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plrs (version 1.12.0)

criteria: 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.

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

Run this code

# 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)

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