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報告題目：Adaptive Selection for False Discovery Rate Control Leveraging Symmetry

主講人：許王莉教授（中國人民大學）

時間：2025年4月24日（周四）9:00 a.m.

地點：北院卓遠樓305會議室

主辦單位：統計與數學學院

摘要：Controlling the false discovery rate (FDR) in high-dimensional multiple testing has recently been advanced through mirror statistics via knockoff and data splitting. However, these approaches primarily emphasize the symmetry structure of the one-dimensional summary statistics while inadvertently overlooking the distribution information from non-null features when determining the rejection region, potentially causing a power loss. To tackle this challenge, we present a novel framework termed symmetry-based adaptive selection (SAS), which leverages the symmetry property of the two-dimensional statistics associated with the null features to estimate the local FDR and thereby determine the rejection region. We provide theoretical evidence for the asymptotic validity of controlling the FDR and emphasize the superior power performance of our proposed SAS. Extensive numerical results from both synthetic experiments and two real-world datasets demonstrate that the proposed SAS achieves satisfactory FDR control and significant power improvements over existing methods.

主講人簡介：

許王莉，中國人民大學教授，博士生導師。許王莉，中國人民大學吳玉章講席教授，博士生導師。先后主持4項國家自然科學基金，北京市自然科學基金重點研究專題，教育部人文社會科學重點研究基地重大項目和教育部人文社科基金等多項科研課題。 2010年先后入選“新世紀優秀人才計劃”和“北京市科技新星計劃”，先后獲得中國第十二屆北京市統計科研優秀成果獎一等獎(2014)，第一屆統計科學技術進步二等獎（2021）。