R: Akaike Information Statistics

summary,aic-method {aod} | R Documentation

## 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.

[Package aod version 1.3 Index]