_2006_C), # named list for titles - cores = 1, quiet = TRUE, error_model = "tc") - plot(fits[, "FOCUS C"])+ cores = 1, quiet = TRUE, error_model = "tc")#> Warning: Optimisation did not converge: +#> iteration limit reached without convergence (10)# We can also plot a single fit, if we like the way plot.mmkin works, but then the plot # height should be smaller than the plot width (this is not possible for the html pages # generated by pkgdown, as far as I know). @@ -227,7 +227,7 @@ If the current plot device is a tikz device,diff --git a/docs/reference/plot.nafta.html b/docs/reference/plot.nafta.html index 1aa4485a..fdc6e0ac 100644 --- a/docs/reference/plot.nafta.html +++ b/docs/reference/plot.nafta.html @@ -67,7 +67,7 @@ @@ -187,7 +187,7 @@ plot(x, legend = FALSE, main = "auto", …)Examples
-#> mkin version used for fitting: 0.9.49.4 +diff --git a/docs/reference/synthetic_data_for_UBA.html b/docs/reference/synthetic_data_for_UBA.html index 2c2623e4..4a7ca728 100644 --- a/docs/reference/synthetic_data_for_UBA.html +++ b/docs/reference/synthetic_data_for_UBA.html @@ -40,7 +40,7 @@ Variance component 'a' is based on a normal distribution with standard deviation Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07 for the increase of the standard deviation with y. Note that this is a simplified version - of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the + of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the measured values approximates lognormal distribution for high values, whereas we are using normally distributed error components all along. Initial concentrations for metabolites and all values where adding the variance component resulted @@ -78,7 +78,7 @@ Compare also the code in the example section to see the degradation models." /> @@ -151,7 +151,7 @@ Compare also the code in the example section to see the degradation models." /> Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07 for the increase of the standard deviation with y. Note that this is a simplified version - of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the + of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the measured values approximates lognormal distribution for high values, whereas we are using normally distributed error components all along.#> mkin version used for fitting: 0.9.49.5 #> R version used for fitting: 3.6.0 -#> Date of fit: Wed May 8 20:52:12 2019 -#> Date of summary: Wed May 8 20:52:12 2019 +#> Date of fit: Tue Jun 4 15:03:02 2019 +#> Date of summary: Tue Jun 4 15:03:02 2019 #> #> Equations: #> d_parent/dt = - k_parent_sink * parent @@ -307,7 +307,7 @@Initial concentrations for metabolites and all values where adding the variance component resulted @@ -253,7 +253,8 @@ add_err = function(d, sdfunc, LOD = 0.1, reps = 2, seed = 123456789) return(d_NA) } -# The following is the two-component model of Rocke and Lorenzato (1995) +# The following is the simplified version of the two-component model of Rocke +# and Lorenzato (1995) sdfunc_twocomp = function(value, sd_low, rsd_high) { sqrt(sd_low^2 + value^2 * rsd_high^2) } @@ -304,7 +305,7 @@ summary(fit)
diff --git a/docs/reference/test_data_from_UBA_2014-1.png b/docs/reference/test_data_from_UBA_2014-1.png index a9aeea21..fc05f896 100644 Binary files a/docs/reference/test_data_from_UBA_2014-1.png and b/docs/reference/test_data_from_UBA_2014-1.png differ diff --git a/docs/reference/test_data_from_UBA_2014-2.png b/docs/reference/test_data_from_UBA_2014-2.png index f6c91bff..b0dfdd5a 100644 Binary files a/docs/reference/test_data_from_UBA_2014-2.png and b/docs/reference/test_data_from_UBA_2014-2.png differ diff --git a/docs/reference/test_data_from_UBA_2014.html b/docs/reference/test_data_from_UBA_2014.html index bc988340..e40d320f 100644 --- a/docs/reference/test_data_from_UBA_2014.html +++ b/docs/reference/test_data_from_UBA_2014.html @@ -64,7 +64,7 @@ @@ -231,7 +231,7 @@ diff --git a/docs/reference/transform_odeparms.html