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dc.contributor.authorGhosh, Abhik
dc.contributor.authorPonzi, Erica
dc.contributor.authorSandanger, Torkjel M
dc.contributor.authorThoresen, Magne
dc.date.accessioned2023-01-26T11:09:11Z
dc.date.available2023-01-26T11:09:11Z
dc.date.issued2022-12-13
dc.description.abstractWe consider the problem of variable screening in ultra-high-dimensional generalized linear models (GLMs) of nonpolynomial orders. Since the popular SIS approach is extremely unstable in the presence of contamination and noise, we discuss a new robust screening procedure based on the minimum density power divergence estimator (MDPDE) of the marginal regression coefficients. Our proposed screening procedure performs well under pure and contaminated data scenarios. We provide a theoretical motivation for the use of marginal MDPDEs for variable screening from both population as well as sample aspects; in particular, we prove that the marginal MDPDEs are uniformly consistent leading to the sure screening property of our proposed algorithm. Finally, we propose an appropriate MDPDE-based extension for robust conditional screening in GLMs along with the derivation of its sure screening property. Our proposed methods are illustrated through extensive numerical studies along with an interesting real data application.en_US
dc.identifier.citationGhosh, Ponzi, Sandanger, Thoresen. Robust sure independence screening for nonpolynomial dimensional generalized linear models. Scandinavian Journal of Statistics. 2022en_US
dc.identifier.cristinIDFRIDAID 2107135
dc.identifier.doi10.1111/sjos.12628
dc.identifier.issn0303-6898
dc.identifier.issn1467-9469
dc.identifier.urihttps://hdl.handle.net/10037/28388
dc.language.isoengen_US
dc.publisherWileyen_US
dc.relation.journalScandinavian Journal of Statistics
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/FP7-IDEAS-ERC/232997/EU/TRANSCRIPTOMICS IN CANCER EPIDEMIOLOGY/TICE/en_US
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2022 The Author(s)en_US
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0en_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)en_US
dc.titleRobust sure independence screening for nonpolynomial dimensional generalized linear modelsen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)