Akaike information criterion for fitted INAD models

Computes AIC using the fitted log likelihood and a parameter count that respects structural zeros and identifiability constraints.

Usage

aic_inad(fit)

Arguments

fit

A fitted model object returned by fit_inad.

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.

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)
#> [1] 739.6663