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Detection of Changes in the Properties of Time-Varying Random Processes

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Abstract

An approach to analyzing and predicting systems described by time-varying series is developed on the basis of identification of intervals in which time-varying processes do not change their parameters and construction of models for cointegration relations in these intervals and for tracking the changes both in the processes themselves and in the long-range cointegration relations formed by them. CUSUM-type detection algorithms are constructed for detecting the changes in time-varying processes and identifying stationary intervals. If the process parameters are known exactly, these algorithms are optimal by the quickest detection criterion. For the case studied in the paper, the process parameters are not known after the changes in properties, only certain assumptions concerning the type of parameter changes can be made. Therefore, property changes are detected with the help of modified CUSUM-algorithms, which are not optimal, but guarantee a reasonable detection quality.

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  1. Russian Academy of Sciences, Trapeznikov Institute of Control Sciences, Moscow, Russia

    E. A. Grebenyuk

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  1. E. A. Grebenyuk
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Grebenyuk, E.A. Detection of Changes in the Properties of Time-Varying Random Processes. Automation and Remote Control 64, 1868–1881 (2003). https://doi.org/10.1023/B:AURC.0000008425.69456.88

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