Iterative Estimation of the Extreme Value Index

S. Mueller, J. Husler

    Research output: Contribution to journalArticlepeer-review

    6 Citations (Scopus)


    Let {X-n, n >= 1} be a sequence of independent random variables with common continuous distribution function F having finite and unknown upper endpoint. A new iterative estimation procedure for the extreme value index gamma is proposed and one implemented iterative estimator is investigated in detail, which is asymptotically as good as the uniform minimum varianced unbiased estimator in an ideal model. Moreover, the superiority of the iterative estimator over its non iterated counterpart in the non asymptotic case is shown in a simulation study.
    Original languageEnglish
    Pages (from-to)139-148
    JournalMethodology and Computing in Applied Probability
    Publication statusPublished - 2005


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