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statsmodels 0.14.0 (+727) statsmodels.tools.eval_measures.aic

statsmodels.tools.eval_measures.aic¶

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

Akaike information criterion

Parameters:

llf{float, array_like}: value of the loglikelihood
nobsint: number of observations
df_modelwcint: number of parameters including constant

Returns:

aicfloat: information criterion

References

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