BIC {stats4} | R Documentation |
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.
BIC(object, ...)
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.
|
... |
optionally more fitted model objects. |
If just one object is provided, returns a numeric value
with the corresponding BIC; if multiple objects 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.
Schwarz, G. (1978) "Estimating the Dimension of a Model", Annals of Statistics, 6, 461–464.
lm1 <- lm(Fertility ~ . , data = swiss) AIC(lm1) BIC(lm1) ## with two models: lm1. <- update(lm1, . ~ . -Examination) AIC(lm1, lm1.) BIC(lm1, lm1.)