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-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/summary.saem.mmkin.R
-\name{summary.saem.mmkin}
-\alias{summary.saem.mmkin}
-\alias{print.summary.saem.mmkin}
-\title{Summary method for class "saem.mmkin"}
-\usage{
-\method{summary}{saem.mmkin}(object, data = FALSE, verbose = FALSE, distimes = TRUE, ...)
-
-\method{print}{summary.saem.mmkin}(x, digits = max(3, getOption("digits") - 3), verbose = x$verbose, ...)
-}
-\arguments{
-\item{object}{an object of class \link{saem.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.saem.mmkin}}
-
-\item{digits}{Number of digits to use for printing}
-}
-\value{
-The summary function returns a list based on the \link[saemix:SaemixObject-class]{saemix::SaemixObject}
-obtained in the fit, with at least the following additional components
-\item{saemixversion, mkinversion, Rversion}{The saemix, 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 saem
-f_mmkin_dfop_sfo <- mmkin(list(dfop_sfo), ds_syn_dfop_sfo,
-  quiet = TRUE, error_model = "tc", cores = 5)
-f_saem_dfop_sfo <- saem(f_mmkin_dfop_sfo)
-summary(f_saem_dfop_sfo, data = TRUE)
-}
-
-}
-\author{
-Johannes Ranke for the mkin specific parts
-saemix authors for the parts inherited from saemix.
-}