Revision bfc623dd645245240f395e6fa3af15d260d380c5 authored by Douglas Bates on 15 August 2006, 00:00:00 UTC, committed by Gabor Csardi on 15 August 2006, 00:00:00 UTC
1 parent 40bc650
BIC.Rd
\name{BIC}
\docType{genericFunction}
\alias{BIC}
\alias{BIC,logLik-method}
\alias{BIC,ANY-method}
\title{Bayesian Information Criterion}
\description{
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 \eqn{-2 \mbox{log-likelihood} + n_{par}
\log(n_{obs})}{-2*log-likelihood + npar*log(nobs)}, where
\eqn{n_{par}}{npar} represents the
number of parameters and \eqn{n_{obs}}{nobs} the number of
observations in the fitted model.
}
\usage{
BIC(object, \dots)
}
\arguments{
\item{object}{An object of a suitable class for the BIC to be
calculated - usually a \code{\link[base]{logLik}} object
created by a call to the \code{\link[base]{logLik}} generic.
}
\item{\dots}{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
\code{data.frame} with rows corresponding to the objects and columns
representing the number of parameters in the model (\code{df}) and the
BIC.
}
\references{
Schwarz, G. (1978)
Estimating the Dimension of a Model,
\emph{Annals of Statistics} \bold{6}, 461--464.
}
\seealso{\code{\link[base]{logLik}}, \code{\link[stats]{AIC}}}
\keyword{models}
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