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summary.aic

Akaike Information Statistics


Description

Computes Akaike difference and Akaike weights from an object of formal class “aic”.

Usage

## S4 method for signature 'aic'
summary(object, which = c("AIC", "AICc"))

Arguments

object

An object of formal class “aic”.

which

A character string indicating which information criterion is selected to compute Akaike difference and Akaike weights: either “AIC” or “AICc”.

Methods

summary

The models are ordered according to AIC or AICc and 3 statistics are computed:

- the Akaike difference Δ: the change in AIC (or AICc) between successive (ordered) models,

- the Akaike weight W: when r models are compared, W = exp(-0.5 * Δ) / sum(exp(-0.5 * Δ)),

- the cumulative Akaike weight cum.W: the Akaike weights sum to 1 for the r models which are compared.

References

Burnham, K.P., Anderson, D.R., 2002. Model selection and multimodel inference: a practical information-theoretic approach. New-York, Springer-Verlag, 496 p.
Hurvich, C.M., Tsai, C.-L., 1995. Model selection for extended quasi-likelihood models in small samples. Biometrics, 51 (3): 1077-1084.

See Also

Examples in betabin and AIC in package stats.


aod

Analysis of Overdispersed Data

v1.3.1
GPL (>= 2)
Authors
Matthieu Lesnoff <matthieu.lesnoff@cirad.fr> and Renaud Lancelot <renaud.lancelot@cirad.fr>
Initial release
2012-04-10

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