Recombining dependent data: an Order Statistics

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dc.contributor.author Álvarez, Adolfo
dc.contributor.author Peña, Daniel
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned 2009-12-17T13:01:33Z
dc.date.available 2009-12-17T13:01:33Z
dc.date.issued 2009-12
dc.identifier.uri http://hdl.handle.net/10016/6147
dc.description.abstract This article discusses the problem of forming groups from previously split data. Algorithms for Cluster Analysis like SAR proposed by Peña, Rodriguez and Tiao (2004), divide the sample into small very homogeneous groups and then recombine them to form the definitive data configuration. This kind of splitting leads to dependent data in the sense that the groups are disjoint, so no traditional homogeneity of means or variances tests can be used. We propose an alternative by using Order Statistics. Studying the distribution and some moments of linear combination of Order Statistics it is possible to recombine disjoint data groups when they merge into a sample from the same population.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working papers. Statistics and Econometrics
dc.relation.ispartofseries 09-26
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other SAR
dc.subject.other Cluster Analysis
dc.subject.other Order Statistics
dc.subject.other L-statistics
dc.subject.other Bootstrapping
dc.title Recombining dependent data: an Order Statistics
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.identifier.repec ws098526
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