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dc.contributor.authorBirke, Melanieen_US
dc.contributor.authorDette, Holgeren_US
dc.date.accessioned2011-09-06T11:45:34Z-
dc.date.available2011-09-06T11:45:34Z-
dc.date.issued2003en_US
dc.identifier.urihttp://hdl.handle.net/10419/49373-
dc.description.abstractWe consider the problem of testing hypotheses regarding the covariance matrix of multivariate normal data, if the sample size s and dimension n satisfy lim [n,s→∞] n/s = y. Recently, several tests have been proposed in the case, where the sample size and dimension are of the same order, that is y ∈ (0,∞). In this paper we consider the cases y = 0 and y = ∞. It is demonstrated that standard techniques are not applicable to deal with these cases. A new technique is introduced, which is of its own interest, and is used to derive the asymptotic distribution of the test statistics in the extreme cases y = 0 and y = ∞.en_US
dc.language.isoengen_US
dc.publisherUniv., SFB 475 Dortmunden_US
dc.relation.ispartofseriesTechnical Report // Universität Dortmund, SFB 475 Komplexitätsreduktion in Multivariaten Datenstrukturen 2004,02en_US
dc.subject.ddc310en_US
dc.subject.keywordsphericity testen_US
dc.subject.keywordrandom matricesen_US
dc.subject.keywordWishart distributionen_US
dc.titleA note on testing the covariance matrix for large dimensionen_US
dc.typeWorking Paperen_US
dc.identifier.ppn383919045en_US
dc.rightshttp://www.econstor.eu/dspace/Nutzungsbedingungenen_US
dc.identifier.repecRePEc:zbw:sfb475:200402-
Appears in Collections:Technical Reports, SFB 475, TU Dortmund

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