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-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/saemix.R
-\name{saemix}
-\alias{saemix}
-\alias{saemix.mmkin}
-\alias{saemix_model}
-\alias{saemix_data}
-\title{Create saemix models}
-\usage{
-saemix(model, data, control, ...)
-
-\method{saemix}{mmkin}(
-  model,
-  data,
-  control = list(displayProgress = FALSE, print = FALSE, save = FALSE, save.graphs =
-    FALSE),
-  cores = 1,
-  verbose = FALSE,
-  suppressPlot = TRUE,
-  ...
-)
-
-saemix_model(object, cores = 1, verbose = FALSE, ...)
-
-saemix_data(object, verbose = FALSE, ...)
-}
-\arguments{
-\item{model}{For the default method, this is an \link[saemix:saemixModel]{saemix::saemixModel} object.
-If this is an \link{mmkin} row object, the \link[saemix:saemixModel]{saemix::saemixModel} is created
-internally from the \link{mmkin} object.}
-
-\item{\dots}{Further parameters passed to \link[saemix:saemixData]{saemix::saemixData}
-and \link[saemix:saemixModel]{saemix::saemixModel}.}
-
-\item{cores}{The number of cores to be used for multicore processing using
-\code{\link[parallel:mclapply]{parallel::mclapply()}}. Using more than 1 core is experimental and may
-lead to uncontrolled forking, apparently depending on the BLAS version
-used.}
-
-\item{verbose}{Should we print information about created objects?}
-
-\item{object}{An \link{mmkin} row object containing several fits of the same
-\link{mkinmod} model to different datasets}
-}
-\value{
-An \link[saemix:SaemixObject-class]{saemix::SaemixObject}.
-
-An \link[saemix:SaemixModel-class]{saemix::SaemixModel} object.
-
-An \link[saemix:SaemixData-class]{saemix::SaemixData} object.
-}
-\description{
-The saemix function defined in this package is an S3 generic function
-using \code{\link[saemix:saemix]{saemix::saemix()}} as its method for \link[saemix:SaemixModel-class]{saemix::SaemixModel} objects.
-}
-\details{
-The method for mmkin row objects sets up a nonlinear mixed effects model for
-use with the saemix package. An mmkin row object is essentially a list of
-mkinfit objects that have been obtained by fitting the same model to
-a list of datasets.
-
-Starting values for the fixed effects (population mean parameters, argument psi0 of
-\code{\link[saemix:saemixModel]{saemix::saemixModel()}} are the mean values of the parameters found using
-\link{mmkin}.
-}
-\examples{
-\dontrun{
-# We can load saemix, but should exclude the saemix function
-# as it would mask our generic version of it
-library(saemix, exclude = "saemix")
-ds <- lapply(experimental_data_for_UBA_2019[6:10],
- function(x) subset(x$data[c("name", "time", "value")]))
-names(ds) <- paste("Dataset", 6:10)
-f_mmkin_parent_p0_fixed <- mmkin("FOMC", ds, cores = 1,
-  state.ini = c(parent = 100), fixed_initials = "parent", quiet = TRUE)
-f_saemix_p0_fixed <- saemix(f_mmkin_parent_p0_fixed)
-
-f_mmkin_parent <- mmkin(c("SFO", "FOMC", "DFOP"), ds, quiet = TRUE)
-f_saemix_sfo <- saemix(f_mmkin_parent["SFO", ])
-f_saemix_fomc <- saemix(f_mmkin_parent["FOMC", ])
-f_saemix_dfop <- saemix(f_mmkin_parent["DFOP", ])
-
-# As this returns an SaemixObject, we can use functions from saemix
-compare.saemix(list(f_saemix_sfo, f_saemix_fomc, f_saemix_dfop))
-
-f_mmkin_parent_tc <- update(f_mmkin_parent, error_model = "tc")
-f_saemix_fomc_tc <- saemix(f_mmkin_parent_tc["FOMC", ])
-compare.saemix(list(f_saemix_fomc, f_saemix_fomc_tc))
-
-dfop_sfo <- mkinmod(parent = mkinsub("DFOP", "A1"),
-  A1 = mkinsub("SFO"))
-f_mmkin <- mmkin(list("DFOP-SFO" = dfop_sfo), ds, quiet = TRUE, solution_type = "analytical")
-# This takes about 4 minutes on my system
-f_saemix <- saemix(f_mmkin)
-
-# Using a single core, it takes about 6 minutes, using 10 cores it is slower
-# instead of faster
-f_mmkin_des <- mmkin(list("DFOP-SFO" = dfop_sfo), ds, quiet = TRUE, solution_type = "deSolve")
-f_saemix_des <- saemix(f_mmkin_des, cores = 1)
-compare.saemix(list(f_saemix, f_saemix_des))
-
-}
-}