IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v50y2023i1p86-105.html
   My bibliography  Save this article

Inferences for multiple interval type-I censoring scheme

Author

Listed:
  • Shubham Agnihotri
  • Sanjay Kumar Singh
  • Umesh Singh

Abstract

In this paper, we have introduced a new type of censoring scheme named the multiple interval type-I censoring scheme. Further, We have assumed that the test units are drawn from the Weibull population. We have also proposed the maximum product of spacing estimators for unknown parameters under the multiple interval type-I censoring scheme and compare them with the existing maximum likelihood estimators. In addition to this, the Bayes estimators for shape and scale parameters are also obtained under the squared error loss function. Their corresponding asymptotic confidence/credible intervals are also discussed. A real data set containing the breakdown time of insulating fluids are used to demonstrate the appropriateness of the proposed methodology.

Suggested Citation

  • Shubham Agnihotri & Sanjay Kumar Singh & Umesh Singh, 2023. "Inferences for multiple interval type-I censoring scheme," Journal of Applied Statistics, Taylor & Francis Journals, vol. 50(1), pages 86-105, January.
  • Handle: RePEc:taf:japsta:v:50:y:2023:i:1:p:86-105
    DOI: 10.1080/02664763.2021.1981832
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2021.1981832
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/02664763.2021.1981832?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:50:y:2023:i:1:p:86-105. 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.