BIC-rateReg-method function

Bayesian Information Criterion (BIC)

BIC,rateReg-method is an S4 class method calculating Bayesian information criterion (BIC) or so-called Schwarz's Bayesian criterion (SBC) for one or several rateReg objects, according to the formula - 2 * log-likelihood + ln(nObs) * nPar, where nPar represents the number of parameters in the fitted model and nObs is the number of observations.

## S4 method for signature 'rateReg'
BIC(object, ...)

Arguments

• object: An object used to dispatch a method.
• ...: More fitted model objects.

Returns

If just one object is provided, a numeric value representing calculated BIC. If multiple objects are provided, a data frame with rows corresponding to the objects and columns df and BIC, where df means degree of freedom, which is the number of parameters in the fitted model.

Details

When comparing models fitted by maximum likelihood to the same data, the smaller the BIC, the better the fit. help(BIC, stats) for other details.

Examples

## See examples given in function rateReg.

See Also

rateReg for model fitting; summary,rateReg-method for summary of a fitted model; AIC,rateReg-method for AIC.