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| HAL : hal-00015778, version 2 |
| Fiche détaillée |  Récupérer au format |
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| Journal of Statistical Planning and Inference 138 (2008) 1389--1401 |
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| Versions disponibles : | v1 (13-12-2005) | v2 (08-05-2013) |
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| Bias-reduced extreme quantiles estimators of Weibull distributions |
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| Jean Diebolt 1Laurent Gardes 2 |
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| (2008) |
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| In this paper, we consider the problem of estimating an extreme quantile of a Weibull tail-distribution. The new extreme quantile estimator has a reduced bias compared to the more classical ones proposed in the literature. It is based on an exponential regression model that was introduced in Diebolt et al. (2008). Its asymptotic normality is established and a small simulation study is provided in order to illustrate its efficiency. |
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| 1 : | Laboratoire d'Analyse et de Mathématiques Appliquées (LAMA) |
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Université Paris-Est Marne-la-Vallée (UPEMLV) – Université Paris-Est Créteil Val-de-Marne (UPEC) – CNRS : UMR8050 – Fédération de Recherche Bézout |
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| 2 : | MISTIS (INRIA Rhône-Alpes) |
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INRIA |
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| 3 : | Laboratoire de Statistique Théorique et Appliquée (LSTA) |
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Université Pierre et Marie Curie [UPMC] - Paris VI |
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| Domaine | : | Mathématiques/Statistiques Statistiques/Théorie |
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| Weibull tail-distribution – extreme quantile – bias-reduction – least-squares approach – asymptotic normality. |
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| Liste des fichiers attachés à ce document : | |||||
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| hal-00015778, version 2 | |
| http://hal.archives-ouvertes.fr/hal-00015778 | |
| oai:hal.archives-ouvertes.fr:hal-00015778 | |
| Contributeur : Stephane Girard | |
| Soumis le : Mardi 7 Mai 2013, 17:22:36 | |
| Dernière modification le : Mercredi 8 Mai 2013, 08:44:31 | |
