Some sphericity tests for high dimensional data based on ratio of the traces of sample covariance matrices

Xue Ding

Statistics & Probability Letters, 2020, vol. 156, issue C

Abstract: In this paper, we investigate the sphericity test for high dimensional data. The test statistic is proposed based on the ratio of traces of sample covariance matrices. The asymptotic distributions of the test statistics under the null hypothesis are established by linear spectral statistics of large sample covariance matrices. We also obtain the asymptotic power functions in the case of the spiked population model as a specific alternative. Compared with some existing tests, the proposed test can handle data having unknown means and non-Gaussian population with general fourth moment. The numerical performance demonstrates that the proposed tests have satisfactory properties in terms of size and power.

Keywords: High dimensional data; Sphericity test; Random matrix theory; Spiked population model (search for similar items in EconPapers)
Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715219302597
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:stapro:v:156:y:2020:i:c:s0167715219302597

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.spl.2019.108613

Access Statistics for this article

Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul

More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().