A note on overfitting properties of KIC and KICcKICc

The Kullback information criterion, KIC and its univariate bias-corrected version, KICcKICc may be viewed as estimators of the expected Kullback–Leibler symmetric divergence. This correspondence examines the overfitting properties of KIC and KICcKICc through the probabilities of overfitting both in finite samples and asymptotically. It is shown that KIC and KICcKICc have much smaller probabilities of overfitting than the Akaike information criterion, AIC, and its bias-corrected version AICcAICc.