IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-1-4613-3638-9_7.html
   My bibliography  Save this book chapter

Bayes Quantile Estimation and Threshold Selection for the Generalized Pareto Family

In: Extreme Value Theory and Applications

Author

Listed:
  • James Pickands III

    (University of Pennsylvania)

Abstract

There is always a trade off between computational and statistical efficiency. The phenomenal recent advances in computing have shifted the advantage toward Bayesian methods of estimation. We propose an interactive program for analyzing observations above a high threshold. The first phase of the analysis is the “identification” phase. Using parameter estimators which are not too efficient but easy to compute, we perform many iterations to find the empirical optimal combination choice of threshold and choice of monotone increasing function transformation. We review existing methods of estimation. The second phase is the “estimation” phase. We examine the use of Bayes estimators for this phase. We also suggest a method of finding confidence regions.

Suggested Citation

  • James Pickands III, 1994. "Bayes Quantile Estimation and Threshold Selection for the Generalized Pareto Family," Springer Books, in: Janos Galambos & James Lechner & Emil Simiu (ed.), Extreme Value Theory and Applications, pages 123-138, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4613-3638-9_7
    DOI: 10.1007/978-1-4613-3638-9_7
    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

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:978-1-4613-3638-9_7. 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.