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A multivariate descriptor method for change-point detection in nonlinear time series

Author

Listed:
  • P. P. Balestrassi
  • A. P. Paiva
  • A. C. Zambroni de Souza
  • J. B. Turrioni
  • Elmira Popova

Abstract

The purpose of this paper is to present a novel method that is applied to detect dynamic changes in nonlinear time series. The method combines a multivariate control chart that monitors the variation of three normalized descriptors -- Hjorth's descriptors of activity, mobility and complexity -- and is applied to the change-point detection problem of nonlinear time series. The approach is estimated using six simulated nonlinear time series. In addition, a case study of six time series of short-term electricity load consumption was used to illustrate the power of the method.

Suggested Citation

  • P. P. Balestrassi & A. P. Paiva & A. C. Zambroni de Souza & J. B. Turrioni & Elmira Popova, 2011. "A multivariate descriptor method for change-point detection in nonlinear time series," Journal of Applied Statistics, Taylor & Francis Journals, vol. 38(2), pages 327-342, September.
    • Handle: RePEc:taf:japsta:v:38:y:2011:i:2:p:327-342
    DOI: 10.1080/02664760903406496
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