586 citations to https://www.mathnet.ru/rus/tvp4645
-
Austin Warner, Georgios Fellouris, “Sequential change diagnosis revisited and the Adaptive Matrix CuSum”, Bernoulli, 30:3 (2024)
-
Yanglei Song, Georgios Fellouris, “Change acceleration and detection”, Ann. Statist., 52:3 (2024)
-
Xinyuan Zhang, Yajun Mei, 2024 IEEE International Symposium on Information Theory (ISIT), 2024, 1065
-
Taposh Banerjee, Vahid Tarokh, “Bayesian quickest change detection for unnormalized and score-based models”, Sequential Analysis, 43:3 (2024), 359
-
Soumik Banerjee, Aleksey S. Polunchenko, Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science, 2024, 3
-
Sven Knoth, Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science, 2024, 127
-
Serguei Pergamenchtchikov, Roman Tenzin, Lecture Notes in Networks and Systems, 1154, Proceedings of the Future Technologies Conference (FTC) 2024, Volume 1, 2024, 77
-
А. А. Боровков, “Об асимптотическом подходе к задаче о разладке и экспоненциальной сходимости в эргодической теореме для цепей Маркова”, Теория вероятн. и ее примен., 68:3 (2023), 456–482 ; A. A. Borovkov, “On an asymptotic approach to the change point detection problem and exponential
convergence rate in the ergodic theorem for Markov chains”, Theory Probab. Appl., 68:3 (2023), 370–391
-
В. И. Лотов, А. С. Тарасенко, “Исследование характеристик процедуры кумулятивных сумм в задаче скорейшего обнаружения разладки”, Сиб. электрон. матем. изв., 20:2 (2023), 987–1000
-
Jason J. Ford, Justin M. Kennedy, Caitlin Tompkins, Jasmin James, Aaron McFadyen, “Exactly Optimal Quickest Change Detection of Markov Chains”, IEEE Control Syst. Lett., 2023, 1