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Concise Probability Distributions of Eigenvalues of Real-Valued Wishart Matrices

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arxiv 1402.6757 v2 pith:5GPRYKQ2 submitted 2014-02-27 cs.IT math.IT

classification cs.ITmath.IT
keywords distributionsmatricesarisesderivedeigenvalueintegralsplotsreal-valued
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In this paper, we consider the problem of deriving new eigenvalue distributions of real-valued Wishart matrices that arises in many scientific and engineering applications. The distributions are derived using the tools from the theory of skew symmetric matrices. In particular, we relate the multiple integrals of a determinant, which arises while finding the eigenvalue distributions, in terms of the Pfaffian of skew-symmetric matrices. Pfaffians being the square root of skew symmetric matrices are easy to compute than the conventional distributions that involve Zonal polynomials or beta integrals. We show that the plots of the derived distributions are exactly coinciding with the numerically simulated plots.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Application of Random Matrix Theory in High-Dimensional Statistics

    stat.ME 2024-12 conditional novelty 3.0 of 10

    A review of RMT in high-dimensional statistics that contributes a new CLT for the log-eigenvalues of Wishart matrices, with a flawed proof.

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