Chi-Square Approximation for the Distribution of Individual Eigenvalues of a Singular Wishart Matrix

Abstract

This paper discusses the approximate distributions of eigenvalues of a singular Wishart matrix. We give the approximate joint density of eigenvalues by Laplace approximation for the hypergeometric functions of matrix arguments. Furthermore, we show that the distribution of each eigenvalue can be approximated by the chi-square distribution with varying degrees of freedom when the population eigenvalues are infinitely dispersed. The derived result is applied to testing the equality of eigenvalues in two populations.

Keywords

• hypergeometric functions
• laplace approximation
• spiked covariance model