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

nobs : int¶

number of observations

df_modelwc : int¶

number of parameters including constant

Returns:¶

aic – information criterion

Return type:¶

float

References

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