IDEAS home Printed from https://ideas.repec.org/a/eee/jmvana/v49y1994i1p41-54.html
   My bibliography  Save this article

Asymptotics for Multivariate t-Statistic and Hotelling's T2-Statistic Under Infinite Second Moments via Bootstrapping

Author

Listed:
  • Sepanski, S. J.

Abstract

We define the appropriate analogue of Student's t-statistic for multivariate data, and prove that it is asymptotically normal for random vectors in the domain of attraction of the normal law. We also prove that Hotelling's T2-statistic has a chi-squared limiting distribution for random vectors in the generalized domain of attraction of the normal law. Our tool in proving these results is the bootstrap. We prove that the bootstrap version of the multivariate t-statistic is asymptotically normal when the parent distribution is in the generalized domain of attraction of the normal law.

Suggested Citation

  • Sepanski, S. J., 1994. "Asymptotics for Multivariate t-Statistic and Hotelling's T2-Statistic Under Infinite Second Moments via Bootstrapping," Journal of Multivariate Analysis, Elsevier, vol. 49(1), pages 41-54, April.
  • Handle: RePEc:eee:jmvana:v:49:y:1994:i:1:p:41-54
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047-259X(84)71012-8
    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. Martsynyuk, Yuliya V., 2013. "On the generalized domain of attraction of the multivariate normal law and asymptotic normality of the multivariate Student t-statistic," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 402-411.
    2. Laurens Cherchye & Thomas Demuynck & Bram De Rock & Mikhail Freer, 2018. "Equilibrium Play in First Price Auctions: Revealed Preference Analysis," Working Papers ECARES 2018-36, ULB -- Universite Libre de Bruxelles.
    3. Sepanski, Steven J., 1996. "Asymptotics for multivariate t-statistic for random vectors in the generalized domain of attraction of the multivariate normal law," Statistics & Probability Letters, Elsevier, vol. 30(2), pages 179-188, October.
    4. Xu, Jin & Gupta, Arjun K., 2006. "Improved confidence regions for a mean vector under general conditions," Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 1051-1062, November.

    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:eee:jmvana:v:49:y:1994:i:1:p:41-54. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Dana Niculescu). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.