报告题目：  High-Dimensional Extreme Quantile Regression

报告人：黎德元教授

报告时间：2025年4月29日（星期二）15:00-16:30

报告地点：数学科学学院205

摘要：The estimation of conditional quantiles at extreme tails is of great interest in numerous applications. Various methods that integrate regression analysis with an extrapolation strategy derived from extreme value theory have been proposed to estimate extreme conditional quantiles in scenarios with a fixed number of covariates. However, these methods become less effective in high-dimensional settings, where the number of covariates grows with the sample size. In this article, we develop new estimation methods tailored for extreme conditional quantiles with high-dimensional covariates. We establish the asymptotic properties of the proposed estimators and demonstrate their superior performance through simulation studies, particularly in scenarios of growing dimension and high dimension where existing methods may fail. Furthermore, the analysis of auto insurance data validates the efficacy of our methods in estimating extreme conditional insurance claims and selecting important variables.

报告人简介：黎德元，复旦大学管理学院统计与数据科学系教授，博士生导师。1997年、2000年毕业于北京大学数学科学学院概率统计系，分别获得学士学位和硕士学位；2004年毕业于荷兰Erasmus大学经济学院，获得博士学位；2005年至2007年在瑞士伯尔尼大学统计学系做博士后、研究助理；2008年至今任教于复旦大学管理学院统计与数据科学系。研究方向：极值统计、分位数回归、分布式统计推断、风险管理、隐私保护、因果推断。目前已在Annals of Statistics, JASA, Biometrika，Sinica, JBES, Journal of Economic Theory, Econometric Theory等统计学和经济学期刊上发表高水平学术论文40余篇，主持国家自然科学基金项目5项、教育部科研基金1项,海关总署“百日攻关”项目2项。目前担任中国现场统计研究会教育统计与管理分会副理事长、全国工业统计学教学研究会第十届理事会常务理事。

编辑：王苗   审核：蒋毅   终审：屈加文