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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}
-\alias{print.summary.nlmixr.mmkin}
-\title{Summary method for class "nlmixr.mmkin"}
-\usage{
-\method{summary}{nlmixr.mmkin}(object, data = FALSE, verbose = FALSE, distimes = TRUE, ...)
-
-\method{print}{summary.nlmixr.mmkin}(x, digits = max(3, getOption("digits") - 3), verbose = x$verbose, ...)
-}
-\arguments{
-\item{object}{an object of class \link{nlmixr.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.nlmixr.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_back}{Backtransformed parameters, with confidence intervals if available}
-\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 = "tc", 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")
-# The following takes a very long time but gives
-f_nlmixr_dfop_sfo_focei <- nlmixr(f_mmkin_dfop_sfo, est = "focei")
-AIC(f_nlmixr_dfop_sfo_saem$nm, f_nlmixr_dfop_sfo_focei$nm)
-summary(f_nlmixr_dfop_sfo_sfo, data = TRUE)
-}
-
-}
-\author{
-Johannes Ranke for the mkin specific parts
-nlmixr authors for the parts inherited from nlmixr.
-}

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