criteria: Compute AIC, AICC, BIC and OSAIC for a given 'plrs' model.

In plrs: Piecewise Linear Regression Splines (PLRS) for the association between DNA copy number and gene expression

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 [e-mail]

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)

plrs documentation built on April 28, 2020, 6:09 p.m.