\name{mmkin} \alias{mmkin} \title{ Fit one or more kinetic models with one or more state variables to one or more datasets } \description{ This function calls \code{\link{mkinfit}} on all combinations of models and datasets specified in its first two arguments. } \usage{ mmkin(models, datasets, cores = round(detectCores()/2), cluster = NULL, ...) } \arguments{ \item{models}{ Either a character vector of shorthand names ("SFO", "FOMC", "DFOP", "HS", "SFORB"), or an optionally named list of \code{\link{mkinmod}} objects. } \item{datasets}{ An optionally named list of datasets suitable as observed data for \code{\link{mkinfit}}. } \item{cores}{ The number of cores to be used for multicore processing. This is only used when the \code{cluster} argument is \code{NULL}. } \item{cluster}{ A cluster as returned by \code{\link{makeCluster}} to be used for parallel execution. } \item{\dots}{ Further arguments that will be passed to \code{\link{mkinfit}}. } } \value{ A matrix of \code{\link{mkinfit}} objects that can be indexed using the model and dataset names as row and column indices. } \seealso{ \code{\link{[.mmkin}} for subsetting, \code{\link{plot.mmkin}} for plotting. } \author{ Johannes Ranke } \examples{ \dontrun{ m_synth_SFO_lin <- mkinmod(parent = list(type = "SFO", to = "M1"), M1 = list(type = "SFO", to = "M2"), M2 = list(type = "SFO"), use_of_ff = "max") m_synth_FOMC_lin <- mkinmod(parent = list(type = "FOMC", to = "M1"), M1 = list(type = "SFO", to = "M2"), M2 = list(type = "SFO"), use_of_ff = "max") models <- list(SFO_lin = m_synth_SFO_lin, FOMC_lin = m_synth_FOMC_lin) datasets <- lapply(synthetic_data_for_UBA_2014[1:3], function(x) x$data) time_default <- system.time(fits <- mmkin(models, datasets)) time_1 <- system.time(fits.1 <- mmkin(models, datasets, cores = 1)) time_default time_1 endpoints(fits[["SFO_lin", 2]]) } } \keyword{ optimize }