logLik
, according to the formula
2*log-likelihood + 2*npar, where
npar represents the number of parameters in the fitted
model. When comparing fitted objects, the smaller the AIC, the better
the fit.
AIC(object)
logLik
, usually
resulting from applying a
logLik
method to a fitted model
object.
Sakamoto, Y., Ishiguro, M., and Kitagawa G. (1986) "Akaike Information Criterion Statistics", D. Reidel Publishing Company.
fm1 <- lm(distance ~ age, data = Orthodont) AIC(logLik(fm1))