Synthetic datasets for one parent compound with two metabolites

Example evaluation of FOCUS Example Dataset D

Johannes Ranke

2019-09-18

2019-09-19

## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:07 2019 -## Date of summary: Wed Sep 18 18:24:08 2019 +## Date of fit: Thu Sep 19 09:52:55 2019 +## Date of summary: Thu Sep 19 09:52:56 2019 ## ## Equations: ## d_parent/dt = - k_parent_sink * parent - k_parent_m1 * parent @@ -179,7 +179,7 @@ ## ## Model predictions using solution type deSolve ## -## Fitted using 389 model solutions performed in 1.014 s +## Fitted using 389 model solutions performed in 1.001 s ## ## Error model: Constant variance ## diff --git a/docs/articles/FOCUS_L.html b/docs/articles/FOCUS_L.html index 50c83db6..7b35beeb 100644 --- a/docs/articles/FOCUS_L.html +++ b/docs/articles/FOCUS_L.html @@ -90,7 +90,7 @@ Example evaluation of FOCUS Laboratory Data L1 to L3 Johannes Ranke - 2019-09-18 + 2019-09-19 FOCUS_L.Rmd @@ -116,8 +116,8 @@ summary(m.L1.SFO)

## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:09 2019 -## Date of summary: Wed Sep 18 18:24:09 2019 +## Date of fit: Thu Sep 19 09:52:57 2019 +## Date of summary: Thu Sep 19 09:52:57 2019 ## ## Equations: ## d_parent/dt = - k_parent_sink * parent @@ -218,8 +218,8 @@ ## finite result is doubtful

## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:12 2019 -## Date of summary: Wed Sep 18 18:24:12 2019 +## Date of fit: Thu Sep 19 09:52:59 2019 +## Date of summary: Thu Sep 19 09:52:59 2019 ## ## ## Warning: Optimisation did not converge: @@ -231,7 +231,7 @@ ## ## Model predictions using solution type analytical ## -## Fitted using 899 model solutions performed in 1.954 s +## Fitted using 899 model solutions performed in 1.908 s ## ## Error model: Constant variance ## @@ -323,15 +323,15 @@ summary(m.L2.FOMC, data = FALSE) ## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:13 2019 -## Date of summary: Wed Sep 18 18:24:13 2019 +## Date of fit: Thu Sep 19 09:53:00 2019 +## Date of summary: Thu Sep 19 09:53:00 2019 ## ## Equations: ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent ## ## Model predictions using solution type analytical ## -## Fitted using 239 model solutions performed in 0.497 s +## Fitted using 239 model solutions performed in 0.49 s ## ## Error model: Constant variance ## @@ -399,8 +399,8 @@ summary(m.L2.DFOP, data = FALSE) ## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:14 2019 -## Date of summary: Wed Sep 18 18:24:14 2019 +## Date of fit: Thu Sep 19 09:53:02 2019 +## Date of summary: Thu Sep 19 09:53:02 2019 ## ## Equations: ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * @@ -409,7 +409,7 @@ ## ## Model predictions using solution type analytical ## -## Fitted using 572 model solutions performed in 1.215 s +## Fitted using 572 model solutions performed in 1.204 s ## ## Error model: Constant variance ## @@ -499,8 +499,8 @@ summary(mm.L3[["DFOP", 1]]) ## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:16 2019 -## Date of summary: Wed Sep 18 18:24:16 2019 +## Date of fit: Thu Sep 19 09:53:04 2019 +## Date of summary: Thu Sep 19 09:53:04 2019 ## ## Equations: ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * @@ -509,7 +509,7 @@ ## ## Model predictions using solution type analytical ## -## Fitted using 373 model solutions performed in 0.778 s +## Fitted using 373 model solutions performed in 0.799 s ## ## Error model: Constant variance ## @@ -605,15 +605,15 @@ summary(mm.L4[["SFO", 1]], data = FALSE) ## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:17 2019 -## Date of summary: Wed Sep 18 18:24:17 2019 +## Date of fit: Thu Sep 19 09:53:04 2019 +## Date of summary: Thu Sep 19 09:53:05 2019 ## ## Equations: ## d_parent/dt = - k_parent_sink * parent ## ## Model predictions using solution type analytical ## -## Fitted using 142 model solutions performed in 0.293 s +## Fitted using 142 model solutions performed in 0.287 s ## ## Error model: Constant variance ## @@ -670,15 +670,15 @@ summary(mm.L4[["FOMC", 1]], data = FALSE) ## mkin version used for fitting: 0.9.49.6 ## R version used for fitting: 3.6.1 -## Date of fit: Wed Sep 18 18:24:17 2019 -## Date of summary: Wed Sep 18 18:24:17 2019 +## Date of fit: Thu Sep 19 09:53:05 2019 +## Date of summary: Thu Sep 19 09:53:05 2019 ## ## Equations: ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent ## ## Model predictions using solution type analytical ## -## Fitted using 224 model solutions performed in 0.46 s +## Fitted using 224 model solutions performed in 0.48 s ## ## Error model: Constant variance ## diff --git a/docs/articles/mkin.html b/docs/articles/mkin.html index 90549b0f..ec138595 100644 --- a/docs/articles/mkin.html +++ b/docs/articles/mkin.html @@ -90,7 +90,7 @@ Introduction to mkin Johannes Ranke - 2019-09-18 + 2019-09-19 mkin.Rmd diff --git a/docs/articles/twa.html b/docs/articles/twa.html index 2d44a89d..9cb5873a 100644 --- a/docs/articles/twa.html +++ b/docs/articles/twa.html @@ -90,7 +90,7 @@ Calculation of time weighted average concentrations with mkin Johannes Ranke - 2019-09-18 + 2019-09-19 twa.Rmd diff --git a/docs/articles/web_only/FOCUS_Z.html b/docs/articles/web_only/FOCUS_Z.html index aed1debc..5ea0b256 100644 --- a/docs/articles/web_only/FOCUS_Z.html +++ b/docs/articles/web_only/FOCUS_Z.html @@ -90,7 +90,7 @@ Example evaluation of FOCUS dataset Z Johannes Ranke - 2019-09-18 + 2019-09-19 FOCUS_Z.Rmd diff --git a/docs/articles/web_only/NAFTA_examples.html b/docs/articles/web_only/NAFTA_examples.html index 3ca93667..0476acf8 100644 --- a/docs/articles/web_only/NAFTA_examples.html +++ b/docs/articles/web_only/NAFTA_examples.html @@ -90,7 +90,7 @@ Evaluation of example datasets from Attachment 1 to the US EPA SOP for the NAFTA guidance Johannes Ranke - 2019-09-18 + 2019-09-19 NAFTA_examples.Rmd diff --git a/docs/articles/web_only/benchmarks.html b/docs/articles/web_only/benchmarks.html index d46e738a..c0682cb0 100644 --- a/docs/articles/web_only/benchmarks.html +++ b/docs/articles/web_only/benchmarks.html @@ -90,7 +90,7 @@ Benchmark timings for mkin on various systems Johannes Ranke - 2019-09-18 + 2019-09-19 benchmarks.Rmd @@ -204,77 +204,77 @@ ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 7.064 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 7.296 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 5.936 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 5.970 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 6.005 ## t2 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 11.019 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 22.889 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 12.558 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 21.239 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 20.545 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 36.524 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 37.266 ## t3 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 3.764 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 4.649 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 4.786 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 4.510 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 4.446 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 4.607 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 4.559 ## t4 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 14.347 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 13.789 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 8.461 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 13.805 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 15.335 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 31.617 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 31.574 ## t5 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 9.495 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 