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diff --git a/R/dimethenamid_2018.R b/R/dimethenamid_2018.R
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--- a/R/dimethenamid_2018.R
+++ b/R/dimethenamid_2018.R
@@ -15,7 +15,55 @@
#' @source Rapporteur Member State Germany, Co-Rapporteur Member State Bulgaria (2018)
#' Renewal Assessment Report Dimethenamid-P Volume 3 - B.8 Environmental fate and behaviour
#' Rev. 2 - November 2017
-#' \href{https://open.efsa.europa.eu}{https://open.efsa.europa.eu/study-inventory/EFSA-Q-2014-00716}
+#' \url{https://open.efsa.europa.eu/study-inventory/EFSA-Q-2014-00716}
#' @examples
#' print(dimethenamid_2018)
+#' dmta_ds <- lapply(1:7, function(i) {
+#' ds_i <- dimethenamid_2018$ds[[i]]$data
+#' ds_i[ds_i$name == "DMTAP", "name"] <- "DMTA"
+#' ds_i$time <- ds_i$time * dimethenamid_2018$f_time_norm[i]
+#' ds_i
+#' })
+#' names(dmta_ds) <- sapply(dimethenamid_2018$ds, function(ds) ds$title)
+#' dmta_ds[["Elliot"]] <- rbind(dmta_ds[["Elliot 1"]], dmta_ds[["Elliot 2"]])
+#' dmta_ds[["Elliot 1"]] <- NULL
+#' dmta_ds[["Elliot 2"]] <- NULL
+#' \dontrun{
+#' dfop_sfo3_plus <- mkinmod(
+#' DMTA = mkinsub("DFOP", c("M23", "M27", "M31")),
+#' M23 = mkinsub("SFO"),
+#' M27 = mkinsub("SFO"),
+#' M31 = mkinsub("SFO", "M27", sink = FALSE),
+#' quiet = TRUE
+#' )
+#' f_dmta_mkin_tc <- mmkin(
+#' list("DFOP-SFO3+" = dfop_sfo3_plus),
+#' dmta_ds, quiet = TRUE, error_model = "tc")
+#' nlmixr_model(f_dmta_mkin_tc)
+#' # The focei fit takes about four minutes on my system
+#' system.time(
+#' f_dmta_nlmixr_focei <- nlmixr(f_dmta_mkin_tc, est = "focei",
+#' control = nlmixr::foceiControl(print = 500))
+#' )
+#' summary(f_dmta_nlmixr_focei)
+#' plot(f_dmta_nlmixr_focei)
+#' # Using saemix takes about 18 minutes
+#' system.time(
+#' f_dmta_saemix <- saem(f_dmta_mkin_tc, test_log_parms = TRUE)
+#' )
+#'
+#' # nlmixr with est = "saem" is pretty fast with default iteration numbers, most
+#' # of the time (about 2.5 minutes) is spent for calculating the log likelihood at the end
+#' # The likelihood calculated for the nlmixr fit is much lower than that found by saemix
+#' # Also, the trace plot and the plot of the individual predictions is not
+#' # convincing for the parent. It seems we are fitting an overparameterised
+#' # model, so the result we get strongly depends on starting parameters and control settings.
+#' system.time(
+#' f_dmta_nlmixr_saem <- nlmixr(f_dmta_mkin_tc, est = "saem",
+#' control = nlmixr::saemControl(print = 500, logLik = TRUE, nmc = 9))
+#' )
+#' traceplot(f_dmta_nlmixr_saem$nm)
+#' summary(f_dmta_nlmixr_saem)
+#' plot(f_dmta_nlmixr_saem)
+#' }
"dimethenamid_2018"

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