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報告承辦單位:長沙理工大學數學與統計學院

報告題目：Use of random integration to test equality of high dimensional covariance matrices

報告內容: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.

 報告人姓名: 王學欽

報告人所在單位:中國科學技術大學管理學院

報告人職稱/職務及學術頭銜: 二級教授，博士生導師

報告時間: 2021年11月29日周一晚上7:00-8:00

報告地點: 通訊會議ID：349-716-218

報告人簡介:王學欽，中國科學技術大學管理學院教授。2003年畢業于紐約州立大學賓漢姆頓分校。他現擔任教育部高等學校統計學類專業教學指導委員會委員、統計學國際期刊《JASA》等的Associate Editor、高等教育出版社《Lecture Notes: Data Science, Statistics and Probability》系列叢書的副主編。