# -------------------------------------------- # 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), Guo, Ćevid, and Bühlmann (2022) ). 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) ) and SDForest() for Spectrally Deconfounded Random Forests (Ulmer, Scheidegger, and Bühlmann (2025) ). 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.