An asymptotic test for redundancy of variables in the comparison of two covariance matrices

Bernhard N. Flury

Statistics & Probability Letters, 1986, vol. 4, issue 3, 123-126

Abstract: Let [Sigma]1 and [Sigma]2 denote the p.d.s. covariance matrices of two p-variate normal populations, let [lambda]1 [greater-or-equal, slanted] [lambda]2 [lambda] ... [greater-or-equal, slanted] [lambda]p > 0 denote the characteristic roots of [Sigma]1-1 [Sigma]2, and [beta]1,...,[beta]p the associated characteristic vectors. An asymptotic chi squared test statistic is derived for the hypothesis that some m characteristic vectors depend only on q (

Keywords: eigenvectors; spectral; decomposition; normal; distribution; elliptical; distribution (search for similar items in EconPapers)
Date: 1986
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/0167-7152(86)90074-X
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:4:y:1986:i:3:p:123-126

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

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 ().