Work package 1.1: Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P • mkin

## mkin version used for fitting: 1.1.2 -## R version used for fitting: 4.2.1 -## Date of fit: Wed Sep 14 22:28:35 2022 -## Date of summary: Wed Sep 14 22:28:35 2022 +## mkin version used for fitting: 1.2.2 +## R version used for fitting: 4.2.2 +## Date of fit: Tue Dec 6 09:39:45 2022 +## Date of summary: Tue Dec 6 09:39:45 2022 ## ## Equations: ## d_parent/dt = - k_parent * parent ## ## Model predictions using solution type analytical ## -## Fitted using 133 model solutions performed in 0.032 s +## Fitted using 133 model solutions performed in 0.033 s ## ## Error model: Constant variance ## @@ -1637,10 +1630,10 @@ summary(m.L1.SFO) ## Warning in sqrt(1/diag(V)): NaNs produced ## Warning in cov2cor(ans$covar): diag(.) had 0 or NA entries; non-finite result is ## doubtful -## mkin version used for fitting: 1.1.2 -## R version used for fitting: 4.2.1 -## Date of fit: Wed Sep 14 22:28:35 2022 -## Date of summary: Wed Sep 14 22:28:35 2022 +## mkin version used for fitting: 1.2.2 +## R version used for fitting: 4.2.2 +## Date of fit: Tue Dec 6 09:39:45 2022 +## Date of summary: Tue Dec 6 09:39:45 2022 ## ## Equations: ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent @@ -1742,17 +1735,17 @@ plot(m.L2.FOMC, show_residuals = TRUE, main = "FOCUS L2 - FOMC") summary(m.L2.FOMC, data = FALSE) -## mkin version used for fitting: 1.1.2 -## R version used for fitting: 4.2.1 -## Date of fit: Wed Sep 14 22:28:35 2022 -## Date of summary: Wed Sep 14 22:28:35 2022 +## mkin version used for fitting: 1.2.2 +## R version used for fitting: 4.2.2 +## Date of fit: Tue Dec 6 09:39:45 2022 +## Date of summary: Tue Dec 6 09:39:45 2022 ## ## Equations: ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent ## ## Model predictions using solution type analytical ## -## Fitted using 239 model solutions performed in 0.049 s +## Fitted using 239 model solutions performed in 0.048 s ## ## Error model: Constant variance ## @@ -1820,10 +1813,10 @@ plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE, main = "FOCUS L2 - DFOP") summary(m.L2.DFOP, data = FALSE) -## mkin version used for fitting: 1.1.2 -## R version used for fitting: 4.2.1 -## Date of fit: Wed Sep 14 22:28:36 2022 -## Date of summary: Wed Sep 14 22:28:36 2022 +## mkin version used for fitting: 1.2.2 +## R version used for fitting: 4.2.2 +## Date of fit: Tue Dec 6 09:39:46 2022 +## Date of summary: Tue Dec 6 09:39:46 2022 ## ## Equations: ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1832,7 +1825,7 @@ plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE, ## ## Model predictions using solution type analytical ## -## Fitted using 581 model solutions performed in 0.135 s +## Fitted using 581 model solutions performed in 0.131 s ## ## Error model: Constant variance ## @@ -1920,10 +1913,10 @@ plot(mm.L3) The objects returned by mmkin are arranged like a matrix, with models as a row index and datasets as a column index. We can extract the summary and plot for e.g. the DFOP fit, using square brackets for indexing which will result in the use of the summary and plot functions working on mkinfit objects. summary(mm.L3[["DFOP", 1]]) -## mkin version used for fitting: 1.1.2 -## R version used for fitting: 4.2.1 -## Date of fit: Wed Sep 14 22:28:36 2022 -## Date of summary: Wed Sep 14 22:28:36 2022 +## mkin version used for fitting: 1.2.2 +## R version used for fitting: 4.2.2 +## Date of fit: Tue Dec 6 09:39:46 2022 +## Date of summary: Tue Dec 6 09:39:46 2022 ## ## Equations: ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * @@ -1932,7 +1925,7 @@ plot(mm.L3) ## ## Model predictions using solution type analytical ## -## Fitted using 376 model solutions performed in 0.081 s +## Fitted using 376 model solutions performed in 0.078 s ## ## Error model: Constant variance ## @@ -2028,17 +2021,17 @@ plot(mm.L4) The χ² error level of 3.3% as well as the plot suggest that the SFO model fits very well. The error level at which the χ² test passes is slightly lower for the FOMC model. However, the difference appears negligible. summary(mm.L4[["SFO", 1]], data = FALSE) -## mkin version used for fitting: 1.1.2 -## R version used for fitting: 4.2.1 -## Date of fit: Wed Sep 14 22:28:36 2022 -## Date of summary: Wed Sep 14 22:28:37 2022 +## mkin version used for fitting: 1.2.2 +## R version used for fitting: 4.2.2 +## Date of fit: Tue Dec 6 09:39:47 2022 +## Date of summary: Tue Dec 6 09:39:47 2022 ## ## Equations: ## d_parent/dt = - k_parent * parent ## ## Model predictions using solution type analytical ## -## Fitted using 142 model solutions performed in 0.034 s +## Fitted using 142 model solutions performed in 0.03 s ## ## Error model: Constant variance ## @@ -2092,10 +2085,10 @@ plot(mm.L4) ## DT50 DT90 ## parent 106 352 summary(mm.L4[["FOMC", 1]], data = FALSE) -## mkin version used for fitting: 1.1.2 -## R version used for fitting: 4.2.1 -## Date of fit: Wed Sep 14 22:28:37 2022 -## Date of summary: Wed Sep 14 22:28:37 2022 +## mkin version used for fitting: 1.2.2 +## R version used for fitting: 4.2.2 +## Date of fit: Tue Dec 6 09:39:47 2022 +## Date of summary: Tue Dec 6 09:39:47 2022 ## ## Equations: ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent -- cgit v1.2.3 From 24eb77216700cf8b2f2bde3abad84c1f83f9e32a Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Mon, 9 Jan 2023 06:22:04 +0100 Subject: Prebuilt PDF vignettes, summary_listing --- .Rbuildignore | 2 + .gitignore | 4 + DESCRIPTION | 2 +- GNUmakefile | 7 +- NAMESPACE | 2 + R/hierarchical_kinetics.R | 2 +- R/summary_listing.R | 59 + R/tex_listing.R | 32 - README.md | 2 + _pkgdown.yml | 3 +- docs/dev/articles/2022_wp_1.1_dmta_parent.html | 2177 ++++++++++++++++++++ .../figure-html/convergence-saem-dfop-const-1.png | Bin 0 -> 128154 bytes .../figure-html/convergence-saem-dfop-tc-1.png | Bin 0 -> 109761 bytes .../convergence-saem-dfop-tc-no-ranef-k2-1.png | Bin 0 -> 123528 bytes .../figure-html/convergence-saem-fomc-const-1.png | Bin 0 -> 100169 bytes 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vignettes/prebuilt/references.bib create mode 100644 vignettes/web_only/FOCUS_Z.R create mode 100644 vignettes/web_only/benchmarks.R create mode 100644 vignettes/web_only/compiled_models.R create mode 100644 vignettes/web_only/dimethenamid_2018.R (limited to 'vignettes/FOCUS_L.html') diff --git a/.Rbuildignore b/.Rbuildignore index 70eef830..7e13343b 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -28,6 +28,8 @@ ^vignettes/.*.synctex.gz ^vignettes/.*.toc$ ^vignettes/figure +^vignettes/prebuilt/*_dlls +^vignettes/prebuilt/*.pdf ^vignettes/FOCUS_Z.tex$ ^vignettes/mkin.tex$ ^vignettes/mkin_benchmarks.rda$ diff --git a/.gitignore b/.gitignore index a86197a1..5bec45e6 100644 --- a/.gitignore +++ b/.gitignore @@ -28,3 +28,7 @@ vignettes/cache/ vignettes/figure/ vignettes/*_cache/ vignettes/*_files/ +vignettes/prebuilt/*_cache +vignettes/prebuilt/*_files +vignettes/prebuilt/*_dlls +vignettes/prebuilt/*.pdf diff --git a/DESCRIPTION b/DESCRIPTION index d061a5a9..50dba006 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -2,7 +2,7 @@ Package: mkin Type: Package Title: Kinetic Evaluation of Chemical Degradation Data Version: 1.2.2 -Date: 2023-01-03 +Date: 2023-01-08 Authors@R: c( person("Johannes", "Ranke", role = c("aut", "cre", "cph"), email = "johannes.ranke@jrwb.de", diff --git a/GNUmakefile b/GNUmakefile index 4a33c538..9f268335 100644 --- a/GNUmakefile +++ b/GNUmakefile @@ -37,10 +37,6 @@ pkgfiles = \ all: build $(TGZ): $(pkgfiles) vignettes - $(RM) -r vignettes/*_cache - $(RM) -r vignettes/*_files - $(RM) -r vignettes/*.R - $(RM) -r vignettes/web_only/*.R $(RM) Rplots.pdf "$(RBIN)/R" CMD build . 