报告承办单位:登录入口数学与统计学院

报告题目：Use of random integration to test equality of high dimensional covariance matrices

报告内容:Testing the equality of two covariance matrices is a fundamental problem in statistics, and especially challenging when the data are high-dimensional. Through a novel use of random integration, we can test the equality of high-dimensional covariance matrices without assuming parametric distributions for the two underlying populations, even if the dimension is much larger than the sample size.  The asymptotic properties of our test for arbitrary number of covariates and sample size are studied in depth under a general multivariate model. The finite-sample performance of our test is evaluated through numerical studies. The empirical results demonstrate that our test is highly competitive with existing tests in a wide range of settings. In particular,  our proposed test is distinctly powerful under different settings when there exist a few large or many small diagonal disturbances between the two covariance matrices.

 报告人姓名: 王学钦

报告人所在单位:中国科学技术大学管理学院

报告人职称/职务及学术头衔: 二级教授，博士生导师

报告时间: 2021年11月29日周一晚上7:00-8:00

报告地点: 通讯会议ID：349-716-218

报告人简介:王学钦，中国科学技术大学管理学院教授。2003年毕业于纽约州立大学宾汉姆顿分校。他现担任教育部高等学校统计学类专业教学指导委员会委员、统计学国际期刊《JASA》等的Associate Editor、高等教育出版社《Lecture Notes: Data Science, Statistics and Probability》系列丛书的副主编。