Strong Convergence of the Empirical Distribution of Eigenvalues of Large Dimensional Random Matrices

J. W. Silverstein

Journal of Multivariate Analysis, 1995, vol. 55, issue 2, 331-339

Abstract: Let X be n - N containing i.i.d. complex entries with E X11 - EX112 = 1, and T an n - n random Hermitian nonnegative definite, independent of X. Assume, almost surely, as n --> [infinity], the empirical distribution function (e.d.f.) of the eigenvalues of T converges in distribution, and the ratio n/N tends to a positive number. Then it is shown that, almost surely, the e.d.f. of the eigenvalues of (1/N) XX*T converges in distribution. The limit is nonrandom and is characterized in terms of its Stieltjes transform, which satisfies a certain equation.

Date: 1995
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