报告题目：Quantile correlation-based variable selection
报 告 人：唐年胜 教授 云南大学
报告时间：2021年7月1日 16:00-17:00
报告地点：腾讯会议 ID：697 814 152 会议密码：0701
校内联系人：朱复康 fzhu@jlu.edu.cn
报告摘要：This paper is concerned with identifying important features in high dimensional data analysis, especially when there are complex relationships among predictors. Without any specification of an actual model, we first introduce a multiple testing procedure based on the quantile correlation to select important predictors in high dimensionality. The quantile-correlation statistic is able to capture a wide range of dependence. A stepwise procedure is studied for further identifying important variables. Moreover, a sure independent screening based on the quantile correlation is developed in handling ultrahigh dimensional data. It is computationally efficient and easy to implement. We establish the theoretical properties under mild conditions. Numerical studies including simulation studies and real data analysis contain supporting evidence that the proposal performs reasonably well in practical settings.
报告人简介：唐年胜，云南大学二级教授、数学与统计学院院长、博士生导师。国家杰出青年科学基金获得者，入选教育部“新世纪优秀人才”计划、国家百千万人才工程，获得“国家有突出贡献中青年专家”荣誉称号，享受国务院政府特殊津贴；云南省科技领军人才、首批“云岭学者”和“省委联系专家”、中青年学术和技术带头人、云南省高等学校教学名师，云南省高校“统计与信息技术重点实验室”负责人，“云南大学复杂数据统计推断方法研究”省创新团队带头人；国际统计学会推选会员（Elected ISI Member），国际泛华统计学会理事会成员（Board of Directors）；2018年获ICSA杰出服务奖。主要从事统计诊断、非线性模型、生物医学统计等方面的研究，在国内外学术刊物发表论文150余篇，其中SCI检索120余篇；获得省部级科研奖励9项。
