IDEAS home Printed from https://ideas.repec.org/a/hin/jjmath/6307435.html
   My bibliography  Save this article

Estimations in a Constant-Stress Partially Accelerated Life Test for Generalized Rayleigh Distribution under Type-II Hybrid Censoring Scheme

Author

Listed:
  • Abdalla Rabie
  • Eslam Hussam
  • Abdisalam Hassan Muse
  • Ramy Abdelhamid Aldallal
  • Amirah Saeed Alharthi
  • Hassan M. Aljohani
  • Melike Kaplan

Abstract

The constant-stress partially accelerated life test (CSPALT) model with Type-II hybrid censoring scheme (Type-II HCS) is the subject of our research. Units have a lifetime that follows the generalized Rayleigh distribution. Bayesian and E-Bayesian estimates are derived by applying two of the loss functions, mainly the squared error loss (SEL) and LINEX loss functions. Bayesian and E-Bayesian estimates are obtained using Markov chain Monte Carlo (MCMC) methods. To prove the applicability and the importance of the subject, a test for real data will be provided. To evaluate the distribution’s effectiveness, we utilized a variety of datasets and proposed several kinds of censoring. Finally, all results are compared in order to determine the effectiveness of the proposed methods. All major findings are concluded in the conclusion section.

Suggested Citation

  • Abdalla Rabie & Eslam Hussam & Abdisalam Hassan Muse & Ramy Abdelhamid Aldallal & Amirah Saeed Alharthi & Hassan M. Aljohani & Melike Kaplan, 2022. "Estimations in a Constant-Stress Partially Accelerated Life Test for Generalized Rayleigh Distribution under Type-II Hybrid Censoring Scheme," Journal of Mathematics, Hindawi, vol. 2022, pages 1-9, April.
    • Handle: RePEc:hin:jjmath:6307435
    DOI: 10.1155/2022/6307435
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/jmath/2022/6307435.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/jmath/2022/6307435.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2022/6307435?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. Weihua Shi & Wenhao Gui, 2024. "Reliability analysis of bathtub-shaped distribution using empirical Bayesian and E-Bayesian estimations under progressive Type-II censoring," Journal of Risk and Reliability, , vol. 238(3), pages 604-621, June.

    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:jjmath:6307435. 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.