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Article: Resampling methods for homogeneity tests of covariance matrices

TitleResampling methods for homogeneity tests of covariance matrices
Authors
KeywordsBartlett homogeneity test
Bootstrap
Non-parametric tests
Permutation test
Random symmetrization
Issue Date2002
PublisherAcademia Sinica, Institute of Statistical Science. The Journal's web site is located at http://www.stat.sinica.edu.tw/statistica/
Citation
Statistica Sinica, 2002, v. 12 n. 3, p. 769-783 How to Cite?
AbstractTesting hypotheses on covariance matrices has long been of interest in statistics. The test of homogeneity is very often a preliminary step in discriminant analysis, cluster analysis, MANOVA, etc. In this article we propose nonparametric tests which are based on the eigenvalues of the differences among the sample covariance matrices after a common rescaling. Three resampling techniques for calculating p-values are shown to be asymptotically valid: Boot-strap, random symmetrization and permutation. Monte Carlo simulations show that the bootstrap performs less satisfactorily than the others in adhering to the nominal level of significance. Some theoretic ground for this phenomenon is given. The simulation results also suggest that the homogeneity tests proposed in this article performs better than the bootstrap version of Bartlett's test.
Persistent Identifierhttp://hdl.handle.net/10722/45355
ISSN
2015 Impact Factor: 0.838
2015 SCImago Journal Rankings: 2.292
References

 

DC FieldValueLanguage
dc.contributor.authorZhu, LXen_HK
dc.contributor.authorNg, KWen_HK
dc.contributor.authorJing, Pen_HK
dc.date.accessioned2007-10-30T06:23:38Z-
dc.date.available2007-10-30T06:23:38Z-
dc.date.issued2002en_HK
dc.identifier.citationStatistica Sinica, 2002, v. 12 n. 3, p. 769-783en_HK
dc.identifier.issn1017-0405en_HK
dc.identifier.urihttp://hdl.handle.net/10722/45355-
dc.description.abstractTesting hypotheses on covariance matrices has long been of interest in statistics. The test of homogeneity is very often a preliminary step in discriminant analysis, cluster analysis, MANOVA, etc. In this article we propose nonparametric tests which are based on the eigenvalues of the differences among the sample covariance matrices after a common rescaling. Three resampling techniques for calculating p-values are shown to be asymptotically valid: Boot-strap, random symmetrization and permutation. Monte Carlo simulations show that the bootstrap performs less satisfactorily than the others in adhering to the nominal level of significance. Some theoretic ground for this phenomenon is given. The simulation results also suggest that the homogeneity tests proposed in this article performs better than the bootstrap version of Bartlett's test.en_HK
dc.format.extent180421 bytes-
dc.format.extent2525 bytes-
dc.format.mimetypeapplication/pdf-
dc.format.mimetypetext/plain-
dc.languageengen_HK
dc.publisherAcademia Sinica, Institute of Statistical Science. The Journal's web site is located at http://www.stat.sinica.edu.tw/statistica/en_HK
dc.relation.ispartofStatistica Sinicaen_HK
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectBartlett homogeneity testen_HK
dc.subjectBootstrapen_HK
dc.subjectNon-parametric testsen_HK
dc.subjectPermutation testen_HK
dc.subjectRandom symmetrizationen_HK
dc.titleResampling methods for homogeneity tests of covariance matricesen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1017-0405&volume=12&issue=3&spage=769&epage=783&date=2002&atitle=Resampling+methods+for+homogeneity+tests+of+covariance+matrices+en_HK
dc.identifier.emailNg, KW: kaing@hkucc.hku.hken_HK
dc.identifier.authorityNg, KW=rp00765en_HK
dc.description.naturepublished_or_final_versionen_HK
dc.identifier.scopuseid_2-s2.0-0036661096en_HK
dc.identifier.hkuros78448-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0036661096&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume12en_HK
dc.identifier.issue3en_HK
dc.identifier.spage769en_HK
dc.identifier.epage783en_HK
dc.publisher.placeTaiwan, Republic of Chinaen_HK
dc.identifier.scopusauthoridZhu, LX=7404201068en_HK
dc.identifier.scopusauthoridNg, KW=7403178774en_HK
dc.identifier.scopusauthoridJing, P=36742345500en_HK

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