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A note on mean testing for high dimensional multivariate data under non-normality
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2013 (English)In: Statistica neerlandica (Print), ISSN 0039-0402, E-ISSN 1467-9574, Vol. 67, no 1, 81-99 p.Article in journal (Refereed) Published
Abstract [en]

A test statistic is considered for testing a hypothesis for the mean vector for multivariate data, when the dimension of the vector, p, may exceed the number of vectors, n, and the underlying distribution need not necessarily be normal. With n,p?8, and under mild assumptions, but without assuming any relationship between n and p, the statistic is shown to asymptotically follow a chi-square distribution. A by product of the paper is the approximate distribution of a quadratic form, based on the reformulation of the well-known Box's approximation, under high-dimensional set up. Using a classical limit theorem, the approximation is further extended to an asymptotic normal limit under the same high dimensional set up. The simulation results, generated under different parameter settings, are used to show the accuracy of the approximation for moderate n and large p.

Place, publisher, year, edition, pages
2013. Vol. 67, no 1, 81-99 p.
National Category
Natural Sciences
URN: urn:nbn:se:uu:diva-194185DOI: 10.1111/j.1467-9574.2012.00533.xISI: 000313270000005OAI: oai:DiVA.org:uu-194185DiVA: diva2:605227
Available from: 2013-02-13 Created: 2013-02-11 Last updated: 2013-02-13Bibliographically approved

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Ahmad, M. Rauf
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