Title

Weighted chi-squared tests for partial common principal component subspaces

Authors

Authors

J. R. Schott

Abbreviated Journal Title

Biometrika

Keywords

correlation matrix; dimensionality reduction; principal components; analysis; SAMPLE CORRELATION MATRIX; Biology; Mathematical & Computational Biology; Statistics & Probability

Abstract

We consider tests of the null hypothesis that g covariance matrices have a partial common principal component subspace of dimension s. Our approach uses a dimensionality matrix which has its rank equal to s when the hypothesis holds. The test can then be based on a statistic computed from the eigenvalues of an estimate of this dimensionality matrix. The asymptotic distribution of this' statistic is that of a linear combination of independent one-degree-of-freedom chi-squared random variables. Simulation results indicate that this test yields significance levels that come closer to the nominal level than do those of a previously proposed method. The procedure is also extended to a test that g correlation matrices have a partial common principal component subspace.

Journal Title

Biometrika

Volume

90

Issue/Number

2

Publication Date

1-1-2003

Document Type

Article

Language

English

First Page

411

Last Page

421

WOS Identifier

WOS:000183818500012

ISSN

0006-3444

Share

COinS