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

P. P. Balestrassi, A. P. Paiva, A. C. Zambroni de Souza, J. B. Turrioni and Elmira Popova

Journal of Applied Statistics, 2011, vol. 38, issue 2, 327-342

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.

Date: 2011
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DOI: 10.1080/02664760903406496

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