A double-indexed functional Hill process and applications

preprint2016arXivOpen access

Abstract

Let X1,n≤....≤Xn,nX_{1,n} \leq .... \leq X_{n,n} be the order statistics associated with a sample X1,....,XnX_{1}, ...., X_{n} whose pertaining distribution function (% \textit{df}) is FF. We are concerned with the functional asymptotic behaviour of the sequence of stochastic processes \begin{equation} T_{n}(f,s)=\sum_{j=1}^{j=k}f(j)\left(\log X_{n-j+1,n}-\log X_{n-j,n}\right)^{s}, \label{fme} \end{equation} indexed by some classes F\mathcal{F} of functions f:Nf:\mathbb{N}% ^{\ast}\longmapsto \mathbb{R}_{+} and s∈]0,+∞[s \in ]0,+\infty[ and where k=k(n)k=k(n) satisfies \begin{equation*} 1\leq k\leq n,k/n\rightarrow 0\text{as}n\rightarrow \infty . \end{equation*} \noindent We show that this is a stochastic process whose margins generate estimators of the extreme value index when FF is in the extreme domain of attraction. We focus in this paper on its finite-dimension asymptotic law and provide a class of new estimators of the extreme value index whose performances are compared to analogous ones. The results are next particularized for one explicit class F\mathcal{F}.

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