% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/multilevel_fit-class.R
\name{dcvar_multilevel_fit-methods}
\alias{dcvar_multilevel_fit-methods}
\alias{print.dcvar_multilevel_fit}
\alias{summary.dcvar_multilevel_fit}
\alias{coef.dcvar_multilevel_fit}
\alias{plot.dcvar_multilevel_fit}
\title{S3 methods for dcvar_multilevel_fit objects}
\usage{
\method{print}{dcvar_multilevel_fit}(x, ...)

\method{summary}{dcvar_multilevel_fit}(object, ...)

\method{coef}{dcvar_multilevel_fit}(object, ...)

\method{plot}{dcvar_multilevel_fit}(x, type = c("random_effects", "diagnostics"), ...)
}
\arguments{
\item{x, object}{A \code{dcvar_multilevel_fit} object.}

\item{...}{Additional arguments (unused).}

\item{type}{Character; one of \code{"random_effects"}, \code{"diagnostics"}.}
}
\value{
Invisibly returns \code{x}.

A \code{dcvar_multilevel_summary} object (a list).

A named list of posterior means.

A ggplot object.
}
\description{
S3 methods for dcvar_multilevel_fit objects
}
\details{
Unlike single-level models (where \code{coef()} returns \verb{$Phi}), the multilevel
model returns hierarchical parameters:
\describe{
\item{\code{phi_bar}}{Population-mean VAR coefficients (analogous to \code{Phi}
in single-level models, vectorised as phi11, phi12, phi21, phi22).}
\item{\code{tau_phi}}{Between-unit SD of VAR coefficients.}
\item{\code{sigma}}{Innovation SDs.}
\item{\code{rho}}{Copula correlation (constant across units).}
}
Use \code{\link[=random_effects]{random_effects()}} to obtain unit-specific VAR coefficients.
}
\section{Functions}{
\itemize{
\item \code{print(dcvar_multilevel_fit)}: Print a concise overview.

\item \code{summary(dcvar_multilevel_fit)}: Produce a detailed summary.

\item \code{coef(dcvar_multilevel_fit)}: Extract posterior means of
population-level coefficients.

\item \code{plot(dcvar_multilevel_fit)}: Dispatch to a plot type.

}}