2>&1 | tee log/build.log @@ -111,7 +107,8 @@ vignettes: vignettes/mkin.html vignettes/FOCUS_D.html vignettes/FOCUS_L.html vig vignettes/web_only/%.html: vignettes/references.bib vignettes/web_only/%.rmd "$(RBIN)/Rscript" -e "tools::buildVignette(file = 'vignettes/web_only/$*.rmd', dir = 'vignettes/web_only', keep=c('mkin_benchmarks.rda', 'saem_benchmarks.rda'))" -articles: vignettes/web_only/FOCUS_Z.html vignettes/web_only/compiled_models.html vignettes/web_only/benchmarks.html vignettes/web_only/dimethenamid_2018.html vignettes/web_only/multistart.html +vignettes/prebuilt/%.pdf: vignettes/prebuilt/references.bib vignettes/prebuilt/%.rmd + "$(RBIN)/Rscript" -e "rmarkdown::render('vignettes/prebuilt/$*.rmd')" pd: roxygen "$(RBIN)/Rscript" -e "pkgdown::build_site(run_dont_run = TRUE, lazy = TRUE)" diff --git a/NAMESPACE b/NAMESPACE index 84d6b713..b41bf614 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -97,6 +97,7 @@ export(endpoints) export(f_time_norm_focus) export(get_deg_func) export(hierarchical_kinetics) +export(html_listing) export(illparms) export(ilr) export(intervals) @@ -145,6 +146,7 @@ export(set_nd_nq) export(set_nd_nq_focus) export(sigma_twocomp) export(status) +export(summary_listing) export(tex_listing) export(transform_odeparms) export(which.best) diff --git a/R/hierarchical_kinetics.R b/R/hierarchical_kinetics.R index a90dd619..e545754a 100644 --- a/R/hierarchical_kinetics.R +++ b/R/hierarchical_kinetics.R @@ -13,7 +13,7 @@ #' #' \dontrun{ #' library(rmarkdown) -#' draft("New analysis.rmd", template = "hierarchical_kinetics", package = "mkin") +#' draft("example_analysis.rmd", template = "hierarchical_kinetics", package = "mkin") #' } #' #' @export diff --git a/R/summary_listing.R b/R/summary_listing.R new file mode 100644 index 00000000..38b52240 --- /dev/null +++ b/R/summary_listing.R @@ -0,0 +1,59 @@ +#' Display the output of a summary function according to the output format +#' +#' This function is intended for use in a R markdown code chunk with the chunk +#' option `results = "asis"`. +#' +#' @param object The object for which the summary is to be listed +#' @param caption An optional caption +#' @param label An optional label, ignored in html output +#' @param clearpage Should a new page be started after the listing? Ignored in html output +#' @export +summary_listing <- function(object, caption = NULL, label = NULL, + clearpage = TRUE) { + if (knitr::is_latex_output()) { + tex_listing(object = object, caption = caption, label = label, + clearpage = clearpage) + } + if (knitr::is_html_output()) { + html_listing(object = object, caption = caption) + } +} + +#' @rdname summary_listing +#' @export +tex_listing <- function(object, caption = NULL, label = NULL, + clearpage = TRUE) { + cat("\n") + cat("\\begin{listing}", "\n") + if (!is.null(caption)) { + cat("\\caption{", caption, "}", "\n", sep = "") + } + if (!is.null(label)) { + cat("\\caption{", label, "}", "\n", sep = "") + } + cat("\\begin{snugshade}", "\n") + cat("\\scriptsize", "\n") + cat("\\begin{verbatim}", "\n") + cat(capture.output(suppressWarnings(summary(object))), sep = "\n") + cat("\n") + cat("\\end{verbatim}", "\n") + cat("\\end{snugshade}", "\n") + cat("\\end{listing}", "\n") + if (clearpage) { + cat("\\clearpage", "\n") + } +} + +#' @rdname summary_listing +#' @export +html_listing <- function(object, caption = NULL) { + cat("\n") + if (!is.null(caption)) { + cat("", caption, "", "\n", sep = "") + } + cat("\n") + cat(capture.output(suppressWarnings(summary(object))), sep = "\n") + cat("\n") + cat("\n") +} + diff --git a/R/tex_listing.R b/R/tex_listing.R deleted file mode 100644 index 05f662e4..00000000 --- a/R/tex_listing.R +++ /dev/null @@ -1,32 +0,0 @@ -#' Wrap the output of a summary function in tex listing environment -#' -#' This function can be used in a R markdown code chunk with the chunk -#' option `results = "asis"`. -#' -#' @param object The object for which the summary is to be listed -#' @param caption An optional caption -#' @param label An optional label -#' @param clearpage Should a new page be started after the listing? -#' @export -tex_listing <- function(object, caption = NULL, label = NULL, - clearpage = TRUE) { - cat("\n") - cat("\\begin{listing}", "\n") - if (!is.null(caption)) { - cat("\\caption{", caption, "}", "\n", sep = "") - } - if (!is.null(label)) { - cat("\\caption{", label, "}", "\n", sep = "") - } - cat("\\begin{snugshade}", "\n") - cat("\\scriptsize", "\n") - cat("\\begin{verbatim}", "\n") - cat(capture.output(suppressWarnings(summary(object))), sep = "\n") - cat("\n") - cat("\\end{verbatim}", "\n") - cat("\\end{snugshade}", "\n") - cat("\\end{listing}", "\n") - if (clearpage) { - cat("\\clearpage", "\n") - } -} diff --git a/README.md b/README.md index f3c36890..b6171767 100644 --- a/README.md +++ b/README.md @@ -214,6 +214,8 @@ to ModelMaker 4.0, 2014-2015) of the visual fit in the kinetic evaluation of degradation data, 2019-2020) - Project Number 146839 (Checking the feasibility of using mixed-effects models for the derivation of kinetic modelling parameters from degradation studies, 2020-2021) +- Project Number 173340 (Application of nonlinear hierarchical models to the + kinetic evaluation of chemical degradation data) Thanks to everyone involved for collaboration and support! diff --git a/_pkgdown.yml b/_pkgdown.yml index ca5ea6e0..5d7fdbf4 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -47,6 +47,7 @@ reference: - title: Mixed models desc: Create and work with nonlinear hierarchical models contents: + - hierarchical_kinetics - read_spreadsheet - nlme.mmkin - saem.mmkin @@ -92,7 +93,7 @@ reference: - plot.nafta - title: Utility functions contents: - - tex_listing + - summary_listing - f_time_norm_focus - set_nd_nq - max_twa_parent diff --git a/docs/dev/articles/2022_wp_1.1_dmta_parent.html b/docs/dev/articles/2022_wp_1.1_dmta_parent.html new file mode 100644 index 00000000..61bb81d3 --- /dev/null +++ b/docs/dev/articles/2022_wp_1.1_dmta_parent.html @@ -0,0 +1,2177 @@ + + + + + + + +Work package 1.1: Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P • mkin + + + + + + + + + + + + + + + + + + + + mkin + 1.2.2 + + + + + + + Functions and data + + + + Articles + + + + + + Introduction to mkin + + + Example evaluation of FOCUS Example Dataset D + + + Example evaluation of FOCUS Laboratory Data L1 to L3 + + + Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models + + + Short demo of the multistart method + + + Performance benefit by using compiled model definitions in mkin + + + Example evaluation of FOCUS Example Dataset Z + + + Calculation of time weighted average concentrations with mkin + + + Example evaluation of NAFTA SOP Attachment examples + + + Benchmark timings for mkin + + + Benchmark timings for saem.mmkin + + + + + News + + + + + + + + + + + + + + + + + + + + + + + Work package 1.1: Testing hierarchical parent +degradation kinetics with residue data on dimethenamid and +dimethenamid-P + Johannes +Ranke + + Last change on 5 January +2022, last compiled on 5 Januar 2023 + + Source: vignettes/2022_wp_1.1_dmta_parent.rmd + 2022_wp_1.1_dmta_parent.rmd + + + + + + +Introduction + +The purpose of this document is to demonstrate how nonlinear +hierarchical models (NLHM) based on the parent degradation models SFO, +FOMC, DFOP and HS can be fitted with the mkin package. +The mkin package is used in version 1.2.2. It contains the test data +and the functions used in the evaluations. The saemix +package is used as a backend for fitting the NLHM, but is also loaded to +make the convergence plot function available. +This document is processed with the knitr package, which +also provides the kable function that is used to improve +the display of tabular data in R markdown documents. For parallel +processing, the parallel package is used. ++library(mkin) +library(knitr) +library(saemix) +library(parallel) +n_cores <- detectCores() +if (Sys.info()["sysname"] == "Windows") { + cl <- makePSOCKcluster(n_cores) +} else { + cl <- makeForkCluster(n_cores) +} + +Preprocessing of test data + +The test data are available in the mkin package as an object of class +mkindsg (mkin dataset group) under the identifier +dimethenamid_2018. The following preprocessing steps are +still necessary: + +The data available for the enantiomer dimethenamid-P (DMTAP) are +renamed to have the same substance name as the data for the racemic +mixture dimethenamid (DMTA). The reason for this is that no difference +between their degradation behaviour was identified in the EU risk +assessment. +The data for transformation products and unnecessary columns are +discarded +The observation times of each dataset are multiplied with the +corresponding normalisation factor also available in the dataset, in +order to make it possible to describe all datasets with a single set of +parameters that are independent of temperature +Finally, datasets observed in the same soil (Elliot 1 +and Elliot 2) are combined, resulting in dimethenamid +(DMTA) data from six soils. + +The following commented R code performs this preprocessing. ++# Apply a function to each of the seven datasets in the mkindsg object to create a list +dmta_ds <- lapply(1:7, function(i) { + ds_i <- dimethenamid_2018$ds[[i]]$data # Get a dataset + ds_i[ds_i$name == "DMTAP", "name"] <- "DMTA" # Rename DMTAP to DMTA + ds_i <- subset(ds_i, name == "DMTA", c("name", "time", "value")) # Select data + ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i] # Normalise time + ds_i # Return the dataset +}) + +# Use dataset titles as names for the list elements +names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title) + +# Combine data for Elliot soil to obtain a named list with six elements +dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]]) # +dmta_ds[["Elliot 1"]] <- NULL +dmta_ds[["Elliot 2"]] <- NULL +The following tables show the 6 datasets. ++for (ds_name in names(dmta_ds)) { + print(kable(mkin_long_to_wide(dmta_ds[[ds_name]]), + caption = paste("Dataset", ds_name), + label = paste0("tab:", ds_name), booktabs = TRUE)) + cat("\n\\clearpage\n") +} + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Dataset Calketime DMTA 0 95.8 0 98.7 14 60.5 30 39.1 59 15.2 120 4.8 120 4.6 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Dataset Borsteltime DMTA 0.000000 100.5 0.000000 99.6 1.941295 91.9 1.941295 91.3 6.794534 81.8 6.794534 82.1 13.589067 69.1 13.589067 68.0 27.178135 51.4 27.178135 51.4 56.297565 27.6 56.297565 26.8 86.387643 15.7 86.387643 15.3 115.507073 7.9 115.507073 8.1 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Dataset Flaachtime DMTA 0.0000000 96.5 0.0000000 96.8 0.0000000 97.0 0.6233856 82.9 0.6233856 86.7 0.6233856 87.4 1.8701567 72.8 1.8701567 69.9 1.8701567 71.9 4.3636989 51.4 4.3636989 52.9 4.3636989 48.6 8.7273979 28.5 8.7273979 27.3 8.7273979 27.5 13.0910968 14.8 13.0910968 13.4 13.0910968 14.4 17.4547957 7.7 17.4547957 7.3 17.4547957 8.1 26.1821936 2.0 26.1821936 1.5 26.1821936 1.9 34.9095915 1.3 34.9095915 1.0 34.9095915 1.1 43.6369893 0.9 43.6369893 0.7 43.6369893 0.7 52.3643872 0.6 52.3643872 0.4 52.3643872 0.5 74.8062674 0.4 74.8062674 0.3 74.8062674 0.3 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Dataset BBA 2.2time DMTA 0.0000000 98.09 0.0000000 98.77 0.7678922 93.52 0.7678922 92.03 2.3036765 88.39 2.3036765 87.18 5.3752452 69.38 5.3752452 71.06 10.7504904 45.21 10.7504904 46.81 16.1257355 30.54 16.1257355 30.07 21.5009807 21.60 21.5009807 20.41 32.2514711 9.10 32.2514711 9.70 43.0019614 6.58 43.0019614 6.31 53.7524518 3.47 53.7524518 3.52 64.5029421 3.40 64.5029421 3.67 91.3791680 1.62 91.3791680 1.62 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Dataset BBA 2.3time DMTA 0.0000000 99.33 0.0000000 97.44 0.6733938 93.73 0.6733938 93.77 2.0201814 87.84 2.0201814 89.82 4.7137565 71.61 4.7137565 71.42 9.4275131 45.60 9.4275131 45.42 14.1412696 31.12 14.1412696 31.68 18.8550262 23.20 18.8550262 24.13 28.2825393 9.43 28.2825393 9.82 37.7100523 7.08 37.7100523 8.64 47.1375654 4.41 47.1375654 4.78 56.5650785 4.92 56.5650785 5.08 80.1338612 2.13 80.1338612 2.23 + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + +Dataset Elliottime DMTA 0.000000 97.5 0.000000 100.7 1.228478 86.4 1.228478 88.5 3.685435 69.8 3.685435 77.1 8.599349 59.0 8.599349 54.2 17.198697 31.3 17.198697 33.5 25.798046 19.6 25.798046 20.9 34.397395 13.3 34.397395 15.8 51.596092 6.7 51.596092 8.7 68.794789 8.8 68.794789 8.7 103.192184 6.0 103.192184 4.4 146.188928 3.3 146.188928 2.8 223.583066 1.4 223.583066 1.8 0.000000 93.4 0.000000 103.2 1.228478 89.2 1.228478 86.6 3.685435 78.2 3.685435 78.1 8.599349 55.6 8.599349 53.0 17.198697 33.7 17.198697 33.2 25.798046 20.9 25.798046 19.9 34.397395 18.2 34.397395 12.7 51.596092 7.8 51.596092 9.0 68.794789 11.4 68.794789 9.0 103.192184 3.9 103.192184 4.4 146.188928 2.6 146.188928 3.4 223.583066 2.0 223.583066 1.7 + + + +Separate evaluations + +In order to obtain suitable starting parameters for the NLHM fits, +separate fits of the four models to the data for each soil are generated +using the mmkin function from the mkin +package. In a first step, constant variance is assumed. Convergence is +checked with the status function. ++deg_mods <- c("SFO", "FOMC", "DFOP", "HS") +f_sep_const <- mmkin( + deg_mods, + dmta_ds, + error_model = "const", + quiet = TRUE) + +status(f_sep_const) |> kable() + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Calke Borstel Flaach BBA 2.2 BBA 2.3 Elliot SFO OK OK OK OK OK OK FOMC OK OK OK OK OK OK DFOP OK OK OK OK OK OK HS OK OK OK C OK OK +In the table above, OK indicates convergence, and C indicates failure +to converge. All separate fits with constant variance converged, with +the sole exception of the HS fit to the BBA 2.2 data. To prepare for +fitting NLHM using the two-component error model, the separate fits are +updated assuming two-component error. ++f_sep_tc <- update(f_sep_const, error_model = "tc") +status(f_sep_tc) |> kable() + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + Calke Borstel Flaach BBA 2.2 BBA 2.3 Elliot SFO OK OK OK OK OK OK FOMC OK OK OK OK C OK DFOP OK OK C OK C OK HS OK C OK OK OK OK +Using the two-component error model, the one fit that did not +converge with constant variance did converge, but other non-SFO fits +failed to converge. + + +Hierarchichal model fits + +The following code fits eight versions of hierarchical models to the +data, using SFO, FOMC, DFOP and HS for the parent compound, and using +either constant variance or two-component error for the error model. The +default parameter distribution model in mkin allows for variation of all +degradation parameters across the assumed population of soils. In other +words, each degradation parameter is associated with a random effect as +a first step. The mhmkin function makes it possible to fit +all eight versions in parallel (given a sufficient number of computing +cores being available) to save execution time. +Convergence plots and summaries for these fits are shown in the +appendix. ++f_saem <- mhmkin(list(f_sep_const, f_sep_tc), transformations = "saemix") +The output of the status function shows that all fits +terminated successfully. ++status(f_saem) |> kable() + + + + + + + + + + + + + + + + + + + + + + + + + + + + + const tc SFO OK OK FOMC OK OK DFOP OK OK HS OK OK +The AIC and BIC values show that the biphasic models DFOP and HS give +the best fits. ++anova(f_saem) |> kable(digits = 1) + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + npar AIC BIC Lik SFO const 5 796.3 795.3 -393.2 SFO tc 6 798.3 797.1 -393.2 FOMC const 7 734.2 732.7 -360.1 FOMC tc 8 720.4 718.8 -352.2 DFOP const 9 711.8 710.0 -346.9 HS const 9 714.0 712.1 -348.0 DFOP tc 10 665.5 663.4 -322.8 HS tc 10 667.1 665.0 -323.6 +The DFOP model is preferred here, as it has a better mechanistic +basis for batch experiments with constant incubation conditions. Also, +it shows the lowest AIC and BIC values in the first set of fits when +combined with the two-component error model. Therefore, the DFOP model +was selected for further refinements of the fits with the aim to make +the model fully identifiable. + +Parameter identifiability based on the Fisher Information +Matrix + +Using the illparms function, ill-defined statistical +model parameters such as standard deviations of the degradation +parameters in the population and error model parameters can be +found. ++illparms(f_saem) |> kable() + + + + + + + + + + + + + + + + + + + + + + + + + + + + + const tc SFO b.1 FOMC sd(DMTA_0) DFOP sd(k2) sd(k2) HS sd(tb) +According to the illparms function, the fitted standard +deviation of the second kinetic rate constant k2 is +ill-defined in both DFOP fits. This suggests that different values would +be obtained for this standard deviation when using different starting +values. +The thus identified overparameterisation is addressed by removing the +random effect for k2 from the parameter model. ++f_saem_dfop_tc_no_ranef_k2 <- update(f_saem[["DFOP", "tc"]], + no_random_effect = "k2") +For the resulting fit, it is checked whether there are still +ill-defined parameters, ++illparms(f_saem_dfop_tc_no_ranef_k2) +which is not the case. Below, the refined model is compared with the +previous best model. The model without random effect for k2 +is a reduced version of the previous model. Therefore, the models are +nested and can be compared using the likelihood ratio test. This is +achieved with the argument test = TRUE to the +anova function. ++anova(f_saem[["DFOP", "tc"]], f_saem_dfop_tc_no_ranef_k2, test = TRUE) |> + kable(format.args = list(digits = 4)) + ++++++++++ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + npar AIC BIC Lik Chisq Df Pr(>Chisq) f_saem_dfop_tc_no_ranef_k2 9 663.8 661.9 -322.9 NA NA NA f_saem[[“DFOP”, “tc”]] 10 665.5 663.4 -322.8 0.2809 1 0.5961 +The AIC and BIC criteria are lower after removal of the ill-defined +random effect for k2. The p value of the likelihood ratio +test is much greater than 0.05, indicating that the model with the +higher likelihood (here the model with random effects for all +degradation parameters f_saem[["DFOP", "tc"]]) does not fit +significantly better than the model with the lower likelihood (the +reduced model f_saem_dfop_tc_no_ranef_k2). +Therefore, AIC, BIC and likelihood ratio test suggest the use of the +reduced model. +The convergence of the fit is checked visually. + + +Convergence plot for the NLHM DFOP fit with two-component error and +without a random effect on ‘k2’ + + +All parameters appear to have converged to a satisfactory degree. The +final fit is plotted using the plot method from the mkin package. ++plot(f_saem_dfop_tc_no_ranef_k2) + + +Plot of the final NLHM DFOP fit + + +Finally, a summary report of the fit is produced. ++summary(f_saem_dfop_tc_no_ranef_k2) +saemix version used for fitting: 3.2 +mkin version used for pre-fitting: 1.2.2 +R version used for fitting: 4.2.2 +Date of fit: Thu Jan 5 