SLOPE
Sorted L1 Penalized Estimation
Efficient implementations for Sorted L-One Penalized Estimation (SLOPE): generalized linear models regularized with the sorted L1-norm (Bogdan et al. 2015). Supported models include ordinary least-squares regression, binomial regression, multinomial regression, and Poisson regression. Both dense and sparse predictor matrices are supported. In addition, the package features predictor screening rules that enable fast and efficient solutions to high-dimensional problems.
- Version1.2.0
- R version3.5.0
- LicenseGPL-3
- Needs compilation?Yes
- Languageen-US
- SLOPE citation info
- Last release11/11/2025
Documentation
Team
Johan Larsson
MaintainerShow author detailsMathurin Massias
Show author detailsRolesAuthorEmmanuel Candes
Show author detailsRolesAuthorQuentin Klopfenstein
Show author detailsRolesAuthorJerome Friedman
Show author detailsRolesContributorTrevor Hastie
Show author detailsRolesContributorChiara Sabatti
Show author detailsRolesAuthorMichal Burdukiewicz
Ewout van den Berg
Show author detailsRolesAuthorRob Tibshirani
Show author detailsRolesContributorNoah Simon
Show author detailsRolesContributorEvan Patterson
Show author detailsRolesAuthorJonas Wallin
Balasubramanian Narasimhan
Show author detailsRolesContributorWeijie Su
Show author detailsRolesAuthorKrystyna Grzesiak
Show author detailsRolesAuthorMalgorzata Bogdan
Junyang Qian
Show author detailsRolesContributorJakub Kała
Show author detailsRolesAuthorAkarsh Goyal
Show author detailsRolesContributor
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