Testing the equality of several covariance matrices with fewer observations than the dimension |
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Authors: | Muni S Srivastava Hirokazu Yanagihara |
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Institution: | a Department of Statistics, University of Toronto, 100 St George Street, Toronto, Ontario, M5S 3G3, Canada b Department of Mathematics, Graduate School of Science, Hiroshima University, 1-3-1 Kagamiyama, Higashi-Hiroshima, Hiroshima 739-8626, Japan |
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Abstract: | For normally distributed data from the k populations with m×m covariance matrices Σ1,…,Σk, we test the hypothesis H:Σ1=?=Σk vs the alternative A≠H when the number of observations Ni, i=1,…,k from each population are less than or equal to the dimension m, Ni≤m, i=1,…,k. Two tests are proposed and compared with two other tests proposed in the literature. These tests, however, do not require that Ni≤m, and thus can be used in all situations, including when the likelihood ratio test is available. The asymptotic distributions of the test statistics are given, and the power compared by simulations with other test statistics proposed in the literature. The proposed tests perform well and better in several cases than the other two tests available in the literature. |
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Keywords: | primary 62H15 secondary 62H10 |
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