IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v53y2024i23p8498-8524.html
   My bibliography  Save this article

Phase-type stress-strength reliability models under progressive type-II right censoring

Author

Listed:
  • Joby K. Jose
  • Drisya M
  • Kulathinal Sangita
  • Sebastian George

Abstract

The study of stress-strength reliability estimation based on phase-type distribution helps to gather results on estimation of stress-strength reliability with any probability distribution that is defined on the non negative real numbers as any discrete or continuous probability distributions on the positive real line can be represented as phase-type. The matrix representation of the parameters of phase-type distributions helps in their flexible evaluation and easy manipulation. Also in many of the experimental studies, it is very convenient and useful to apply progressive type-II right censoring mechanism in the process of data collection. In this article, we consider the estimation of stress-strength reliability (R) based on phase-type distribution under progressive type-II right censoring mechanism. Both stress and strength random variables are assumed to follow either continuous phase-type or discrete phase-type distribution. We have developed the algorithm for computing Maximum likelihood estimate (MLE) of R based on the expectation maximization (EM) method and the Bayes estimate of R using Markov Chain Monte Carlo technique. A detailed numerical illustration using simulated data/ real data sets are carried out.

Suggested Citation

  • Joby K. Jose & Drisya M & Kulathinal Sangita & Sebastian George, 2024. "Phase-type stress-strength reliability models under progressive type-II right censoring," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 53(23), pages 8498-8524, December.
  • Handle: RePEc:taf:lstaxx:v:53:y:2024:i:23:p:8498-8524
    DOI: 10.1080/03610926.2023.2292968
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2023.2292968
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03610926.2023.2292968?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

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

    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:taf:lstaxx:v:53:y:2024:i:23:p:8498-8524. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/lsta .

    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.