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