International audienceIn this paper, we propose to include Weibull tail-distributions in a more general family of distributions. In particular, the considered model also encompasses the whole Fréchet maximum domain of attraction as well as log-Weibull tail-distributions. The asymptotic normality of some tail estimators based on the log-spacings between the largest order statistics is established in an unified way within the considered family. This result permits to understand the similarity between most estimators of the Weibull tail-coefficient and the Hill estimator. Some different asymptotic properties, in terms of bias, rate of convergence, are also highlighted
International audienceIn the case of Weibull tail distributions, the most commonly used methodology ...
We propose a new family of distributions referred to as shifted Weibull tail-distributions. It is de...
During the past couple of years, statistical distributions have been widely used in applied areas su...
International audienceIn this paper, we propose to include Weibull tail-distributions in a more gene...
International audienceIn this paper, we propose to include Weibull tail-distributions in a more gene...
International audienceThe Gnedenko theorem is a general result in extreme value theory establishing ...
International audienceWe present a new family of estimators of the Weibull tail-coefficient. The Wei...
International audienceWe present a new estimator of the Weibull tail-coefficient. The Weibull tail-c...
International audienceThe Weibull-tail class of distributions is a sub-class of the Gumbel extreme d...
The Weibull tail coefficient (WTC) is the parameter θ θ in a right-tail function of the type F¯:=1−...
By assuming that the underlying distribution belongs to the domain of attraction of an extreme value...
We address the estimation of extreme quantiles of Weibull tail-distributions. Since such quantiles a...
Based on suitable left-truncated or censored data, two flexible classes of M-estimations of Weibull ...
Due to the specificity of the Weibull tail coefficient, most of the estimators available in the lite...
International audienceIn this paper, we consider the problem of the estimation of the Weibull tail-c...
International audienceIn the case of Weibull tail distributions, the most commonly used methodology ...
We propose a new family of distributions referred to as shifted Weibull tail-distributions. It is de...
During the past couple of years, statistical distributions have been widely used in applied areas su...
International audienceIn this paper, we propose to include Weibull tail-distributions in a more gene...
International audienceIn this paper, we propose to include Weibull tail-distributions in a more gene...
International audienceThe Gnedenko theorem is a general result in extreme value theory establishing ...
International audienceWe present a new family of estimators of the Weibull tail-coefficient. The Wei...
International audienceWe present a new estimator of the Weibull tail-coefficient. The Weibull tail-c...
International audienceThe Weibull-tail class of distributions is a sub-class of the Gumbel extreme d...
The Weibull tail coefficient (WTC) is the parameter θ θ in a right-tail function of the type F¯:=1−...
By assuming that the underlying distribution belongs to the domain of attraction of an extreme value...
We address the estimation of extreme quantiles of Weibull tail-distributions. Since such quantiles a...
Based on suitable left-truncated or censored data, two flexible classes of M-estimations of Weibull ...
Due to the specificity of the Weibull tail coefficient, most of the estimators available in the lite...
International audienceIn this paper, we consider the problem of the estimation of the Weibull tail-c...
International audienceIn the case of Weibull tail distributions, the most commonly used methodology ...
We propose a new family of distributions referred to as shifted Weibull tail-distributions. It is de...
During the past couple of years, statistical distributions have been widely used in applied areas su...