b/docs/reference/transform_odeparms.html index 7e05480e..bf134334 100644 --- a/docs/reference/transform_odeparms.html +++ b/docs/reference/transform_odeparms.html @@ -71,7 +71,7 @@ The transformation of sets of formation fractions is fragile, as it supposes @@ -293,7 +293,7 @@ The transformation of sets of formation fractions is fragile, as it supposes -- cgit v1.2.1 From b6027bbd157734e1c7f8c3ba6373451f5c85fc38 Mon Sep 17 00:00:00 2001 From: Johannes RankeDate: Wed, 5 Jun 2019 15:16:59 +0200 Subject: Add error model algorithm to output --- docs/reference/Extract.mmkin.html | 8 ++-- docs/reference/experimental_data_for_UBA.html | 66 ++++++++++++++++++++++++++- docs/reference/mkinfit.html | 50 +++++++++++--------- docs/reference/mkinmod.html | 2 +- docs/reference/mkinpredict.html | 6 +-- docs/reference/mmkin.html | 4 +- docs/reference/summary.mkinfit.html | 11 +++-- 7 files changed, 108 insertions(+), 39 deletions(-) (limited to 'docs/reference') diff --git a/docs/reference/Extract.mmkin.html b/docs/reference/Extract.mmkin.html index 1d1da50e..37c0b361 100644 --- a/docs/reference/Extract.mmkin.html +++ b/docs/reference/Extract.mmkin.html @@ -172,16 +172,16 @@ cores = 1, quiet = TRUE) fits["FOMC", ] #> dataset #> model B C -#> FOMC List,36 List,36 +#> FOMC List,37 List,37 #> attr(,"class") #> [1] "mmkin"fits[, "B"]#> dataset #> model B -#> SFO List,36 -#> FOMC List,36 +#> SFO List,37 +#> FOMC List,37 #> attr(,"class") #> [1] "mmkin"fits["SFO", "B"]#> dataset #> model B -#> SFO List,36 +#> SFO List,37 #> attr(,"class") #> [1] "mmkin"head( diff --git a/docs/reference/experimental_data_for_UBA.html b/docs/reference/experimental_data_for_UBA.html index 3e8d20ef..bb94fd11 100644 --- a/docs/reference/experimental_data_for_UBA.html +++ b/docs/reference/experimental_data_for_UBA.html @@ -37,7 +37,30 @@ and advance error model specifications. The fact that these data and some results are shown here do not imply a license to use them in the context of pesticide registrations, as the use of the data may be constrained by - data protection regulations." /> + data protection regulations. +Preprocessing of data was performed based on the recommendations of the FOCUS + kinetics workgroup (FOCUS, 2014) as described below. +Datasets 1 and 2 are from the Renewal Assessment Report (RAR) for imazamox + (France, 2015, p. 15). For setting values reported as zero, an LOQ of 0.1 + was assumed. Metabolite residues reported for day zero were added to the + parent compound residues. +Datasets 3 and 4 are from the Renewal Assessment Report (RAR) for isofetamid + (Belgium, 2014, p. 8) and show the data for two different radiolabels. For + dataset 4, the value given for the metabolite in the day zero sampling + in replicate B was added to the parent compound, following the respective + FOCUS recommendation. +Dataset 5 is from the Renewal Assessment Report (RAR) for ethofumesate + (Austria, 2015, p. 16). +Datasets 6 to 10 are from the Renewal Assessment Report (RAR) for glyphosate + (Germany, 2013a, pages 8, 28, 50, 51). For the initial sampling, + the residues given for the metabolite were added to the parent + value, following the recommendation of the FOCUS kinetics workgroup. +Dataset 11 is from the Renewal Assessment Report (RAR) for 2,4-D + (Germany, 2013b, p. 644). Values reported as zero were set to NA, with + the exception of the day three sampling of metabolite A2, which was set + to one half of the LOD reported to be 1% AR. +Dataset 12 is from the Renewal Assessment Report (RAR) for thifensulfuron-methyl + (United Kingdom, 2014, p. 81)." /> @@ -139,6 +162,29 @@ results are shown here do not imply a license to use them in the context of pesticide registrations, as the use of the data may be constrained by data protection regulations. +@@ -154,8 +200,24 @@Preprocessing of data was performed based on the recommendations of the FOCUS + kinetics workgroup (FOCUS, 2014) as described below.
