Bayesian information criterion (BIC) (also called the Schwarz Criterion)

An index used as an aid in choosing between competing models. It is defined as

-2L_m + mlnn
where n is the sample size, L_m is the maximized log-likelihood of the model and m is the number of parameters in the model. The index takes into account both the statistical goodness of fit and the number of parameters that have to be estimated to achieve this particular degree of fit, by imposing a penalty for increasing the number of parameters.

In statistics, the Schwarz criterion (also Schwarz information criterion (SIC) or Bayesian information criterion (BIC) or Schwarz-Bayesian information criterion) is an information criterion.
Wikipedia (2005)

"The Schwarz Criterion is a criterion for selecting among formal econometric models."
About, Inc. (2006)

"...the measure BIC = -2lnL + plnn. This form is derived from different points of view by Schwarz (1978), Akaike (1977), and Rissanen (1978)."
Hjorth (1994)