Strong convergence of the empirical distribution of eigenvalues of sample covariance matrices with a perturbation matrix

DOI10.1016/j.jmva.2010.02.001zbMath1191.15034OpenAlexW2038302754MaRDI QIDQ968484

Guangming Pan

Publication date: 5 May 2010

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

Full work available at URL: https://doi.org/10.1016/j.jmva.2010.02.001

zbMATH Keywords

Stieltjes transformrandom matricesempirical distributiondistribution of eigenvaluessample covariance matrices

Mathematics Subject Classification ID

Probability distributions: general theory (60E05) Eigenvalues, singular values, and eigenvectors (15A18) Random matrices (algebraic aspects) (15B52)

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Cites Work

• The eigenvalues and eigenvectors of finite, low rank perturbations of large random matrices
• On limit theorem for the eigenvalues of product of two random matrices
• Central limit theorem for linear eigenvalue statistics of random matrices with independent entries
• Distribution function inequalities for martingales
• Limiting spectral distribution for a class of random 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
• DISTRIBUTION OF EIGENVALUES FOR SOME SETS OF RANDOM MATRICES
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