% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/pmm3_ts_methods.R
\name{vcov,TS3fit-method}
\alias{vcov,TS3fit-method}
\title{Variance-covariance matrix for TS3fit AR models}
\usage{
\S4method{vcov}{TS3fit}(object, ...)
}
\arguments{
\item{object}{TS3fit (or subclass) object}

\item{...}{Additional arguments (not used)}
}
\value{
Numeric covariance matrix (AR models only)
}
\description{
For AR models, returns \eqn{\sigma^2 g_3 (X^\top X)^{-1}} where X is
the lagged design matrix and
\eqn{g_3 = 1 - \gamma_4^{2} / (6 + 9\gamma_4 + \gamma_6)} is the PMM3
efficiency factor (Kunchenko, s = 3 specialised to symmetric
platykurtic innovations). For MA/ARMA/ARIMA models the asymptotic
covariance requires the full Fisher information matrix; use bootstrap
standard errors via \code{\link{ts_pmm2_inference}} on an analogous
PMM2 fit, or refit with \code{\link{ar_pmm3}} on the residual series.
}
