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Mixtures of traces of Wishart and inverse Wishart matrices
Stockholm University, Faculty of Social Sciences, Department of Statistics. Linnaeus University, Sweden.ORCID iD: 0000-0002-0341-7472
Number of Authors: 22019 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415XArticle in journal (Refereed) Epub ahead of print
Abstract [en]

Traces of Wishart matrices appear in many applications, for example in finance, discriminant analysis, Mahalanobis distances and angles, loss functions and many more. These applications typically involve mixtures of traces of Wishart and inverse Wishart matrices that are concerned in this paper. Of particular interest are the sampling moments and their limiting joint distribution. The covariance matrix of the marginal positive and negative spectral moments is derived in closed form (covariance matrix of where ). The results are obtained through convenient recursive formulas for and Moreover, we derive an explicit central limit theorem for the scaled vector Y, when and present a simulation study on the convergence to normality and on a skewness measure.

Place, publisher, year, edition, pages
2019.
Keywords [en]
covariance matrix, central limit theorem, eigenvalue distribution, inverse Wishart Matrix, Wishart matrix
National Category
Mathematics
Identifiers
URN: urn:nbn:se:su:diva-176506DOI: 10.1080/03610926.2019.1691733ISI: 000497229800001OAI: oai:DiVA.org:su-176506DiVA, id: diva2:1381290
Available from: 2019-12-20 Created: 2019-12-20 Last updated: 2019-12-20

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