Distribution and dependence-function estimation for bivariate extreme-value distributions

Peter Hall*, Nader Tajvidi

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    80 Citations (Scopus)

    Abstract

    Two new methods are suggested for estimating the dependence function of a bivariate extreme-value distribution. One is based on a multiplicative modification of an earlier technique proposed by Pickands, and the other employs spline smoothing under constraints. Both produce estimators that satisfy all the conditions that define a dependence function, including convexity and the restriction that its curve lie within a certain triangular region. The first approach does not require selection of smoothing parameters; the second does, and for that purpose we suggest explicit tuning methods, one of them based on cross-validation.

    Original languageEnglish
    Pages (from-to)835-844
    Number of pages10
    JournalBernoulli
    Volume6
    Issue number5
    DOIs
    Publication statusPublished - 2000

    Fingerprint

    Dive into the research topics of 'Distribution and dependence-function estimation for bivariate extreme-value distributions'. Together they form a unique fingerprint.

    Cite this