select.grpregOverlap: Select an value of lambda along a regularization path

In YaohuiZeng/grpregOverlap: Penalized Regression Models with Overlapping Grouped Covariates

Description

The function selects a point along the regularization path of a fitted "grpregOverlap object" according to the AIC, BIC, or GCV criteria.

Usage

select(obj,...)

## S3 method for class 'grpregOverlap'
select(obj, criterion = c("BIC", "AIC", "GCV", "AICc", "EBIC"), 
    df.method = c("default", "active"), smooth = FALSE, ...)

Arguments

obj	A fitted "grpregOverlap" model object.
criterion	The criterion by which to select the regularization parameter. One of "AIC", "BIC", "GCV", "AICc", or "EBIC"; default is "BIC".
df.method	How should effective model parameters be calculated? One of: "active", which counts the number of nonzero coefficients; or "default", which uses the calculated df returned by grpregOverlap. Default is "default".
smooth	Applies a smoother to the information criteria before selecting the optimal value.
...	For S3 method compatibility.

Details

See R Package grpreg for details about the selection criteria as well as the methods for computing degrees of freedom.

Value

A list containing:

lambda	The selected value of the regularization parameter, lambda.
beta	The vector of coefficients at the chosen value of lambda.
beta.latent	The vector of latent coefficients at the chosen value of lambda.
df	The effective number of model parameters at the chosen value of lambda.
IC	A vector of the calculated model selection criteria for each point on the regularization path.

Author(s)

Yaohui Zeng and Patrick Breheny

Maintainer: Yaohui Zeng <[e-mail]>

See Also

grpregOverlap

Examples

## See examples in "grpregOverlap".

YaohuiZeng/grpregOverlap documentation built on Aug. 10, 2020, 3:13 p.m.