aic_gau: Akaike information criterion for fitted Gaussian AD models

In antedep: Antedependence Models for Longitudinal Data

Akaike information criterion for fitted Gaussian AD models

Description

Computes AIC using the fitted log likelihood and a parameter count that respects identifiability constraints for the Gaussian antedependence parameters.

Usage

aic_gau(fit)

Arguments

fit	A fitted model object returned by fit_gau.

Details

The AIC is computed as:

AIC = -2 \times \ell + 2k

where \ell is the log-likelihood and k is the number of free parameters.

This function applies to Gaussian AD fits from fit_gau.

Value

A numeric scalar AIC value.

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)

antedep documentation built on April 25, 2026, 1:06 a.m.