【专家简介】：周望，2004年7月起在新加坡国立大学统计系任教，Random matrices, SLE等。近年来发表高水平论文八十多篇。其中在概率统计学方面的国际公认的顶尖杂志Annals of Statistics, Journal of American Statistical Association, Biometrika, Annals of Probability, Probability Theory and Related Fields, Annals of Applied Probability上发表论文二十余篇。2005年起主持新加坡政府基金项目十余项。国际著名期刊 Random Matrices-Theory and Applications 的主编。主要研究方向为: High dimensional statistics，并于2009年1月获终身教授。现为新加坡国立大学教授，
【报告摘要】：In this paper, we examine the feasibility (i.e., both the good advantages and the bad limitations) and the adaptivity (i.e., the potential for beneficial modifications) of employing multiplier bootstrap to analyze the asymptotic distributions of the largest eigenvalues of potentially spiked high-dimensional sample covariance matrices. Our findings and proposed algorithms demonstrate that multiplier bootstrap remains valid, provided the multipliers are appropriately chosen and the bootstrap procedures are applied multiple times with suitable corrections.
【报告时间】：2026年07月10日（周五）09:30-10:30
【报告地点】：崇真楼110
