Akaike Information Criterion

The Akaike information criterion (AIC) is a criterion for comparing statistical models fitted to the same data. If is the maximized likelihood and is the number of estimated parameters, it is defined by

Among the candidate models, the model with the smallest AIC is preferred. The criterion estimates relative expected information loss, so its numerical value has meaning only in comparison with other models fitted to the same data.