题    目：Adaptive L-statistics for high dimensional test problem

主讲人：冯龙   教授

单    位：南开大学

时    间：2025年10月23日 15:00

腾讯ID：446930125

摘  要：In this study, we focus on applying L-statistics to the high-dimensional one-sample location test problem. Intuitively, an L-statistic with k parameters tends to perform optimally when the sparsity level of the alternative hypothesis matches k. We begin by deriving the limiting distributions for both L-statistics with fixed parameters and those with diverging parameters. To ensure robustness across varying sparsity levels of alternative hypotheses, we first establish the asymptotic independence between L-statistics with fixed and diverging parameters. Building on this, we propose a Cauchy combination test that integrates L-statistics with different parameters. Both simulation results and real data applications highlight the advantages of our proposed methods.

简  介：冯龙，南开大学统计与数据科学学院教授、博士生导师。入选教育部青年人才计划、南开大学百名青年学科带头人。曾获得教育部学术新人奖，南开大学优秀博士论文奖。主要从事高维数据分析方面的研究，在统计学国际顶尖杂志JRSSB, JASA、Biometrika、Annals of Statistics、JOE、JBES等发表40余篇论文。主持一项天津市杰出青年基金、国家自然科学基金面上项目和青年项目。担任Statistical Theory and Related Field副主编。