.\" -*- nroff -*- generated from .Rd format
.BG
.FN BIC
.TL
Bayesian Information Criterion
.DN
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.
.CS
BIC(object, ...)
.RA
.AG object
a fitted model object, for which there exists a
`logLik' method to extract the corresponding log-likelihood, or
an object inheriting from class `logLik'.
.OA
.AG ...
optional fitted model objects.
.RT
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.
.SH REFERENCES
Schwarz, G. (1978) "Estimating the Dimension of a Model", Annals of
Statistics, 6, 461-464.
.SA
`logLik', `AIC', `BIC.logLik'
.EX
fm1 <- lm(distance ~ age, data = Orthodont) # no random effects
fm2 <- lme(distance ~ age, data = Orthodont) # random is ~age
BIC(fm1, fm2)
.KW models
.WR
