IDEAS home Printed from https://ideas.repec.org/a/ids/ijpqma/v14y2014i3p336-351.html
   My bibliography  Save this article

Estimating the change point of binary profiles in phase II

Author

Listed:
  • Alireza Sharafi
  • Majid Aminnayeri
  • Amirhossein Amiri

Abstract

Identifying the real time change in a process, when an out-of-control signal is given by a control chart is crucial and leads to cost and time savings significantly. There are processes or products whose quality is described by a relationship between a response variable and one or more explanatory variable. This relationship is known as profile in the literature of statistical process control and is modelled by different regression types including logistic regression. This type of profile is used where the response variable follows a binomial distribution. In this paper, a maximum likelihood estimator (MLE) based on regression parameters is developed to find the real time of a step change in logistic regression profiles. Simulation studies are provided to evaluate the performance of the proposed change point estimator under both single step change and linear trend change.

Suggested Citation

  • Alireza Sharafi & Majid Aminnayeri & Amirhossein Amiri, 2014. "Estimating the change point of binary profiles in phase II," International Journal of Productivity and Quality Management, Inderscience Enterprises Ltd, vol. 14(3), pages 336-351.
    • Handle: RePEc:ids:ijpqma:v:14:y:2014:i:3:p:336-351
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=64809
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ali Ghazizadeh & Mehrdad Sarani & Mahdi Hamid & Ahmad Ghasemkhani, 2023. "Detecting and estimating the time of a single-step change in nonlinear profiles using artificial neural networks," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 14(1), pages 74-86, February.

    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:ids:ijpqma:v:14:y:2014:i:3:p:336-351. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=177 .

    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.