Rudimentary support for setting up nlmixr models

- All degradation models are specified as ODE models. This appears to be
fast enough
- Error models are being translated to nlmixr as close to the mkin error
model as possible. When using the 'saem' backend, it appears not to be
possible to use the same error model for more than one observed variable
- No support yet for models with parallel formation of metabolites, where
the ilr transformation is used in mkin per default
- There is a bug in nlmixr which appears to be triggered if the data are
not balanced, see nlmixrdevelopment/nlmixr#530
- There is a print and a plot method, the summary method is not finished

1 files changed, 100 insertions, 0 deletions

diff --git a/man/summary.nlmixr.mmkin.Rd b/man/summary.nlmixr.mmkin.Rd
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+++ b/man/summary.nlmixr.mmkin.Rd
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+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/summary.nlmixr.mmkin.R
+\name{summary.nlmixr.mmkin}
+\alias{summary.nlmixr.mmkin}
+\title{Summary method for class "nlmixr.mmkin"}
+\usage{
+\method{summary}{nlmixr.mmkin}(object, data = FALSE, verbose = FALSE, distimes = TRUE, ...)
+}
+\arguments{
+\item{object}{an object of class \link{nlmix.mmkin}}
+
+\item{data}{logical, indicating whether the full data should be included in
+the summary.}
+
+\item{verbose}{Should the summary be verbose?}
+
+\item{distimes}{logical, indicating whether DT50 and DT90 values should be
+included.}
+
+\item{\dots}{optional arguments passed to methods like \code{print}.}
+
+\item{x}{an object of class \link{summary.nlmix.mmkin}}
+
+\item{digits}{Number of digits to use for printing}
+}
+\value{
+The summary function returns a list obtained in the fit, with at
+least the following additional components
+\item{nlmixrversion, mkinversion, Rversion}{The nlmixr, mkin and R versions used}
+\item{date.fit, date.summary}{The dates where the fit and the summary were
+produced}
+\item{diffs}{The differential equations used in the degradation model}
+\item{use_of_ff}{Was maximum or minimum use made of formation fractions}
+\item{data}{The data}
+\item{confint_trans}{Transformed parameters as used in the optimisation, with confidence intervals}
+\item{confint_back}{Backtransformed parameters, with confidence intervals if available}
+\item{confint_errmod}{Error model parameters with confidence intervals}
+\item{ff}{The estimated formation fractions derived from the fitted
+model.}
+\item{distimes}{The DT50 and DT90 values for each observed variable.}
+\item{SFORB}{If applicable, eigenvalues of SFORB components of the model.}
+The print method is called for its side effect, i.e. printing the summary.
+}
+\description{
+Lists model equations, initial parameter values, optimised parameters
+for fixed effects (population), random effects (deviations from the
+population mean) and residual error model, as well as the resulting
+endpoints such as formation fractions and DT50 values. Optionally
+(default is FALSE), the data are listed in full.
+}
+\examples{
+# Generate five datasets following DFOP-SFO kinetics
+sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
+dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "m1"),
+ m1 = mkinsub("SFO"), quiet = TRUE)
+set.seed(1234)
+k1_in <- rlnorm(5, log(0.1), 0.3)
+k2_in <- rlnorm(5, log(0.02), 0.3)
+g_in <- plogis(rnorm(5, qlogis(0.5), 0.3))
+f_parent_to_m1_in <- plogis(rnorm(5, qlogis(0.3), 0.3))
+k_m1_in <- rlnorm(5, log(0.02), 0.3)
+
+pred_dfop_sfo <- function(k1, k2, g, f_parent_to_m1, k_m1) {
+  mkinpredict(dfop_sfo,
+    c(k1 = k1, k2 = k2, g = g, f_parent_to_m1 = f_parent_to_m1, k_m1 = k_m1),
+    c(parent = 100, m1 = 0),
+    sampling_times)
+}
+
+ds_mean_dfop_sfo <- lapply(1:5, function(i) {
+  mkinpredict(dfop_sfo,
+    c(k1 = k1_in[i], k2 = k2_in[i], g = g_in[i],
+      f_parent_to_m1 = f_parent_to_m1_in[i], k_m1 = k_m1_in[i]),
+    c(parent = 100, m1 = 0),
+    sampling_times)
+})
+names(ds_mean_dfop_sfo) <- paste("ds", 1:5)
+
+ds_syn_dfop_sfo <- lapply(ds_mean_dfop_sfo, function(ds) {
+  add_err(ds,
+    sdfunc = function(value) sqrt(1^2 + value^2 * 0.07^2),
+    n = 1)[[1]]
+})
+
+\dontrun{
+# Evaluate using mmkin and nlmixr
+f_mmkin_dfop_sfo <- mmkin(list(dfop_sfo), ds_syn_dfop_sfo,
+  quiet = TRUE, error_model = "obs", cores = 5)
+f_saemix_dfop_sfo <- mkin::saem(f_mmkin_dfop_sfo)
+f_nlme_dfop_sfo <- mkin::nlme(f_mmkin_dfop_sfo)
+f_nlmixr_dfop_sfo_saem <- nlmixr(f_mmkin_dfop_sfo, est = "saem")
+#f_nlmixr_dfop_sfo_focei <- nlmixr(f_mmkin_dfop_sfo, est = "focei")
+summary(f_nlmixr_dfop_sfo, data = TRUE)
+}
+
+}
+\author{
+Johannes Ranke for the mkin specific parts
+nlmixr authors for the parts inherited from nlmixr.
+}