IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v52y2025i7p1446-1469.html
   My bibliography  Save this article

A bivariate load-sharing model

Author

Listed:
  • Debasis Kundu

Abstract

The motivation of this work came from a data set obtained from an experiment performed on diabetic patients, with diabetic retinopathy disorder. The aim of this experiment is to test whether there is any significant difference between two different treatments which are being used for this disease. The two eyes can be considered as a two-component load-sharing system. In a two-component load-sharing system after the failure of one component, the surviving component has to shoulder extra load. Hence, it is prone to failure at an earlier time than what is expected under the original model. It may also happen sometimes that the failure of one component may release extra resources to the survivor, thus delaying the failure. In most of the existing literature, it has been assumed that at the beginning the lifetime distributions of the two components are independently distributed, which may not be very reasonable in this case. In this paper, we have introduced a new bivariate load-sharing model where the independence assumptions of the lifetime distributions of the two components at the beginning have been relaxed. In this present model, they may be dependent. Further, there is a positive probability that the two components may fail simultaneously. If the two components do not fail simultaneously, it is assumed that the lifetime of the surviving component changes based on the tampered failure rate assumption. The proposed bivariate distribution has a singular component. The likelihood inference of the unknown parameters has been provided. Simulation results and the analysis of the data set have been presented to show the effectiveness of the proposed model.

Suggested Citation

  • Debasis Kundu, 2025. "A bivariate load-sharing model," Journal of Applied Statistics, Taylor & Francis Journals, vol. 52(7), pages 1446-1469, May.
  • Handle: RePEc:taf:japsta:v:52:y:2025:i:7:p:1446-1469
    DOI: 10.1080/02664763.2024.2428267
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2024.2428267
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/02664763.2024.2428267?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:taf:japsta:v:52:y:2025:i:7:p:1446-1469. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.