Published June 2, 2026 | Version v2.1.0
Software Open

SLOPE: Sorted L1 Penalized Estimation

Authors/Creators

  • 1. Department of Statistics, Lund University

Description

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.

Notes

If you use this software, please cite our article on arXiv.

Files

jolars/SLOPE-v2.1.0.zip

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Additional details

Related works

Is supplement to
Software: https://github.com/jolars/SLOPE/tree/v2.1.0 (URL)

Software

Repository URL
https://github.com/jolars/SLOPE