Two-sample tests for high-dimensional covariance matrices using both difference and ratio (Q2219224)
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| Language | Label | Description | Also known as |
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| English | Two-sample tests for high-dimensional covariance matrices using both difference and ratio |
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Two-sample tests for high-dimensional covariance matrices using both difference and ratio (English)
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19 January 2021
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The problem of testing for high-dimensional distributions between two treatments is considered. The two-sample tests on high-dimensional variance-covariances are proposed without imposing the normality assumption. The dimension is allowed to be much larger comparing with the sample size. An empirical study on a leukemia data along with synthetic data analysis are employed to validate the proposed tests.
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asymptotic normality
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high-dimensional covariance matrices
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power enhancement
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random matrix theory
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