AIC,rateReg-method: Akaike Information Criterion (AIC)
Description
AIC,rateReg-method is an S4 class method calculating
Akaike information criterion (AIC) for one or several
rateReg-class objects, according to the formula
- 2 * log-likelihood + 2 * nPar, where nPar represents the number
of parameters in the fitted model.
Usage
"AIC"(object, ..., k = 2)
Arguments
object
An object used to dispatch a method.
...
Optionally more fitted model objects.
k
An optional numeric value used as the penalty per parameter.
The default k = 2 is the classic AIC.
Value
If just one object is provided, a numeric value representing
calculated AIC.
If multiple objects are provided, a data frame with rows
corresponding to the objects and columns df and AIC,
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 AIC, the better the fit.
help(AIC, stats) for other details.