Akaike information criterion for fitted Gaussian AD models

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.

Value

A numeric scalar AIC value.

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.

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)
#> [1] 408.7908