BIC {lme4}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*log-likelihood + npar*log(nobs), where npar represents the number of parameters and nobs 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 created by a call to the logLik generic.
... 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 data.frame with rows corresponding to the objects and columns representing the number of parameters in the model (df) and the BIC.

References

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

See Also

logLik, AIC


[Package lme4 version 0.9975-9 Index]