Xiangyu Guo, Fukang Zhu, “Negative binomial community network vector autoregression for multivariate integer-valued time series”, Applied Mathematical Modelling, 134 (2024), 713
Pavel Yaskov, “Marchenko–Pastur law for a random tensor model”, Electron. Commun. Probab., 28 (2023), 23–17
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
Mirko Armillotta, Konstantinos Fokianos, “Nonlinear network autoregression”, Ann. Statist., 51:6 (2023)
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
Sisheng Liu, Xiaoli Kong, “A generalized correlated C criterion for derivative estimation with dependent errors”, Computational Statistics & Data Analysis, 171 (2022), 107473
Xiaoli Kong, Solomon W. Harrar, “High-dimensional MANOVA under weak conditions”, Statistics, 55:2 (2021), 321
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
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
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