6.395 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 5.675 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 7.386 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 6.002 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 10.543 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 10.659 ## t6 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 2.623 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 2.542 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 2.723 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 2.643 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 2.635 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 2.579 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 2.634 ## t7 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 4.587 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 4.128 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 4.478 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 4.374 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 4.259 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 4.341 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 4.324 ## t8 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 7.525 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 4.632 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 4.862 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 7.02 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 4.737 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 8.101 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 8.233 ## t9 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 16.621 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 8.171 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 7.618 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 11.124 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 7.763 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 16.211 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 16.376 ## t10 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 8.576 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 3.676 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 3.579 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 5.388 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 3.427 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 8.041 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 8.058 ## t11 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.48.1 31.267 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.1 5.636 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.2 5.574 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.3 7.365 ## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.4 5.626 -## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 10.804 +## Linux, AMD Ryzen 7 1700 Eight-Core Processor, mkin version 0.9.49.6 11.133 save(mkin_benchmarks, file = "~/git/mkin/vignettes/mkin_benchmarks.rda") diff --git a/docs/articles/web_only/compiled_models.html b/docs/articles/web_only/compiled_models.html index 1876e2b3..6df504ed 100644 --- a/docs/articles/web_only/compiled_models.html +++ b/docs/articles/web_only/compiled_models.html @@ -90,7 +90,7 @@ Performance benefit by using compiled model definitions in mkin Johannes Ranke - 2019-09-18 + 2019-09-19 compiled_models.Rmd @@ -165,9 +165,9 @@ ## Warning in mkinfit(SFO_SFO, FOCUS_2006_D, solution_type = "deSolve", quiet ## = TRUE): Observations with value of zero were removed from the data ## test replications elapsed relative user.self sys.self -## 3 deSolve, compiled 3 3.129 1.000 3.127 0 -## 1 deSolve, not compiled 3 28.841 9.217 28.827 0 -## 2 Eigenvalue based 3 4.433 1.417 4.430 0 +## 3 deSolve, compiled 3 3.171 1.000 3.170 0 +## 1 deSolve, not compiled 3 29.012 9.149 28.996 0 +## 2 Eigenvalue based 3 4.473 1.411 4.470 0 ## user.child sys.child ## 3 0 0 ## 