[Lecture] Changliang Zou：FDR Control Under General Dependence by Symmetrized Data Aggregation
Time: 9:30-10:30am, Jun. 5th, 2021, Saturday
Venue: Tencent meeting ID：612 438 046
Spreker: Changliang Zou, Professor, School of Statistics and Data Sciences, Nankai University
Abstract:We develop a new class of distribution–free multiple testing rules for FDR control under general dependence. A key element in our proposal is a symmetrized data aggregation (SDA) approach to incorporating the dependence structure via sample splitting, data screening and information pooling. The SDA filter substantially outperforms the knockoff method in power under moderate to strong dependence, and is more robust than existing methods based on asymptotic p-values.
Speaker’s Bio:邹长亮，南开大学统计与数据科学学院教授。08年于南开大学获博士学位，随后留校任教。主要从事统计学及其与数据科学领域的交叉研究和实际应用。研究兴趣包括：高维数据统计推断、大规模数据流分析、变点和异常点检测等，在Ann.Stat.、Biometrika、 J.Am.Stat.Asso.、Math. Program.、Technometrics等统计学和工业工程领域期刊上发表论文几十篇，主持国家自然科学基金委项目多项。
