This function calls mkinfit
on all combinations of models and datasets
specified in its first two arguments.
mmkin(models, datasets, cores = round(detectCores()/2), cluster = NULL, ...)
mkinmod
objects.
mkinfit
.
cluster
argument is NULL
.
makeCluster
to be used for parallel
execution.
mkinfit
.
A matrix of mkinfit
objects that can be indexed using the model
and dataset names as row and column indices.
[.mmkin
for subsetting, plot.mmkin
for plotting.
## Not run: ------------------------------------ # m_synth_SFO_lin <- mkinmod(parent = mkinsub("SFO", "M1"), # M1 = mkinsub("SFO", "M2"), # M2 = mkinsub("SFO"), use_of_ff = "max") # # m_synth_FOMC_lin <- mkinmod(parent = mkinsub("FOMC", "M1"), # M1 = mkinsub("SFO", "M2"), # M2 = mkinsub("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) # names(datasets) <- paste("Dataset", 1:3) # # time_default <- system.time(fits.0 <- mmkin(models, datasets)) # time_1 <- system.time(fits.1 <- mmkin(models, datasets, cores = 1)) # # time_default # time_1 # # endpoints(fits[["SFO_lin", 2]]) # # # Plot.mkinfit handles rows or columns of mmkin result objects # plot(fits.0[1, ]) # plot(fits.0[1, ], obs_var = c("M1", "M2")) # plot(fits.0[, 1]) # # Use double brackets to extract a single mkinfit object, which will be plotted # # by plot.mkinfit # plot(fits.0[[1, 1]], sep_obs = TRUE, show_residuals = TRUE, show_errmin = TRUE) # # Plotting with mmkin (single brackets, extracting an mmkin object) does not # # allow to plot the observed variables separately # plot(fits.0[1, 1]) ## ---------------------------------------------