IDEAS home Printed from https://ideas.repec.org/a/hin/jnljps/4860167.html
   My bibliography  Save this article

Maximum Likelihood and Bayes Estimation in Randomly Censored Geometric Distribution

Author

Listed:
  • Hare Krishna
  • Neha Goel

Abstract

In this article, we study the geometric distribution under randomly censored data. Maximum likelihood estimators and confidence intervals based on Fisher information matrix are derived for the unknown parameters with randomly censored data. Bayes estimators are also developed using beta priors under generalized entropy and LINEX loss functions. Also, Bayesian credible and highest posterior density (HPD) credible intervals are obtained for the parameters. Expected time on test and reliability characteristics are also analyzed in this article. To compare various estimates developed in the article, a Monte Carlo simulation study is carried out. Finally, for illustration purpose, a randomly censored real data set is discussed.

Suggested Citation

  • Hare Krishna & Neha Goel, 2017. "Maximum Likelihood and Bayes Estimation in Randomly Censored Geometric Distribution," Journal of Probability and Statistics, Hindawi, vol. 2017, pages 1-12, February.
    • Handle: RePEc:hin:jnljps:4860167
    DOI: 10.1155/2017/4860167
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/JPS/2017/4860167.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/JPS/2017/4860167.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2017/4860167?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
    ---><---

    Citations

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


    Cited by:

    1. Neha Goel & Hare Krishna, 2022. "Different methods of estimation in two parameter Geometric distribution with randomly censored data," 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. 13(4), pages 1652-1665, August.

    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:hin:jnljps:4860167. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.