This generic function calculates the Bayesian information criterion, also known as Schwarz's Bayesian criterion (SBC), for one or several fitted model objects for which a log-likelihood value can be obtained, according to the formula -2*log-likelihood + npar*log(nobs), where npar represents the number of parameters and nobs the number of observations in the fitted model.
- An object of a suitable class for the BIC to be calculated - usually a
"logLik"object or an object for which a
- optionally more fitted model objects.
If just one object is provided, returns a numeric value with the corresponding BIC; if multiple objects are provided, returns a
data.frame with rows corresponding to the objects and columns representing the number of parameters in the model (
df) and the BIC.
Schwarz, G. (1978) "Estimating the Dimension of a Model", Annals of Statistics, 6, 461--464.
Documentation reproduced from R 2.12.1. License: GPL-2.