IDEAS home Printed from https://ideas.repec.org/a/ids/ijdsci/v2y2017i4p352-368.html
   My bibliography  Save this article

Bayesian estimation of Lomax distribution under type-II hybrid censored data using Lindley's approximation method

Author

Listed:
  • Sanjay Kumar Singh
  • Umesh Singh
  • Abhimanyu Singh Yadav

Abstract

In this paper, we have discussed the estimation procedure for two parameter Lomax distribution under Type-II hybrid censoring scheme. The maximum likelihood estimation (MLE) and Bayes estimation for the parameters and reliability characteristics have been considered. The Lindley's approximation technique has been used to obtain the Bayes estimates. The performances of the Bayes estimators are compared with the corresponding maximum likelihood estimators (MLEs) in term of their mean square error (MSE). Finally, a real dataset has been used to illustrate the discussed methodology.

Suggested Citation

  • Sanjay Kumar Singh & Umesh Singh & Abhimanyu Singh Yadav, 2017. "Bayesian estimation of Lomax distribution under type-II hybrid censored data using Lindley's approximation method," International Journal of Data Science, Inderscience Enterprises Ltd, vol. 2(4), pages 352-368.
  • Handle: RePEc:ids:ijdsci:v:2:y:2017:i:4:p:352-368
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=88104
    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.

    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:ijdsci:v:2:y:2017:i:4:p:352-368. 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=429 .

    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.