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  • 统计与管理学院2018年学术报告第16期

    【主 题】 Doubly Robust Sure Screening for Elliptical Copula Regression Model

    【报告人】 何勇  副教授

    山东财经大学

    【时 间】 2018年05月19日(星期六)10:30-11:30

    【地 点】 上海财经大学统计与管理学院大楼1114报告厅

    摘 要】Regression analysis has always been a hot research area in statistics. We propose a very flexible semi-parametric regression model called Elliptical Copula Regression (ECR) model, which covers a large class of linear and nonlinear regression models such as additive regression model, single index model. Besides, ECR model can model the heavy-tailed data and tail dependence between variables, thus it could be widely applied in many areas such as econometrics and finance. In this paper we mainly focus on the feature screening problem for ECR model in ultra-high dimensional setting. We propose a doubly robust sure screening procedure for ECR model, in which two types of correlation coefficient are involved: Kendall' tau correlation and Canonical correlation.  Theoretical analysis shows that the procedure enjoys sure screening property, i.e., with probability tending to 1, the screening procedure selects out all important variables and substantially reduces the dimensionality to a moderate size against the sample size. Thorough numerical studies are conducted to illustrate its advantage over existing sure independence screening methods and thus it can be used as a safe replacement of the existing procedures in practice. At last, the proposed procedure is applied on a gene-expression real data set to show its empirical usefulness.