IDEAS home Printed from https://ideas.repec.org/a/eee/jmvana/v58y1996i1p1-20.html
   My bibliography  Save this article

A Geometric Approach to an Asymptotic Expansion for Large Deviation Probabilities of Gaussian Random Vectors

Author

Listed:
  • Breitung, K.
  • Richter, W. -D.

Abstract

For the probabilities of large deviations of Gaussian random vectors an asymptotic expansion is derived. Based upon a geometric measure representation for the Gaussian law the interactions between global and local geometric properties both of the distribution and of the large deviation domain are studied. The advantage of the result is that the expansion coefficients can be obtained by making a series expansion of a surface integral avoiding the calculation of higher order derivatives.

Suggested Citation

  • Breitung, K. & Richter, W. -D., 1996. "A Geometric Approach to an Asymptotic Expansion for Large Deviation Probabilities of Gaussian Random Vectors," Journal of Multivariate Analysis, Elsevier, vol. 58(1), pages 1-20, July.
    • Handle: RePEc:eee:jmvana:v:58:y:1996:i:1:p:1-20
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047-259X(96)90036-6
    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. Richter, W. -D. & Schumacher, J., 2000. "Asymptotic Expansions for Large Deviation Probabilities of Noncentral Generalized Chi-Square Distributions," Journal of Multivariate Analysis, Elsevier, vol. 75(2), pages 184-218, November.

    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:58:y:1996:i:1:p:1-20. 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.