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Conditional Quantile Estimation based on Optimal Quantization: from Theory to Practice

hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
hal.structure.identifierQuality control and dynamic reliability [CQFD]
hal.structure.identifierEuropean Center for Advanced Research in Economics and Statistics [ECARES]
hal.structure.identifierDépartement de Mathématique [Bruxelles] [ULB]
dc.contributor.authorCHARLIER, Isabelle
hal.structure.identifierDépartement de Mathématique [Bruxelles] [ULB]
hal.structure.identifierEuropean Center for Advanced Research in Economics and Statistics [ECARES]
dc.contributor.authorPAINDAVEINE, Davy
hal.structure.identifierQuality control and dynamic reliability [CQFD]
hal.structure.identifierInstitut de Mathématiques de Bordeaux [IMB]
dc.contributor.authorSARACCO, Jérôme
dc.date.accessioned2024-04-04T03:16:18Z
dc.date.available2024-04-04T03:16:18Z
dc.date.issued2015
dc.identifier.issn0167-9473
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/194205
dc.description.abstractEnSmall-sample properties of a nonparametric estimator of conditional quantiles based on optimal quantization, that was recently introduced (J. Statist. Plann. Inference, 156, 14–30, 2015), are investigated. More precisely, (i) the practical implementation of this estimator is discussed (by proposing in particular a method to properly select the corresponding smoothing parameter, namely the number of quantizers) and (ii) its finite- sample performances are compared to those of classical competitors. Monte Carlo studies reveal that the quantization-based estimator competes well in all cases and sometimes dominates its competitors, particularly when the regression function is quite complex. A real data set is also treated. While the main focus is on the case of a univariate covariate, simulations are also conducted in the bivariate case.
dc.language.isoen
dc.publisherElsevier
dc.subject.enConditional quantiles
dc.subject.enOptimal quantization
dc.subject.enNonparametric regression
dc.title.enConditional Quantile Estimation based on Optimal Quantization: from Theory to Practice
dc.typeArticle de revue
dc.subject.halMathématiques [math]/Statistiques [math.ST]
bordeaux.journalComputational Statistics and Data Analysis
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.peerReviewedoui
hal.identifierhal-01108504
hal.version1
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01108504v1
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