Iterative estimation of the extreme value index

Samuel Müller*, Jürg Hüsler

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


Let {Xn, 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 γ 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
Number of pages10
JournalMethodology and Computing in Applied Probability
Issue number2
Publication statusPublished - Jun 2005
Externally publishedYes


  • extreme value theory
  • tail index estimation
  • iterative estimator


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