期刊
BIOMETRIKA
卷 101, 期 1, 页码 229-236出版社
OXFORD UNIV PRESS
DOI: 10.1093/biomet/ast040
关键词
Asymptotic normality; Large p; small n; Spatial median; Spatial sign; Sphericity test
资金
- National Natural Science Foundation
- Research Fund for the Doctoral Program of Higher Education of China
- Foundation for the Authors of National Excellent Doctoral Dissertations
- Program for New Century Excellent Talents in University
This article concerns tests for sphericity in cases where the data dimension is larger than the sample size. The existing multivariate sign-based procedure (Hallin & Paindaveine, 2006) for sphericity is not robust with respect to high dimensionality, producing tests with Type I error rates that are much larger than the nominal levels. This is mainly due to bias from estimating the location parameter. We develop a correction that makes the existing test statistic robust with respect to high dimensionality, and show that the proposed test statistic is asymptotically normal under elliptical distributions. The proposed method allows the dimensionality to increase as the square of the sample size. Simulations demonstrate that it has good size and power in a wide range of settings.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据