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.
if just one object is provided, returns a numeric value with the corresponding BIC; if more than one object 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 package nlme, version 3.1-98. License: GPL (>= 2)