IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-031-69111-9_9.html
   My bibliography  Save this book chapter

Control Charts for Poisson Counts Based on the Stein–Chen Identity

In: Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science

Author

Listed:
  • Christian H. Weiß

    (Helmut Schmidt University Hamburg, Department of Mathematics and Statistics)

Abstract

If monitoring Poisson count data for a possible mean shift (while the Poisson distribution is preserved), then the ordinary Poisson exponentially weighted moving-average (EWMA) control chart proved to be a good solution. In practice, however, mean shifts might occur in combination with further changes in the distribution family. Or due to a misspecification during Phase-I analysis, the Poisson assumption might not be appropriate at all. In such cases, the ordinary EWMA chart might not perform satisfactorily. Therefore, two novel classes of generalized EWMA charts are proposed, which utilize the so-called Stein–Chen identity and are thus sensitive to further distributional changes than just sole mean shifts. Their average run length (ARL) performance is investigated with simulations, where it becomes clear that especially the class of so-called ABC-EWMA charts shows an appealing ARL performance. The practical application of the novel Stein–Chen EWMA charts is illustrated with an application to count data from semiconductor manufacturing.

Suggested Citation

  • Christian H. Weiß, 2024. "Control Charts for Poisson Counts Based on the Stein–Chen Identity," Springer Books, in: Sven Knoth & Yarema Okhrin & Philipp Otto (ed.), Advanced Statistical Methods in Process Monitoring, Finance, and Environmental Science, pages 195-209, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-69111-9_9
    DOI: 10.1007/978-3-031-69111-9_9
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:sprchp:978-3-031-69111-9_9. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.