The Bayesian information criterion (BIC) or Schwarz information criterion (SIC) is a criterion for model selection in a finite set of models. We prefer the model with the lowest BIC. Its general defenition is1

\text{BIC} = \log N\cdot d - 2\ \text{loglik} ,

where N is the number of data points d is the number of parameters estimated by the model and \text{loglik} is the log of the maximized likelihood function.