# R: Bayesian Information Criterion

BIC {stats4} | 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 or an object for which a `logLik` method exists.
`...` | Some methods for this generic function may take additional, optional arguments. At present none do.

### Value

Returns 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

`logLik-methods`, `AIC-methods`

### Examples

    lm1 <- lm(Fertility ~ . , data = swiss)
    AIC(lm1)
    BIC(lm1)

[Package stats4 version 2.6.0 Index]