statsmodels.tools.eval_measures.aicc_sigma

statsmodels.tools.eval_measures.aicc_sigma(sigma2, nobs, df_modelwc, islog=False)[source]

Akaike information criterion (AIC) with small sample correction

Parameters:
sigma2float

estimate of the residual variance or determinant of Sigma_hat in the multivariate case. If islog is true, then it is assumed that sigma is already log-ed, for example logdetSigma.

nobsint

number of observations

df_modelwcint

number of parameters including constant

Returns:
aiccfloat

information criterion

Notes

A constant has been dropped in comparison to the loglikelihood base information criteria. These should be used to compare for comparable models.

References

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


Last update: Jun 14, 2024