時   間：2024年11月15日14:00 - 15:00

地   點：普陀校區(qū)理科大樓A1514

報告人：韓瀟中國科學技術大學管理學院教授

主持人：馬慧娟華東師范大學副教授

摘   要：

In this paper, we introduce the Generalized Linear Spectral Statistics (GLSS) of a high-dimensional sample covariance matrix. The joint asymptotic normality of GLSS associated with different test functions is established when the dimension and the sample size are comparable under weak assumptions. Subsequently, we propose a novel functional projection approach based on GLSS for hypothesis testing on eigenspaces of population-spiked covariance matrices. The theoretical accuracy of our results established for GLSS and the advantages of the newly suggested testing procedure are demonstrated through various numerical studies.

報告人簡介：

韓瀟，中國科學技術大學管理學院特任教授，研究方向為大維隨機矩陣；高維統(tǒng)計推斷，入選國家創(chuàng)新人才計劃青年項目，主持青年基金項目與面上基金項目各一項