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An adaptive SIR method for block-wise evolving data streams

hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorCHAVENT, Marie
hal.structure.identifierModelling and Inference of Complex and Structured Stochastic Systems [MISTIS]
dc.contributor.authorGIRARD, Stéphane
hal.structure.identifierAménités et dynamiques des espaces ruraux [UR ADBX]
dc.contributor.authorKUENTZ, Vanessa
hal.structure.identifierEpidémiologie et Biostatistique [Bordeaux]
dc.contributor.authorLIQUET, Benoit
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorNGUYEN, Thi Mong Ngoc
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorSARACCO, Jérôme
dc.contributor.editorGuglielmo D'Amico and Giuseppe Di Biase and Jacques Janssen and Raimondo Manca
dc.date.accessioned2024-04-04T02:26:54Z
dc.date.available2024-04-04T02:26:54Z
dc.date.issued2011-06
dc.date.conference2011-06-07
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/189992
dc.description.abstractEnIn this communication, we consider block-wise evolving data streams. When a semiparametric regression model involving a common dimension reduction direction B is assumed for each block, we propose an adaptive SIR (for sliced inverse regression) estimator of B. This estimator is faster than usual SIR applied to the union of all the blocks, both from computational complexity and running time points of view. We show the consistency of our estimator at the root-n rate. In a simulation, we illustrate the good numerical behaviour of the estimator. We also provide a graphical tool in order to detect if there exists a drift of the dimension reduction direction or some aberrant blocks of data. We illustrate our approach with various scenarios. Finally, possible extensions of this method are given.
dc.language.isoen
dc.publisherEdizioni ETS
dc.source.titleXIVth International Symposium of Applied Stochastic Models and Data Analysis (ASMDA 2011)
dc.title.enAn adaptive SIR method for block-wise evolving data streams
dc.typeCommunication dans un congrès
dc.subject.halMathématiques [math]/Systèmes dynamiques [math.DS]
bordeaux.page257-264
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.conference.titleASMDA 2011 - XIVth International Symposium of Applied Stochastic Models and Data Analysis
bordeaux.countryIT
bordeaux.title.proceedingXIVth International Symposium of Applied Stochastic Models and Data Analysis (ASMDA 2011)
bordeaux.conference.cityRome
bordeaux.peerReviewedoui
hal.identifierhal-00601924
hal.version1
hal.invitednon
hal.proceedingsoui
hal.conference.end2011-06-10
hal.popularnon
hal.audienceInternationale
dc.subject.itregression
dc.subject.itnumerical model
dc.subject.itnumerical simulation
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-00601924v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.btitle=XIVth%20International%20Symposium%20of%20Applied%20Stochastic%20Models%20and%20Data%20Analysis%20(ASMDA%202011)&rft.date=2011-06&rft.spage=257-264&rft.epage=257-264&rft.au=CHAVENT,%20Marie&GIRARD,%20St%C3%A9phane&KUENTZ,%20Vanessa&LIQUET,%20Benoit&NGUYEN,%20Thi%20Mong%20Ngoc&rft.genre=unknown


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