统计与数据科学系系列学术报告之四百五十七期

时   间：2024年12月6日（星期五）10:00-11:00

地   点：史带楼302室

主持人：复旦大学 管理学院 统计与数据科学系 朱仲义 教授

报告人：Prof. Jun S Liu  Department of Statistics，Harvard University

题   目：P-value free Methods for FDR Controls

摘   要：There has been significant interest among researchers in false discovery rate (FDR) control methods partially due to the strong desire from the scientific community for reproducibility and replicability of scientific discoveries. I will discuss my own perspectives on both methodological and theoretical developments in FDR control methods applicable to a wide class of regression models, covering the knockoff filter, data splitting (DS), and Gaussian mirror (GM). A classical statistical idea is to introduce certain data perturbations and examine their impacts on a statistical procedure, and all these methods follow this line of thinking one way or another. We present some power analysis of these methods under the weak-and-rare signal framework and discuss its implications under different correlation structures of the design matrix. We then focus on the DS procedure and its variation, Multiple Data Splitting (MDS), which are straightforward conceptually, easy to implement algorithmically, and applicable to a wide class of linear and nonlinear models. Their specializations in GLMs result in scale-free procedures that can circumvent difficulties caused by non-traditional asymptotic behaviors of MLEs in moderate-dimensions and debiased Lasso estimates in high-dimensions. Some future developments along the line of e-values will be discussed. The presentation is based on joint work with Chenguang Dai, Buyu Lin, Yuanchuan Guo, and Tracy Ke.

个人简介：刘军，美国哈佛大学统计系教授。他曾任斯坦福大学统计系助理教授、副教授、终身教授；还曾任美国统计协会会刊联席主编及多个国际一流统计杂志副主编等职。他领导创建清华大学统计学研究中心，并任名誉主任；以筹建发展委员会主任身份在清华大学创建统计与数据科学系。刘军教授是美国数理统计学会和美国统计学会会士和国际计算生物学会会士（Fellow）；曾获得北美五大统计协会联合颁发的“考普斯会长奖”；世界华人数学家大会的晨兴应用数学金奖；泛华统计协会许宝騄奖； Jerome Sacks 杰出交叉学科贡献奖，泛华统计协会杰出成就奖；2014年被ISI评为论文高频引用的数学家。刘军教授在各类国际顶尖学术杂志及书刊上发表论文300余篇和一本专著， 被引用近8万7千余次。

统计与数据科学系

2024-11-25