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sgs  

Sparse-Group SLOPE: Adaptive Bi-Level Selection with FDR Control
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("sgs", "0.3.5")



Attach the package and use:
library("sgs")
Maintained by
Fabio Feser
[Scholar Profile | Author Map]
First Published: 2023-05-19
Latest Update: 2023-08-22
Description:
Implementation of Sparse-group SLOPE: Adaptive bi-level with FDR-control (Feser et al. (2023) ). Linear and logistic regression models are supported, both of which can be fit using k-fold cross-validation. Dense and sparse input matrices are supported. In addition, a general adaptive three operator splitting (ATOS) implementation is provided.
How to cite:
Fabio Feser (2023). sgs: Sparse-Group SLOPE: Adaptive Bi-Level Selection with FDR Control. R package version 0.3.5, https://cran.r-project.org/web/packages/sgs. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1.0 (2023-05-19 19:20), 0.1.1 (2023-08-22 17:50), 0.2.0 (2024-07-14 05:30), 0.3.0 (2024-09-18 23:20), 0.3.1 (2024-11-16 15:20), 0.3.2 (2024-11-28 14:50), 0.3.3 (2025-02-03 17:40), 0.3.4 (2025-02-06 11:50)
Other packages that cited sgs R package
View sgs citation profile
Other R packages that sgs depends, imports, suggests or enhances
Complete documentation for sgs
Functions, R codes and Examples using the sgs R package
Some associated functions: arma_mv . as_sgs . atos . fit_sgs . fit_sgs_cv . generate_penalties . generate_toy_data . plot.sgs_cv . predict.sgs . print.sgs . scaled_sgs . sgs-package . 
Some associated R codes: RcppExports.R . as_sgs.R . atos.R . fit_sgs.R . fit_sgs_cv.R . generate_penalties.R . plot.R . predict.R . print.R . run_algorithm.R . scaled_sgs.R . sgs-package.R . toy_data_gen.R . utils.R .  Full sgs package functions and examples
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