vcov: Variance-Covariance Matrix for INLAvaan Models

In INLAvaan: Approximate Bayesian Latent Variable Analysis

Variance-Covariance Matrix for INLAvaan Models

Description

Extract the posterior variance-covariance matrix of model parameters from a fitted INLAvaan model.

Usage

## S4 method for signature 'INLAvaan'
vcov(object, type = c("lavaan", "theta"), ...)

Arguments

object	An object of class INLAvaan.
type	Character. "lavaan" (default) returns the posterior covariance matrix of the model parameters computed from posterior samples (matching lavaan output). "theta" returns the Laplace approximation covariance in the internal parameterisation.
...	Currently unused.

Value

A square numeric matrix.

See Also

summary(), coef(), standardisedsolution()

Examples

HS.model <- "
  visual  =~ x1 + x2 + x3
  textual =~ x4 + x5 + x6
  speed   =~ x7 + x8 + x9
"
utils::data("HolzingerSwineford1939", package = "lavaan")
fit <- acfa(HS.model, HolzingerSwineford1939, std.lv = TRUE, nsamp = 100,
            test = "none", verbose = FALSE)

# Default: posterior covariance of lavaan parameters
vcov(fit)

# Internal parameterisation (Laplace approximation)
vcov(fit, type = "theta")

INLAvaan documentation built on Oct. 2, 2026, 1:07 a.m.