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`

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