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Zapiski Nauchnykh Seminarov POMI, 2022, Volume 510, Pages 65–86 (Mi znsl7194)  

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
References:
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
English version:
Journal of Mathematical Sciences (New York), 2024, Volume 286, Issue 5, Pages 668–683
DOI: https://doi.org/10.1007/s10958-024-07533-y
Bibliographic databases:
Document Type: Article
UDC: 519.2
Language: English
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
Citation in format AMSBIB
\Bibitem{GotTikTim22}
\by F.~G\"otze, A.~N.~Tikhomirov, D.~A.~Timushev
\paper Local laws for sparse sample covariance matrices without the truncation condition
\inbook Probability and statistics. Part~32
\serial Zap. Nauchn. Sem. POMI
\yr 2022
\vol 510
\pages 65--86
\publ POMI
\publaddr St.~Petersburg
\mathnet{http://mi.mathnet.ru/znsl7194}
\mathscinet{https://mathscinet.ams.org/mathscinet-getitem?mr=4503189}
\transl
\jour J. Math. Sci. (N. Y.)
\yr 2024
\vol 286
\issue 5
\pages 668--683
\crossref{https://doi.org/10.1007/s10958-024-07533-y}
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