Implementation of Sparse-group SLOPE (SGS) (Feser and Evangelou (2023) tools:::Rd_expr_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) tools:::Rd_expr_doi("10.48550/arXiv.1804.02339")) implementation is provided. Group SLOPE (gSLOPE) (Brzyski et al. (2019) tools:::Rd_expr_doi("10.1080/01621459.2017.1411269")) and group-based OSCAR models (Feser and Evangelou (2024) tools:::Rd_expr_doi("10.48550/arXiv.2405.15357")) are also implemented. All models are available with strong screening rules (Feser and Evangelou (2024) tools:::Rd_expr_doi("10.48550/arXiv.2405.15357")) for computational speed-up.
Maintainer: Fabio Feser ff120@ic.ac.uk (ORCID)
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