IDEAS home Printed from https://ideas.repec.org/h/spr/sprchp/978-1-4612-0099-4_12.html
   My bibliography  Save this book chapter

Tail Empirical Processes Under Mixing Conditions

In: Empirical Process Techniques for Dependent Data

Author

Listed:
  • Holger Drees

    (Saarland University, Faculty of Mathematics and Computer Science)

Abstract

Limit theorems for tail processes of absolutely regular time series are surveyed. First we discuss Rootzén’s [29] result on the uniform tail empirical process and generalizations thereof. Then similar results on the uniform tail quantile process are derived. If the observations come from a distribution function that belongs to the domain of attraction of an extreme value distribution, then one can prove weighted approximations of the linearly standardized tail quantile function. Moreover, asymptotic normality can be deduced for many estimators of interest in extreme value statistics. Finally, we apply the limit theorems to particular linear and nonlinear time series models.

Suggested Citation

  • Holger Drees, 2002. "Tail Empirical Processes Under Mixing Conditions," Springer Books, in: Herold Dehling & Thomas Mikosch & Michael Sørensen (ed.), Empirical Process Techniques for Dependent Data, pages 325-342, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4612-0099-4_12
    DOI: 10.1007/978-1-4612-0099-4_12
    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:978-1-4612-0099-4_12. 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.