BIC-rateReg-method: Bayesian Information Criterion (BIC)

In reda: Recurrent Event Data Analysis

Bayesian Information Criterion (BIC)

Description

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.

Usage

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

Arguments

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

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.

Value

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.

See Also

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

Examples

## See examples given in function rateReg.

reda documentation built on July 9, 2022, 1:06 a.m.