Analysis of the limiting spectral distribution of large dimensional information-plus-noise type matrices

被引:46
|
作者
Dozier, R. Brent [1 ]
Silverstein, Jack W. [1 ]
机构
[1] N Carolina State Univ, Raleigh, NC 27695 USA
关键词
random matrix; empirical distribution function of eigenvalues; Stieltjes transform;
D O I
10.1016/j.jmva.2006.12.005
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
A derivation of results on the analytic behavior of the limiting spectral distribution of sample covariance matrices of the "information-plus-noise" type, as studied in Dozier and Silverstein [On the empirical distribution of eigenvalues of large dimensional information-plus-noise type matrices, 2004, submitted for publication], is presented. It is shown that, away from zero, the limiting distribution possesses a continuous density. The density is analytic where it is positive and, for the most relevant cases of a in the boundary of its support, exhibits behavior closely resembling that of root vertical bar x-a vertical bar for x near a. A procedure to determine its support is also analyzed. (c) 2007 Elsevier Inc. All rights reserved.
引用
收藏
页码:1099 / 1122
页数:24
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