BIC

0th

Percentile

Bayesian Information Criterion

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.

Keywords
models
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

Aliases
  • BIC
  • BIC,logLik-method
  • BIC,ANY-method
Documentation reproduced from package lme4, version 0.99875-8, License: GPL version 2 or later

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