08:19:13 2023 +Date of summary: Thu Jan 5 08:19:13 2023 + +Equations: +d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * + time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) + * DMTA + +Data: +155 observations of 1 variable(s) grouped in 6 datasets + +Model predictions using solution type analytical + +Fitted in 4.075 s +Using 300, 100 iterations and 9 chains + +Variance model: Two-component variance function + +Starting values for degradation parameters: + DMTA_0 k1 k2 g +98.759266 0.087034 0.009933 0.930827 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + DMTA_0 k1 k2 g +DMTA_0 98.76 0 0 0 +k1 0.00 1 0 0 +k2 0.00 0 1 0 +g 0.00 0 0 1 + +Starting values for error model parameters: +a.1 b.1 + 1 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 663.8 661.9 -322.9 + +Optimised parameters: + est. lower upper +DMTA_0 98.228939 96.285869 100.17201 +k1 0.064063 0.033477 0.09465 +k2 0.008297 0.005824 0.01077 +g 0.953821 0.914328 0.99331 +a.1 1.068479 0.869538 1.26742 +b.1 0.029424 0.022406 0.03644 +SD.DMTA_0 2.030437 0.404824 3.65605 +SD.k1 0.594692 0.256660 0.93272 +SD.g 1.006754 0.361327 1.65218 + +Correlation: + DMTA_0 k1 k2 +k1 0.0218 +k2 0.0556 0.0355 +g -0.0516 -0.0284 -0.2800 + +Random effects: + est. lower upper +SD.DMTA_0 2.0304 0.4048 3.6560 +SD.k1 0.5947 0.2567 0.9327 +SD.g 1.0068 0.3613 1.6522 + +Variance model: + est. lower upper +a.1 1.06848 0.86954 1.26742 +b.1 0.02942 0.02241 0.03644 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +DMTA 11.45 41.4 12.46 10.82 83.54 + + +Alternative check of parameter identifiability + +The parameter check used in the illparms function is +based on a quadratic approximation of the likelihood surface near its +optimum, which is calculated using the Fisher Information Matrix (FIM). +An alternative way to check parameter identifiability based on a +multistart approach has recently been implemented in mkin. +The graph below shows boxplots of the parameters obtained in 50 runs +of the saem algorithm with different parameter combinations, sampled +from the range of the parameters obtained for the individual datasets +fitted separately using nonlinear regression. ++f_saem_dfop_tc_multi <- multistart(f_saem[["DFOP", "tc"]], n = 50, cores = 15) ++par(mar = c(6.1, 4.1, 2.1, 2.1)) +parplot(f_saem_dfop_tc_multi, lpos = "bottomright", ylim = c(0.3, 10), las = 2) + + +Scaled parameters from the multistart runs, full model + + +The graph clearly confirms the lack of identifiability of the +variance of k2 in the full model. The overparameterisation +of the model also indicates a lack of identifiability of the variance of +parameter g. +The parameter boxplots of the multistart runs with the reduced model +shown below indicate that all runs give similar results, regardless of +the starting parameters. ++f_saem_dfop_tc_no_ranef_k2_multi <- multistart(f_saem_dfop_tc_no_ranef_k2, + n = 50, cores = 15) ++par(mar = c(6.1, 4.1, 2.1, 2.1)) +parplot(f_saem_dfop_tc_no_ranef_k2_multi, ylim = c(0.5, 2), las = 2, + lpos = "bottomright") + + +Scaled parameters from the multistart runs, reduced model + + +When only the parameters of the top 25% of the fits are shown (based +on a feature introduced in mkin 1.2.2 currently under development), the +scatter is even less as shown below. ++par(mar = c(6.1, 4.1, 2.1, 2.1)) +parplot(f_saem_dfop_tc_no_ranef_k2_multi, ylim = c(0.5, 2), las = 2, llquant = 0.25, + lpos = "bottomright") + + +Scaled parameters from the multistart runs, reduced model, fits with the +top 25% likelihood values + + + + + +Conclusions + +Fitting the four parent degradation models SFO, FOMC, DFOP and HS as +part of hierarchical model fits with two different error models and +normal distributions of the transformed degradation parameters works +without technical problems. The biphasic models DFOP and HS gave the +best fit to the data, but the default parameter distribution model was +not fully identifiable. Removing the random effect for the second +kinetic rate constant of the DFOP model resulted in a reduced model that +was fully identifiable and showed the lowest values for the model +selection criteria AIC and BIC. The reliability of the identification of +all model parameters was confirmed using multiple starting values. + + +Appendix + + +Hierarchical model fit listings + + +Hierarchical mkin fit of the SFO model with error model const + + +saemix version used for fitting: 3.2 +mkin version used for pre-fitting: 1.2.2 +R version used for fitting: 4.2.2 +Date of fit: Thu Jan 5 08:19:06 2023 +Date of summary: Thu Jan 5 08:20:11 2023 + +Equations: +d_DMTA/dt = - k_DMTA * DMTA + +Data: +155 observations of 1 variable(s) grouped in 6 datasets + +Model predictions using solution type analytical + +Fitted in 1.09 s +Using 300, 100 iterations and 9 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + DMTA_0 k_DMTA +97.2953 0.0566 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + DMTA_0 k_DMTA +DMTA_0 97.3 0 +k_DMTA 0.0 1 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 796.3 795.3 -393.2 + +Optimised parameters: + est. lower upper +DMTA_0 97.28130 95.71113 98.8515 +k_DMTA 0.05665 0.02909 0.0842 +a.1 2.66442 2.35579 2.9731 +SD.DMTA_0 1.54776 0.15447 2.9411 +SD.k_DMTA 0.60690 0.26248 0.9513 + +Correlation: + DMTA_0 +k_DMTA 0.0168 + +Random effects: + est. lower upper +SD.DMTA_0 1.5478 0.1545 2.9411 +SD.k_DMTA 0.6069 0.2625 0.9513 + +Variance model: + est. lower upper +a.1 2.664 2.356 2.973 + +Estimated disappearance times: + DT50 DT90 +DMTA 12.24 40.65 + + + + +Hierarchical mkin fit of the SFO model with error model tc + + +saemix version used for fitting: 3.2 +mkin version used for pre-fitting: 1.2.2 +R version used for fitting: 4.2.2 +Date of fit: Thu Jan 5 08:19:07 2023 +Date of summary: Thu Jan 5 08:20:11 2023 + +Equations: +d_DMTA/dt = - k_DMTA * DMTA + +Data: +155 observations of 1 variable(s) grouped in 6 datasets + +Model predictions using solution type analytical + +Fitted in 2.441 s +Using 300, 100 iterations and 9 chains + +Variance model: Two-component variance function + +Starting values for degradation parameters: + DMTA_0 k_DMTA +96.99175 0.05603 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + DMTA_0 k_DMTA +DMTA_0 96.99 0 +k_DMTA 0.00 1 + +Starting values for error model parameters: +a.1 b.1 + 1 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 798.3 797.1 -393.2 + +Optimised parameters: + est. lower upper +DMTA_0 97.271822 95.703157 98.84049 +k_DMTA 0.056638 0.029110 0.08417 +a.1 2.660081 2.230398 3.08976 +b.1 0.001665 -0.006911 0.01024 +SD.DMTA_0 1.545520 0.145035 2.94601 +SD.k_DMTA 0.606422 0.262274 0.95057 + +Correlation: + DMTA_0 +k_DMTA 0.0169 + +Random effects: + est. lower upper +SD.DMTA_0 1.5455 0.1450 2.9460 +SD.k_DMTA 0.6064 0.2623 0.9506 + +Variance model: + est. lower upper +a.1 2.660081 2.230398 3.08976 +b.1 0.001665 -0.006911 0.01024 + +Estimated disappearance times: + DT50 DT90 +DMTA 12.24 40.65 + + + + +Hierarchical mkin fit of the FOMC model with error model const + + +saemix version used for fitting: 3.2 +mkin version used for pre-fitting: 1.2.2 +R version used for fitting: 4.2.2 +Date of fit: Thu Jan 5 08:19:06 2023 +Date of summary: Thu Jan 5 08:20:11 2023 + +Equations: +d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA + +Data: +155 observations of 1 variable(s) grouped in 6 datasets + +Model predictions using solution type analytical + +Fitted in 1.156 s +Using 300, 100 iterations and 9 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + DMTA_0 alpha beta + 98.292 9.909 156.341 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + DMTA_0 alpha beta +DMTA_0 98.29 0 0 +alpha 0.00 1 0 +beta 0.00 0 1 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 734.2 732.7 -360.1 + +Optimised parameters: + est. lower upper +DMTA_0 98.3435 96.9033 99.784 +alpha 7.2007 2.5889 11.812 +beta 112.8746 34.8816 190.868 +a.1 2.0459 1.8054 2.286 +SD.DMTA_0 1.4795 0.2717 2.687 +SD.alpha 0.6396 0.1509 1.128 +SD.beta 0.6874 0.1587 1.216 + +Correlation: + DMTA_0 alpha +alpha -0.1125 +beta -0.1227 0.3632 + +Random effects: + est. lower upper +SD.DMTA_0 1.4795 0.2717 2.687 +SD.alpha 0.6396 0.1509 1.128 +SD.beta 0.6874 0.1587 1.216 + +Variance model: + est. lower upper +a.1 2.046 1.805 2.286 + +Estimated disappearance times: + DT50 DT90 DT50back +DMTA 11.41 42.53 12.8 + + + + +Hierarchical mkin fit of the FOMC model with error model tc + + +saemix version used for fitting: 3.2 +mkin version used for pre-fitting: 1.2.2 +R version used for fitting: 4.2.2 +Date of fit: Thu Jan 5 08:19:07 2023 +Date of summary: Thu Jan 5 08:20:11 2023 + +Equations: +d_DMTA/dt = - (alpha/beta) * 1/((time/beta) + 1) * DMTA + +Data: +155 observations of 1 variable(s) grouped in 6 datasets + +Model predictions using solution type analytical + +Fitted in 2.729 s +Using 300, 100 iterations and 9 chains + +Variance model: Two-component variance function + +Starting values for degradation parameters: +DMTA_0 alpha beta +98.772 4.663 92.597 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + DMTA_0 alpha beta +DMTA_0 98.77 0 0 +alpha 0.00 1 0 +beta 0.00 0 1 + +Starting values for error model parameters: +a.1 b.1 + 1 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 720.4 718.8 -352.2 + +Optimised parameters: + est. lower upper +DMTA_0 98.99136 97.26011 100.72261 +alpha 5.86312 2.57485 9.15138 +beta 88.55571 29.20889 147.90254 +a.1 1.51063 1.24384 1.77741 +b.1 0.02824 0.02040 0.03609 +SD.DMTA_0 1.57436 -0.04867 3.19739 +SD.alpha 0.59871 0.17132 1.02611 +SD.beta 0.72994 0.22849 1.23139 + +Correlation: + DMTA_0 alpha +alpha -0.1363 +beta -0.1414 0.2542 + +Random effects: + est. lower upper +SD.DMTA_0 1.5744 -0.04867 3.197 +SD.alpha 0.5987 0.17132 1.026 +SD.beta 0.7299 0.22849 1.231 + +Variance model: + est. lower upper +a.1 1.51063 1.2438 1.77741 +b.1 0.02824 0.0204 0.03609 + +Estimated disappearance times: + DT50 DT90 DT50back +DMTA 11.11 42.6 12.82 + + + + +Hierarchical mkin fit of the DFOP model with error model const + + +saemix version used for fitting: 3.2 +mkin version used for pre-fitting: 1.2.2 +R version used for fitting: 4.2.2 +Date of fit: Thu Jan 5 08:19:07 2023 +Date of summary: Thu Jan 5 08:20:11 2023 + +Equations: +d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * + time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) + * DMTA + +Data: +155 observations of 1 variable(s) grouped in 6 datasets + +Model predictions using solution type analytical + +Fitted in 2.007 s +Using 300, 100 iterations and 9 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + DMTA_0 k1 k2 g +98.64383 0.09211 0.02999 0.76814 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + DMTA_0 k1 k2 g +DMTA_0 98.64 0 0 0 +k1 0.00 1 0 0 +k2 0.00 0 1 0 +g 0.00 0 0 1 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 711.8 710 -346.9 + +Optimised parameters: + est. lower upper +DMTA_0 98.092481 96.573898 99.61106 +k1 0.062499 0.030336 0.09466 +k2 0.009065 -0.005133 0.02326 +g 0.948967 0.862079 1.03586 +a.1 1.821671 1.604774 2.03857 +SD.DMTA_0 1.677785 0.472066 2.88350 +SD.k1 0.634962 0.270788 0.99914 +SD.k2 1.033498 -0.205994 2.27299 +SD.g 1.710046 0.428642 2.99145 + +Correlation: + DMTA_0 k1 k2 +k1 0.0246 +k2 0.0491 0.0953 +g -0.0552 -0.0889 -0.4795 + +Random effects: + est. lower upper +SD.DMTA_0 1.678 0.4721 2.8835 +SD.k1 0.635 0.2708 0.9991 +SD.k2 1.033 -0.2060 2.2730 +SD.g 1.710 0.4286 2.9914 + +Variance model: + est. lower upper +a.1 1.822 1.605 2.039 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +DMTA 11.79 42.8 12.88 11.09 76.46 + + + + +Hierarchical mkin fit of the DFOP model with error model tc + + +saemix version used for fitting: 3.2 +mkin version used for pre-fitting: 1.2.2 +R version used for fitting: 4.2.2 +Date of fit: Thu Jan 5 08:19:08 2023 +Date of summary: Thu Jan 5 08:20:11 2023 + +Equations: +d_DMTA/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 * + time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time))) + * DMTA + +Data: +155 observations of 1 variable(s) grouped in 6 datasets + +Model predictions using solution type analytical + +Fitted in 3.033 s +Using 300, 100 iterations and 9 chains + +Variance model: Two-component variance function + +Starting values for degradation parameters: + DMTA_0 k1 k2 g +98.759266 0.087034 0.009933 0.930827 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + DMTA_0 k1 k2 g +DMTA_0 98.76 0 0 0 +k1 0.00 1 0 0 +k2 0.00 0 1 0 +g 0.00 0 0 1 + +Starting values for error model parameters: +a.1 b.1 + 1 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 665.5 663.4 -322.8 + +Optimised parameters: + est. lower upper +DMTA_0 98.377019 96.447952 100.30609 +k1 0.064843 0.034607 0.09508 +k2 0.008895 0.006368 0.01142 +g 0.949696 0.903815 0.99558 +a.1 1.065241 0.865754 1.26473 +b.1 0.029340 0.022336 0.03634 +SD.DMTA_0 2.007754 0.387982 3.62753 +SD.k1 0.580473 0.250286 0.91066 +SD.k2 0.006105 -4.920337 4.93255 +SD.g 1.097149 0.412779 1.78152 + +Correlation: + DMTA_0 k1 k2 +k1 0.0235 +k2 0.0595 0.0424 +g -0.0470 -0.0278 -0.2731 + +Random effects: + est. lower upper +SD.DMTA_0 2.007754 0.3880 3.6275 +SD.k1 0.580473 0.2503 0.9107 +SD.k2 0.006105 -4.9203 4.9325 +SD.g 1.097149 0.4128 1.7815 + +Variance model: + est. lower upper +a.1 1.06524 0.86575 1.26473 +b.1 0.02934 0.02234 0.03634 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +DMTA 11.36 41.32 12.44 10.69 77.92 + + + + +Hierarchical mkin fit of the HS model with error model const + + +saemix version used for fitting: 3.2 +mkin version used for pre-fitting: 1.2.2 +R version used for fitting: 4.2.2 +Date of fit: Thu Jan 5 08:19:07 2023 +Date of summary: Thu Jan 5 08:20:11 2023 + +Equations: +d_DMTA/dt = - ifelse(time <= tb, k1, k2) * DMTA + +Data: +155 observations of 1 variable(s) grouped in 6 datasets + +Model predictions using solution type analytical + +Fitted in 2.004 s +Using 300, 100 iterations and 9 chains + +Variance model: Constant variance + +Starting values for degradation parameters: + DMTA_0 k1 k2 tb +97.82176 0.06931 0.02997 11.13945 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + DMTA_0 k1 k2 tb +DMTA_0 97.82 0 0 0 +k1 0.00 1 0 0 +k2 0.00 0 1 0 +tb 0.00 0 0 1 + +Starting values for error model parameters: +a.1 + 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 714 712.1 -348 + +Optimised parameters: + est. lower upper +DMTA_0 98.16102 96.47747 99.84456 +k1 0.07876 0.05261 0.10491 +k2 0.02227 0.01706 0.02747 +tb 13.99089 -7.40049 35.38228 +a.1 1.82305 1.60700 2.03910 +SD.DMTA_0 1.88413 0.56204 3.20622 +SD.k1 0.34292 0.10482 0.58102 +SD.k2 0.19851 0.01718 0.37985 +SD.tb 1.68168 0.58064 2.78272 + +Correlation: + DMTA_0 k1 k2 +k1 0.0142 +k2 0.0001 -0.0025 +tb 0.0165 -0.1256 -0.0301 + +Random effects: + est. lower upper +SD.DMTA_0 1.8841 0.56204 3.2062 +SD.k1 0.3429 0.10482 0.5810 +SD.k2 0.1985 0.01718 0.3798 +SD.tb 1.6817 0.58064 2.7827 + +Variance model: + est. lower upper +a.1 1.823 1.607 2.039 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +DMTA 8.801 67.91 20.44 8.801 31.13 + + + + +Hierarchical mkin fit of the HS model with error model tc + + +saemix version used for fitting: 3.2 +mkin version used for pre-fitting: 1.2.2 +R version used for fitting: 4.2.2 +Date of fit: Thu Jan 5 08:19:08 2023 +Date of summary: Thu Jan 5 08:20:11 2023 + +Equations: +d_DMTA/dt = - ifelse(time <= tb, k1, k2) * DMTA + +Data: +155 observations of 1 variable(s) grouped in 6 datasets + +Model predictions using solution type analytical + +Fitted in 3.287 s +Using 300, 100 iterations and 9 chains + +Variance model: Two-component variance function + +Starting values for degradation parameters: + DMTA_0 k1 k2 tb +98.45190 0.07525 0.02576 19.19375 + +Fixed degradation parameter values: +None + +Starting values for random effects (square root of initial entries in omega): + DMTA_0 k1 k2 tb +DMTA_0 98.45 0 0 0 +k1 0.00 1 0 0 +k2 0.00 0 1 0 +tb 0.00 0 0 1 + +Starting values for error model parameters: +a.1 b.1 + 1 1 + +Results: + +Likelihood computed by importance sampling + AIC BIC logLik + 667.1 665 -323.6 + +Optimised parameters: + est. lower upper +DMTA_0 97.76570 95.81350 99.71791 +k1 0.05855 0.03080 0.08630 +k2 0.02337 0.01664 0.03010 +tb 31.09638 29.38289 32.80987 +a.1 1.08835 0.88590 1.29080 +b.1 0.02964 0.02257 0.03671 +SD.DMTA_0 2.04877 0.42607 3.67147 +SD.k1 0.59166 0.25621 0.92711 +SD.k2 0.30698 0.09561 0.51835 +SD.tb 0.01274 -0.10914 0.13462 + +Correlation: + DMTA_0 k1 k2 +k1 0.0160 +k2 -0.0070 -0.0024 +tb -0.0668 -0.0103 -0.2013 + +Random effects: + est. lower upper +SD.DMTA_0 2.04877 0.42607 3.6715 +SD.k1 0.59166 0.25621 0.9271 +SD.k2 0.30698 0.09561 0.5183 +SD.tb 0.01274 -0.10914 0.1346 + +Variance model: + est. lower upper +a.1 1.08835 0.88590 1.29080 +b.1 0.02964 0.02257 0.03671 + +Estimated disappearance times: + DT50 DT90 DT50back DT50_k1 DT50_k2 +DMTA 11.84 51.71 15.57 11.84 29.66 + + + + + +Hierarchical model convergence plots + + + +Convergence plot for the NLHM SFO fit with constant variance + + + + +Convergence plot for the NLHM SFO fit with two-component error + + + + +Convergence plot for the NLHM FOMC fit with constant variance + + + + +Convergence plot for the NLHM FOMC fit with two-component error + + + + +Convergence plot for the NLHM DFOP fit with constant variance + + + + +Convergence plot for the NLHM DFOP fit with two-component error + + + + +Convergence plot for the NLHM HS fit with constant variance + + + + +Convergence plot for the NLHM HS fit with two-component error + + + + +Session info + +R version 4.2.2 Patched (2022-11-10 r83330) +Platform: x86_64-pc-linux-gnu (64-bit) +Running under: Debian GNU/Linux bookworm/sid + +Matrix products: default +BLAS: /usr/lib/x86_64-linux-gnu/openblas-serial/libblas.so.3 +LAPACK: /usr/lib/x86_64-linux-gnu/openblas-serial/libopenblas-r0.3.21.so + +locale: + [1] LC_CTYPE=de_DE.UTF-8 