def aicc(llf, nobs, df_modelwc):
 return (((-2.0) * llf) + (((2.0 * df_modelwc) * nobs) / ((nobs - df_modelwc) - 1.0)))

def aicc ( llf , nobs , df_modelwc ) : return ( ( ( - 2.0 ) * llf ) + ( ( ( 2.0 * df_modelwc ) * nobs ) / ( ( nobs - df_modelwc ) - 1.0 ) ) )
akaike information criterion with small sample correction parameters llf : float value of the loglikelihood nobs : int number of observations df_modelwc : int number of parameters including constant returns aicc : float information criterion references URL#aicc .