学术报告
报告题目：Two Sample Tests for High Dimensional Means
报 告 人：陈松蹊 教授
北京大学统计科学中心主任
时 间：5月16日(星期三)下午2:30
地 点：统计研究院432教室
摘 要: This paper considers testing the equality of two high dimensional means. Two approaches are utilized to formulate L2-type tests for better power performance when the two high dimensional mean vectors differ only in sparsely populated coordinates and the differences are faint. One is to conduct thresholding to remove the non-signal bearing dimensions for variance reduction of the test statistics. The other is to transform the data via the precision matrix for signal enhancement. It is shown that the thresholding and data transformation lead to attractive detection boundaries for the tests. Furthermore, we demonstrate explicitly the effects of precision matrix estimation on the detection boundary for the test with thresholding and data transformation. Numerical studies are performed to confirm the theoretical findings and demonstrate the practical implementations.
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统计研究院
2018年5月14日