Please use this identifier to cite or link to this item:
Title: Convergence rates to the Marchenko-Pastur type distribution
Authors: Bai, Z.
Hu, J.
Zhou, W. 
Keywords: Convergence rate
Sample covariance matrix
Spectral distribution
Issue Date: Jan-2012
Citation: Bai, Z., Hu, J., Zhou, W. (2012-01). Convergence rates to the Marchenko-Pastur type distribution. Stochastic Processes and their Applications 122 (1) : 68-92. ScholarBank@NUS Repository.
Abstract: S n = 1 n T 1/2 n X nX n T 1/2 n , where X n = (xi j ) is a p n matrix consisting of independent complex entries with mean zero and variance one, Tn is a p p nonrandom positive definite Hermitian matrix with spectral norm uniformly bounded in p. In this paper, if supn supi, j E | x 8 i j |> ∞ and y n = p/n > 1 uniformly as n → ∞, we obtain that the rate of the expected empirical spectral distribution of Sn converging to its limit spectral distribution is O(n 1/2). Moreover, under the same assumption, we prove that for any < 0, the rates of the convergence of the empirical spectral distribution of Sn in probability and the almost sure convergence are O(n 2/5) and O(n 2/5+) respectively. © 2011 Elsevier B.V. All rights reserved.
Source Title: Stochastic Processes and their Applications
ISSN: 03044149
DOI: 10.1016/
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.