SLOPE/CITATION.cff at main · jolars/SLOPE · GitHub

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cff-version: 1.2.0
title: 'SLOPE: Sorted L1 Penalized Estimation'
type: software
authors:
  - given-names: Johan
    family-names: Larsson
    email: johan@jolars.co
    affiliation: 'Department of Statistics, Lund University'
    orcid: 'https://orcid.org/0000-0002-4029-5945'
  - given-names: Jonas
    family-names: Wallin
    email: jonas.wallin@stat.lu.se
    affiliation: 'Department of Statistics, Lund University'
    orcid: 'https://orcid.org/0000-0003-0381-6593'
  - given-names: Malgorzata
    family-names: Bogdan
    orcid: 'https://orcid.org/0000-0002-0657-4342'
    email: malgorzata.bogdan@stat.lu.se
  - given-names: Ewout
    name-particle: van der
    family-names: Berg
  - given-names: Chiara
    family-names: Sabatti
  - given-names: Emmanuel
    family-names: Candes
  - given-names: Evan
    family-names: Patterson
  - given-names: Weijie
    family-names: Su
  - given-names: Jakub
    family-names: Kała
  - given-names: Krystyna
    family-names: Grzesiak
  - given-names: Michal
    family-names: Burdukiewicz
    orcid: 'https://orcid.org/0000-0001-8926-582X'
  - given-names: Mathurin
    family-names: Massias
    orcid: 'https://orcid.org/0000-0002-8950-0356'
  - given-names: Quentin
    family-names: Klopfenstein
    orcid: 'https://orcid.org/0000-0002-5771-6013'
repository-code: 'https://github.com/jolars/SLOPE'
url: 'https://jolars.github.io/SLOPE/'
abstract: >-
  Efficient implementations for Sorted L-One
  Penalized Estimation (SLOPE): generalized linear
  models regularized with the sorted L1-norm (Bogdan
  et al. (2015) <doi:10.1214/15-AOAS842>). 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.
keywords:
  - SLOPE
  - regularization
  - sparse regression
  - generalized linear models
license: GPL-3.0-or-later
message: If you use this software, please cite our article on
  arXiv.
preferred-citation:
  authors:
    - family: Larsson
      given: Johan
      orcid: "https://orcid.org/0000-0002-4029-5945"
    - family: Bogdan
      given: Malgorzata
    - family: Grzesiak
      given: Krystyna
    - family: Massias
      given: Mathurin
    - family: Wallin
      given: Jonas
    - family-names: Larsson
      given-names: Johan
  date-published: 2025-11-05
  doi: 10.48550/arXiv.2511.02430
  url: https://joss.theoj.org/papers/10.21105/joss.08936
  number: arXiv:2511.02430
  publisher:
    name: arXiv
  title: "Efficient Solvers for SLOPE in R, Python, Julia, and C++"
  type: article
  source: arXiv.org