statsmodels.tools.eval_measures.aicc

statsmodels.tools.eval_measures.aicc(llf, nobs, df_modelwc)[source]

Akaike information criterion (AIC) with small sample correction

Parameters:
llf{float, array_like}

value of the loglikelihood

nobsint

number of observations

df_modelwcint

number of parameters including constant

Returns:
aiccfloat

information criterion

Notes

Returns +inf if the effective degrees of freedom, defined as nobs - df_modelwc - 1.0, is <= 0.

References

https://en.wikipedia.org/wiki/Akaike_information_criterion#AICc


Last update: Sep 01, 2023