statsmodels.tools.eval_measures.bic_sigma

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

Bayesian information criterion (BIC) or Schwarz criterion

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:

bic – information criterion
Return type:

float

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/Bayesian_information_criterion