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Conference papers

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, Grenoble INP - Institut polytechnique de Grenoble - Grenoble Institute of Technology, LJK - Laboratoire Jean Kuntzmann
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,
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Submitted on : Wednesday, September 14, 2016 - 10:59:50 AM
Last modification on : Wednesday, November 3, 2021 - 5:13:42 AM


  • HAL Id : hal-01366174, version 1



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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