1 0 0 @@ -216,8 +216,8 @@ ## Warning in mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE): Observations with ## value of zero were removed from the data ## test replications elapsed relative user.self sys.self -## 2 deSolve, compiled 3 4.860 1.000 4.857 0 -## 1 deSolve, not compiled 3 53.877 11.086 53.850 0 +## 2 deSolve, compiled 3 4.913 1.000 4.909 0 +## 1 deSolve, not compiled 3 53.418 10.873 53.393 0 ## user.child sys.child ## 2 0 0 ## 1 0 0 diff --git a/docs/reference/index.html b/docs/reference/index.html index b86df636..a8b326d7 100644 --- a/docs/reference/index.html +++ b/docs/reference/index.html @@ -311,7 +311,7 @@ - synthetic_data_for_UBA_2014 + synthetic_data_for_UBA_2014 Synthetic datasets for one parent compound with two metabolites diff --git a/docs/reference/mkinfit.html b/docs/reference/mkinfit.html index dc052f2a..0767d2f8 100644 --- a/docs/reference/mkinfit.html +++ b/docs/reference/mkinfit.html @@ -408,15 +408,15 @@ 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: 0.9.49.6 #> R version used for fitting: 3.6.1 -#> Date of fit: Wed Sep 18 18:22:06 2019 -#> Date of summary: Wed Sep 18 18:22:06 2019 +#> Date of fit: Thu Sep 19 09:50:54 2019 +#> Date of summary: Thu Sep 19 09:50:54 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 0.459 s +#> Fitted using 222 model solutions performed in 0.458 s #> #> Error model: Constant variance #> @@ -490,7 +490,7 @@ Per default, parameters in the kinetic models are internally transformed in m1 = mkinsub("SFO")) #> Successfully compiled differential equation model from auto-generated C code. # 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 -#> 1.494 0.000 1.496 coef(fit) #> NULL endpoints(fit) #> $ff +#> 1.479 0.002 1.482 coef(fit) #> NULL endpoints(fit) #> $ff #> parent_sink parent_m1 m1_sink #> 0.485524 0.514476 1.000000 #> @@ -563,7 +563,7 @@ 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 #> Optimisation successfully terminated. #> User System verstrichen -#> 1.056 0.000 1.057 coef(fit.deSolve) #> NULL endpoints(fit.deSolve) #> $ff +#> 1.053 0.000 1.054 coef(fit.deSolve) #> NULL endpoints(fit.deSolve) #> $ff #> parent_sink parent_m1 m1_sink #> 0.485524 0.514476 1.000000 #> @@ -599,8 +599,8 @@ 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") #> Successfully compiled differential equation model from auto-generated C code. f.noweight <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, quiet = TRUE) #> Warning: Observations with value of zero were removed from the data summary(f.noweight) #> mkin version used for fitting: 0.9.49.6 #> R version used for fitting: 3.6.1 -#> Date of fit: Wed Sep 18 18:22:22 2019 -#> Date of summary: Wed Sep 18 18:22:22 2019 +#> Date of fit: Thu Sep 19 09:51:10 2019 +#> Date of summary: Thu Sep 19 09:51:10 2019 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -608,7 +608,7 @@ Per default, parameters in the kinetic models are internally transformed in #> #> Model predictions using solution type deSolve #> -#> Fitted using 421 model solutions performed in 1.15 s +#> Fitted using 421 model solutions performed in 1.138 s #> #> Error model: Constant variance #> @@ -718,8 +718,8 @@ 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+00 f.obs <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, error_model = "obs", quiet = TRUE) #> Warning: Observations with value of zero were removed from the data summary(f.obs) #> mkin version used for fitting: 0.9.49.6 #> R version used for fitting: 3.6.1 -#> Date of fit: Wed Sep 18 18:22:24 2019 -#> Date of summary: Wed Sep 18 18:22:24 2019 +#> Date of fit: Thu Sep 19 09:51:12 2019 +#> Date of summary: Thu Sep 19 09:51:12 2019 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -727,7 +727,7 @@ Per default, parameters in the kinetic models are internally transformed in #> #> Model predictions using solution type deSolve #> -#> Fitted using 979 model solutions performed in 2.553 s +#> Fitted