Inference on Eigenvalues of Wishart Distribution Using Asymptotics with respect to the Dispersion of Population Eigenvalues

dc.creatorSheena, Yo
dc.creatorTakemura, Akimichi
dc.date2007-04-18
dc.date.accessioned2026-07-07T12:34:09Z
dc.date.available2026-07-07T12:34:09Z
dc.descriptionIn this paper we derive some new and practical results on testing and interval estimation problems for the population eigenvalues of a Wishart matrix based on the asymptotic theory for block-wise infinite dispersion of the population eigenvalues. This new type of asymptotic theory has been developed by the present authors in Takemura and Sheena (2005) and Sheena and Takemura (2007a,b) and in these papers it was applied to point estimation problem of population covariance matrix in a decision theoretic framework. In this paper we apply it to some testing and interval estimation problems. We show that the approximation based on this type of asymptotics is generally much better than the traditional large-sample asymptotics for the problems.
dc.identifierhttps://arxiv.org/abs/0704.2278
dc.identifierhttp://arxiv.org/abs/0704.2278
dc.identifierSankhya, Vol. 69, No.4, 717-733. (2007)
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/217322
dc.subjectStatistics Theory
dc.subject62H10
dc.titleInference on Eigenvalues of Wishart Distribution Using Asymptotics with respect to the Dispersion of Population Eigenvalues
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