报告题目：ADAPTIVE L-STATISTICS FOR HIGH DIMENSIONAL TEST PROBLEM

报告时间：2025年6月23日下午17：00

报告地点：南湖校区新图书馆5302室

主办单位：欧洲杯

报告人：冯龙

报告人简介：冯龙，现任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。

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.