GLM model selection {brainGraph}

Model selection for bg_GLM objects

Description

These functions compute the log-likelihood and Akaike's An Information Criterion (AIC) of a bg_GLM object. See logLik.lm and extractAIC for details.

Usage

## S3 method for class 'bg_GLM'
logLik(object, REML = FALSE, ...)

## S3 method for class 'bg_GLM'
extractAIC(fit, scale = 0, k = 2, ...)

Arguments

object, fit

A bg_GLM object

REML

Logical indicating whether to return the restricted log-likelihood. Default: FALSE

...

Unused

scale

Should be left at its default

k

Numeric; the weight of the equivalent degrees of freedom

Details

The functions AIC and BIC will also work for bg_GLM objects because they each call logLik.

Value

logLik returns an object of class logLik with several attributes. extractAIC returns a numeric vector in which the first element is the equivalent degrees of freedom and the remaining are the AIC's for each region