IDEAS home Printed from https://ideas.repec.org/h/spr/ssrchp/978-3-031-55048-5_8.html
   My bibliography  Save this book chapter

Analysis of Progressively Censored Repair Time of Airborne Communication Transceiver with Burr-Hatke Exponential Model

In: Reliability Engineering for Industrial Processes

Author

Listed:
  • Kartik Waliya

    (Meerut College)

  • Alka Chaudhary

    (Meerut College)

  • Abhishek Tyagi

    (Chaudhary Charan Singh University)

Abstract

In this chapter, the parameter estimation of a Burr-Hatke exponential model based on the progressive type-II censored sample is investigated. Various methods of estimation for complete data are generalized to the case under progressive censored samples. These approaches comprise maximum likelihood, least squares, maximum product spacings, and Bayesian estimation. Interval estimate and coverage probability for the parameter are derived by the use of maximum likelihood and Bayesian estimation techniques. Markov chain Monte Carlo algorithm has been employed to obtain the Bayes estimator of the parameter with gamma prior under squared error loss function. A vast comparative analysis of the four methods is made using a Monte Carlo empirical study. The empirical findings are used in the formulation of certain suggestions, and a real-world data example is shown to illustrate how the developed theory may be applied in practice.

Suggested Citation

  • Kartik Waliya & Alka Chaudhary & Abhishek Tyagi, 2024. "Analysis of Progressively Censored Repair Time of Airborne Communication Transceiver with Burr-Hatke Exponential Model," Springer Series in Reliability Engineering, in: P. K. Kapur & Hoang Pham & Gurinder Singh & Vivek Kumar (ed.), Reliability Engineering for Industrial Processes, pages 107-135, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-031-55048-5_8
    DOI: 10.1007/978-3-031-55048-5_8
    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.

    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:ssrchp:978-3-031-55048-5_8. 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.