11 citations to https://www.mathnet.ru/rus/ecp2
  1. Wangjun Yuan, “On spectrum of sample covariance matrices from large tensor vectors”, ALEA, 21:2 (2024), 1527  crossref
  2. П. А. Яськов, “Об асимптотике спектра случайных матриц с независимыми элементами”, УМН, 79:5(479) (2024), 181–182  mathnet  crossref
  3. П. А. Яськов, “О достаточных условиях в теореме Марченко–Пастура”, Теория вероятн. и ее примен., 68:4 (2023), 813–833  mathnet  crossref; P. A. Yaskov, “Sufficient conditions for the Marchenko–Pastur theorem”, Theory Probab. Appl., 68:4 (2024), 657–673  crossref
  4. Pavel Yaskov, “Marchenko–Pastur law for a random tensor model”, Electron. Commun. Probab., 28 (2023), 23–17  mathnet  crossref
  5. П. А. Яськов, “Предельный спектр выборочных ковариационных матриц растущей размерности с граф-зависимыми элементами”, Теория вероятн. и ее примен., 67:3 (2022), 471–488  mathnet  crossref; P. A. Yaskov, “Limiting spectral distribution for large sample covariance matrices with graph-dependent elements”, Theory Probab. Appl., 67:3 (2022), 375–388  crossref
  6. 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)  crossref
  7. 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  mathnet  crossref  scopus
  8. G. L. Zitelli, “Random matrix models for datasets with fixed time horizons”, Quantitative Finance, 20:5 (2020), 769  crossref
  9. M Kornyik, “A note on the asymptotics of random density matrices”, J. Phys. Commun., 2:4 (2018), 045012  crossref
  10. 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  mathnet  crossref  isi  scopus
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