Universality for the largest eigenvalue of sample covariance matrices with general population

This paper is aimed at deriving the universality of the largest eigenvalue of a class of high-dimensional real or complex sample covariance matrices of the form WN = Σ 1 /2 XX* Σ 1/2. Here, X = (xij)M,N is an M x N random matrix with independent entries xij, 1 ≤ i ≤ M, 1 ≤ j ≤ N such that Exij = 0,...

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Main Authors: Bao, Zhigang, Pan, Guangming, Zhou, Wang
Other Authors: School of Physical and Mathematical Sciences
Format: Article
Language:English
Published: 2015
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Online Access:https://hdl.handle.net/10356/106732
http://hdl.handle.net/10220/25091
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spelling sg-ntu-dr.10356-1067322023-02-28T19:44:04Z Universality for the largest eigenvalue of sample covariance matrices with general population Bao, Zhigang Pan, Guangming Zhou, Wang School of Physical and Mathematical Sciences DRNTU::Science::Mathematics::Statistics This paper is aimed at deriving the universality of the largest eigenvalue of a class of high-dimensional real or complex sample covariance matrices of the form WN = Σ 1 /2 XX* Σ 1/2. Here, X = (xij)M,N is an M x N random matrix with independent entries xij, 1 ≤ i ≤ M, 1 ≤ j ≤ N such that Exij = 0, E|xij|2 = 1/N. On dimensionality, we assume that M = M(N) and N/M → d ∈ (0, ∞) as N → ∞. For a class of general deterministic positive-definite M x M matrices Σ, under some additional assumptions on the distribution of xij's, we show that the limiting behavior of the largest eigenvalue of WN is universal, via pursuing a Green function comparison strategy raised in [Probab. Theory Related Fields 154 (2012) 341-407, Adv. Math. 229 (2012) 1435-1515] by Erdős, Yau and Yin for Wigner matrices and extended by Pillai and Yin [Ann. Appl. Probab. 24 (2014) 935-1001] to sample covariance matrices in the null case (Σ = I). Consequently, in the standard complex case (Exij2 = 0), combing this universality property and the results known for Gaussian matrices obtained by El Karoui in [Ann. Probab. 35 (2007) 663-714] (nonsingular case) and Onatski in [Ann. Appl. Probab. 18 (2008) 470-490] (singular case), we show that after an appropriate normalization the largest eigenvalue of WN converges weakly to the type 2 Tracy—Widom distribution TW2). Moreover, in the real case, we show that when E is spiked with a fixed number of subcritical spikes, the type 1 Tracy—Widom limit TWi holds for the normalized largest eigenvalue of WN, which extends a result of Féral and Péché in [J. Math. Phys. 50 (2009) 073302] to the scenario of nondiagonal Σ and more generally distributed X. In summary, we establish the Tracy—Widom type universality for the largest eigenvalue of generally distributed sample covariance matrices under quite light assumptions on Σ. Applications of these limiting results to statistical signal detection and structure recognition of separable covariance matrices are also discussed. Published version 2015-02-25T05:33:31Z 2019-12-06T22:17:11Z 2015-02-25T05:33:31Z 2019-12-06T22:17:11Z 2015 2015 Journal Article Bao, Z., Pan, G., & Zhou, W. (2015). Universality for the largest eigenvalue of sample covariance matrices with general population. The annals of statistics, 43(1), 382-421. 0090-5364 https://hdl.handle.net/10356/106732 http://hdl.handle.net/10220/25091 10.1214/14-AOS1281 en The annals of statistics © 2015 Institute of Mathematical Statistics. This paper was published in The Annals of Statistics and is made available as an electronic reprint (preprint) with permission of Institute of Mathematical Statistics. The paper can be found at the following official DOI: [http://dx.doi.org/ 10.1214/14-AOS1281]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law. 40 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Science::Mathematics::Statistics
spellingShingle DRNTU::Science::Mathematics::Statistics
Bao, Zhigang
Pan, Guangming
Zhou, Wang
Universality for the largest eigenvalue of sample covariance matrices with general population
description This paper is aimed at deriving the universality of the largest eigenvalue of a class of high-dimensional real or complex sample covariance matrices of the form WN = Σ 1 /2 XX* Σ 1/2. Here, X = (xij)M,N is an M x N random matrix with independent entries xij, 1 ≤ i ≤ M, 1 ≤ j ≤ N such that Exij = 0, E|xij|2 = 1/N. On dimensionality, we assume that M = M(N) and N/M → d ∈ (0, ∞) as N → ∞. For a class of general deterministic positive-definite M x M matrices Σ, under some additional assumptions on the distribution of xij's, we show that the limiting behavior of the largest eigenvalue of WN is universal, via pursuing a Green function comparison strategy raised in [Probab. Theory Related Fields 154 (2012) 341-407, Adv. Math. 229 (2012) 1435-1515] by Erdős, Yau and Yin for Wigner matrices and extended by Pillai and Yin [Ann. Appl. Probab. 24 (2014) 935-1001] to sample covariance matrices in the null case (Σ = I). Consequently, in the standard complex case (Exij2 = 0), combing this universality property and the results known for Gaussian matrices obtained by El Karoui in [Ann. Probab. 35 (2007) 663-714] (nonsingular case) and Onatski in [Ann. Appl. Probab. 18 (2008) 470-490] (singular case), we show that after an appropriate normalization the largest eigenvalue of WN converges weakly to the type 2 Tracy—Widom distribution TW2). Moreover, in the real case, we show that when E is spiked with a fixed number of subcritical spikes, the type 1 Tracy—Widom limit TWi holds for the normalized largest eigenvalue of WN, which extends a result of Féral and Péché in [J. Math. Phys. 50 (2009) 073302] to the scenario of nondiagonal Σ and more generally distributed X. In summary, we establish the Tracy—Widom type universality for the largest eigenvalue of generally distributed sample covariance matrices under quite light assumptions on Σ. Applications of these limiting results to statistical signal detection and structure recognition of separable covariance matrices are also discussed.
author2 School of Physical and Mathematical Sciences
author_facet School of Physical and Mathematical Sciences
Bao, Zhigang
Pan, Guangming
Zhou, Wang
format Article
author Bao, Zhigang
Pan, Guangming
Zhou, Wang
author_sort Bao, Zhigang
title Universality for the largest eigenvalue of sample covariance matrices with general population
title_short Universality for the largest eigenvalue of sample covariance matrices with general population
title_full Universality for the largest eigenvalue of sample covariance matrices with general population
title_fullStr Universality for the largest eigenvalue of sample covariance matrices with general population
title_full_unstemmed Universality for the largest eigenvalue of sample covariance matrices with general population
title_sort universality for the largest eigenvalue of sample covariance matrices with general population
publishDate 2015
url https://hdl.handle.net/10356/106732
http://hdl.handle.net/10220/25091
_version_ 1759857976836882432