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Diagonal Likelihood Ratio Test for Equality of Mean Vectors in High-Dimensional Data-童铁军教授(香港浸会大学深圳研究院)

作者:   来源:  时间:2018-11-12

题目: Diagonal Likelihood Ratio Test for Equality of Mean Vectors in High-Dimensional Data

报告人:童铁军 教授  (香港浸会大学深圳研究院)

Abstract : We propose a likelihood ratio test framework for testing normal mean vectors in high-dimensional data under two common scenarios: the one-sample test and the two-sample test with equal covariance matrices. We derive the test statistics under the assumption that the covariance matrices follow a diagonal matrix structure. In comparison with the diagonal Hotelling’s tests, our proposed test statistics display some interesting characteristics. In particular, they are a summation of the log-transformed squared t-statistics rather than a direct summation of those components. More importantly, to derive the asymptotic normality of our test statistics under the null and local alternative hypotheses, we do not require the assumption that the covariance matrix follows a diagonal matrix structure. As a consequence, our proposed test methods are very flexible and can be widely applied in practice. Finally, simulation studies and a real data analysis are also conducted to demonstrate the advantages of our likelihood ratio test method.

时间: 11月12日(周一)10:00-12:00

地点:首都师范大学本部教二楼 513 教室

 

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