IDEAS home Printed from https://ideas.repec.org/a/spr/opsear/v55y2018i3d10.1007_s12597-018-0342-0.html
   My bibliography  Save this article

Parametric estimation of an M|Er|1 queue

Author

Listed:
  • V. S. Vaidyanathan

    (Pondicherry University)

  • P. Chandrasekhar

    (Loyola College)

Abstract

By considering an M|Er|1 queueing model, the maximum likelihood and consistent estimators of arrival and service parameters are obtained by observing interarrival and service times in the system. Bayes estimators of the parameters both under squared error loss function (SELF) and entropy loss function along with minimum posterior risk and minimum Bayes risk associated with the estimators under SELF are derived. Further, Bayes estimator, minimum posterior risk and minimum Bayes risk of the expected number of entity arrivals in the system under SELF are obtained. An expression for the Bayes estimator of the expected number of entity arrivals in the system under LINEX loss function is also derived. Simulation study to illustrate the performance of the proposed estimators is carried out.

Suggested Citation

  • V. S. Vaidyanathan & P. Chandrasekhar, 2018. "Parametric estimation of an M|Er|1 queue," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 628-641, November.
    • Handle: RePEc:spr:opsear:v:55:y:2018:i:3:d:10.1007_s12597-018-0342-0
    DOI: 10.1007/s12597-018-0342-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s12597-018-0342-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s12597-018-0342-0?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.

    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:opsear:v:55:y:2018:i:3:d:10.1007_s12597-018-0342-0. 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.