报告人:钟威(厦门大学)
时间:2022年05月30日10:30开始
腾讯会议ID:512 159 605
点击链接入会:https://meeting.tencent.com/dm/MKDWVraMP9ep
摘要:This paper studies the projection test for high-dimensional mean vectors via optimal projection. The idea of projection test is to project high-dimensional data onto a space of low dimension such that traditional methods can be applied. We propose a new estimation for the optimal projection direction by solving a constrained and regularized quadratic programming. The test is constructed using the estimated optimal projection direction. It is based on a data-splitting procedure, which achieves an exact t-test under normality assumption. To mitigate the power loss due to data-splitting, we further propose an online framework, which iteratively updates the estimation of projection direction when new observations arrive. Various simulation studies as well as a real data example show that the proposed online-style projection test retains the type I error rate well and is more powerful than other existing tests.
简介:钟威,现任厦门大学王亚南经济研究院和经济学院统计系教授、博士生导师。2012年获得美国宾夕法尼亚州立大学统计学博士学位,2014年和2017年分别破格晋升副教授和教授,2018年入选厦门大学“南强青年拔尖人才”(A类),国家自然科学基金优秀青年基金获得者(2019),福建省杰出青年基金获得者(2019)。主要从事高维数据统计分析、统计学习算法、计量经济学、统计学和数据科学的应用等研究。担任美国统计协会(ASA)期刊《Statistical Analysis and Data Mining》和加拿大统计学会期刊《Canadian Journal of Statistics》的AE,在The Annals of Statistics, Journal of the American Statistical Association, Biometrika, Journal of Econometrics, Journal of Business & Economic Statistics, Biometrics, Annals of Applied Statistics, Statistica Sinica,中国科学数学等国内外统计学权威期刊发表(含接收)20多篇论文,其中入选ESI前1%高被引论文2篇。主要讲授《数理统计》、《广义线性模型》、《计量经济学》、《统计数据分析》等本科和研究生课程,多次获得学院教学优秀奖,2016年获得厦门大学第五届英语教学比赛一等奖,2020年获得厦门大学第十五届青年教师技能比赛特等奖,2021年获得厦门大学教学创新大赛一等奖,2021年获得福建省“向上向善好青年”称号。个人主页:https://wise.xmu.edu.cn/people/faculty/bd5bc78c-99d3-46b0-873d-32fa79a278f5.html
邀请人:夏小超
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