Random matrices;
Sample covariance matrices;
Marcenko-Pastur law;
Dependent random variables;
EIGENVALUES;
THEOREMS;
LIMIT;
D O I:
10.1016/j.jmva.2012.08.004
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:
It is known (Hofmann-Credner and Stolz (2008) [4]) that the convergence of the mean empirical spectral distribution of a sample covariance matrix W-n = 1/n YnYnt to the Martenko-Pastur law remains unaffected if the rows and columns of Y-n exhibit some dependence, where only the growth of the number of dependent entries, but not the joint distribution of dependent entries needs to be controlled. In this paper we show that the well-known CLT for traces of powers of W-n also extends to the dependent case. (C) 2012 Elsevier Inc. All rights reserved.
机构:
Hefei Univ Technol, Sch Math, Hefei, Peoples R ChinaNanyang Technol Univ, Div Math Sci, Sch Phys & Math Sci, Singapore, Singapore
Hui, Jun
Pan, Guangming
论文数: 0引用数: 0
h-index: 0
机构:
Nanyang Technol Univ, Div Math Sci, Sch Phys & Math Sci, Singapore, SingaporeNanyang Technol Univ, Div Math Sci, Sch Phys & Math Sci, Singapore, Singapore
机构:
Univ Toronto, Dept Stat Sci, Sidney Smith Hall,100 St George St, Toronto, ON M5S 3G3, CanadaUniv Toronto, Dept Stat Sci, Sidney Smith Hall,100 St George St, Toronto, ON M5S 3G3, Canada