11 citations to https://www.mathnet.ru/rus/ecp2
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Wangjun Yuan, “On spectrum of sample covariance matrices from large tensor vectors”, ALEA, 21:2 (2024), 1527
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П. А. Яськов, “Об асимптотике спектра случайных матриц с независимыми элементами”, УМН, 79:5(479) (2024), 181–182
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П. А. Яськов, “О достаточных условиях в теореме Марченко–Пастура”, Теория вероятн. и ее примен., 68:4 (2023), 813–833 ; P. A. Yaskov, “Sufficient conditions for the Marchenko–Pastur theorem”, Theory Probab. Appl., 68:4 (2024), 657–673
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Pavel Yaskov, “Marchenko–Pastur law for a random tensor model”, Electron. Commun. Probab., 28 (2023), 23–17
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П. А. Яськов, “Предельный спектр выборочных ковариационных матриц растущей размерности с граф-зависимыми элементами”, Теория вероятн. и ее примен., 67:3 (2022), 471–488 ; P. A. Yaskov, “Limiting spectral distribution for large sample covariance matrices with graph-dependent elements”, Theory Probab. Appl., 67:3 (2022), 375–388
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Benoît Collins, Jianfeng Yao, Wangjun Yuan, “On spectral distribution of sample covariance matrices from large dimensional and large k-fold tensor products”, Electron. J. Probab., 27:none (2022)
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Pavel Yaskov, “Limit of the smallest eigenvalue of a sample covariance matrix for spherical and related distributions”, Springer Proc. Math. Statist., 371 (2021), 229–241
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G. L. Zitelli, “Random matrix models for datasets with fixed time horizons”, Quantitative Finance, 20:5 (2020), 769
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M Kornyik, “A note on the asymptotics of random density matrices”, J. Phys. Commun., 2:4 (2018), 045012
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Pavel Yaskov, “LLN for quadratic forms of long memory time series and its applications in random matrix theory”, J. Theor. Probability, 31:4 (2018), 2032–2055