Corrected Akaike information criterion ($\mathrm{AICc}=\mathrm{AIC}+2k(k+1)/(n-k-1)$)

The corrected Akaike information criterion adds a finite-sample penalty to the Akaike information criterion, where $k$ counts fitted parameters and $n>k+1$. The displayed correction is commonly used for small samples; its exact unbiasedness depends on the model family.