# --------------------------------------------
# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
# --------------------------------------------
 
cff-version: 1.2.0
message: 'To cite package "SDModels" in publications use:'
type: software
license: GPL-3.0-only
title: 'SDModels: Spectrally Deconfounded Models'
version: 1.0.6
identifiers:
- type: doi
  value: 10.32614/CRAN.package.SDModels
abstract: Screen for and analyze non-linear sparse direct effects in the presence
  of unobserved confounding using the spectral deconfounding techniques (Ćevid, Bühlmann,
  and Meinshausen (2020)<jmlr.org/papers/v21/19-545.html>, Guo, Ćevid, and Bühlmann
  (2022) <https://doi.org/10.1214/21-AOS2152>). These methods have been shown to be
  a good estimate for the true direct effect if we observe many covariates, e.g.,
  high-dimensional settings, and we have fairly dense confounding. Even if the assumptions
  are violated, it seems like there is not much to lose, and the deconfounded models
  will, in general, estimate a function closer to the true one than classical least
  squares optimization. 'SDModels' provides functions SDAM() for Spectrally Deconfounded
  Additive Models (Scheidegger, Guo, and Bühlmann (2025) <https://doi.org/10.1145/3711116>)
  and SDForest() for Spectrally Deconfounded Random Forests (Ulmer, Scheidegger, and
  Bühlmann (2025) <https://doi.org/10.48550/arXiv.2502.03969>).
authors:
- family-names: Ulmer
  given-names: Markus
  email: markus.ulmer@stat.math.ethz.ch
  orcid: https://orcid.org/0000-0001-7783-8475
- family-names: Scheidegger
  given-names: Cyrill
  orcid: https://orcid.org/0009-0005-2851-1384
preferred-citation:
  type: article
  title: Spectrally Deconfounded Random Forests
  authors:
  - family-names: Ulmer
    given-names: Markus
    email: markus.ulmer@stat.math.ethz.ch
    orcid: https://orcid.org/0000-0001-7783-8475
  - family-names: Scheidegger
    given-names: Cyrill
    orcid: https://orcid.org/0009-0005-2851-1384
  - family-names: B"uhlmann
    given-names: Peter
  year: '2025'
  journal: arXiv
  url: https://arxiv.org/abs/2502.03969
repository: https://markusul.r-universe.dev
repository-code: https://github.com/markusul/SDModels
commit: ba5caaafd43ff57074fff84b96c565693f025135
url: https://markusul.github.io/SDModels/
contact:
- family-names: Ulmer
  given-names: Markus
  email: markus.ulmer@stat.math.ethz.ch
  orcid: https://orcid.org/0000-0001-7783-8475
references:
- type: article
  title: Spectral Deconfounding for High-Dimensional Sparse Additive Models
  authors:
  - name: Scheidegger
  - name: Cyrill
  - name: Guo
  - name: Zijian
  - name: B"uhlmann
  - name: Peter
  year: '2025'
  publisher:
    name: Association for Computing Machinery
    address: New York, NY, USA
  url: https://doi.org/10.1145/3711116
  doi: 10.1145/3711116
  journal: ACM / IMS J. Data Sci.