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Advanced topics in Sliced Inverse Regression

hal.structure.identifierModèles statistiques bayésiens et des valeurs extrêmes pour données structurées et de grande dimension [STATIFY]
dc.contributor.authorGIRARD, Stéphane
hal.structure.identifierMéthodes avancées d’apprentissage statistique et de contrôle [ASTRAL]
dc.contributor.authorLORENZO, Hadrien
hal.structure.identifierMéthodes avancées d’apprentissage statistique et de contrôle [ASTRAL]
dc.contributor.authorSARACCO, Jérôme
dc.date.accessioned2024-04-04T02:45:20Z
dc.date.available2024-04-04T02:45:20Z
dc.date.issued2022
dc.identifier.issn0047-259X
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/191458
dc.description.abstractEnSince its introduction in the early 90's, the Sliced Inverse Regression (SIR) methodology has evolved adapting to increasingly complex data sets in contexts combining linear dimension reduction with non linear regression. The assumption of dependence of the response variable with respect to only a few linear combinations of the covariates makes it appealing for many computational and real data application aspects. This work proposes an overview of the most active research directions in SIR modeling from multivariate regression models to regularization and variable selection.
dc.language.isoen
dc.publisherElsevier
dc.subject.enCurse of dimensionality
dc.subject.enMultivariate response
dc.subject.enRegularization
dc.subject.enSemi-parametric regression model
dc.subject.enSufficient dimension reduction
dc.subject.enVariable selection
dc.title.enAdvanced topics in Sliced Inverse Regression
dc.typeArticle de revue
dc.identifier.doi10.1016/j.jmva.2021.104852
dc.subject.halMathématiques [math]/Statistiques [math.ST]
bordeaux.journalJournal of Multivariate Analysis
bordeaux.page104852
bordeaux.volume188
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-03367798
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-03367798v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Journal%20of%20Multivariate%20Analysis&rft.date=2022&rft.volume=188&rft.spage=104852&rft.epage=104852&rft.eissn=0047-259X&rft.issn=0047-259X&rft.au=GIRARD,%20St%C3%A9phane&LORENZO,%20Hadrien&SARACCO,%20J%C3%A9r%C3%B4me&rft.genre=article


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