Limiting spectral distribution for a type of sample covariance matrices

DOI10.1007/s13226-013-0037-4zbMath1279.62042OpenAlexW2053596761MaRDI QIDQ395125

Junshan Xie

Publication date: 28 January 2014

Published in: Indian Journal of Pure \& Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s13226-013-0037-4

zbMATH Keywords

empirical spectral distributionisotropic log-concave random vector

Mathematics Subject Classification ID

Asymptotic distribution theory in statistics (62E20) Central limit and other weak theorems (60F05) Inference from stochastic processes and spectral analysis (62M15)

Cites Work

• On the Marchenko-Pastur and circular laws for some classes of random matrices with dependent entries
• Random points in the unit ball of \(\ell^{ n }_{ p }\)
• Power-law estimates for the central limit theorem for convex sets
• Analysis of the limiting spectral distribution of large dimensional information-plus-noise type matrices
• On the empirical distribution of eigenvalues of a class of large dimensional random matrices
• Strong convergence of the empirical distribution of eigenvalues of large dimensional random matrices
• On the empirical distribution of eigenvalues of large dimensional information-plus-noise-type matrices
• On the limiting empirical measure of eigenvalues of the sum of rank one matrices with log-concave distribution
• Quantitative estimates of the convergence of the empirical covariance matrix in log-concave ensembles
• Limit Theorem for the Eigenvalues of the Sample Covariance Matrix when the Underlying Distribution is Isotropic
• DISTRIBUTION OF EIGENVALUES FOR SOME SETS OF RANDOM MATRICES
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