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Change-point detection as model selection
Volume 3, Issue 1 (1992), pp. 3–20
Jimmy Baikovicius   László Gerencsér  

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https://doi.org/10.3233/INF-1992-3101
Pub. online: 1 January 1992      Type: Research Article     

Published
1 January 1992

Abstract

We present a new method for solving the change-point detection problem for ARMA systems which are assumed to have a slow and non-decaying drift after the change occurs. The proposed technique is inspired by the stochastic complexity theory, which gives a basis of comparison of different models with different change-point times. Some partial results on the analysis of the estimator are stated. A simulation is included which shows that the approach exhibits surprisingly good detection capabilities.

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Keywords
stochastic systems stochastic complexity time varying systems recursive estimation time-varying Ljung's scheme L-mixing processes failure detection

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INFORMATICA

  • Online ISSN: 1822-8844
  • Print ISSN: 0868-4952
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