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https://hdl.handle.net/10419/49373
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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Birke, Melanie | en |
dc.contributor.author | Dette, Holger | en |
dc.date.accessioned | 2011-09-06T11:45:34Z | - |
dc.date.available | 2011-09-06T11:45:34Z | - |
dc.date.issued | 2003 | - |
dc.identifier.uri | http://hdl.handle.net/10419/49373 | - |
dc.description.abstract | We 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 |
dc.language.iso | eng | en |
dc.publisher | |aUniversität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen |cDortmund | en |
dc.relation.ispartofseries | |aTechnical Report |x2004,02 | en |
dc.subject.ddc | 519 | en |
dc.subject.keyword | sphericity test | en |
dc.subject.keyword | random matrices | en |
dc.subject.keyword | Wishart distribution | en |
dc.title | A note on testing the covariance matrix for large dimension | - |
dc.type | Working Paper | en |
dc.identifier.ppn | 823996093 | en |
dc.rights | http://www.econstor.eu/dspace/Nutzungsbedingungen | en |
dc.identifier.repec | RePEc:zbw:sfb475:200402 | en |
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