LC_NUMERIC=C + [3] LC_TIME=de_DE.UTF-8 LC_COLLATE=de_DE.UTF-8 + [5] LC_MONETARY=de_DE.UTF-8 LC_MESSAGES=de_DE.UTF-8 + [7] LC_PAPER=de_DE.UTF-8 LC_NAME=C + [9] LC_ADDRESS=C LC_TELEPHONE=C +[11] LC_MEASUREMENT=de_DE.UTF-8 LC_IDENTIFICATION=C + +attached base packages: +[1] parallel stats graphics grDevices utils datasets methods +[8] base + +other attached packages: +[1] saemix_3.2 npde_3.3 knitr_1.41 mkin_1.2.2 + +loaded via a namespace (and not attached): + [1] deSolve_1.34 zoo_1.8-11 tidyselect_1.2.0 xfun_0.35 + [5] bslib_0.4.2 purrr_1.0.0 lattice_0.20-45 colorspace_2.0-3 + [9] vctrs_0.5.1 generics_0.1.3 htmltools_0.5.4 yaml_2.3.6 +[13] utf8_1.2.2 rlang_1.0.6 pkgdown_2.0.7 jquerylib_0.1.4 +[17] pillar_1.8.1 glue_1.6.2 DBI_1.1.3 lifecycle_1.0.3 +[21] stringr_1.5.0 munsell_0.5.0 gtable_0.3.1 ragg_1.2.4 +[25] codetools_0.2-18 memoise_2.0.1 evaluate_0.19 fastmap_1.1.0 +[29] lmtest_0.9-40 fansi_1.0.3 highr_0.9 scales_1.2.1 +[33] cachem_1.0.6 desc_1.4.2 jsonlite_1.8.4 systemfonts_1.0.4 +[37] fs_1.5.2 textshaping_0.3.6 gridExtra_2.3 ggplot2_3.4.0 +[41] digest_0.6.31 stringi_1.7.8 dplyr_1.0.10 grid_4.2.2 +[45] rprojroot_2.0.3 cli_3.5.0 tools_4.2.2 magrittr_2.0.3 +[49] sass_0.4.4 tibble_3.1.8 pkgconfig_2.0.3 assertthat_0.2.1 +[53] rmarkdown_2.19 R6_2.5.1 mclust_6.0.0 nlme_3.1-161 +[57] compiler_4.2.2 + + + + + + + Contents + + + + + + + + + +Developed by Johannes Ranke. + + + + +Site built with pkgdown 2.0.7. + + + + + + + + + + + + diff --git a/docs/dev/articles/2022_wp_1.1_dmta_parent_files/figure-html/convergence-saem-dfop-const-1.png b/docs/dev/articles/2022_wp_1.1_dmta_parent_files/figure-html/convergence-saem-dfop-const-1.png new file mode 100644 index 00000000..4f87b956 Binary files /dev/null and b/docs/dev/articles/2022_wp_1.1_dmta_parent_files/figure-html/convergence-saem-dfop-const-1.png differ diff --git a/docs/dev/articles/2022_wp_1.1_dmta_parent_files/figure-html/convergence-saem-dfop-tc-1.png b/docs/dev/articles/2022_wp_1.1_dmta_parent_files/figure-html/convergence-saem-dfop-tc-1.png new file mode 100644 index 00000000..58825300 Binary files /dev/null and b/docs/dev/articles/2022_wp_1.1_dmta_parent_files/figure-html/convergence-saem-dfop-tc-1.png differ diff --git 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Binary files /dev/null and b/docs/dev/articles/2022_wp_1.1_dmta_parent_files/figure-html/plot-saem-dfop-tc-no-ranef-k2-1.png differ diff --git a/docs/dev/articles/index.html b/docs/dev/articles/index.html index e04302ef..cd0e315f 100644 --- a/docs/dev/articles/index.html +++ b/docs/dev/articles/index.html @@ -90,7 +90,9 @@ All vignettes - Example evaluation of FOCUS Example Dataset D + Work package 1.1: Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P + + Example evaluation of FOCUS Example Dataset D Example evaluation of FOCUS Laboratory Data L1 to L3 @@ -122,7 +124,7 @@ - Site built with pkgdown 2.0.6. + Site built with pkgdown 2.0.7. diff --git a/docs/dev/authors.html b/docs/dev/authors.html index bd58bc3d..165e2400 100644 --- a/docs/dev/authors.html +++ b/docs/dev/authors.html @@ -113,14 +113,14 @@ - Ranke J (2022). + Ranke J (2023). mkin: Kinetic Evaluation of Chemical Degradation Data. R package version 1.2.2, https://pkgdown.jrwb.de/mkin/. @Manual{, title = {mkin: Kinetic Evaluation of Chemical Degradation Data}, author = {Johannes Ranke}, - year = {2022}, + year = {2023}, note = {R package version 1.2.2}, url = {https://pkgdown.jrwb.de/mkin/}, } @@ -136,7 +136,7 @@ R package version 1.2.2, https://pkgdown - Site built with pkgdown 2.0.6. + Site built with pkgdown 2.0.7. diff --git a/docs/dev/index.html b/docs/dev/index.html index 4723879e..993b8eea 100644 --- a/docs/dev/index.html +++ b/docs/dev/index.html @@ -19,11 +19,11 @@ equation models are solved using automatically generated C functions. Heteroscedasticity can be taken into account using variance by variable or two-component error models as described by Ranke and Meinecke (2018) - <doi:10.3390/environments6120124>. Interfaces to several nonlinear - mixed-effects model packages are available, some of which are described by - Ranke et al. (2021) <doi:10.3390/environments8080071>. Please note that no - warranty is implied for correctness of results or fitness for a particular - purpose."> + <doi:10.3390/environments6120124>. Hierarchical degradation models can + be fitted using nonlinear mixed-effects model packages as a backend as + described by Ranke et al. (2021) <doi:10.3390/environments8080071>. Please + note that no warranty is implied for correctness of results or fitness for a + particular purpose."> Hierarchical kinetics template — hierarchical_kinetics • mkin + + + + + + + + + mkin + 1.2.2 + + + + + + Functions and data + + + + Articles + + + + + Introduction to mkin + + + Example evaluation of FOCUS Example Dataset D + + + Example evaluation of FOCUS Laboratory Data L1 to L3 + + + Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models + + + Short demo of the multistart method + + + Performance benefit by using compiled model definitions in mkin + + + Example evaluation of FOCUS Example Dataset Z + + + Calculation of time weighted average concentrations with mkin + + + Example evaluation of NAFTA SOP Attachment examples + + + Benchmark timings for mkin + + + Benchmark timings for saem.mmkin + + + + News + + + + + + + + + + + + + + + + + Hierarchical kinetics template + Source: R/hierarchical_kinetics.R + hierarchical_kinetics.Rd + + + + R markdown format for setting up hierarchical kinetics based on a template +provided with the mkin package. + + + + hierarchical_kinetics(..., keep_tex = FALSE) + + + + Arguments + ... +Arguments to rmarkdown::pdf_document + + +keep_tex +Keep the intermediate tex file used in the conversion to PDF + + + + Value + + +R Markdown output format to pass to +render + + + + + + Examples + +# \dontrun{ +library(rmarkdown) +draft("example_analysis.rmd", template = "hierarchical_kinetics", package = "mkin") +# } + + + + + + Contents + + + + + + Developed by Johannes Ranke. + + + + Site built with pkgdown 2.0.7. + + + + + + + + + + + diff --git a/docs/dev/reference/index.html b/docs/dev/reference/index.html index 794126cf..525551fd 100644 --- a/docs/dev/reference/index.html +++ b/docs/dev/reference/index.html @@ -195,6 +195,10 @@ of an mmkin object Create and work with nonlinear hierarchical models + hierarchical_kinetics() + + Hierarchical kinetics template + read_spreadsheet() Read datasets and relevant meta information from a spreadsheet file @@ -356,9 +360,9 @@ degradation models and one or more error models - tex_listing() + summary_listing() tex_listing() html_listing() - Wrap the output of a summary function in tex listing environment + Display the output of a summary function according to the output format f_time_norm_focus() @@ -493,7 +497,7 @@ kinetic models fitted with mkinfit - Site built with pkgdown 2.0.6. + Site built with pkgdown 2.0.7. diff --git a/docs/dev/reference/mkinmod.html b/docs/dev/reference/mkinmod.html index 251215a7..145dee83 100644 --- a/docs/dev/reference/mkinmod.html +++ b/docs/dev/reference/mkinmod.html @@ -132,7 +132,7 @@ the source compartment. Additionally, mkinsub() has an argument to, specifying names of variables to which a transfer is to be assumed in the model. If the argument use_of_ff is set to "min" -(default) and the model for the compartment is "SFO" or "SFORB", an +and the model for the compartment is "SFO" or "SFORB", an additional mkinsub() argument can be sink = FALSE, effectively fixing the flux to sink to zero. In print.mkinmod, this argument is currently not used. @@ -247,7 +247,7 @@ in the FOCUS and NAFTA guidance documents are used. For kinetic models with more than one observed variable, a symbolic solution of the system of differential equations is included in the resulting mkinmod object in some cases, speeding up the solution. -If a C compiler is found by pkgbuild::has_compiler() and there + If a C compiler is found by pkgbuild::has_compiler() and there is more than one observed variable in the specification, C code is generated for evaluating the differential equations, compiled using inline::cfunction() and added to the resulting mkinmod object. @@ -310,7 +310,7 @@ Evaluating and Calculating Degradation Kinetics in Environmental Media parent = mkinsub("SFO", "m1", full_name = "Test compound"), m1 = mkinsub("SFO", full_name = "Metabolite M1"), name = "SFO_SFO", dll_dir = DLL_dir, unload = TRUE, overwrite = TRUE) -#> Copied DLL from /tmp/RtmpbZbZ8Y/file8c6a9f402f42.so to /home/jranke/.local/share/mkin/SFO_SFO.so +#> Copied DLL from /tmp/RtmpelWAOB/fileb43c31a25a86.so to /home/jranke/.local/share/mkin/SFO_SFO.so # Now we can save the model and restore it in a new session saveRDS(SFO_SFO.2, file = "~/SFO_SFO.rds") # Terminate the R session here if you would like to check, and then do @@ -363,7 +363,7 @@ Evaluating and Calculating Degradation