IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v27y1996i4p367-373.html
   My bibliography  Save this article

Tests of hypotheses in discrete models based on the penalized Hellinger distance

Author

Listed:
  • Basu, Ayanendranath
  • Harris, Ian R.
  • Basu, Srabashi

Abstract

Analogues of the likelihood ratio, Rao, and Wald tests are introduced in discrete parametric models based on the family of penalized Hellinger distances. It is shown that the tests based on a particular member of this family provide attractive alternatives to the tests based on the ordinary Hellinger distance. These tests share the robustness of the Hellinger distance test, but are often closer to the likelihood-based tests at the model, especially in small samples. The convergence of ordinary Hellinger distance tests to limiting [chi]2 distributions are quite slow. The proposed tests are improvements in this respect.

Suggested Citation

  • Basu, Ayanendranath & Harris, Ian R. & Basu, Srabashi, 1996. "Tests of hypotheses in discrete models based on the penalized Hellinger distance," Statistics & Probability Letters, Elsevier, vol. 27(4), pages 367-373, May.
    • Handle: RePEc:eee:stapro:v:27:y:1996:i:4:p:367-373
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0167-7152(95)00101-8
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

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

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mandal, Abhijit & Basu, Ayanendranath, 2013. "Minimum disparity estimation: Improved efficiency through inlier modification," Computational Statistics & Data Analysis, Elsevier, vol. 64(C), pages 71-86.
    2. Basu, A. & Mandal, A. & Pardo, L., 2010. "Hypothesis testing for two discrete populations based on the Hellinger distance," Statistics & Probability Letters, Elsevier, vol. 80(3-4), pages 206-214, February.
    3. Park, Chanseok & Basu, Ayanendranath & G. Lindsay, Bruce, 2002. "The residual adjustment function and weighted likelihood: a graphical interpretation of robustness of minimum disparity estimators," Computational Statistics & Data Analysis, Elsevier, vol. 39(1), pages 21-33, March.
    4. Basu, Ayanendranath & Park, Chanseok & Lindsay, Bruce G. & Li, Haihong, 2004. "Some variants of minimum disparity estimation," Computational Statistics & Data Analysis, Elsevier, vol. 45(4), pages 741-763, May.
    5. Basu, Ayanendranath & Chakraborty, Soumya & Ghosh, Abhik & Pardo, Leandro, 2022. "Robust density power divergence based tests in multivariate analysis: A comparative overview of different approaches," Journal of Multivariate Analysis, Elsevier, vol. 188(C).

    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:eee:stapro:v:27:y:1996:i:4:p:367-373. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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.