A robust test for sphericity of high-dimensional covariance matrices

Xintao Tian, Yuting Lu and Weiming Li

Journal of Multivariate Analysis, 2015, vol. 141, issue C, 217-227

Abstract: This paper discusses the problem of testing the sphericity of a covariance matrix in high-dimensional frameworks. A new test procedure is put forward by taking the maximum of two existing statistics which are proved weakly independent in our settings. Asymptotic distribution of the new statistic is derived for generally distributed population with a finite fourth moment. Extensive simulations demonstrate that the proposed test has a great improvement in robustness of power against various models under the alternative hypothesis.

Keywords: Covariance matrix; High-dimensional data; Sphericity test (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0047259X15001797
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:jmvana:v:141:y:2015:i:c:p:217-227

Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01

DOI: 10.1016/j.jmva.2015.07.010

Access Statistics for this article

Journal of Multivariate Analysis is currently edited by de Leeuw, J.

More articles in Journal of Multivariate Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().