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

Let , where is a random symmetric matrix, a random symmetric matrix, and with being independent real random variables. Suppose that , and are independent. It is proved that the empirical spectral distribution of the eigenvalues of random symmetric matrices converges almost surely to a non-random distribution.

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Year of publication:	2010
Authors:	Pan, Guangming
Published in:	Journal of Multivariate Analysis. - Elsevier, ISSN 0047-259X. - Vol. 101.2010, 6, p. 1330-1338
Publisher:	Elsevier
Keywords:	Empirical distribution Random matrices Stieltjes transform

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008488072