Calculate Variance-Covariance Matrix for a Fitted glmmTMB model
# S3 method for glmmTMB
vcov(
object,
full = FALSE,
include_nonest = TRUE,
sandwich = FALSE,
cluster = getGroups(object),
...
)By default (full==FALSE), a list of separate variance-covariance matrices for each model component (conditional, zero-inflation, dispersion). If full==TRUE, a single square variance-covariance matrix for all top-level model parameters (conditional, dispersion, and variance-covariance parameters)
a “glmmTMB” fit
return a full variance-covariance matrix?
include variables that are mapped or dropped due to rank-deficiency? (these will be given variances and covariances of NA)
use the sandwich estimator for the variance-covariance matrix? (this only works for ML fits, but not for REML fits)
grouping factor for the sandwich estimator, only used if sandwich==TRUE.
ignored, for method compatibility