BIC.logLik {nlme}R Documentation

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 log-likelihood + npar*log(nobs), where npar represents the number of parameters and nobs 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.
... some methods for this generic use optional arguments. None are used in this method.

Value

a numeric value with the corresponding BIC.

Author(s)

Jose Pinheiro Jose.Pinheiro@pharma.novartis.com and Douglas Bates bates@stat.wisc.edu

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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