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SGPR  

Sparse Group Penalized Regression for Bi-Level Variable Selection
View on CRAN: Click here


Download and install SGPR package within the R console
Install from CRAN:
install.packages("SGPR")

Install from Github:
library("remotes")
install_github("cran/SGPR")

Install by package version:
library("remotes")
install_version("SGPR", "0.1.2")



Attach the package and use:
library("SGPR")
Maintained by
Gregor Buch
[Scholar Profile | Author Map]
First Published: 2024-05-16
Latest Update: 2024-05-16
Description:
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>.
How to cite:
Gregor Buch (2024). SGPR: Sparse Group Penalized Regression for Bi-Level Variable Selection. R package version 0.1.2, https://cran.r-project.org/web/packages/SGPR. Accessed 03 Apr. 2025.
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Complete documentation for SGPR
Functions, R codes and Examples using the SGPR R package
Full SGPR package functions and examples
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