A novel moment-based sufficient dimension reduction approach in multivariate regression

被引:11
|
作者
Yoo, Jae Keun [1 ]
机构
[1] Univ Louisville, Sch Publ Hlth & Informat Sci, Dept Bioinformat & Biostat, Louisville, KY 40202 USA
关键词
D O I
10.1016/j.csda.2008.01.004
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Recently, a moment-based sufficient dimension reduction methodology in multivariate regression, focusing on the first two moments, was introduced. We present in this article a novel approach of the earlier method in roughly the same context. This novel method possesses several desirable properties that the earlier method did not have such as dimension tests with chi-squared distributions,. predictor effects test without assuming any model, and so on. Simulated and real data examples are presented for studying various properties of the proposed method and for a numerical comparison to the earlier method. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:3843 / 3851
页数:9
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