Fit one or more kinetic models with one or more state variables to one or more datasets

Usage

mmkin(models, datasets, cores = round(detectCores()/2), cluster = NULL, ...)

Arguments

models

Either a character vector of shorthand names ("SFO", "FOMC", "DFOP", "HS", "SFORB"), or an optionally named list of mkinmod objects.

datasets

An optionally named list of datasets suitable as observed data for mkinfit.

cores

The number of cores to be used for multicore processing. This is only used when the cluster argument is NULL.

cluster

A cluster as returned by makeCluster to be used for parallel execution.

...

Further arguments that will be passed to mkinfit.

Examples

## Not run: 
# 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]])
# ## End(Not run)

See also

Author