Ultrahigh dimensional feature screening for additive model with multivariate response

被引：0

作者：

Liu, Shishi ^{[1
]}

Li, Xiangjie ^{[1
]}

Zhang, Jingxiao ^{[1
]}

机构：

[1] Renmin Univ China, Sch Stat, Ctr Appl Stat, Beijing 100872, Peoples R China

来源：

JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION | 2020年 / 90卷 / 05期

关键词：

Feature screening; additive model; multivariate response; generalized correlation; sure screening; ranking consistency; VARIABLE SELECTION; REGRESSION;

D O I：

10.1080/00949655.2019.1703371

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

We consider feature screening for ultrahigh dimensional additive model with multivariate response in this paper. A new method named generalized correlation based projection screening is proposed by using generalized correlation between each predictor and multivariate response. The sure screening and ranking consistency properties are established under some regularized conditions for the proposed procedure. In addition, we construct an iterative version of the proposed screening procedure to enhance the finite sample screening performance. Both simulation studies and the real data analysis demonstrate that the proposed method works effectively.

引用

页码：775 / 799

页数：25

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