Unified predictor hypothesis tests in sufficient dimension reduction: A bootstrap approach

被引：5
|
作者：
Yoo, Jae Keun [1 ]
机构：
[1] Ewha Womans Univ, Dept Stat, Seoul 120750, South Korea
来源：
JOURNAL OF THE KOREAN STATISTICAL SOCIETY | 2011年 / 40卷 / 02期
关键词：
Bootstrapping; Predictor hypothesis tests; Sufficient dimension reduction; Vector correlation coefficient; PRINCIPAL HESSIAN DIRECTIONS;
D O I：
10.1016/j.jkss.2010.09.006
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
In this paper, we newly define a unified predictor hypothesis that is applicable to all sufficient dimension reduction (SDR) methodologies. To test the predictor hypothesis, we propose a bootstrap approach by measuring the distances between reference subspaces and bootstrap subspaces. To measure the distances between two subspaces, the vector correlation coefficient is considered. Simulation studies confirm the background reasoning of the proposed tests. (C) 2010 The Korean Statistical Society. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码：217 / 225
页数：9
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