Testing homogeneity of several covariance matrices and multi-sample sphericity for high-dimensional data under non-normality
2017 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 46, no 8, 3738-3753 p.Article in journal (Refereed) Published
A test for homogeneity of g 2 covariance matrices is presented when the dimension, p, may exceed the sample size, n(i), i = 1, ..., g, and the populations may not be normal. Under some mild assumptions on covariance matrices, the asymptotic distribution of the test is shown to be normal when n(i), p . Under the null hypothesis, the test is extended for common covariance matrix to be of a specified structure, including sphericity. Theory of U-statistics is employed in constructing the tests and deriving their limits. Simulations are used to show the accuracy of tests.
Place, publisher, year, edition, pages
2017. Vol. 46, no 8, 3738-3753 p.
High-dimensionality, multi-sample sphericity, non-normality, U-statistics, 62H15
Probability Theory and Statistics
IdentifiersURN: urn:nbn:se:uu:diva-316050DOI: 10.1080/03610926.2015.1073310ISI: 000392413900010OAI: oai:DiVA.org:uu-316050DiVA: diva2:1076776