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Diffstat (limited to 'vignettes/web_only/dimethenamid_2018.rmd')
| -rw-r--r-- | vignettes/web_only/dimethenamid_2018.rmd | 20 |
1 files changed, 14 insertions, 6 deletions
diff --git a/vignettes/web_only/dimethenamid_2018.rmd b/vignettes/web_only/dimethenamid_2018.rmd index e5c8764d..7679edc4 100644 --- a/vignettes/web_only/dimethenamid_2018.rmd +++ b/vignettes/web_only/dimethenamid_2018.rmd @@ -1,7 +1,7 @@ --- title: Example evaluations of the dimethenamid data from 2018 author: Johannes Ranke -date: Last change 16 September 2021, built on `r format(Sys.Date(), format = "%d %b %Y")` +date: Last change 17 September 2021, built on `r format(Sys.Date(), format = "%d %b %Y")` output: html_document: toc: true @@ -32,7 +32,8 @@ During the preparation of the journal article on nonlinear mixed-effects models in degradation kinetics [@ranke2021] and the analysis of the dimethenamid degradation data analysed therein, a need for a more detailed analysis using not only nlme and saemix, but also nlmixr for fitting the mixed-effects models -was identified. +was identified, as many model variants do not converge when fitted with nlme, +and not all relevant error models can be fitted with saemix. This vignette is an attempt to satisfy this need. @@ -59,7 +60,7 @@ Also, datasets observed in the same soil are merged, resulting in dimethenamid (DMTA) data from six soils. ```{r dimethenamid_data} -library(mkin) +library(mkin, quietly = TRUE) dmta_ds <- lapply(1:7, function(i) { ds_i <- dimethenamid_2018$ds[[i]]$data ds_i[ds_i$name == "DMTAP", "name"] <- "DMTA" @@ -294,9 +295,12 @@ are compared. ```{r AIC_parent_saemix_methods, cache = FALSE} f_parent_saemix_dfop_tc$so <- llgq.saemix(f_parent_saemix_dfop_tc$so) -AIC(f_parent_saemix_dfop_tc$so) -AIC(f_parent_saemix_dfop_tc$so, method = "gq") -AIC(f_parent_saemix_dfop_tc$so, method = "lin") +AIC_parent_saemix_methods <- c( + is = AIC(f_parent_saemix_dfop_tc$so, method = "is"), + gq = AIC(f_parent_saemix_dfop_tc$so, method = "gq"), + lin = AIC(f_parent_saemix_dfop_tc$so, method = "lin") +) +print(AIC_parent_saemix_methods) ``` The AIC values based on importance sampling and Gaussian quadrature are very similar. Using linearisation is known to be less accurate, but still gives a @@ -398,6 +402,8 @@ AIC(f_parent_nlmixr_saem_sfo_const$nm, f_parent_nlmixr_saem_sfo_tc$nm, f_parent_nlmixr_saem_dfop_const$nm, f_parent_nlmixr_saem_dfop_tc$nm) ``` +### Comparison + The following table gives the AIC values obtained with the three packages. ```{r AIC_all, cache = FALSE} @@ -416,6 +422,8 @@ AIC_all <- data.frame( kable(AIC_all) ``` + + # References <!-- vim: set foldmethod=syntax: --> |