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Online non-parametric changepoint detection with application to monitoring operational performance of network devices

Author

Listed:
  • Austin, Edward
  • Romano, Gaetano
  • Eckley, Idris A.
  • Fearnhead, Paul

Abstract

Motivated by a telecommunications application where there are few computational constraints, a novel nonparametric algorithm, NUNC, is introduced to perform an online detection for changes in the distribution of data. Two variants are considered: the first, NUNC Local, detects changes within a sliding window. Conversely, NUNC Global, compares the current window of data to all of the historic information seen so far and makes use of an efficient update step so that this historic information does not need to be stored. To explore the properties of both algorithms, both real and simulated datasets are analysed. Furthermore, a theoretical result for the choice of test threshold to control the false alarm rate is presented, a result that could be applied in other binary segmentation change detection settings.

Suggested Citation

  • Austin, Edward & Romano, Gaetano & Eckley, Idris A. & Fearnhead, Paul, 2023. "Online non-parametric changepoint detection with application to monitoring operational performance of network devices," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
    • Handle: RePEc:eee:csdana:v:177:y:2023:i:c:s0167947322001311
    DOI: 10.1016/j.csda.2022.107551
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    References listed on IDEAS

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    1. Oscar Hernan Madrid Padilla & Alex Athey & Alex Reinhart & James G. Scott, 2019. "Sequential Nonparametric Tests for a Change in Distribution: An Application to Detecting Radiological Anomalies," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 114(526), pages 514-528, April.
    2. Dabuxilatu Wang & Liang Zhang & Qiang Xiong, 2017. "A non parametric CUSUM control chart based on the Mann–Whitney statistic," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(10), pages 4713-4725, May.
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