Patrice Abry, Gustavo Didier, Oliver Orejola, Herwig Wendt, “On the empirical spectral distribution of large wavelet random matrices based on mixed-Gaussian fractional measurements in moderately high dimensions”, Electron. J. Probab., 30:none (2025)
П. А. Яськов, “О спектре случайных матриц Грама большой размерности в условиях частичной зависимости”, УМН, 80:5 (2025), 105–174 [P. A. Yaskov, “On the spectrum of random Gram matrices of large dimension in the case of partial dependence”, Uspekhi Mat. Nauk, 80:5 (2025), 105–174 ]
Pavel Yaskov, “A remark on the spectrum of sample covariance matrices from large random tensors”, ALEA, 22:2 (2025), 1301
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
Yifu Tang, Claudia Kirch, Jeong Eun Lee, Renate Meyer, “Posterior consistency for the spectral density of non‐Gaussian stationary time series”, Scandinavian J Statistics, 50:3 (2023), 1152
Pavel Yaskov, “Marchenko–Pastur law for a random tensor model”, Electron. Commun. Probab., 28 (2023), 23–17
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
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
Jennifer Bryson, Roman Vershynin, Hongkai Zhao, “Marchenko–Pastur law with relaxed independence conditions”, Random Matrices: Theory Appl., 10:04 (2021)
П. А. Яськов, “О спектре выборочных ковариационных матриц для временных рядов”, Теория вероятн. и ее примен., 62:3 (2017), 542–555 ; P. A. Yaskov, “On a spectrum of sample covariation matrices for time series”, Theory Probab. Appl., 62:3 (2018), 432–443