This function is used to simulate from the model. It can be called with the estimated parameters (the default), the initial parameters, or with a set of parameters. The original design can be used in the simulations, or a different dataset may be used with the same structure (covariates) as the original design. This function is not yet implemented.
simul.saemix(
saemixObject,
nsim = saemixObject["options"]$nb.sim,
predictions = TRUE,
res.var = TRUE,
uncertainty = FALSE
)an object returned by the saemix function
Number of simulations to perform. Defaults to the nb.simpred element in options
Whether the simulated parameters should be used to compute predictions. Defaults to TRUE
Whether residual variability should be added to the predictions. Defaults to TRUE
Uses uncertainty (currently not implemented). Defaults to FALSE
This function is used to produce Visual Predictive Check graphs, as well as to compute the normalised prediction distribution errors (npde).
Brendel, K, Comets, E, Laffont, C, Laveille, C, Mentre, F. Metrics for external model evaluation with an application to the population pharmacokinetics of gliclazide, Pharmaceutical Research 23 (2006), 2036-2049.
Holford, N. The Visual Predictive Check: superiority to standard diagnostic (Rorschach) plots (Abstract 738), in: 14th Meeting of the Population Approach Group in Europe, Pamplona, Spain, 2005.
SaemixObject,saemix,
saemix.plot.data, saemix.plot.convergence,
saemix.plot.llis, saemix.plot.randeff,
saemix.plot.obsvspred, saemix.plot.fits,
saemix.plot.parcov, saemix.plot.distpsi,
saemix.plot.scatterresiduals, saemix.plot.vpc