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Convergence rate to the Tracy–Widom laws for the largest eigenvalue of sample covariance matrices
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.ORCID iD: 0000-0003-0954-3231
Institute of Science and Technology Austria.
2023 (English)In: The Annals of Applied Probability, ISSN 1050-5164, E-ISSN 2168-8737, Vol. 33, no 1, p. 677-725Article in journal (Refereed) Published
Abstract [en]

We establish a quantitative version of the Tracy–Widom law for the largest eigenvalue of high-dimensional sample covariance matrices. To be precise, we show that the fluctuations of the largest eigenvalue of a sample covariance matrix X∗X converge to its Tracy–Widom limit at a rate nearly N-1/3, where X is an M × N random matrix whose entries are independent real or complex random variables, assuming that both M and N tend to infinity at a constant rate. This result improves the previous estimate N-2/9 obtained by Wang (2019). Our proof relies on a Green function comparison method (Adv. Math. 229 (2012) 1435–1515) using iterative cumulant expansions, the local laws for the Green function and asymptotic properties of the correlation kernel of the white Wishart ensemble.

Place, publisher, year, edition, pages
Institute of Mathematical Statistics , 2023. Vol. 33, no 1, p. 677-725
Keywords [en]
rate of convergence, sample covariance matrix, Tracy–Widom law
National Category
Probability Theory and Statistics Mathematical Analysis
Identifiers
URN: urn:nbn:se:kth:diva-331094DOI: 10.1214/22-AAP1826ISI: 000946432400021Scopus ID: 2-s2.0-85150303441OAI: oai:DiVA.org:kth-331094DiVA, id: diva2:1780254
Note

QC 20230705

Available from: 2023-07-05 Created: 2023-07-05 Last updated: 2023-07-05Bibliographically approved

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Schnelli, Kevin

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