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Simulate new responses from a fitted gllvmTMB model

Source: R/methods-gllvmTMB.R
simulate.gllvmTMB_multi.Rd

Draws nsim new response vectors from a fitted model. By default (condition_on_RE = FALSE) the random effects are redrawn from the fitted covariance and the response is drawn from the fitted family — the unconditional simulation appropriate for a parametric bootstrap. Redraw is not implemented for every tier; a fit using an unhandled tier falls back to conditional simulation with a warning, and intervals derived from it are too narrow. Set condition_on_RE = TRUE for the older conditional behaviour, which reuses the fitted random-effect modes and only adds residual noise.

Usage

# S3 method for class 'gllvmTMB_multi'
simulate(
  object,
  nsim = 1,
  seed = NULL,
  newdata = NULL,
  condition_on_RE = FALSE,
  ...
)

Arguments

object

A fit returned by gllvmTMB().

nsim

Number of replicate response vectors to draw. Default 1.

seed

Optional RNG seed.

newdata

Optional new data frame; if supplied, predictions are computed at newdata and noise is drawn around them. The newdata must contain enough columns to rebuild the fixed-effects design and any random-effect grouping that was active.

condition_on_RE

Logical (default FALSE). When FALSE (the default), random effects are redrawn from the fitted covariance — the unconditional simulation appropriate for parametric bootstrap. Redraw is currently implemented for the rr_B, diag_B, rr_W, diag_W, propto, lv_B, phylo_rr, and diag_species tiers.

Not every tier is covered. A fit using any other active tier — notably the SPDE spatial tier (spde) and the diagonal phylogenetic tier (phylo_diag) — falls back to conditional simulation and emits a one-shot warning naming the unhandled tiers. Because conditional simulation reuses the fitted random- effect modes rather than redrawing them, it understates between-unit variability: intervals derived from it (for example via bootstrap_Sigma()) are too narrow and should not be read as calibrated. Treat the warning as a signal that simulate-based uncertainty is not trustworthy for that fit.

When TRUE, the existing fitted RE modes are reused (the older glmmTMB-style conditional simulation that only adds Gaussian noise on top of fit$report$eta). Forced to TRUE when newdata is supplied (RE modes for unseen levels cannot be redrawn).

...

Currently unused.

Value

A matrix of dimension n_obs x nsim (or nrow(newdata) x nsim when newdata is supplied).