报告题目：Chatterjee相关系数相关研究

报告时间：2026年9月11日下午14:30

报告地点：北湖东校区数统新楼201室

主办单位：欧洲杯 /科研处

报告人：李启寨

报告人简介：李启寨，中国科学院数学与系统科学研究院研究员，系统科学研究所副所长；2001年本科毕业于中国科学技术大学，2006年博士毕业于中国科学院数学与系统科学研究院，2006-2009年在美国国立卫生健康研究院(NIH)国家癌症研究所(NCI)从事博士后研究；研究方向：生物医学统计、遗传统计、复杂数据推断；在Nature Genetics, Science Advances, Angewandte Chemie International Edition, Cancer Research, AJHG, Bioinformatics,IEEE TPAMI, Psychometrika, JASA, JRSSB, Biometrics等期刊发表学术论文130余篇；曾获美国统计学会会士(ASA Fellow, 2020),国际统计学会当选会员(ISI Elected Member, 2016),中国工业与应用数学学会优秀青年学者奖(2015);主持及曾主持国家自然科学基金重点、杰青、优青、面上、青年5项；现任中国现场统计研究会党委书记、副理事长，中国数学会常务理事等。

摘要：Quantifying the strength of functional dependence between random variables is a fundamental statistical problem. We propose a family of simple and computationally efficient correlation coefficients that encompasses a wide class of dependency measures, including the Chatterjee’s correlation coefficient as a special case. We prove that each of our correlation coefficients converges to a population-level correlation measure as the sample size grows, and a central limit theorem is established under the assumption of independence. We also consider the conditional Azadkia and Chatterjee’s measure. We prove that, under general dependence, it is asymptotically normal and its limiting variance admits a closed form. We also construct consistent variance estimators that are computationally efficient and implementable in O(n log n) time.