1. Ktisis Cyprus University of Technology
  2. Cyprus University of Technology (Research Output)
  3. Άρθρα/Articles
Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/2147
DC FieldValueLanguage
dc.contributor.authorYatracos, Yannis G.-
dc.contributor.otherΓιατράκος, Γιάννης-
dc.date.accessioned2013-01-23T12:32:03Zen
dc.date.accessioned2013-05-16T08:22:15Z-
dc.date.accessioned2015-12-02T09:27:10Z-
dc.date.available2013-01-23T12:32:03Zen
dc.date.available2013-05-16T08:22:15Z-
dc.date.available2015-12-02T09:27:10Z-
dc.date.issued2005-
dc.identifier.citationJournal of the American Statistical Association, 2005, vol. 100, no. 472, pp. 1168-1175en_US
dc.identifier.issn01621459-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/2147-
dc.description.abstractAn inequality is provided that determines when shrinkage reduces the mean squared error (MSE) of an unbiased estimate. Artificially augmented samples are then used to obtain, among others, shrinkage estimates of the population's variance and covariance, which improve the unbiased estimates for all parameter values and for all probability models with marginals having finite second moments, and alternative jackknife estimates that complement the usual jackknife estimates in reducing the MSE.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofJournal of the American Statistical Associationen_US
dc.rights© American Statistical Associationen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectMultiple imputation (Statistics)en_US
dc.subjectU-statisticsen_US
dc.titleArtificially augmented samples, shrinkage, and mean squared error reductionen_US
dc.typeArticleen_US
dc.affiliationNational University of Singaporeen
dc.collaborationNational University of Singaporeen_US
dc.journalsHybrid Open Accessen_US
dc.countrySingaporeen_US
dc.subject.fieldSocial Sciencesen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.1198/016214505000000321en_US
dc.dept.handle123456789/54en
dc.relation.issue472en_US
dc.relation.volume100en_US
cut.common.academicyear2005-2006en_US
dc.identifier.spage1168en_US
dc.identifier.epage1175en_US
item.grantfulltextnone-
item.languageiso639-1en-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.openairetypearticle-
item.fulltextNo Fulltext-
crisitem.journal.journalissn1537-274X-
crisitem.journal.publisherTaylor & Francis-
crisitem.author.deptDepartment of Communication and Internet Studies-
crisitem.author.facultyFaculty of Communication and Media Studies-
crisitem.author.parentorgFaculty of Communication and Media Studies-
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