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On Testing Sphericity and Identity of a Covariance Matrix with Large Dimensions
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics. Uppsala Univ, Dept Stat, Uppsala, Sweden.
2016 (English)In: Mathematical Methods of Statistics, ISSN 1066-5307, E-ISSN 1934-8045, Vol. 25, no 2, p. 121-132Article in journal (Refereed) Published
Abstract [en]

Tests for certain covariance structures, including sphericity, are presented when the data may be high-dimensional but not necessarily normal. The tests are formulated as functions of location-invariant estimators defined as U-statistics of higher order kernels. Under a few mild assumptions, the limit distributions of the tests are shown to be normal. The accuracy of the tests is demonstrated by simulations.

Place, publisher, year, edition, pages
PLEIADES PUBLISHING INC , 2016. Vol. 25, no 2, p. 121-132
Keywords [en]
covariance testing, high-dimensional inference, non-normality
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:uu:diva-400807DOI: 10.3103/S1066530716020034ISI: 000410341800003OAI: oai:DiVA.org:uu-400807DiVA, id: diva2:1382566
Available from: 2020-01-03 Created: 2020-01-03 Last updated: 2020-01-03Bibliographically approved

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Ahmad, M. Rauf

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