This function calculates the Akaike information criterion for
an object inheriting from class logLik, according to the formula
$-2 \mbox{log-likelihood} + 2 n_{par}$, where
$n_{par}$ represents the number of parameters in the fitted
model. When comparing fitted objects, the smaller the AIC, the better
the fit.
Usage
AIC(object)
Arguments
object
an object inheriting from class logLik, usually
resulting from applying a logLik method to a fitted model
object.
Value
a numeric value with the corresponding AIC.
References
Sakamoto, Y., Ishiguro, M., and Kitagawa G. (1986) "Akaike
Information Criterion Statistics", D. Reidel Publishing Company.