+Datasets 1 and 2 are from the Renewal Assessment Report (RAR) for imazamox + (France, 2015, p. 15). For setting values reported as zero, an LOQ of 0.1 + was assumed. Metabolite residues reported for day zero were added to the + parent compound residues.
+Datasets 3 and 4 are from the Renewal Assessment Report (RAR) for isofetamid + (Belgium, 2014, p. 8) and show the data for two different radiolabels. For + dataset 4, the value given for the metabolite in the day zero sampling + in replicate B was added to the parent compound, following the respective + FOCUS recommendation.
+Dataset 5 is from the Renewal Assessment Report (RAR) for ethofumesate + (Austria, 2015, p. 16).
+Datasets 6 to 10 are from the Renewal Assessment Report (RAR) for glyphosate + (Germany, 2013a, pages 8, 28, 50, 51). For the initial sampling, + the residues given for the metabolite were added to the parent + value, following the recommendation of the FOCUS kinetics workgroup.
+Dataset 11 is from the Renewal Assessment Report (RAR) for 2,4-D + (Germany, 2013b, p. 644). Values reported as zero were set to NA, with + the exception of the day three sampling of metabolite A2, which was set + to one half of the LOD reported to be 1% AR.
+Dataset 12 is from the Renewal Assessment Report (RAR) for thifensulfuron-methyl + (United Kingdom, 2014, p. 81).
Source
-Ranke (2019) Documentation of results obtained for the error model expertise + +
Austria (2015). Ethofumesate Renewal Assessment Report Volume 3 Annex B.8 (AS)
+Belgium (2014). Isofetamid (IKF-5411) Draft Assessment Report Volume 3 Annex B.8 (AS)
+France (2015). Imazamox Draft Renewal Assessment Report Volume 3 Annex B.8 (AS)
+FOCUS (2014) “Generic guidance for Estimating Persistence and + Degradation Kinetics from Environmental Fate Studies on Pesticides in EU + Registration” Report of the FOCUS Work Group on Degradation Kinetics, + Version 1.1, 18 December 2014 + http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics
+Germany (2013a). Renewal Assessment Report Glyphosate Volume 3 Annex B.8: Environmental Fate + and Behaviour
+Germany (2013b). Renewal Assessment Report 2,4-D Volume 3 Annex B.8: Fate and behaviour in the + environment
+Ranke (2019) Documentation of results obtained for the error model expertise written for the German Umweltbundesamt.
+United Kingdom (2014). Thifensulfuron-methyl - Annex B.8 (Volume 3) to the Report and Proposed + Decision of the United Kingdom made to the European Commission under Regulation (EC) No. + 1141/2010 for renewal of an active substance
Examples
diff --git a/docs/reference/mkinfit.html b/docs/reference/mkinfit.html index 8cabcb21..700b6805 100644 --- a/docs/reference/mkinfit.html +++ b/docs/reference/mkinfit.html @@ -399,18 +399,19 @@ Per default, parameters in the kinetic models are internally transformed in fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE) summary(fit)#> mkin version used for fitting: 0.9.49.5 #> R version used for fitting: 3.6.0 -#> Date of fit: Tue Jun 4 15:01:15 2019 -#> Date of summary: Tue Jun 4 15:01:15 2019 +#> Date of fit: Wed Jun 5 15:08:20 2019 +#> Date of summary: Wed Jun 5 15:08:20 2019 #> #> Equations: #> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent #> #> Model predictions using solution type analytical #> -#> Fitted using 222 model solutions performed in 0.461 s +#> Fitted using 222 model solutions performed in 0.469 s #> -#> Error model: -#> Constant variance +#> Error model: Constant variance +#> +#> Error model algorithm: d_3 #> #> Starting values for parameters to be optimised: #> value type @@ -480,7 +481,7 @@ Per default, parameters in the kinetic models are internally transformed in m1 = mkinsub("SFO"))#># Fit the model to the FOCUS example dataset D using defaults