extractAIC.BranchGLM: Extract AIC from BranchGLM Objects

In BranchGLM: Efficient Best Subset Selection for GLMs via Branch and Bound Algorithms

Extract AIC from BranchGLM Objects

Description

Computes the (generalized) Akaike An Information Criterion for BranchGLM objects.

Usage

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

Arguments

fit	a BranchGLM object.
scale	ignored.
k	a non-negative number specifying the ‘weight’ of the equivalent degrees of freedom (= edf) part in the AIC formula.
...	further arguments passed to or from other methods.

Value

A numeric vector of length 2, with first and second elements giving

edf	the ‘equivalent degrees of freedom’ for fit
AIC	the (generalized) Akaike Information Criterion for fit

Examples

Data <- iris
Fit <- BranchGLM(Sepal.Length ~ ., data = Data, family = "gaussian", link = "identity")
extractAIC(Fit)

BranchGLM documentation built on Sept. 28, 2024, 9:07 a.m.