% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/bic_gau.R
\name{aic_gau}
\alias{aic_gau}
\title{Akaike information criterion for fitted Gaussian AD models}
\usage{
aic_gau(fit)
}
\arguments{
\item{fit}{A fitted model object returned by \code{\link{fit_gau}}.}
}
\value{
A numeric scalar AIC value.
}
\description{
Computes AIC using the fitted log likelihood and a parameter count that
respects identifiability constraints for the Gaussian antedependence
parameters.
}
\details{
The AIC is computed as:
\deqn{AIC = -2 \times \ell + 2k}
where \eqn{\ell} is the log-likelihood and \eqn{k} is the number of free
parameters.

This function applies to Gaussian AD fits from \code{\link{fit_gau}}.
}
\examples{
set.seed(1)
y <- simulate_gau(n_subjects = 30, n_time = 5, order = 1, phi = 0.3)
fit <- fit_gau(y, order = 1)
aic_gau(fit)
}
