The Annals of Mathematical Statistics
- Ann. Math. Statist.
- Volume 35, Number 1 (1964), 190-199.
Tests for the Equality of Two Covariance Matrices in Relation to a Best Linear Discriminator Analysis
Abstract
A pair of test statistics is proposed for the null hypothesis $\mathbf{\Sigma}_1 = \mathbf{\Sigma}_2$ when the data consists of a sample from each of the $p$-variate normal distributions $N(\mathbf{u}_1, \mathbf{\Sigma}_1)$ and $N(\mathbf{u}_2, \mathbf{\Sigma}_2)$. These tests are motivated in Section 1 and defined explicitly in Section 2. Section 3 proves a theorem which includes the null hypothesis distribution theory of the tests. Section 4 gives some details of the computation of the test statistics. An appendix describes the shadow property of concentration ellipsoids which facilitates the geometrical discussion earlier in the paper.
Article information
Source
Ann. Math. Statist., Volume 35, Number 1 (1964), 190-199.
Dates
First available in Project Euclid: 27 April 2007
Permanent link to this document
https://projecteuclid.org/euclid.aoms/1177703741
Digital Object Identifier
doi:10.1214/aoms/1177703741
Mathematical Reviews number (MathSciNet)
MR161420
Zentralblatt MATH identifier
0124.09604
JSTOR
links.jstor.org
Citation
Dempster, A. P. Tests for the Equality of Two Covariance Matrices in Relation to a Best Linear Discriminator Analysis. Ann. Math. Statist. 35 (1964), no. 1, 190--199. doi:10.1214/aoms/1177703741. https://projecteuclid.org/euclid.aoms/1177703741