报 告 人：李卫明

　　报告地点：数学与统计学院623室

　　报告时间：2014年06月16日星期一16:00-17:00

　　报告简介：

　　We discuss the problem of testing for high-dimensional covariance matrices. Tests for an identity matrix and for the equality of two covariance matrices are considered when the data dimension and the sample size are both large. The proposed test statistics are built upon the Stieltjes transform of the spectral distribution of the sample covariance matrix. We prove that the proposed statistics are asymptotically chi-square distributed under the null hypotheses, and normally distributed under the alternative hypotheses. Simulation results show that for finite dimension and sample size the proposed tests outperform some existing methods in various cases.

　　主讲人简介：

　　李卫明, 北京邮电大学理学院讲师, 曾在香港大学、新加坡南洋理工大学和北京航空航天大学做博士后研究。在Sinica，JMA等杂志发表论文十余篇。