Extract the random effects variance covariance matrix

Returns the posterior mean of the variance-covariance matrix/matrices of the random effects in a fitted JointAI object.

Usage

rd_vcov(object, outcome = NULL, start = NULL, end = NULL, thin = NULL,
  exclude_chains = NULL, mess = TRUE, warn = TRUE)

object: object inheriting from class 'JointAI'
outcome: optional; vector of integers giving the indices of the outcomes for which the random effects variance-covariance matrix/matrices should be returned.
start: the first iteration of interest (see window.mcmc)
end: the last iteration of interest (see window.mcmc)
thin: thinning interval (integer; see window.mcmc). For example, thin = 1 (default) will keep the MCMC samples from all iterations; thin = 5 would only keep every 5th iteration.
exclude_chains: optional vector of the index numbers of chains that should be excluded
mess: logical; should messages be given? Default is TRUE.
warn: logical; should warnings be given? Default is TRUE.