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diff --git a/man/summary.nlmixr.mmkin.Rd b/man/summary.nlmixr.mmkin.Rd deleted file mode 100644 index ab8abd5d..00000000 --- a/man/summary.nlmixr.mmkin.Rd +++ /dev/null @@ -1,103 +0,0 @@ -% 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. -} |