586 citations to https://www.mathnet.ru/rus/tvp4645
  1. Haoyun Wang, Yao Xie, “Sequential change‐point detection: Computation versus statistical performance”, WIREs Computational Stats, 16:1 (2024)  crossref
  2. Kim Hammar, Rolf Stadler, “Learning Near-Optimal Intrusion Responses Against Dynamic Attackers”, IEEE Trans. Netw. Serv. Manage., 21:1 (2024), 1158  crossref
  3. Shuyu Chu, Xueying Liu, Achla Marathe, Xinwei Deng, “A latent process approach to change-point detection of mixed-type observations”, Quality Engineering, 36:2 (2024), 407  crossref
  4. Neha Deopa, Daniele Rinaldo, “Quickest Detection of Ecological Regimes for Natural Resource Management”, Environ Resource Econ, 2024  crossref
  5. Houda Harkat, Luis M. Camarinha-Matos, João Goes, Hasmath F.T. Ahmed, “Cyber-physical systems security: A systematic review”, Computers & Industrial Engineering, 188 (2024), 109891  crossref
  6. Marvin Borsch, Alexander Mayer, Dominik Wied, “Consistent Estimation of Multiple Breakpoints in Dependence Measures”, Journal of Business & Economic Statistics, 42:2 (2024), 695  crossref
  7. Lajos Horváth, Gregory Rice, Springer Series in Statistics, Change Point Analysis for Time Series, 2024, 325  crossref
  8. Yingze Hou, Yousef Oleyaeimotlagh, Rahul Mishra, Hoda Bidkhori, Taposh Banerjee, “Robust quickest change detection in nonstationary processes”, Sequential Analysis, 2024, 1  crossref
  9. Hao Chen, Abhishek Gupta, Yin Sun, Ness Shroff, “Model-Free Change Point Detection for Mixing Processes”, IEEE Open J. Control. Syst., 3 (2024), 202  crossref
  10. Tong Si, Yunge Wang, Lingling Zhang, Evan Richmond, Tae-Hyuk Ahn, Haijun Gong, “Multivariate Time Series Change-Point Detection with a Novel Pearson-like Scaled Bregman Divergence”, Stats, 7:2 (2024), 462  crossref
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