code: def bic(llf, nobs, df_modelwc):
      """
      Bayesian information criterion (BIC) or Schwarz criterion
  
      Parameters
      ----------
      llf : {float, array_like}
          value of the loglikelihood
      nobs : int
          number of observations
      df_modelwc : int
          number of parameters including constant
  
      Returns
      -------
      bic : float
          information criterion
  
      References
      ----------
      https://en.wikipedia.org/wiki/Bayesian_information_criterion
      """
      return -2.0 * llf + np.log(nobs) * df_modelwc
  
imports: import numpy
  from statsmodels.tools.validation import array_like
label_desc: Use image node_id 14 for calling a global function with example usage: bic(llf, nobs, df_modelwc) and returns: unknown