using 979 model solutions performed in 2.565 s #> #> Error model: Variance unique to each observed variable #> @@ -850,8 +850,8 @@ 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+00 f.tc <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, error_model = "tc", quiet = TRUE) #> Warning: Observations with value of zero were removed from the data summary(f.tc) #> mkin version used for fitting: 0.9.49.6 #> R version used for fitting: 3.6.1 -#> Date of fit: Wed Sep 18 18:22:34 2019 -#> Date of summary: Wed Sep 18 18:22:34 2019 +#> Date of fit: Thu Sep 19 09:51:22 2019 +#> Date of summary: Thu Sep 19 09:51:22 2019 #> #> Equations: #> d_parent/dt = - k_parent * parent @@ -859,7 +859,7 @@ Per default, parameters in the kinetic models are internally transformed in #> #> Model predictions using solution type deSolve #> -#> Fitted using 2289 model solutions performed in 9.369 s +#> Fitted using 2289 model solutions performed in 9.24 s #> #> Error model: Two-component variance function #> diff --git a/docs/reference/mkinmod.html b/docs/reference/mkinmod.html index a5cdd04d..f592af1c 100644 --- a/docs/reference/mkinmod.html +++ b/docs/reference/mkinmod.html @@ -239,7 +239,7 @@ 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 file310b6c1fede0.c 2> file310b6c1fede0.c.err.txt +#> /usr/lib/R/bin/R CMD SHLIB file663b71dc323f.c 2> file663b71dc323f.c.err.txt #> Program source: #> 1: #include <R.h> #> 2: diff --git a/docs/reference/mkinpredict.html b/docs/reference/mkinpredict.html index 97d3ca3a..5faff3c7 100644 --- a/docs/reference/mkinpredict.html +++ b/docs/reference/mkinpredict.html @@ -332,17 +332,17 @@ 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 0.004 system.time( +#> 0.004 0.000 0.004 system.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 -#> 0.001 0.000 0.002 system.time( +#> 0.002 0.000 0.002 system.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 0.021 # \dontrun{ # Predict from a fitted model f <- mkinfit(SFO_SFO, FOCUS_2006_C) #> Ordinary least squares optimisation #> Sum of squared residuals at call 1: 552.5739 diff --git a/docs/reference/mmkin.html b/docs/reference/mmkin.html index 81ebde7c..0f384062 100644 --- a/docs/reference/mmkin.html +++ b/docs/reference/mmkin.html @@ -199,8 +199,8 @@ time_1 <- system.time(fits.4 <- mmkin(models, datasets, cores = 1, quiet = TRUE)) time_default #> User System verstrichen -#> 0.013 0.039 5.128 time_1 #> User System verstrichen -#> 18.942 0.000 18.951 +#> 0.016 0.029 4.960 time_1 #> User System verstrichen +#> 19.084 0.004 19.099 endpoints(fits.0[["SFO_lin", 2]]) #> $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 c5d58911..73410181 100644 --- a/docs/reference/summary.mkinfit.html +++ b/docs/reference/summary.mkinfit.html @@ -215,15 +215,15 @@ Examples summary(mkinfit(mkinmod(parent = mkinsub("SFO")), FOCUS_2006_A, quiet = TRUE)) #> mkin version used for fitting: 0.9.49.6 #> R version used for fitting: 3.6.1 -#> Date of fit: Wed Sep 18 18:23:52 2019 -#> Date of summary: Wed Sep 18 18:23:52 2019 +#> Date of fit: Thu Sep 19 09:52:40 2019 +#> Date of summary: Thu Sep 19 09:52:40 2019 #> #> Equations: #> d_parent/dt = - k_parent_sink * parent #> #> Model predictions using solution type analytical #> -#> Fitted using 131 model solutions performed in 0.268 s +#> Fitted using 131 model solutions performed in 0.27 s #> #> Error model: Constant variance #> diff --git a/docs/reference/synthetic_data_for_UBA_2014-1.png b/docs/reference/synthetic_data_for_UBA_2014-1.png new file mode 100644 index 00000000..9d8c0931 Binary files /dev/null and b/docs/reference/synthetic_data_for_UBA_2014-1.png differ diff --git a/docs/reference/synthetic_data_for_UBA_2014.html b/docs/reference/synthetic_data_for_UBA_2014.html new file mode 100644 index 00000000..2c4480d9 --- /dev/null +++ b/docs/reference/synthetic_data_for_UBA_2014.html @@ -0,0 +1,462 @@ + + + + + + + + +Synthetic datasets for one parent compound