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Convergence Rate for Spectral Distributions of Large Dimensional Random Matrices
by
Z. D. Bai
Dept. of Stat. & Applied Probability, National University of Singapore
In this talk, I will introduce some Berry-Esseen type inequalities in terms of
Stieltjes transforms which provide a methodology to evaluate the convergence rate
of empirical spectral distributions of large dimensional random matrices as well
as some results on the convergence rates for large Wigner matrix and large sample
covariance matrix.
I will also introduce some applications of these inequalities to certain related areas, such as the applications to the exact spectrum separation of large sample covariance matrices, to the limiting distributions of rates of polynomials truncated from some analytic functions, etc.
Date received: September 10, 2001
Copyright © 2001 by the author(s). The author(s) of this document and the organizers of the conference have granted their consent to include this abstract in Atlas Conferences Inc. Document # cagd-61.