nlme (version 3.1-1)

BIC.logLik: BIC of a logLik Object

Description

This function calculates the Bayesian information criterion, also known as Schwarz's Bayesian criterion (SBC) for an object inheriting from class logLik, 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. When comparing fitted objects, the smaller the BIC, the better the fit.

Usage

BIC(object)

Arguments

object

an object inheriting from class logLik, usually resulting from applying a logLik method to a fitted model object.

Value

• 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

BIC, logLik, AIC

Examples

data(Orthodont)
fm1 <- lm(distance ~ age, data = Orthodont) 
BIC(logLik(fm1))

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