% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/generics.R
\name{vcov.gau_fit}
\alias{vcov.gau_fit}
\title{Variance-Covariance Matrix for Gaussian AD Fits}
\usage{
\method{vcov}{gau_fit}(object, ...)
}
\arguments{
\item{object}{A \code{gau_fit} object.}

\item{...}{Unused.}
}
\value{
A named square matrix of parameter variances (diagonal entries)
and covariances (off-diagonal entries, all zero in the current
implementation).
}
\description{
Returns an approximate variance-covariance matrix for the estimated
parameters of a \code{gau_fit} object.  The matrix is block-diagonal
(asymptotically exact for the Gaussian AD model given the factored
likelihood) with entries derived from the closed-form standard errors
used by \code{\link{ci_gau}}.
}
\examples{
\donttest{
set.seed(1)
y <- simulate_gau(n_subjects = 40, n_time = 5, order = 1, phi = 0.4)
fit <- fit_gau(y, order = 1)
vcov(fit)
}
}
