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Exponentially Weighted Moving Averages of Counting Processes When the Time between Events Is Weibull Distributed

In: Quality Control - Intelligent Manufacturing, Robust Design and Charts

Author

Listed:
  • Ross Stewart Sparks
  • Hossein Hazrati-Marangaloo

Abstract

There are control charts for Poisson counts, zero-inflated Poisson counts, and over dispersed Poisson counts (negative binomial counts) but nothing on counting processes when the time between events (TBEs) is Weibull distributed. In our experience the in-control distribution for time between events is often Weibull distributed in applications. Counting processes are not Poisson distributed or negative binomial distributed when the time between events is Weibull distributed. This is a gap in the literature meaning that there is no help for practitioners when this is the case. This book chapter is designed to close this gap and provide an approach that could be helpful to those applying control charts in such cases.

Suggested Citation

  • Ross Stewart Sparks & Hossein Hazrati-Marangaloo, 2021. "Exponentially Weighted Moving Averages of Counting Processes When the Time between Events Is Weibull Distributed," Chapters, in: Pengzhong Li & Paulo Pereira & Helena V. G. Navas (ed.), Quality Control - Intelligent Manufacturing, Robust Design and Charts, IntechOpen.
    • Handle: RePEc:ito:pchaps:207366
    DOI: 10.5772/intechopen.90873
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    More about this item

    Keywords

    average run length; counts; monitoring; time between events;
    All these keywords.

    JEL classification:

    • L15 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - Information and Product Quality

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