On limiting spectral distribution of product of two random matrices when the underlying distribution is isotropic

DOI10.1016/0047-259X(86)90103-XzbMath0657.62058OpenAlexW2089295381MaRDI QIDQ1110954

Y. Q. Yin, P. R. Krishnaiah, Zhi-Dong Bai

Publication date: 1986

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0047-259x(86)90103-x

zbMATH Keywords

limiting spectral distributionlarge dimensionsmultivariate normal populationisotropic distributioncentral multivariate F matrixcentral Wishart matricesnonnegative definite symmetric random matrix

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Estimation in multivariate analysis (62H12) Asymptotic distribution theory in statistics (62E20)

Related Items

Non-asymptotic properties of spectral decomposition of large Gram-type matrices and applications, On the limit of the largest eigenvalue of the large dimensional sample covariance matrix, On limit theorem for the eigenvalues of product of two random matrices, On limiting spectral distribution of product of two random matrices when the underlying distribution is isotropic, The norm of polynomials in large random and deterministic matrices, On singular values of large dimensional lag-\(\tau\) sample auto-correlation matrices, Central limit theorems for linear spectral statistics of large dimensional \(F\)-matrices, Limiting spectral distribution of a symmetrized auto-cross covariance matrix, High-dimensional linear models: a random matrix perspective, In memoriam: Paruchuri Rama Krishnaiah (1932--1987). A tribute, Limiting spectral distribution for a class of random matrices

Cites Work

• Unnamed Item
• Comments on a result of Yin, Bai, and Krishnaiah for large dimensional multivariate F matrices
• Limiting behavior of the eigenvalues of a multivariate F matrix
• A limit theorem for the eigenvalues of product of two random matrices
• On limiting spectral distribution of product of two random matrices when the underlying distribution is isotropic
• The limiting empirical measure of multiple discriminant ratios
• The strong limits of random matrix spectra for sample matrices of independent elements
• The Limiting Eigenvalue Distribution of a Multivariate F Matrix