arXiv · 2004.09833
Expressing the largest eigenvalue of a singular beta F-matrix with heterogeneous hypergeometric functions
Abstract
In this paper, the exact distribution of the largest eigenvalue of a singular random matrix for multivariate analysis of variance (MANOVA) is discussed. The key to developing the distribution theory of eigenvalues of a singular random matrix is to use heterogeneous hypergeometric functions with two matrix arguments. In this study, we define the singular beta F-matrix and extend the distributions of a nonsingular beta F -matrix to the singular case. We also give the joint density of eigenvalues and the exact distribution of the largest eigenvalue in terms of heterogeneous hypergeometric functions.
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Koki Shimizu, Hiroki Hashiguchi. 2020-04-21. Expressing the largest eigenvalue of a singular beta F-matrix with heterogeneous hypergeometric functions. https://arxiv.org/abs/2004.09833
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