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hal.structure.identifierBiostatistique
dc.contributor.authorLIQUET, Benoit
hal.structure.identifierGroupe de Recherche en Economie Théorique et Appliquée [GREThA]
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierQuality control and dynamic reliability [CQFD]
dc.contributor.authorSARACCO, Jérôme
dc.date.accessioned2024-04-04T02:41:23Z
dc.date.available2024-04-04T02:41:23Z
dc.date.issued2008-06
dc.identifier.issn0361-0918
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/191147
dc.description.abstractEnTo reduce the dimensionality of regression problems, sliced inverse regression approaches make it possible to determine linear combinations of a set of explanatory variables X related to the response variable Y in general semiparametric regression context. From a practical point of view, the determination of a suitable dimension (number of the linear combination of X) is important. In the literature, statistical tests based on the nullity of some eigenvalues have been proposed. Another approach is to consider the quality of the estimation of the effective dimension reduction (EDR) space. The square trace correlation between the true EDR space and its estimate can be used as goodness of estimation. In this paper, we focus on the SIR method and propose a na¨ıve bootstrap estimation of the square trace correlation criterion. Moreover, this criterion could also select the parameter in the SIR method. We indicate how it can be used in practice. A simulation study is performed to illustrate the behaviour of this approach.
dc.language.isoen
dc.publisherTaylor & Francis
dc.subject.enBootstrap
dc.subject.enDimension Reduction
dc.subject.enSliced Inverse Regression.
dc.subject.enSliced Inverse Regression
dc.title.enApplication of the Bootstrap Approach to the Choice of Dimension and the alpha Parameter in the SIRa Method alpha
dc.typeArticle de revue
dc.identifier.doi10.1080/03610910801889011
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologie
bordeaux.journalCommunications in Statistics - Simulation and Computation
bordeaux.page1198-1218
bordeaux.volume37
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.issue6
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierinserm-00367120
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//inserm-00367120v1
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