IDEAS home Printed from https://ideas.repec.org/a/bot/rivsta/v79y2019i1p47-74.html
   My bibliography  Save this article

Estimation in Inverse Weibull Distribution Based on Randomly Censored Data

Author

Listed:
  • Kapil Kumar

    (Department of Statistics, Central University of Haryana)

  • Indrajeet Kumar

    (Department of Statistics, Central University of Haryana)

Abstract

This article deals with the estimation of the parameters and reliability characteristics in inverse Weibull (IW) distribution based on the random censoring model. The censoring distribution is also taken as an IW distribution. Maximum likelihood estimators of the parameters, survival and failure rate functions are derived. Asymptotic confidence intervals of the parameters based on the Fisher information matrix are constructed. Bayes estimators of the parameters, survival and failure rate functions under squared error loss function using non-informative and gamma informative priors are developed. Furthermore, Bayes estimates are obtained using Tierne -Kadane's approximation method and Markov chain Monte Carlo (MCMC) techniques. Also, highest posterior density (HPD) credible intervals of the parameters based on MCMC techniques are constructed. A simulation study is conducted to compare the performance of various estimates. Finally, a randomly censored real data set supports the estimation procedures developed in this article.

Suggested Citation

  • Kapil Kumar & Indrajeet Kumar, 2019. "Estimation in Inverse Weibull Distribution Based on Randomly Censored Data," Statistica, Department of Statistics, University of Bologna, vol. 79(1), pages 47-74.
  • Handle: RePEc:bot:rivsta:v:79:y:2019:i:1:p:47-74
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    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.
    2. Rajni Goel & Hare Krishna, 2024. "A study of accidental breakages in progressively type-ii censored lifetime experiments," 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. 15(6), pages 2105-2119, June.
    3. Indrajeet Kumar & Kapil Kumar, 2022. "On estimation of $$P(V," 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(1), pages 189-202, February.

    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:bot:rivsta:v:79:y:2019:i:1:p:47-74. 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: Giovanna Galatà (email available below). General contact details of provider: https://edirc.repec.org/data/dsbolit.html .

    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.