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.
- Version0.5.2
- R versionR (≥ 3.5.0)
- LicenseGPL-3
- Needs compilation?Yes
- Languageen-US
- SLOPE citation info
- Last release02/01/2025
Documentation
Team
Johan Larsson
MaintainerShow author detailsKrystyna Grzesiak
Show author detailsRolesAuthorJerome Friedman
Show author detailsRolesContributorEmmanuel Candes
Show author detailsRolesAuthorMalgorzata Bogdan
Show author detailsRolesAuthorWeijie Su
Show author detailsRolesAuthorJonas Wallin
Rob Tibshirani
Show author detailsRolesContributorMichal Burdukiewicz
Ewout van den Berg
Show author detailsRolesAuthorNoah Simon
Show author detailsRolesContributorEvan Patterson
Show author detailsRolesAuthorChiara Sabatti
Show author detailsRolesAuthorTrevor Hastie
Show author detailsRolesContributorBalasubramanian Narasimhan
Show author detailsRolesContributorJunyang Qian
Show author detailsRolesContributorJakub Kała
Show author detailsRolesAuthorAkarsh Goyal
Show author detailsRolesContributor
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Dependencies
- Imports4 packages
- Suggests13 packages
- Linking To2 packages
- Reverse Depends1 package
- Reverse Imports1 package
- Reverse Suggests1 package