IDEAS home Printed from https://ideas.repec.org/a/taf/gnstxx/v32y2020i3p667-703.html
   My bibliography  Save this article

Intermediate efficiency of some weighted goodness-of-fit statistics

Author

Listed:
  • Bogdan Ćmiel
  • Tadeusz Inglot
  • Teresa Ledwina

Abstract

This paper introduces and investigates powerful omnibus test for uniformity and compares it with some classical and recent solutions. All statistics under consideration are weighted functionals of the classical empirical process. The goal is to provide a quantitative comparison of tests under consideration and to study real possibilities of using them to detect departures from the hypothesised distribution that occur in the tails. The newly introduced concept of pathwise variant of intermediate efficiency serves to achieve the goal. This contribution covers the case when under the alternative a moderately large portion of probability mass is allocated towards the tails. It is demonstrated that the approach allows for tractable, analytic comparison between the given test and the benchmark, and for reliable quantitative evaluation of weighted statistics. Finite sample results illustrate the proposed approach and confirm the theoretical findings.

Suggested Citation

  • Bogdan Ćmiel & Tadeusz Inglot & Teresa Ledwina, 2020. "Intermediate efficiency of some weighted goodness-of-fit statistics," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 32(3), pages 667-703, July.
  • Handle: RePEc:taf:gnstxx:v:32:y:2020:i:3:p:667-703
    DOI: 10.1080/10485252.2020.1789126
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/10485252.2020.1789126
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/10485252.2020.1789126?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:gnstxx:v:32:y:2020:i:3:p:667-703. 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/GNST20 .

    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.