Optimal Change-Point Sequential Detection in Autoregressive Time Series

Serguei Pergamenchtchikov; Roman Tenzin

doi:10.1007/978-3-031-65993-5_42

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Optimal Change-Point Sequential Detection in Autoregressive Time Series

Serguei Pergamenchtchikov Roman Tenzin

Year: 2024 Advances in intelligent systems and computing Pages: 342-348 Publisher: Springer Nature

DOI: 10.1007/978-3-031-65993-5_42

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Keywords:

Autoregressive model Series (stratigraphy) Change detection Computer science Time series Point (geometry) STAR model Econometrics Autoregressive integrated moving average Mathematics Artificial intelligence Machine learning Geology

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Advanced Statistical Process Monitoring

Social Sciences → Decision Sciences → Statistics, Probability and Uncertainty

Fault Detection and Control Systems

Physical Sciences → Engineering → Control and Systems Engineering

Advanced Statistical Methods and Models

Physical Sciences → Mathematics → Statistics and Probability

Optimal Change-Point Sequential Detection in Autoregressive Time Series

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