No eigenvalues outside the support of the limiting spectral distribution of large-dimensional sample covariance matrices

被引:1
|
作者
Bai, ZD
Silverstein, JW
机构
[1] Natl Univ Singapore, Dept Math, Singapore 119260, Singapore
[2] N Carolina State Univ, Dept Math, Raleigh, NC 27695 USA
来源
ANNALS OF PROBABILITY | 1998年 / 26卷 / 01期
关键词
random matrix; empirical distribution function of eigenvalues; Stieltjes transform;
D O I
暂无
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
Let B-n = (1/N)T-n(1/2) XnXn*T-n(1/2), where X-n is n x N with i.i.d, complex standardized entries having finite fourth moment and T(n)1/2 is a Hermitian square root of the nonnegative definite Hermitian matrix T-n. It is known that, as n --> infinity, if n/N converges to a positive number and the empirical distribution of the eigenvalues of T-n converges to a proper probability distribution, then the empirical distribution of the eigenvalues of B-n converges a.s. to a nonrandom limit. In this paper we prove that, under certain conditions on the eigenvalues of T-n, for any closed interval outside the support of the limit, with probability 1 there will be no eigenvalues in this interval for all n sufficiently large.
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页码:316 / 345
页数:30
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