IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v50y2021i16p3851-3874.html
   My bibliography  Save this article

Goodness-of-fit test for Rayleigh distribution based on progressively type-II censored sample

Author

Listed:
  • Junru Ren
  • Wenhao Gui

Abstract

In this article, we propose several statistics to conduct goodness-of-fit tests for Rayleigh distribution based on progressively Type-II censored data, where a cumulative entropy and its upper and lower bounds as well as the sample spacings are used respectively, and the corresponding statistics are denoted by TE, TU, TL and TS. Especially, the null distribution of TS test statistic is derived. Then the developed methods are extended to the case of one-parameter Weibull model. The respective performance of these statistics is explored against different alternatives, and the power comparisons with some existing goodness-of-fit test statistics are studied via a wide range of Monte Carlo simulations. The results reveal that TS is more effective than the others in most cases; all test statistics have a remarkable performance for the alternative hypothesis with decreasing hazard function. Finally, the proposed statistics are applied in an illustrative example.

Suggested Citation

  • Junru Ren & Wenhao Gui, 2021. "Goodness-of-fit test for Rayleigh distribution based on progressively type-II censored sample," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 50(16), pages 3851-3874, August.
    • Handle: RePEc:taf:lstaxx:v:50:y:2021:i:16:p:3851-3874
    DOI: 10.1080/03610926.2020.1869988
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2020.1869988
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/03610926.2020.1869988?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:lstaxx:v:50:y:2021:i:16:p:3851-3874. 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/lsta .

    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.