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Residual Responses to Change Patterns of Autocorrelated Processes

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  • Mohamed El Ghourabi
  • Mohamed Limam

Abstract

This article studies the residual behaviour of various stationary processes in the presence of change patterns. Three types of change patterns are considered, Additive Outliers, Innovative Outliers and Level Shift. The knowledge of the residual behaviour is important for monitoring production processes. A new method of residual process control is proposed, the patterns chart. In addition to the advantage of detecting change patterns, it distinguishes their nature. The patterns chart's performance is compared to the performance of the special causes control (SCC) chart based on average run length. The results show that the proposed method performs better than a SCC chart. A real case study illustrates that the patterns chart has all the desirable properties of a SCC chart and it overcomes the negative ones.

Suggested Citation

  • Mohamed El Ghourabi & Mohamed Limam, 2007. "Residual Responses to Change Patterns of Autocorrelated Processes," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(7), pages 785-798.
    • Handle: RePEc:taf:japsta:v:34:y:2007:i:7:p:785-798
    DOI: 10.1080/02664760701240063
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    Cited by:

    1. Amira Dridi & Mohamed El Ghourabi & Mohamed Limam, 2012. "On monitoring financial stress index with extreme value theory," Quantitative Finance, Taylor & Francis Journals, vol. 12(3), pages 329-339, March.
    2. Mohamed El Ghourabi & Amira Dridi & Mohamed Limam, 2015. "A new financial stress index model based on support vector regression and control chart," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(4), pages 775-788, April.

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