IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v30y2003i10p1081-1100.html
   My bibliography  Save this article

Local dependence functions for extreme value distributions

Author

Listed:
  • Saralees Nadarajah
  • Kosto Mitov
  • Samuel Kotz

Abstract

Kotz & Nadarajah (2002) introduced a measure of local dependence which is a localized version of the Pearson's correlation coefficient. In this paper we provide detailed analyses (both algebraic and numerical) of the form of the measure for the class of bivariate extreme value distributions. We consider, in particular, five families of bivariate extreme value distributions. We also discuss two applications of the new measure. In the first application we introduce an overall measure of correlation and produce evidence to suggest that it is superior than the usual Pearson's correlation coefficient. The second application introduces two new concepts for ordering of bivariate dependence.

Suggested Citation

  • Saralees Nadarajah & Kosto Mitov & Samuel Kotz, 2003. "Local dependence functions for extreme value distributions," Journal of Applied Statistics, Taylor & Francis Journals, vol. 30(10), pages 1081-1100.
    • Handle: RePEc:taf:japsta:v:30:y:2003:i:10:p:1081-1100
    DOI: 10.1080/0266476032000107123
    as

    Download full text from publisher

    File URL: http://www.tandfonline.com/doi/abs/10.1080/0266476032000107123
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/0266476032000107123?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jones, M. C., 1998. "Constant Local Dependence," Journal of Multivariate Analysis, Elsevier, vol. 64(2), pages 148-155, February.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Cees Diks & Florian Wagener, 2006. "A Weak Bifurcation Theory for Discrete Time Stochastic Dynamical Systems," Tinbergen Institute Discussion Papers 06-043/1, Tinbergen Institute.
    2. Cees Diks & Florian Wagener, 2005. "Equivalence and Bifurcations of Finite Order Stochastic Processes," Tinbergen Institute Discussion Papers 05-043/1, Tinbergen Institute.
    3. Karoline Bax & Emanuele Taufer & Sandra Paterlini, 2022. "A generalized precision matrix for t-Student distributions in portfolio optimization," Papers 2203.13740, arXiv.org.
    4. M. Zargar & H. Jabbari & M. Amini, 2017. "Dependence structure and test of independence for some well-known bivariate distributions," Computational Statistics, Springer, vol. 32(4), pages 1423-1451, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tjøstheim, Dag & Hufthammer, Karl Ove, 2013. "Local Gaussian correlation: A new measure of dependence," Journal of Econometrics, Elsevier, vol. 172(1), pages 33-48.
    2. Indranil Ghosh & Osborne Banks, 2021. "A Study of Bivariate Generalized Pareto Distribution and its Dependence Structure Among Model Parameters," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 575-604, November.
    3. Ramesh Gupta, 2011. "Bivariate odds ratio and association measures," Statistical Papers, Springer, vol. 52(1), pages 125-138, February.
    4. Gwo Dong Lin & Xiaoling Dou & Satoshi Kuriki, 2019. "The Bivariate Lack-of-Memory Distributions," Sankhya A: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(2), pages 273-297, December.
    5. Ip, Edward H. & Wang, Yuchung J. & Yeh, Yeong-nan, 2004. "Structural decompositions of multivariate distributions with applications in moment and cumulant," Journal of Multivariate Analysis, Elsevier, vol. 89(1), pages 119-134, April.
    6. Abberger, Klaus, 2002. "Exploring local dependence," CoFE Discussion Papers 02/14, University of Konstanz, Center of Finance and Econometrics (CoFE).
    7. Karoline Bax & Emanuele Taufer & Sandra Paterlini, 2022. "A generalized precision matrix for t-Student distributions in portfolio optimization," Papers 2203.13740, arXiv.org.

    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:taf:japsta:v:30:y:2003:i:10:p:1081-1100. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.