The random matrix regime of Maronna's M-estimator with elliptically distributed samples

被引:40
作者
Couillet, Romain [1 ]
Pascal, Frederic [1 ]
Silverstein, Jack W. [2 ]
机构
[1] Univ Paris 11, CNRS, UMR 8506, Signaux & Syst Lab,L2S,CentraleSupelec, F-91192 Gif Sur Yvette, France
[2] N Carolina State Univ, Dept Math, Raleigh, NC 27695 USA
关键词
Random matrix theory; Robust estimation; Elliptical distribution; LIMITING SPECTRAL DISTRIBUTION; COVARIANCE MATRICES; PERFORMANCE ANALYSIS; LARGEST EIGENVALUE; NO EIGENVALUES; LOCATION; SUPPORT; SIGNALS;
D O I
10.1016/j.jmva.2015.02.020
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
This article demonstrates that the robust scatter matrix estimator (C) over cap (N) is an element of C-NxN of a multivariate elliptical population x(1), ... ,x(n) is an element of C-N originally proposed by Maronna in 1976, and defined as the solution (when existent) of an implicit equation, behaves similar to a well-known random matrix model in the limiting regime where the population N and sample n sizes grow at the same speed. We show precisely that (C) over cap (N) is an element of C-NxN is defined for all n large with probability one and that, under some light hypotheses, parallel to(C) over cap (N) - (S) over cap (N)parallel to -> 0 almost surely in spectral norm, where (S) over cap (N) follows a classical random matrix model. As a corollary, the limiting eigenvalue distribution of (C) over cap (N) is derived. This analysis finds applications in the fields of statistical inference and signal processing. (C) 2015 Elsevier Inc. All rights reserved.
引用
收藏
页码:56 / 78
页数:23
相关论文
共 42 条
[1]  
[Anonymous], J MULTIVARIATE UNPUB
[2]  
Bai Z., 2009, SPRINGER SERIES STAT
[3]  
Bai Z.D., 2008, LIMIT THEOREMS SAMPL
[4]  
Bai ZD, 1998, ANN PROBAB, V26, P316
[5]   Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices [J].
Baik, J ;
Ben Arous, G ;
Péché, S .
ANNALS OF PROBABILITY, 2005, 33 (05) :1643-1697
[6]   Eigenvalues of large sample covariance matrices of spiked population models [J].
Baik, Jinho ;
Silverstein, Jack W. .
JOURNAL OF MULTIVARIATE ANALYSIS, 2006, 97 (06) :1382-1408
[7]   Performance of Statistical Tests for Single-Source Detection Using Random Matrix Theory [J].
Bianchi, P. ;
Debbah, M. ;
Maida, M. ;
Najim, J. .
IEEE TRANSACTIONS ON INFORMATION THEORY, 2011, 57 (04) :2400-2419
[8]  
Billingsley P., 1995, Probability and Measure, Vthird
[9]   Cooperative spectrum sensing using random matrix theory [J].
Cardoso, Leonardo S. ;
Debbah, Merouane ;
Bianchi, Pascal ;
Najim, Jamal .
2008 3RD INTERNATIONAL SYMPOSIUM ON WIRELESS PERVASIVE COMPUTING, VOLS 1-2, 2008, :334-+
[10]   Analysis of the limiting spectral measure of large random matrices of the separable covariance type [J].
Couillet, Romain ;
Hachem, Walid .
RANDOM MATRICES-THEORY AND APPLICATIONS, 2014, 3 (04)