IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v53y2024i10p3517-3546.html
   My bibliography  Save this article

Classical and Bayesian estimations of performance measures in a single server Markovian queueing system based on arrivals during service times

Author

Listed:
  • Saroja Kumar Singh
  • Frederico R. B. Cruz
  • Eriky S. Gomes
  • Abhijit Datta Banik

Abstract

The present study considers a single-server Markovian queueing system by observing the number of customer arrivals during the service time of a customer. We estimate the traffic intensity in this queueing system along with the average queue length and the expected number of customers in the system. We propose classical and Bayesian frameworks to estimate the parameters of interest. In the Bayesian setup, three forms of prior distributions for ρ and two loss functions are considered. Furthermore, the predictive distribution of the number of customer arrivals during the service time of a customer and the equal-tailed credible region of ρ are obtained. The aforementioned approaches are illustrated with numerical examples based on simulation studies.

Suggested Citation

  • Saroja Kumar Singh & Frederico R. B. Cruz & Eriky S. Gomes & Abhijit Datta Banik, 2024. "Classical and Bayesian estimations of performance measures in a single server Markovian queueing system based on arrivals during service times," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 53(10), pages 3517-3546, May.
    • Handle: RePEc:taf:lstaxx:v:53:y:2024:i:10:p:3517-3546
    DOI: 10.1080/03610926.2022.2155789
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2022.2155789
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/03610926.2022.2155789?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:10:p:3517-3546. 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.