报告题目 (Title)：High dimensional PCA(高维主成分分析)
报告人 (Speaker)：潘光明 教授（随机矩阵领域知名专家，南洋理工大学）
报告时间 (Time)：2021年11月5日(周五) 9：00
报告地点 (Place)：腾讯会议（会议号：958 938 143）
邀请人(Inviter)：张阳春
报告摘要：We propose an approach based on sample eigenvalues of sample covariance matrices to estimate the number of significant components in high dimensional data. We show the consistency of the estimator in different type of data. Simulations are run to compare the performance with those existed approaches.