High-dimensional sample covariance matrices with Curie-Weiss entries

被引:5
作者
Fleermann, Michael [1 ]
Heiny, Johannes [2 ]
机构
[1] Fernuniv, Fak Math & Informat, Univ Str 1, D-58084 Hagen, Germany
[2] Ruhr Univ Bochum, Fak Math, Univ Str 150, D-44801 Bochum, Germany
来源
ALEA-LATIN AMERICAN JOURNAL OF PROBABILITY AND MATHEMATICAL STATISTICS | 2020年 / 17卷 / 02期
关键词
Curie-Weiss; random matrix; Marcenko-Pastur law; semicircle law; high dimension; dependent entries; full correlation; SEMICIRCLE LAW; EIGENVALUES; CONVERGENCE; INDEPENDENCE; LIMIT;
D O I
10.30757/ALEA.v17-33
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
We study the limiting spectral distribution of sample covariance matrices XXT, where X are p x n random matrices with correlated entries and p/n -> y is an element of [0, infinity). If y > 0, we obtain the Marcenko-Pastur distribution and in the case y = 0 the semicircle distribution after appropriate rescaling. The entries we consider are Curie-Weiss spins, which are correlated random signs, where the degree of the correlation is governed by an inverse temperature beta > 0. The model exhibits a phase transition at beta = 1. The correlation between any two entries is of order O((np)(-1)) for beta is an element of (0, 1), O ((np)(-1/2)) for beta = 1, and for beta > 1 the correlation does not vanish in the limit. In our proofs we use Stieltjes transforms and concentration of random quadratic forms.
引用
收藏
页码:857 / 876
页数:20
相关论文
共 31 条
[11]   CONCENTRATION OF MEASURE AND SPECTRA OF RANDOM MATRICES: APPLICATIONS TO CORRELATION MATRICES, ELLIPTICAL DISTRIBUTIONS AND BEYOND [J].
El Karoui, Noureddine .
ANNALS OF APPLIED PROBABILITY, 2009, 19 (06) :2362-2405
[12]  
Fleermann M., 2019, THESIS
[13]  
Fleermann M., 2019, ARXIV190708782
[14]  
Fleermann M., 2020, LOCAL LAWS CURIE WEI
[15]   The almost sure semicircle law for random band matrices with dependent entries [J].
Fleermann, Michael ;
Kirsch, Werner ;
Kriecherbauer, Thomas .
STOCHASTIC PROCESSES AND THEIR APPLICATIONS, 2021, 131 :172-200
[16]   A phase transition for the limiting spectral density of random matrices [J].
Friesen, Olga ;
Loewe, Matthias .
ELECTRONIC JOURNAL OF PROBABILITY, 2013, 18 :1-17
[17]   A LIMIT-THEOREM FOR THE NORM OF RANDOM MATRICES [J].
GEMAN, S .
ANNALS OF PROBABILITY, 1980, 8 (02) :252-261
[18]  
Heiny J., 2020, ARXIV200303857
[19]   The eigenstructure of the sample covariance matrices of high-dimensional stochastic volatility models with heavy tails [J].
Heiny, Johannes ;
Mikosch, Thomas .
BERNOULLI, 2019, 25 (4B) :3590-3622
[20]   Almost sure convergence of the largest and smallest eigenvalues of high-dimensional sample correlation matrices [J].
Heiny, Johannes ;
Mikosch, Thomas .
STOCHASTIC PROCESSES AND THEIR APPLICATIONS, 2018, 128 (08) :2779-2815