with two metabolites — synthetic_data_for_UBA_2014 • mkin + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + mkin + 0.9.49.6 + + + + + + + Functions and data + + + + Articles + + + + + + Introduction to mkin + + + Example evaluation of FOCUS Example Dataset D + + + Example evaluation of FOCUS Laboratory Data L1 to L3 + + + Example evaluation of FOCUS Example Dataset Z + + + Performance benefit by using compiled model definitions in mkin + + + Calculation of time weighted average concentrations with mkin + + + Example evaluation of NAFTA SOP Attachment examples + + + + + News + + + + + + + + + + + + + + + + + + + Synthetic datasets for one parent compound with two metabolites + + synthetic_data_for_UBA_2014.Rd + + + + + The 12 datasets were generated using four different models and three different + variance components. The four models are either the SFO or the DFOP model with either + two sequential or two parallel metabolites. +Variance component 'a' is based on a normal distribution with standard deviation of 3, + Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7. + Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the + minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07 + for the increase of the standard deviation with y. Note that this is a simplified version + of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the + measured values approximates lognormal distribution for high values, whereas we are using + normally distributed error components all along. +Initial concentrations for metabolites and all values where adding the variance component resulted + in a value below the assumed limit of detection of 0.1 were set to NA. +As an example, the first dataset has the title SFO_lin_a and is based on the SFO model + with two sequential metabolites (linear pathway), with added variance component 'a'. +Compare also the code in the example section to see the degradation models. + + + + synthetic_data_for_UBA_2014 + + Format + + A list containing twelve datasets as an R6 class defined by mkinds, + each containing, among others, the following components + title The name of the dataset, e.g. SFO_lin_a + data A data frame with the data in the form expected by mkinfit + + + + + Source + + Ranke (2014) Prüfung und Validierung von Modellierungssoftware als Alternative + zu ModelMaker 4.0, Umweltbundesamt Projektnummer 27452 +Rocke, David M. und Lorenzato, Stefan (1995) A two-component model for + measurement error in analytical chemistry. Technometrics 37(2), 176-184. + + + Examples + # The data have been generated using the following kinetic models +m_synth_SFO_lin <- mkinmod(parent = list(type = "SFO", to = "M1"), + M1 = list(type = "SFO", to = "M2"), + M2 = list(type = "SFO"), use_of_ff = "max") #> Successfully compiled differential equation model from auto-generated C code. + +m_synth_SFO_par <- mkinmod(parent = list(type = "SFO", to = c("M1", "M2"), + sink = FALSE), + M1 = list(type = "SFO"), + M2 = list(type = "SFO"), use_of_ff = "max") #> Successfully compiled differential equation model from auto-generated C code. +m_synth_DFOP_lin <- mkinmod(parent = list(type = "DFOP", to = "M1"), + M1 = list(type = "SFO", to = "M2"), + M2 = list(type = "SFO"), use_of_ff = "max") #> Successfully compiled differential equation model from auto-generated C code. +m_synth_DFOP_par <- mkinmod(parent = list(type = "DFOP", to = c("M1", "M2"), + sink = FALSE), + M1 = list(type = "SFO"), + M2 = list(type = "SFO"), use_of_ff = "max") #> Successfully compiled differential equation model from auto-generated C code. +# The model predictions without intentional error were generated as follows +sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120) + +d_synth_SFO_lin <- mkinpredict(m_synth_SFO_lin, + c(k_parent = 0.7, f_parent_to_M1 = 0.8, + k_M1 = 0.3, f_M1_to_M2 = 0.7, + k_M2 = 0.02), + c(parent = 100, M1 = 0, M2 = 0), + sampling_times) + +d_synth_DFOP_lin <- mkinpredict(m_synth_DFOP_lin, + c(k1 = 0.2, k2 = 0.02, g = 0.5, + f_parent_to_M1 = 0.5, k_M1 = 0.3, + f_M1_to_M2 = 0.7, k_M2 = 0.02), + c(parent = 100, M1 = 0, M2 = 0), + sampling_times) + +d_synth_SFO_par <- mkinpredict(m_synth_SFO_par, + c(k_parent = 0.2, + f_parent_to_M1 = 0.8, k_M1 = 0.01, + f_parent_to_M2 = 0.2, k_M2 = 0.02), + c(parent = 100, M1 = 0, M2 = 0), + sampling_times) + +d_synth_DFOP_par <- mkinpredict(m_synth_DFOP_par, + c(k1 = 0.3, k2 = 0.02, g = 0.7, + f_parent_to_M1 = 0.6, k_M1 = 0.04, + f_parent_to_M2 = 0.4, k_M2 = 0.01), + c(parent = 100, M1 = 0, M2 = 0), + sampling_times) + +# Construct names for datasets with errors +d_synth_names = paste0("d_synth_", c("SFO_lin", "SFO_par", + "DFOP_lin", "DFOP_par")) + +# Original function used or adding errors. The add_err function now published +# with this package is a slightly generalised version where the names of +# secondary compartments that should have an initial value of zero (M1 and M2 +# in this case) are not hardcoded any more. +# add_err = function(d, sdfunc, LOD = 0.1, reps = 2, seed = 123456789) +# { +# set.seed(seed) +# d_long = mkin_wide_to_long(d, time = "time") +# d_rep = data.frame(lapply(d_long, rep, each = 2)) +# d_rep$value = rnorm(length(d_rep$value), d_rep$value, sdfunc(d_rep$value)) +# +# d_rep[d_rep$time == 0 & match(d_rep$name, c("M1", "M2"), "value"] <- 0 +# d_NA <- transform(d_rep, value = ifelse(value < LOD, NA, value)) +# d_NA$value <- round(d_NA$value, 1) +# return(d_NA) +# } + +# The following is the simplified version of the two-component model of Rocke +# and Lorenzato (1995) +sdfunc_twocomp = function(value, sd_low, rsd_high) { + sqrt(sd_low^2 + value^2 * rsd_high^2) +} + +# Add the errors. +for (d_synth_name in d_synth_names) +{ + d_synth = get(d_synth_name) + assign(paste0(d_synth_name, "_a"), add_err(d_synth, function(value) 3)) + assign(paste0(d_synth_name, "_b"), add_err(d_synth, function(value) 7)) + assign(paste0(d_synth_name, "_c"), add_err(d_synth, + function(value) sdfunc_twocomp(value, 0.5, 0.07))) + +} + +d_synth_err_names = c( + paste(rep(d_synth_names, each = 3), letters[1:3], sep = "_") +) + +# This is just one example of an evaluation using the kinetic model used for +# the generation of the data +fit <- mkinfit(m_synth_SFO_lin, synthetic_data_for_UBA_2014[[1]]$data, + quiet = TRUE) +plot_sep(fit) summary(fit) #> mkin version used for fitting: 0.9.49.6 +#> R version used for fitting: 3.6.1 +#> Date of fit: Thu Sep 19 12:43:02 2019 +#> Date of summary: Thu Sep 19 12:43:02 2019 +#> +#> Equations: +#> d_parent/dt = - k_parent * parent +#> d_M1/dt = + f_parent_to_M1 * k_parent * parent - k_M1 * M1 +#> d_M2/dt = + f_M1_to_M2 * k_M1 * M1 - k_M2 * M2 +#> +#> Model predictions using solution type deSolve +#> +#> Fitted using 847 model solutions performed in 2.51 s +#> +#> Error model: Constant variance +#> +#> Error model algorithm: OLS +#> +#> Starting values for parameters to be optimised: +#> value type +#> parent_0 101.350000 state +#> k_parent 0.100000 deparm +#> k_M1 0.100100 deparm +#> k_M2 0.100200 deparm +#> f_parent_to_M1 0.500000 deparm +#> f_M1_to_M2 0.500000 deparm +#> sigma 2.273126 error +#> +#> Starting values for the transformed parameters actually optimised: +#> value lower upper +#> parent_0 101.350000 -Inf Inf +#> log_k_parent -2.302585 -Inf Inf +#> log_k_M1 -2.301586 -Inf Inf +#> log_k_M2 -2.300587 -Inf Inf +#> f_parent_ilr_1 0.000000 -Inf Inf +#> f_M1_ilr_1 0.000000 -Inf Inf +#> sigma 2.273126 0 Inf +#> +#> Fixed parameter values: +#> value type +#> M1_0 0 state +#> M2_0 0 state +#> +#> Optimised, transformed parameters with symmetric confidence intervals: +#> Estimate Std. Error Lower Upper +#> parent_0 102.1000 1.57000 98.8600 105.3000 +#> log_k_parent -0.3020 0.03885 -0.3812 -0.2229 +#> log_k_M1 -1.2070 0.07123 -1.3520 -1.0620 +#> log_k_M2 -3.9010 0.06571 -4.0350 -3.7670 +#> f_parent_ilr_1 0.8492 0.16640 0.5103 1.1880 +#> f_M1_ilr_1 