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
$-2 \mbox{log-likelihood} + n_{par} \log(n_{obs})$, where $n_{par}$ represents the number of
parameters and $n_{obs}$ the number of observations in the
fitted model. When comparing fitted objects, the smaller the BIC, the
better the fit.
Usage
## S3 method for class 'logLik':
BIC(object, \dots)
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.
References
Schwarz, G. (1978) "Estimating the Dimension of a Model", Annals of
Statistics, 6, 461-464.