Fulltext

Iterative Estimation of the Extreme Value Index

Müller, Samuel ; Hüsler, Jürg

In: Methodology and Computing in Applied Probability, 2005, vol. 7, no. 2, p. 139-148

Ajouter à la liste personnelle
    Titre
    • Iterative Estimation of the Extreme Value Index
    Auteur
    • Müller, Samuel. Department of Mathematical Statistics and Actuarial Science, University of Bern, 3012, Bern, Switzerland
    • Hüsler, Jürg. Department of Mathematical Statistics and Actuarial Science, University of Bern, 3012, Bern, Switzerland
    Type de document
    • Postprint
    Langue
    • Anglais
    Publié dans
    • Methodology and Computing in Applied Probability, 2005, vol. 7, no. 2, p. 139-148. Kluwer Academic Publishers
    Autre version électronique
    Identifiant OAI-PMH
    • oai:doc.rero.ch:320860
    Summary
    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