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Zapiski Nauchnykh Seminarov POMI, 2022, Volume 510, Pages 65–86
(Mi znsl7194)
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Local laws for sparse sample covariance matrices without the truncation condition
F. Götzea, A. N. Tikhomirovb, D. A. Timushevb a Faculty of Mathematics, Bielefeld University, Bielefeld, Germany
b Institute of Physics and Mathematics, Komi Science Center of Ural Division of RAS Syktyvkar, Russia
Abstract:
We consider sparse sample covariance matrices $\frac1{np_n}\mathbf X\mathbf X^*$, where $\mathbf X$ is a sparse matrix of order $n\times m$ with the sparse probability $p_n$. We prove the local Marchenko–Pastur law in some complex domain assuming that $np_n>\log^{\beta}n$, $\beta>0$ and some $(4+\delta)$-moment condition is fulfilled, $\delta>0$.
Key words and phrases:
Random matrices, sample covariance matrices, Marchenko–Pastur law.
Received: 20.09.2022
Citation:
F. Götze, A. N. Tikhomirov, D. A. Timushev, “Local laws for sparse sample covariance matrices without the truncation condition”, Probability and statistics. Part 32, Zap. Nauchn. Sem. POMI, 510, POMI, St. Petersburg, 2022, 65–86; J. Math. Sci. (N. Y.), 286:5 (2024), 668–683
Linking options:
https://www.mathnet.ru/eng/znsl7194 https://www.mathnet.ru/eng/znsl/v510/p65
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