Estimation of the functional Weibull-tail coefficient

Laurent Gardes 1 Stéphane Girard 2
2 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : We present a nonparametric family of estimators for the tail index of a Weibull tail-distribution when functional covariate is available. Our estimators are based on a kernel estimator of extreme conditional quantiles, extending a previous work Daouia et al. (2013) to the infinite dimensional case. Asymptotic normality of the estimators is proved under mild regularity conditions. Their finite sample performances are illustrated both on simulated and real data. We refer to Gardes and Girard (2016) for further details. Daouia, A., Gardes, L., Girard, S. (2013). On kernel smoothing for extremal quantile regression. Bernoulli, 19, 2557–2589. Gardes, L., Girard, S. (2016). On the estimation of the functional Weibull tail-coefficient, Journal of Multivariate Analysis, to appear, http://dx.doi.org/10.1016/j.jmva.2015.05.007
Type de document :
Communication dans un congrès
3rd conference of the International Society for Non-Parametric Statistics (ISNPS), Jun 2016, Avignon, France
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https://hal.inria.fr/hal-01366174
Contributeur : Stephane Girard <>
Soumis le : mercredi 14 septembre 2016 - 10:59:50
Dernière modification le : mercredi 11 avril 2018 - 01:58:43

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  • HAL Id : hal-01366174, version 1

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Laurent Gardes, Stéphane Girard. Estimation of the functional Weibull-tail coefficient. 3rd conference of the International Society for Non-Parametric Statistics (ISNPS), Jun 2016, Avignon, France. 〈hal-01366174〉

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