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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:

sigma2 : float

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.

nobs : int

number of observations

df_modelwc : int

number of parameters including constant

Returns:

aicc : float

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

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

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