% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/bic_inad.R
\name{aic_inad}
\alias{aic_inad}
\title{Akaike information criterion for fitted INAD models}
\usage{
aic_inad(fit)
}
\arguments{
\item{fit}{A fitted model object returned by \code{\link{fit_inad}}.}
}
\value{
A numeric scalar AIC value.
}
\description{
Computes AIC using the fitted log likelihood and a parameter count that
respects structural zeros and identifiability constraints.
}
\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.
}
\examples{
set.seed(1)
y <- simulate_inad(
  n_subjects = 40,
  n_time = 5,
  order = 1,
  thinning = "binom",
  innovation = "pois",
  alpha = 0.3,
  theta = 2
)
fit <- fit_inad(y, order = 1, thinning = "binom", innovation = "pois", max_iter = 20)
aic_inad(fit)
}
