sgs-package {sgs}R Documentation

sgs: Sparse-Group SLOPE: Adaptive Bi-Level Selection with FDR Control

Description

Implementation of Sparse-group SLOPE (SGS) (Feser and Evangelou (2023) doi:10.48550/arXiv.2305.09467) models. 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) (Pedregosa and Gidel (2018) doi:10.48550/arXiv.1804.02339) implementation is provided. Group SLOPE (gSLOPE) (Brzyski et al. (2019) doi:10.1080/01621459.2017.1411269) and group-based OSCAR models (Feser and Evangelou (2024) doi:10.48550/arXiv.2405.15357) are also implemented. All models are available with strong screening rules (Feser and Evangelou (2024) doi:10.48550/arXiv.2405.15357) for computational speed-up.

Author(s)

Maintainer: Fabio Feser ff120@ic.ac.uk (ORCID)

See Also

Useful links:


[Package sgs version 0.3.2 Index]