process.group

A function that checks the group information for possible errors and processes it.

Fits the regularization path of regression models
(linear and logistic) with additively combined penalty terms. All
possible combinations with Least Absolute Shrinkage and Selection Operator (LASSO),
Smoothly Clipped Absolute Deviation (SCAD), Minimax Concave Penalty (MCP) and
Exponential Penalty (EP) are supported. This includes Sparse Group LASSO (SGL),
Sparse Group SCAD (SGS), Sparse Group MCP (SGM) and Sparse Group EP (SGE).
For more information, see Buch, G., Schulz, A., Schmidtmann, I., Strauch, K., & Wild, P. S. (2024) <doi:10.1002/bimj.202200334>.

Gregor Buch

SGPR

Sparse Group Penalized Regression for Bi-Level Variable
Selection

Andreas Schulz

Irene Schmidtmann

Konstantin Strauch

Philipp Wild

process.group function

<dl><dt>group</dt>
<dd>A vector that specifies the group membership of each variable in X.</dd>
<dt>group.weight</dt>
<dd>A vector specifying weights that are multiplied by the group penalty to account for different group sizes.</dd></dl>

Arguments

Process groupings for a sparse group penalty — process.group

<dl>

<dt>group</dt>
<dd>A vector that specifies the group membership of each variable in X.</dd>


<dt>group.weight</dt>
<dd>A vector specifying weights that are multiplied by the group penalty to account for different group sizes.</dd>

</dl>

process.group: Process groupings for a sparse group penalty

Description

Usage

Value

Arguments