print(system.time(fit <- mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "eigen", quiet = TRUE)))#> Warning: Observations with value of zero were removed from the data#> User System verstrichen -#> 1.521 0.000 1.526coef(fit)#> NULLendpoints(fit)#> $ff +#> 1.579 0.000 1.581coef(fit)#> NULLendpoints(fit)#> $ff #> parent_sink parent_m1 m1_sink #> 0.485524 0.514476 1.000000 #> @@ -552,7 +553,7 @@ Per default, parameters in the kinetic models are internally transformed in #> Sum of squared residuals at call 126: 371.2134 #> Sum of squared residuals at call 135: 371.2134 #> Negative log-likelihood at call 145: 97.22429#>#> User System verstrichen -#> 1.093 0.000 1.093coef(fit.deSolve)#> NULLendpoints(fit.deSolve)#> $ff +#> 1.159 0.000 1.160coef(fit.deSolve)#> NULLendpoints(fit.deSolve)#> $ff #> parent_sink parent_m1 m1_sink #> 0.485524 0.514476 1.000000 #> @@ -584,8 +585,8 @@ Per default, parameters in the kinetic models are internally transformed in SFO_SFO.ff <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"), use_of_ff = "max")#>f.noweight <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE)#> Warning: Observations with value of zero were removed from the datasummary(f.noweight)#> mkin version used for fitting: 0.9.49.5 #> R version used for fitting: 3.6.0 -#> Date of fit: Tue Jun 4 15:01:31 2019 -#> Date of summary: Tue Jun 4 15:01:31 2019 +#> Date of fit: Wed Jun 5 15:08:36 2019 +#> Date of summary: Wed Jun 5 15:08:36 2019 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -593,10 +594,11 @@ Per default, parameters in the kinetic models are internally transformed in #> #> Model predictions using solution type deSolve #> -#> Fitted using 421 model solutions performed in 1.096 s +#> Fitted using 421 model solutions performed in 1.181 s +#> +#> Error model: Constant variance #> -#> Error model: -#> Constant variance +#> Error model algorithm: d_3 #> #> Starting values for parameters to be optimised: #> value type @@ -702,8 +704,8 @@ Per default, parameters in the kinetic models are internally transformed in #> 120 m1 25.15 28.78984 -3.640e+00 #> 120 m1 33.31 28.78984 4.520e+00f.obs <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, error_model = "obs", quiet = TRUE)#> Warning: Observations with value of zero were removed from the datasummary(f.obs)#> mkin version used for fitting: 0.9.49.5 #> R version used for fitting: 3.6.0 -#> Date of fit: Tue Jun 4 15:01:34 2019 -#> Date of summary: Tue Jun 4 15:01:34 2019 +#> Date of fit: Wed Jun 5 15:08:39 2019 +#> Date of summary: Wed Jun 5 15:08:39 2019 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -711,10 +713,12 @@ Per default, parameters in the kinetic models are internally transformed in #> #> Model predictions using solution type deSolve #> -#> Fitted using 979 model solutions performed in 2.603 s +#> Fitted using 979 model solutions performed in 2.672 s #> -#> Error model: -#> Variance unique to each observed variable +#> Error model: Variance unique to each observed variable +#> +#> Error model algorithm: d_3 +#> Direct fitting and three-step fitting yield approximately the same likelihood #> #> Starting values for parameters to be optimised: #> value type @@ -832,8 +836,8 @@ Per default, parameters in the kinetic models are internally transformed in #> 120 m1 25.15 28.80429 -3.654e+00 #> 120 m1 33.31 28.80429 4.506e+00f.tc <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, error_model = "tc", quiet = TRUE)#> Warning: Observations with value of zero were removed from the datasummary(f.tc)#> mkin version used for fitting: 0.9.49.5 #> R version used for fitting: 3.6.0 -#> Date of fit: Tue Jun 4 15:01:43 2019 -#> Date of summary: Tue Jun 4 15:01:43 2019 +#> Date of fit: Wed Jun 5 15:08:50 2019 +#> Date of summary: Wed Jun 5 