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科学研究
RESEARCH
RANK: Large-Scale Inference with Graphical Nonlinear Knockoffs
时间  Datetime
2019-08-19 13:30 — 14:30
地点  Venue
Zoom APP(2)()
报告人  Speaker
李高荣
单位  Affiliation
北京师范大学
邀请人  Host
统计系
备注  remarks
Zoom 会议号:663 173 51260 会议密码: 753637
报告摘要  Abstract

摘要:Power and reproducibility are key to enabling refined scientific discoveries in contemporary big data applications with general high-dimensional nonlinear models. In this article, we provide theoretical foundations on the power and robustness for the model-X knockoffs procedure introduced recently in Candès, Fan, Janson and Lv in high-dimensional setting when the covariate distribution is characterized by Gaussian with known covariate distribution in high-dimensional linear models is asymptotically one as sample size goes to infinity. When moving away from the ideal case, we suggest the modified model-X knockoffs method called graphical nonlinear knockoffs (RANK) to accommodate the unknown covariate distribution. We provide theoretical justifications on the robustness of our modified procedure by showing that the false discovery rate (FDR) is asymptotically controlled at the target level and the power is asymptotically one with the estimated covariate distribution. To the best of our knowledge, this is the first formal theoretical result on the power for the knockoffs procedure. Simulation results demonstrate that compared to existing approaches, our method performs competitively in both FDR control and power. A real dataset is analyzed to further assess the performance of the suggested knockoffs procedure.


凯时kb88.com报告人简介:李高荣,北京师范大学统计学院教授,博士生导师。全国工业统计学教学研究会常务理事、中国概率统计学会第十一届理事、北京应用统计学会常务理事、中国现场统计研究会高维数据统计分会理事、生存分析分会理事和副秘书长、北京大数据协会理事和美国数学评论评论员。主要研究方向是非参数统计、高维统计、统计学习、纵向数据、测量误差数据和因果推断等。迄今为止,在Annals of Statistics, Journal of the American Statistical Association, Statistics and Computing, Statistica Sinica,中国科学:数学,和统计研究等学术期刊上发表学术论文90余篇。在科学出版社出版专著《纵向数据半参数模型》和《现代测量误差模型》,后者入选《现代数学基础丛书》系列。入选北京市属高等学校人才强教深化计划“中青年骨干人才培养计划”,北京市优秀人才培养资助计划和北京工业大学“京华人才”支持计划。主持国家自然科学基金、北京市自然科学基金和北京市教委科技计划面上项目等国家和省部级科研项目10余项。