IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-3-031-61853-6_8.html
   My bibliography  Save this book chapter

How to Build Optimal Tests for Normality Under Possibly Singular Fisher Information

In: Recent Advances in Econometrics and Statistics

Author

Listed:
  • Andreas Anastasiou

    (University of Cyprus)

  • Christophe Ley

    (University of Luxembourg)

Abstract

In this chapter, we show how to construct efficient tests for normality against generalized skew-normal distributions, which contain the most popular skew alternative, namely, the skew-normal distribution. This task is highly nontrivial due to the fact that the Fisher information matrix for location and skewness is singular in the vicinity of symmetry. Thanks to a reparametrization proposed in a paper by Marc Hallin with the second author, we are able to develop the usual Le Cam methodology for this peculiar model and hence derive optimal tests for normality, hereby shedding new light on some well-known tests from the literature.

Suggested Citation

  • Andreas Anastasiou & Christophe Ley, 2024. "How to Build Optimal Tests for Normality Under Possibly Singular Fisher Information," Springer Books, in: Matteo Barigozzi & Siegfried Hörmann & Davy Paindaveine (ed.), Recent Advances in Econometrics and Statistics, pages 149-166, Springer.
    • Handle: RePEc:spr:sprchp:978-3-031-61853-6_8
    DOI: 10.1007/978-3-031-61853-6_8
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    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:spr:sprchp:978-3-031-61853-6_8. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.