criteria {plrs} | R Documentation

## Compute AIC, AICC, BIC and OSAIC for a given `plrs` model.

### Description

Extract AIC, AICC, BIC and OSAIC from an object of class `plrs-class`.

### Usage

    criteria(obj, crit = "all")

### Arguments

`obj` | object of class `plrs-class`
`crit` | A `character` (vector) among `"aic"`, `"aicc"`, `"bic"`, `"osaic"` or `"all"`.

### Value

A `list` with the following components (if specified):

`aic` | Akaike's information criterion
`aicc` | Small sample correction of AIC
`bic` | Bayesian Information Criterion
`osaic` | One-Sided AIC. See Hughes and King (2003) for more details.

### Author(s)

Gwenael G.R. Leday g.g.r.leday@vu.nl

### References

Hughes, A. W. and King, M. L. (2003). Model selection using AIC in the presence of one-sided information. J Stat Plan Infer, 115(2): 397 411.

### Examples

    # Simulate data
    sim <- plrs.sim(n=80, states=4, sigma=0.5)

    # Fit
    model <- plrs(expr=sim$expr, cghseg=sim$seg, cghcall=sim$cal)

    criteria(model)

[Package plrs version 1.26.0 Index]