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Simulate from a fitted dsem model

Usage

# S3 method for class 'dsem'
simulate(
  object,
  nsim = 1,
  seed = NULL,
  variance = c("none", "random", "both"),
  resimulate_gmrf = FALSE,
  ...
)

Arguments

object

Output from dsem

nsim

number of simulated data sets

seed

random seed

variance

whether to ignore uncertainty in fixed and random effects, include estimation uncertainty in random effects, or include estimation uncertainty in both fixed and random effects

resimulate_gmrf

whether to resimulate the GMRF based on estimated or simulated random effects (determined by argument variance)

...

Not used

Value

Simulated data, either from obj$simulate where obj is the compiled TMB object, first simulating a new GMRF and then calling obj$simulate.

Details

This function conducts a parametric bootstrap, i.e., simulates new data conditional upon estimated values for fixed and random effects. The user can optionally simulate new random effects conditional upon their estimated covariance, or simulate new fixed and random effects conditional upon their imprecision.

Note that simulate will have no effect on states x_tj for which there is a measurement and when those measurements are fitted using family="fixed", unless resimulate_gmrf=TRUE. In this latter case, the GMRF is resimulated given estimated path coefficients