Kinetics in Environmental Media #> }) #> return(predicted) #> } -#> <environment: 0x55556029f678> +#> <environment: 0x55555f013820> # If we have several parallel metabolites # (compare tests/testthat/test_synthetic_data_for_UBA_2014.R) @@ -392,7 +392,7 @@ Evaluating and Calculating Degradation Kinetics in Environmental Media - Site built with pkgdown 2.0.6. + Site built with pkgdown 2.0.7. diff --git a/docs/dev/reference/summary_listing.html b/docs/dev/reference/summary_listing.html new file mode 100644 index 00000000..876412cc --- /dev/null +++ b/docs/dev/reference/summary_listing.html @@ -0,0 +1,147 @@ + +Display the output of a summary function according to the output format — summary_listing • mkin + + + + + + + + + mkin + 1.2.2 + + + + + + Functions and data + + + + Articles + + + + + Introduction to mkin + + + Example evaluation of FOCUS Example Dataset D + + + Example evaluation of FOCUS Laboratory Data L1 to L3 + + + Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models + + + Short demo of the multistart method + + + Performance benefit by using compiled model definitions in mkin + + + Example evaluation of FOCUS Example Dataset Z + + + Calculation of time weighted average concentrations with mkin + + + Example evaluation of NAFTA SOP Attachment examples + + + Benchmark timings for mkin + + + Benchmark timings for saem.mmkin + + + + News + + + + + + + + + + + + + + + + + Display the output of a summary function according to the output format + Source: R/summary_listing.R + summary_listing.Rd + + + + This function is intended for use in a R markdown code chunk with the chunk +option results = "asis". + + + + summary_listing(object, caption = NULL, label = NULL, clearpage = TRUE) + +tex_listing(object, caption = NULL, label = NULL, clearpage = TRUE) + +html_listing(object, caption = NULL) + + + + Arguments + object +The object for which the summary is to be listed + + +caption +An optional caption + + +label +An optional label, ignored in html output + + +clearpage +Should a new page be started after the listing? Ignored in html output + + + + + + Contents + + + + + + Developed by Johannes Ranke. + + + + Site built with pkgdown 2.0.7. + + + + + + + + + + + diff --git a/docs/dev/sitemap.xml b/docs/dev/sitemap.xml index 06f56c5d..6e51371c 100644 --- a/docs/dev/sitemap.xml +++ b/docs/dev/sitemap.xml @@ -3,6 +3,9 @@ https://pkgdown.jrwb.de/mkin/404.html + + https://pkgdown.jrwb.de/mkin/articles/2022_wp_1.1_dmta_parent.html + https://pkgdown.jrwb.de/mkin/articles/FOCUS_D.html @@ -138,6 +141,9 @@ https://pkgdown.jrwb.de/mkin/reference/get_deg_func.html + + https://pkgdown.jrwb.de/mkin/reference/hierarchical_kinetics.html + https://pkgdown.jrwb.de/mkin/reference/illparms.html @@ -306,6 +312,9 @@ https://pkgdown.jrwb.de/mkin/reference/summary.saem.mmkin.html + + https://pkgdown.jrwb.de/mkin/reference/summary_listing.html + https://pkgdown.jrwb.de/mkin/reference/synthetic_data_for_UBA_2014.html diff --git a/inst/testdata/cyantraniliprole_soil_efsa_2014.xlsx b/inst/testdata/cyantraniliprole_soil_efsa_2014.xlsx new file mode 100644 index 00000000..3252fdf1 Binary files /dev/null and b/inst/testdata/cyantraniliprole_soil_efsa_2014.xlsx differ diff --git a/log/check.log b/log/check.log index aec61e33..a81475d9 100644 --- a/log/check.log +++ b/log/check.log @@ -7,11 +7,28 @@ * checking extension type ... Package * this is package ‘mkin’ version ‘1.2.2’ * package encoding: UTF-8 -* checking CRAN incoming feasibility ... Note_to_CRAN_maintainers +* checking CRAN incoming feasibility ... NOTE Maintainer: ‘Johannes Ranke ’ + +Size of tarball: 6636884 bytes * checking package namespace information ... OK * checking package dependencies ... OK -* checking if this is a source package ... OK +* checking if this is a source package ... NOTE +Found the following apparent object files/libraries: + vignettes/2022_wp_1/cyan_dlls/dfop_path_1.so + vignettes/2022_wp_1/cyan_dlls/dfop_path_2.so + vignettes/2022_wp_1/cyan_dlls/fomc_path_1.so + vignettes/2022_wp_1/cyan_dlls/fomc_path_2.so + vignettes/2022_wp_1/cyan_dlls/hs_path_1.so + vignettes/2022_wp_1/cyan_dlls/sfo_path_1.so + vignettes/2022_wp_1/cyan_dlls/sforb_path_1.so + vignettes/2022_wp_1/cyan_dlls/sforb_path_2.so + vignettes/2022_wp_1/dmta_dlls/m_dfop_path.so + vignettes/2022_wp_1/dmta_dlls/m_fomc_path.so + vignettes/2022_wp_1/dmta_dlls/m_hs_path.so + vignettes/2022_wp_1/dmta_dlls/m_sfo_path.so + vignettes/2022_wp_1/dmta_dlls/m_sforb_path.so +Object files/libraries should not be included in a source package. * checking if there is a namespace ... OK * checking for executable files ... OK * checking for hidden files and directories ... OK @@ -41,14 +58,7 @@ Maintainer: ‘Johannes Ranke ’ * checking S3 generic/method consistency ... OK * checking replacement functions ... OK * checking foreign function calls ... OK -* checking R code for possible problems ... NOTE -parplot.multistart.saem.mmkin: no visible global function definition - for ‘quantile’ -Undefined global functions or variables: - quantile -Consider adding - importFrom("stats", "quantile") -to your NAMESPACE file. +* checking R code for possible problems ... OK * checking Rd files ... OK * checking Rd metadata ... OK * checking Rd line widths ... OK @@ -64,7 +74,7 @@ to your NAMESPACE file. * checking data for ASCII and uncompressed saves ... OK * checking installed files from ‘inst/doc’ ... OK * checking files in ‘vignettes’ ... OK -* checking examples ... [11s/11s] OK +* checking examples ... [10s/10s] OK * checking for unstated dependencies in ‘tests’ ... OK * checking tests ... SKIPPED * checking for unstated dependencies in vignettes ... OK @@ -76,7 +86,7 @@ to your NAMESPACE file. * checking for detritus in the temp directory ... OK * DONE -Status: 1 NOTE +Status: 2 NOTEs See ‘/home/jranke/git/mkin/mkin.Rcheck/00check.log’ for details. diff --git a/man/hierarchical_kinetics.Rd b/man/hierarchical_kinetics.Rd index 4bb82a4c..2a8e211c 100644 --- a/man/hierarchical_kinetics.Rd +++ b/man/hierarchical_kinetics.Rd @@ -23,7 +23,7 @@ provided with the mkin package. \dontrun{ library(rmarkdown) -draft("New analysis.rmd", template = "hierarchical_kinetics", package = "mkin") +draft("example_analysis.rmd", template = "hierarchical_kinetics", package = "mkin") } } diff --git a/man/mkinmod.Rd b/man/mkinmod.Rd index 87ce9016..65b5de1a 100644 --- a/man/mkinmod.Rd +++ b/man/mkinmod.Rd @@ -33,7 +33,7 @@ the source compartment. Additionally, \code{\link[=mkinsub]{mkinsub()}} has an argument \code{to}, specifying names of variables to which a transfer is to be assumed in the model. If the argument \code{use_of_ff} is set to "min" -(default) and the model for the compartment is "SFO" or "SFORB", an +and the model for the compartment is "SFO" or "SFORB", an additional \code{\link[=mkinsub]{mkinsub()}} argument can be \code{sink = FALSE}, effectively fixing the flux to sink to zero. In print.mkinmod, this argument is currently not used.} diff --git a/man/summary_listing.Rd b/man/summary_listing.Rd new file mode 100644 index 00000000..995ebd8d --- /dev/null +++ b/man/summary_listing.Rd @@ -0,0 +1,27 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/summary_listing.R +\name{summary_listing} +\alias{summary_listing} +\alias{tex_listing} +\alias{html_listing} +\title{Display the output of a summary function according to the output format} +\usage{ +summary_listing(object, caption = NULL, label = NULL, clearpage = TRUE) + +tex_listing(object, caption = NULL, label = NULL, clearpage = TRUE) + +html_listing(object, caption = NULL) +} +\arguments{ +\item{object}{The object for which the summary is to be listed} + +\item{caption}{An optional caption} + +\item{label}{An optional label, ignored in html output} + +\item{clearpage}{Should a new page be started after the listing? Ignored in html output} +} +\description{ +This function is intended for use in a R markdown code chunk with the chunk +option \code{results = "asis"}. +} diff --git a/man/tex_listing.Rd b/man/tex_listing.Rd deleted file mode 100644 index 2f11d211..00000000 --- a/man/tex_listing.Rd +++ /dev/null @@ -1,21 +0,0 @@ -% Generated by roxygen2: do not edit by hand -% Please edit documentation in R/tex_listing.R -\name{tex_listing} -\alias{tex_listing} -\title{Wrap the output of a summary function in tex listing environment} -\usage{ -tex_listing(object, caption = NULL, label = NULL, clearpage = TRUE) -} -\arguments{ -\item{object}{The object for which the summary is to be listed} - -\item{caption}{An optional caption} - -\item{label}{An optional label} - -\item{clearpage}{Should a new page be started after the listing?} -} -\description{ -This function can be used in a R markdown code chunk with the chunk -option \code{results = "asis"}. -} diff --git a/vignettes/FOCUS_D.html 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Example evaluation of FOCUS Laboratory Data L1 to L3

