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 $-2 \mbox{log-likelihood} + n_{par}
\log(n_{obs})$, where
$n_{par}$ represents the
number of parameters and $n_{obs}$ the number of
observations in the fitted model.
Usage
BIC(object, ...)
Arguments
object
An object of a suitable class for the BIC to be
calculated - usually a logLik object
created by a call to the logLik generic.
...
Some methods for this generic function may take
additional, optional arguments. At present none do.
Value
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.
References
Schwarz, G. (1978)
Estimating the Dimension of a Model,
Annals of Statistics6, 461--464.