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dc.contributor.authorReyes, Miguel
dc.contributor.authorFrancisco-Fernández, Mario
dc.contributor.authorCao, Ricardo
dc.contributor.authorBarreiro-Ures, Daniel
dc.date.accessioned2023-11-27T16:50:47Z
dc.date.available2023-11-27T16:50:47Z
dc.date.issued2019
dc.identifier.citationReyes, M. [et al.]. Kernel distribution estimation for grouped data. Sort: Statistics and Operations Research Transactions, 2019, Vol. 43, Nº. 2, 2019, p. 259-288es_ES
dc.identifier.issn1696-2281
dc.identifier.urihttp://hdl.handle.net/2183/34341
dc.description.abstract[Abstract]: Interval-grouped data appear when the observations are not obtained in continuous time, but monitored in periodical time instants. In this framework, a nonparametric kernel distribution esti- mator is proposed and studied. The asymptotic bias, variance and mean integrated squared error of the new approach are derived. From the asymptotic mean integrated squared error, a plug-in bandwidth is proposed. Additionally, a bootstrap selector to be used in this context is designed. Through a comprehensive simulation study, the behaviour of the estimator and the bandwidth se- lectors considering different scenarios of data grouping is shown. The performance of the different approaches is also illustrated with a real grouped emergence data set of Avena sterilis (wild oat).es_ES
dc.description.sponsorshipThe authors thank three anonymous referees and the Editor for numerous useful comments that significantly improved this article. The authors also thank Dr. Fernando Bastida and Dr. José Luis González-Andújar for providing the Avena sterilis L. emergence data employed in Section 6. This research has been supported by MINECO grants MTM2014-52876-R and MTM2017-82724-R, and by the Xunta de Galicia (Grupos de Referencia Competitiva ED431C-2016-015 and Centro Singular de Investigación de Galicia ED431G/01), all of them through the ERDF.es_ES
dc.description.sponsorshipXunta de Galicia; ED431C-2016-015es_ES
dc.description.sponsorshipXunta de Galicia; ED431G/01es_ES
dc.language.isoenges_ES
dc.publisherInstitut d'Estadística de Catalunyaes_ES
dc.relationinfo:eu-repo/grantAgreement/MINECO/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/MTM2014-52876-R/ES/INFERENCIA ESTADISTICA COMPLEJA Y DE ALTA DIMENSION: EN GENOMICA, NEUROCIENCIA, ONCOLOGIA, MATERIALES COMPLEJOS, MALHERBOLOGIA, MEDIO AMBIENTE, ENERGIA Y APLICACIONES INDUSTRIes_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/MTM2017-82724-R/ES/INFERENCIA ESTADISTICA FLEXIBLE PARA DATOS COMPLEJOS DE GRAN VOLUMEN Y DE ALTA DIMENSIONes_ES
dc.relation.urihttps://doi.org/10.2436/20.8080.02.88es_ES
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 Españaes_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subjectBootstrap bandwidthes_ES
dc.subjectCumulative distribution function estimatores_ES
dc.subjectInterval dataes_ES
dc.subjectPlug-in bandwidthes_ES
dc.titleKernel distribution estimation for grouped dataes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleSORT (Statistics and Operations Research Transactions)es_ES
UDC.volume43es_ES
UDC.issue2es_ES
UDC.startPage259es_ES
UDC.endPage288es_ES
dc.identifier.doi10.2436/20.8080.02.88


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