National audienceExtreme quantile estimation remains a major statistical challenge. In this communication, the problem is addressed in the framework of the so-called "log-Generalized Weibull tail limit", where the logarithm of the inverse cumulative hazard rate function is supposed to be of extended regular variation. Based on this model, a new estimator of extreme quantiles is proposed. Its asymptotic normality is established and its behavior in practice is illustrated on simulated data.L'estimation de quantiles extrêmes demeure un problème statistique majeur. Dans cette communication, le problème est abordé dans le cadre du modèle " log Weibull-tail " généralisé, où le logarithme de l'inverse du taux de hasard cumulé est supposé à variati...
We consider the estimation of an extreme conditional quantile. In a first part, we propose a new tai...
International audienceThe notion of quantiles lies at the heart of extreme-value theory and is one o...
International audienceWe present a nonparametric family of estimators for the tail coefficient of a ...
International audienceA new estimator for extreme quantiles is proposed under the log-generalized We...
International audienceIn this paper, we consider the problem of estimating an extreme quantile of a ...
We address the estimation of extreme quantiles of Weibull tail-distributions. Since such quantiles a...
International audienceIn the case of Weibull tail distributions, the most commonly used methodology ...
International audienceIn the case of Weibull tail distributions, the most commonly used methodology ...
This thesis takes place in the extreme value statistics framework. It provides three main contributi...
This thesis considers estimation of the quantiles of the smallest extreme value distribution, someti...
International audienceThe Weibull-tail class of distributions is a sub-class of the Gumbel extreme d...
International audienceWe address the problem of estimating the Weibull tail-coefficient which is the...
International audienceThe class of quantiles lies at the heart of extreme-value theory and is one of...
Cette thèse s'inscrit dans le contexte de la statistique des valeurs extrêmes. Elle y apporte deux c...
This thesis can be viewed within the context of extreme value statistics. It provides two main contr...
We consider the estimation of an extreme conditional quantile. In a first part, we propose a new tai...
International audienceThe notion of quantiles lies at the heart of extreme-value theory and is one o...
International audienceWe present a nonparametric family of estimators for the tail coefficient of a ...
International audienceA new estimator for extreme quantiles is proposed under the log-generalized We...
International audienceIn this paper, we consider the problem of estimating an extreme quantile of a ...
We address the estimation of extreme quantiles of Weibull tail-distributions. Since such quantiles a...
International audienceIn the case of Weibull tail distributions, the most commonly used methodology ...
International audienceIn the case of Weibull tail distributions, the most commonly used methodology ...
This thesis takes place in the extreme value statistics framework. It provides three main contributi...
This thesis considers estimation of the quantiles of the smallest extreme value distribution, someti...
International audienceThe Weibull-tail class of distributions is a sub-class of the Gumbel extreme d...
International audienceWe address the problem of estimating the Weibull tail-coefficient which is the...
International audienceThe class of quantiles lies at the heart of extreme-value theory and is one of...
Cette thèse s'inscrit dans le contexte de la statistique des valeurs extrêmes. Elle y apporte deux c...
This thesis can be viewed within the context of extreme value statistics. It provides two main contr...
We consider the estimation of an extreme conditional quantile. In a first part, we propose a new tai...
International audienceThe notion of quantiles lies at the heart of extreme-value theory and is one o...
International audienceWe present a nonparametric family of estimators for the tail coefficient of a ...