BIC {stats4}

R Documentation

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 -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 or an object for which a logLik method exists.
...	Some methods for this generic function may take additional, optional arguments. At present none do.

Value

Returns a numeric value with the corresponding BIC.

References

Schwarz, G. (1978) "Estimating the Dimension of a Model", Annals of Statistics, 6, 461-464.

See Also

logLik-methods, AIC-methods

Examples

lm1 <- lm(Fertility ~ . , data = swiss)
AIC(lm1)
BIC(lm1)

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