Bivariate tail estimation : dependence in asymptotic independence

G. Draisma, H. Drees, A. Ferreira, L. Haan, de

    Research output: Contribution to journalArticleAcademicpeer-review

    95 Citations (Scopus)
    108 Downloads (Pure)

    Abstract

    In the classical setting of bivariate extreme value theory, the procedures for estimating the probability of an extreme event are not applicable if the componentwise maxima of the observations are asymptotically independent. To cope with this problem, Ledford and Tawn proposed a submodel in which the penultimate dependence is characterized by an additional parameter. We discuss the asymptotic properties of two estimators for this parameter in an extended model. Moreover, we develop an estimator for the probability of an extreme event that works in the case of asymptotic independence as well as in the case of asymptotic dependence, and prove its consistency.
    Original languageEnglish
    Pages (from-to)251-280
    JournalBernoulli
    Volume10
    Issue number2
    DOIs
    Publication statusPublished - 2004

    Fingerprint

    Dive into the research topics of 'Bivariate tail estimation : dependence in asymptotic independence'. Together they form a unique fingerprint.

    Cite this