15:08:50 2019 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -841,10 +845,12 @@ Per default, parameters in the kinetic models are internally transformed in #> #> Model predictions using solution type deSolve #> -#> Fitted using 2289 model solutions performed in 9.499 s +#> Fitted using 2289 model solutions performed in 10.959 s +#> +#> Error model: Two-component variance function #> -#> Error model: -#> Two-component variance function +#> Error model algorithm: d_3 +#> Direct fitting and three-step fitting yield approximately the same likelihood #> #> Starting values for parameters to be optimised: #> value type diff --git a/docs/reference/mkinmod.html b/docs/reference/mkinmod.html index 2c5f056e..ddab656c 100644 --- a/docs/reference/mkinmod.html +++ b/docs/reference/mkinmod.html @@ -234,7 +234,7 @@ For the definition of model types and their parameters, the equations given SFO_SFO <- mkinmod( parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"), verbose = TRUE)#> Compilation argument: -#> /usr/lib/R/bin/R CMD SHLIB filebbe6b539c4f.c 2> filebbe6b539c4f.c.err.txt +#> /usr/lib/R/bin/R CMD SHLIB file50a55c3108b2.c 2> file50a55c3108b2.c.err.txt #> Program source: #> 1: #include <R.h> #> 2: diff --git a/docs/reference/mkinpredict.html b/docs/reference/mkinpredict.html index f339b26a..7e71ec27 100644 --- a/docs/reference/mkinpredict.html +++ b/docs/reference/mkinpredict.html @@ -328,17 +328,17 @@ c(parent = 100, m1 = 0), seq(0, 20, by = 0.1), solution_type = "eigen")[201,]))#> time parent m1 #> 201 20 4.978707 27.46227#> User System verstrichen -#> 0.003 0.000 0.003system.time( +#> 0.004 0.000 0.004system.time( print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01), c(parent = 100, m1 = 0), seq(0, 20, by = 0.1), solution_type = "deSolve")[201,]))#> time parent m1 #> 201 20 4.978707 27.46227#> User System verstrichen -#> 0.002 0.000 0.002system.time( +#> 0.003 0.000 0.002system.time( print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01), c(parent = 100, m1 = 0), seq(0, 20, by = 0.1), solution_type = "deSolve", use_compiled = FALSE)[201,]))#> time parent m1 #> 201 20 4.978707 27.46227#> User System verstrichen -#> 0.021 0.000 0.022+#> 0.022 0.000 0.022#>#> Sum of squared residuals at call 1: 552.5739 #> Sum of squared residuals at call 3: 552.5739 diff --git a/docs/reference/mmkin.html b/docs/reference/mmkin.html index a830646f..61a029fc 100644 --- a/docs/reference/mmkin.html +++ b/docs/reference/mmkin.html @@ -194,8 +194,8 @@ time_1 <- system.time(fits.4 <- mmkin(models, datasets, cores = 1, quiet = TRUE)) time_default#> User System verstrichen -#> 0.046 0.032 5.094time_1#> User System verstrichen -#> 19.798 0.004 19.814+#> 0.038 0.050 6.779time_1#> User System verstrichen +#> 27.209 0.004 27.278#> $ff #> parent_M1 parent_sink M1_M2 M1_sink #> 0.7340481 0.2659519 0.7505684 0.2494316 diff --git a/docs/reference/summary.mkinfit.html b/docs/reference/summary.mkinfit.html index ffe1edb1..68b36542 100644 --- a/docs/reference/summary.mkinfit.html +++ b/docs/reference/summary.mkinfit.html @@ -211,18 +211,19 @@Examples
#> mkin version used for fitting: 0.9.49.5 #> R version used for fitting: 3.6.0 -#> Date of fit: Tue Jun 4 15:03:02 2019 -#> Date of summary: Tue Jun 4 15:03:02 2019 +#> Date of fit: Wed Jun 5 15:10:34 2019 +#> Date of summary: Wed Jun 5 15:10:34 2019 #> #> Equations: #> d_parent/dt = - k_parent_sink * parent #> #> Model predictions using solution type analytical #> -#> Fitted using 131 model solutions performed in 0.266 s +#> Fitted using 131 model solutions performed in 0.268 s #> -#> Error model: -#> Constant variance +#> Error model: Constant variance +#> +#> Error model algorithm: d_3 #> #> Starting values for parameters to be optimised: #> value type -- cgit v1.2.1