Johannes Ranke

Last change 18 May 2022 (rebuilt 2022-09-14)

Last change 18 May 2022 (rebuilt 2022-12-06)

Work package 1.1: Testing hierarchical parent +degradation kinetics with residue data on dimethenamid and +dimethenamid-P

Johannes +Ranke

Last change on 5 January +2022, last compiled on 5 Januar 2023

Introduction +

Preprocessing of test data +

Separate evaluations +

Hierarchichal model fits +

Parameter identifiability based on the Fisher Information +Matrix +

Alternative check of parameter identifiability +

Conclusions +

Appendix +

Hierarchical model fit listings +

Hierarchical model convergence plots +

Session info +

All vignettes

Hierarchical kinetics template

Arguments

Value

Examples

Display the output of a summary function according to the output format

Arguments

time	DMTA
0.000000	100.5
0.000000	99.6
1.941295	91.9
1.941295	91.3
6.794534	81.8
6.794534	82.1
13.589067	69.1
13.589067	68.0
27.178135	51.4
27.178135	51.4
56.297565	27.6
56.297565	26.8
86.387643	15.7
86.387643	15.3
115.507073	7.9
115.507073	8.1

time	DMTA
0.0000000	96.5
0.0000000	96.8
0.0000000	97.0
0.6233856	82.9
0.6233856	86.7
0.6233856	87.4
1.8701567	72.8
1.8701567	69.9
1.8701567	71.9
4.3636989	51.4
4.3636989	52.9
4.3636989	48.6
8.7273979	28.5
8.7273979	27.3
8.7273979	27.5
13.0910968	14.8
13.0910968	13.4
13.0910968	14.4
17.4547957	7.7
17.4547957	7.3
17.4547957	8.1
26.1821936	2.0
26.1821936	1.5
26.1821936	1.9
34.9095915	1.3
34.9095915	1.0
34.9095915	1.1
43.6369893	0.9
43.6369893	0.7
43.6369893	0.7
52.3643872	0.6
52.3643872	0.4
52.3643872	0.5
74.8062674	0.4
74.8062674	0.3
74.8062674	0.3

time	DMTA
0.0000000	98.09
0.0000000	98.77
0.7678922	93.52
0.7678922	92.03
2.3036765	88.39
2.3036765	87.18
5.3752452	69.38
5.3752452	71.06
10.7504904	45.21
10.7504904	46.81
16.1257355	30.54
16.1257355	30.07
21.5009807	21.60
21.5009807	20.41
32.2514711	9.10
32.2514711	9.70
43.0019614	6.58
43.0019614	6.31
53.7524518	3.47
53.7524518	3.52
64.5029421	3.40
64.5029421	3.67
91.3791680	1.62
91.3791680	1.62

time	DMTA
0.0000000	99.33
0.0000000	97.44
0.6733938	93.73
0.6733938	93.77
2.0201814	87.84
2.0201814	89.82
4.7137565	71.61
4.7137565	71.42
9.4275131	45.60
9.4275131	45.42
14.1412696	31.12
14.1412696	31.68
18.8550262	23.20
18.8550262	24.13
28.2825393	9.43
28.2825393	9.82
37.7100523	7.08
37.7100523	8.64
47.1375654	4.41
47.1375654	4.78
56.5650785	4.92
56.5650785	5.08
80.1338612	2.13
80.1338612	2.23

time	DMTA
0.000000	97.5
0.000000	100.7
1.228478	86.4
1.228478	88.5
3.685435	69.8
3.685435	77.1
8.599349	59.0
8.599349	54.2
17.198697	31.3
17.198697	33.5
25.798046	19.6
25.798046	20.9
34.397395	13.3
34.397395	15.8
51.596092	6.7
51.596092	8.7
68.794789	8.8
68.794789	8.7
103.192184	6.0
103.192184	4.4
146.188928	3.3
146.188928	2.8
223.583066	1.4
223.583066	1.8
0.000000	93.4
0.000000	103.2
1.228478	89.2
1.228478	86.6
3.685435	78.2
3.685435	78.1
8.599349	55.6
8.599349	53.0
17.198697	33.7
17.198697	33.2
25.798046	20.9
25.798046	19.9
34.397395	18.2
34.397395	12.7
51.596092	7.8
51.596092	9.0
68.794789	11.4
68.794789	9.0
103.192184	3.9
103.192184	4.4
146.188928	2.6
146.188928	3.4
223.583066	2.0
223.583066	1.7

	Calke	Borstel	Flaach	BBA 2.2	BBA 2.3	Elliot
SFO	OK	OK	OK	OK	OK	OK
FOMC	OK	OK	OK	OK	OK	OK
DFOP	OK	OK	OK	OK	OK	OK
HS	OK	OK	OK	C	OK	OK

	npar	AIC	BIC	Lik
SFO const	5	796.3	795.3	-393.2
SFO tc	6	798.3	797.1	-393.2
FOMC const	7	734.2	732.7	-360.1
FOMC tc	8	720.4	718.8	-352.2
DFOP const	9	711.8	710.0	-346.9
HS const	9	714.0	712.1	-348.0
DFOP tc	10	665.5	663.4	-322.8
HS tc	10	667.1	665.0	-323.6

	npar	AIC	BIC	Lik	Chisq	Df	Pr(>Chisq)
f_saem_dfop_tc_no_ranef_k2	9	663.8	661.9	-322.9	NA	NA	NA
f_saem[[“DFOP”, “tc”]]	10	665.5	663.4	-322.8	0.2809	1	0.5961