0.6780 0.17600 0.3196 1.0360 +#> sigma 2.2730 0.25740 1.7490 2.7970 +#> +#> Parameter correlation: +#> parent_0 log_k_parent log_k_M1 log_k_M2 f_parent_ilr_1 +#> parent_0 1.000e+00 3.933e-01 -1.605e-01 2.819e-02 -4.624e-01 +#> log_k_parent 3.933e-01 1.000e+00 -4.082e-01 7.166e-02 -5.682e-01 +#> log_k_M1 -1.605e-01 -4.082e-01 1.000e+00 -3.929e-01 7.478e-01 +#> log_k_M2 2.819e-02 7.166e-02 -3.929e-01 1.000e+00 -2.658e-01 +#> f_parent_ilr_1 -4.624e-01 -5.682e-01 7.478e-01 -2.658e-01 1.000e+00 +#> f_M1_ilr_1 1.614e-01 4.102e-01 -8.109e-01 5.419e-01 -8.605e-01 +#> sigma -3.704e-09 -1.104e-08 5.922e-08 -3.673e-08 5.867e-08 +#> f_M1_ilr_1 sigma +#> parent_0 1.614e-01 -3.704e-09 +#> log_k_parent 4.102e-01 -1.104e-08 +#> log_k_M1 -8.109e-01 5.922e-08 +#> log_k_M2 5.419e-01 -3.673e-08 +#> f_parent_ilr_1 -8.605e-01 5.867e-08 +#> f_M1_ilr_1 1.000e+00 -8.075e-08 +#> sigma -8.075e-08 1.000e+00 +#> +#> Backtransformed parameters: +#> Confidence intervals for internally transformed parameters are asymmetric. +#> t-test (unrealistically) based on the assumption of normal distribution +#> for estimators of untransformed parameters. +#> Estimate t value Pr(>t) Lower Upper +#> parent_0 102.10000 65.000 7.281e-36 98.86000 105.30000 +#> k_parent 0.73930 25.740 2.948e-23 0.68310 0.80020 +#> k_M1 0.29920 14.040 1.577e-15 0.25880 0.34590 +#> k_M2 0.02023 15.220 1.653e-16 0.01769 0.02312 +#> f_parent_to_M1 0.76870 18.370 7.295e-19 0.67300 0.84290 +#> f_M1_to_M2 0.72290 14.500 6.418e-16 0.61110 0.81240 +#> sigma 2.27300 8.832 2.161e-10 1.74900 2.79700 +#> +#> FOCUS Chi2 error levels in percent: +#> err.min n.optim df +#> All data 8.454 6 17 +#> parent 8.660 2 6 +#> M1 10.583 2 5 +#> M2 3.586 2 6 +#> +#> Resulting formation fractions: +#> ff +#> parent_M1 0.7687 +#> parent_sink 0.2313 +#> M1_M2 0.7229 +#> M1_sink 0.2771 +#> +#> Estimated disappearance times: +#> DT50 DT90 +#> parent 0.9376 3.114 +#> M1 2.3170 7.697 +#> M2 34.2689 113.839 +#> +#> Data: +#> time variable observed predicted residual +#> 0 parent 101.5 1.021e+02 -0.56248 +#> 0 parent 101.2 1.021e+02 -0.86248 +#> 1 parent 53.9 4.873e+01 5.17118 +#> 1 parent 47.5 4.873e+01 -1.22882 +#> 3 parent 10.4 1.111e+01 -0.70773 +#> 3 parent 7.6 1.111e+01 -3.50773 +#> 7 parent 1.1 5.772e-01 0.52283 +#> 7 parent 0.3 5.772e-01 -0.27717 +#> 14 parent 3.5 3.264e-03 3.49674 +#> 28 parent 3.2 1.045e-07 3.20000 +#> 90 parent 0.6 -1.875e-11 0.60000 +#> 120 parent 3.5 -2.805e-11 3.50000 +#> 1 M1 36.4 3.479e+01 1.61088 +#> 1 M1 37.4 3.479e+01 2.61088 +#> 3 M1 34.3 3.937e+01 -5.07027 +#> 3 M1 39.8 3.937e+01 0.42973 +#> 7 M1 15.1 1.549e+01 -0.38715 +#> 7 M1 17.8 1.549e+01 2.31285 +#> 14 M1 5.8 1.995e+00 3.80469 +#> 14 M1 1.2 1.995e+00 -0.79531 +#> 60 M1 0.5 2.111e-06 0.50000 +#> 90 M1 3.2 2.913e-10 3.20000 +#> 120 M1 1.5 3.625e-11 1.50000 +#> 120 M1 0.6 3.625e-11 0.60000 +#> 1 M2 4.8 4.455e+00 0.34517 +#> 3 M2 20.9 2.153e+01 -0.62527 +#> 3 M2 19.3 2.153e+01 -2.22527 +#> 7 M2 42.0 4.192e+01 0.07941 +#> 7 M2 43.1 4.192e+01 1.17941 +#> 14 M2 49.4 4.557e+01 3.83353 +#> 14 M2 44.3 4.557e+01 -1.26647 +#> 28 M2 34.6 3.547e+01 -0.87275 +#> 28 M2 33.0 3.547e+01 -2.47275 +#> 60 M2 18.8 1.858e+01 0.21837 +#> 60 M2 17.6 1.858e+01 -0.98163 +#> 90 M2 10.6 1.013e+01 0.47130 +#> 90 M2 10.8 1.013e+01 0.67130 +#> 120 M2 9.8 5.521e+00 4.27893 +#> 120 M2 3.3 5.521e+00 -2.22107 + + + Contents + + + Format + + Source + + Examples + + + + + + + + + Developed by Johannes Ranke. + + + + Site built with pkgdown 1.4.1. + + + + + + + + + + + + diff --git a/docs/sitemap.xml b/docs/sitemap.xml index e75a0097..00d1a840 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -148,7 +148,7 @@ https://pkgdown.jrwb.de/mkin/reference/summary.mkinfit.html - https://pkgdown.jrwb.de/mkin/reference/synthetic_data_for_UBA.html + https://pkgdown.jrwb.de/mkin/reference/synthetic_data_for_UBA_2014.html https://pkgdown.jrwb.de/mkin/reference/test_data_from_UBA_2014.html -- cgit v1.2.1