Please use this identifier to cite or link to this item:
Title: Estimating Functionals for Heavy-Tailed Distributions and Application
Authors: Abdelhakim Necir
Djamel Meraghni
Issue Date: 11-Apr-2014
Abstract: 𝐿-functionals summarize numerous statistical parameters and actuarial risk measures. Their sample estimators are linear combinations of order statistics (𝐿-statistics). There exists a class of heavy-tailed distributions for which the asymptotic normality of these estimators cannot be obtained by classical results. In this paper we propose, by means of extreme value theory, alternative estimators for 𝐿-functionals and establish their asymptotic normality. Our results may be applied to estimate the trimmed 𝐿-moments and financial risk measures for heavy-tailed distributions. Link
Appears in Collections:Publications Internationales

Files in This Item:
File Description SizeFormat 
Estimating Functionals for Heavy-Tailed Distributions and Application.pdf41,37 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.