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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "dfr" in publications use:'
type: software
license: GPL-3.0-or-later
title: 'dfr: Dual Feature Reduction for SGL'
version: 0.1.2
doi: 10.48550/arXiv.2405.17094
identifiers:
- type: doi
  value: 10.32614/CRAN.package.dfr
abstract: Implementation of the Dual Feature Reduction (DFR) approach for the Sparse
  Group Lasso (SGL) and the Adaptive Sparse Group Lasso (aSGL) (Feser and Evangelou
  (2024) <https://doi.org/10.48550/arXiv.2405.17094>). The DFR approach is a feature
  reduction approach that applies strong screening to reduce the feature space before
  optimisation, leading to speed-up improvements for fitting SGL (Simon et al. (2013)
  <https://doi.org/10.1080/10618600.2012.681250>) and aSGL (Mendez-Civieta et al.
  (2020) <https://doi.org/10.1007/s11634-020-00413-8> and Poignard (2020) <https://doi.org/10.1007/s10463-018-0692-7>)
  models. DFR is implemented using the Adaptive Three Operator Splitting (ATOS) (Pedregosa
  and Gidel (2018) <https://doi.org/10.48550/arXiv.1804.02339>) algorithm, with linear
  and logistic SGL models supported, both of which can be fit using k-fold cross-validation.
  Dense and sparse input matrices are supported.
authors:
- family-names: Feser
  given-names: Fabio
  email: ff120@ic.ac.uk
  orcid: https://orcid.org/0009-0007-3088-9727
preferred-citation:
  type: article
  title: Dual feature reduction for the sparse-group lasso and its adaptive variant
  authors:
  - family-names: Feser
    given-names: Fabio
    email: ff120@ic.ac.uk
    orcid: https://orcid.org/0009-0007-3088-9727
  - family-names: Evangelou
    given-names: Marina
    orcid: https://orcid.org/0000-0003-0789-8944
  journal: arXiv
  year: '2024'
  doi: 10.48550/arXiv.2405.17094
  url: https://arxiv.org/abs/2405.17094
repository: https://CRAN.R-project.org/package=dfr
repository-code: https://github.com/ff1201/dfr
url: https://github.com/ff1201/dfr
date-released: '2024-11-28'
contact:
- family-names: Feser
  given-names: Fabio
  email: ff120@ic.ac.uk
  orcid: https://orcid.org/0009-0007-3088-9727
references:
- type: manual
  title: dfr
  authors:
  - family-names: Feser
    given-names: Fabio
    email: ff120@ic.ac.uk
    orcid: https://orcid.org/0009-0007-3088-9727
  year: '2024'
  url: https://CRAN.R-project.org/package=dfr