报告题目：A Semiparametric Approach to Dimension Reduction
主讲人：马彦源教授（南卡罗莱纳大学）
时间：2015年7月3日15:00-16:00
地点：北院卓远楼305
主办单位：统计与数学学院
摘要：
We provide a novel and completely different approach to dimension-reduction problems from the existing literature. We cast the dimension reduction problem in a semiparametric estimation framework and derive estimating equations. Viewing this problem from the new angle allows us to derive a rich class of estimators, and obtain the classical dimension reduction techniques as special cases in this class. The semiparametric approach also reveals that in the inverse regression context while keeping the estimation structure intact, the common assumption of linearity and/or constant variance on the covariates can be removed at the cost of performing additional nonparametric regression. The semiparametric estimators without these common assumptions are illustrated through simulation studies and a real data example. This article has online supplementary material.
马彦源教授简介：应用数学博士（MIT），南卡罗莱纳大学统计系教授，主要研究领域为半参数模型，测量误差模型，降维理论，潜在变量模型等。在Annals of Statistics, Journal of the Royal Statistical Society (Series B), Journal of the American Statistical Association, Biometrika等顶级统计学期刊发表论文数十篇，现担任Journal of the Royal Statistical Society (Series B)的副主编。
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