Probability densities and distributions for spiked and general variance Wishart $\beta$-ensembles

Abstract

A Wishart matrix is said to be spiked when the underlying covariance matrix has a single eigenvalue $b$ different from unity. As $b$ increases through $b=2$, a gap forms from the largest eigenvalue to the rest of the spectrum, and with $b-2$ of order $N^{-1/3}$ the scaled largest eigenvalues form a well defined parameter dependent state. Recent works by Bloemendal and Virág [BV], and Mo, have quantified this parameter dependent state for real Wishart matrices from different viewpoints, and the former authors have done similarly for the spiked Wishart $\beta$-ensemble. The latter is defined in terms of certain random bidiagonal matrices. We use a recursive structure to give an alternative construction of the spiked and more generally the general variance Wishart $\beta$-ensemble, and we give the exact form of the joint eigenvalue PDF for the two matrices in the recurrence. In the case of real quaternion Wishart matrices ($\beta =4$) the latter is recognised as having appeared in earlier studies on symmetrized last passage percolation, allowing the exact form of the scaled distribution of the largest eigenvalue to be given. This extends and simplifies earlier work of Wang, and is an alternative derivation to a result in [BV]. We also use the construction of the spiked Wishart $\beta$-ensemble from [BV] to give a simple derivation of the explicit form of the eigenvalue PDF.

18 pages

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• The largest eigenvalue of real symmetric, Hermitian and Hermitian self-dual random matrix models with rank one external source, part I
• Limits of spiked random matrices II
• The averaged characteristic polynomial for the Gaussian and chiral Gaussian ensembles with a source
• Eigenvalue statistics for the sum of two complex Wishart matrices
• Rank one HCIZ at high temperature: interpolating between classical and free convolutions
• Scaling limits of correlations of characteristic polynomials for the Gaussian beta-ensemble with external source
• Painleve II in random matrix theory and related fields
• Hard edge for beta-ensembles and Painlevé III
• Hypergeometric Functions of Matrix Arguments and Linear Statistics of Multi-Spiked Hermitian Matrix Models
• Joint density of eigenvalues in spiked multivariate models
• Phase transitions for products of characteristic polynomials under Dyson Brownian motion
• On estimation in the reduced-rank regression with a large number of responses and predictors