AIC-methods {aod}R Documentation

Methods for Function "AIC" in Package "aod"

Description

Extracts the Akaike information criterion (AIC) from fitted models of formal class “glimML”.

Usage

## S4 method for signature 'glimML':
AIC(object, ..., k = 2)

Arguments

object A fitted model of formal class “glimML” (functions betabin or negbin).
... An optional list of fitted models separated by commas.
k A numeric scalar, with a default value set to 2, thus providing the regular AIC.

Methods

ANY
Generic function: see AIC.
glimML
Extract the AIC from models of formal class “glimML”, fitted by functions betabin and negbin. The AIC is defined as -2*log-likelihood + 2*npar, where npar represents the number of parameters in the fitted model.

References

Burnham, K.P., Anderson, D.R., 2002. Model selection and multimodel inference: a practical information-theoretic approach. New-York, Springer-Verlag, 496 p.

See Also

Check the examples in betabin and see AIC in package stats.


[Package aod version 1.1-1 Index]