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Semi-parametric estimation for heavy tailed distributions

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Abstract

In this paper, we generalize several studies in the area of extreme value theory for the estimation of the extreme value index and the second order parameter. Weak consistency and asymptotic normality are proven under classical assumptions. Some numerical simulations and computations are also performed to illustrate the finite-sample and the limiting behavior of the estimators.

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Authors and Affiliations

  1. Université de Lyon, Université Lyon 1 - CNRS, Institut Camille Jordan - UMR 5208, 43 boulevard du 11 novembre 1918, F-69622, Villeurbanne Cedex, France

    Gabriela Ciuperca & Cécile Mercadier

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  1. Gabriela Ciuperca
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  2. Cécile Mercadier
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Correspondence to Cécile Mercadier.

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Ciuperca, G., Mercadier, C. Semi-parametric estimation for heavy tailed distributions. Extremes 13, 55–87 (2010). https://doi.org/10.1007/s10687-009-0086-6

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  • DOI: https://doi.org/10.1007/s10687-009-0086-6

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