process.y

A function that checks the response vector y for possible errors.

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.y function

<dl><dt>y</dt>
<dd>The response vector.</dd>
<dt>type</dt>
<dd>A string indicating the type of regression model (linear or binomial).</dd></dl>

Arguments

Process y for a sparse group penalty — process.y

<dl>

<dt>y</dt>
<dd>The response vector.</dd>


<dt>type</dt>
<dd>A string indicating the type of regression model (linear or binomial).</dd>

</dl>

process.y: Process y for a sparse group penalty

Description

Usage

Value

Arguments