Package: sgs
Title: Sparse-Group SLOPE: Adaptive Bi-Level Selection with FDR Control
Version: 0.3.9
Date: 2025-09-30
Authors@R: person("Fabio", "Feser", role = c("aut", "cre"), email = "ff120@ic.ac.uk",comment = c(ORCID = "0009-0007-3088-9727"))
Maintainer: Fabio Feser <ff120@ic.ac.uk>
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.
Imports: Matrix, MASS, caret, grDevices, graphics, methods, stats,
        SLOPE, Rlab, Rcpp (>= 1.0.10)
LinkingTo: Rcpp, RcppArmadillo
Suggests: SGL, gglasso, glmnet, testthat, knitr, grpSLOPE, rmarkdown
RoxygenNote: 7.3.1
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/ff1201/sgs
BugReports: https://github.com/ff1201/sgs/issues
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-10-28 11:33:32 UTC; root
Author: Fabio Feser [aut, cre] (ORCID:
        <https://orcid.org/0009-0007-3088-9727>)
Repository: https://cran.r-universe.dev
Date/Publication: 2025-09-30 13:50:02 UTC
RemoteUrl: https://github.com/cran/sgs
RemoteRef: HEAD
RemoteSha: 520c238631e7e2a46018e58909b3ef455013e329