Tests for the Equality of Two Covariance Matrices in Relation to a Best Linear Discriminator Analysis
Dempster, A. P.
Ann. Math. Statist., Tome 35 (1964) no. 4, p. 190-199 / Harvested from Project Euclid
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.
Publié le : 1964-03-14
Classification: 
@article{1177703741,
     author = {Dempster, A. P.},
     title = {Tests for the Equality of Two Covariance Matrices in Relation to a Best Linear Discriminator Analysis},
     journal = {Ann. Math. Statist.},
     volume = {35},
     number = {4},
     year = {1964},
     pages = { 190-199},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1177703741}
}
Dempster, A. P. Tests for the Equality of Two Covariance Matrices in Relation to a Best Linear Discriminator Analysis. Ann. Math. Statist., Tome 35 (1964) no. 4, pp.  190-199. http://gdmltest.u-ga.fr/item/1177703741/