The bootstrap methodology in statistics of extremes -- choice of optimal sample fraction
type: Item
instance of: scholarly article
title: The bootstrap methodology in statistics of extremes -- choice of optimal sample fraction
zbMATH Open document ID: 1023.62048
author: M. Ivette Gomes
author: Orlando Oliveira
published in: Extremes
publication date: 2003-10-22T00:00:00Z
review text: The Hill estimator \(\widehat\gamma_n=n^{-1} \sum_{i=1}^K(\ln X_{n-i:n}-\ln X_{n-k:n})\) is considered for an i.i.d. sample \(X_1\),\dots, \(X_n\). Bootstrap methodologies of the optimal choice of sample proportion \(k/n\) are discussed. The techniques of bootstrapped MSE and asymptotic MSE optimization are described. As an alternative the use of auxiliary statistics is discussed. Different approaches are compared via simulation.
Mathematics Subject Classification ID: 62G09
Mathematics Subject Classification ID: 62G32
zbMATH DE Number: 1995752
zbMATH Keywords: semi-parametric estimation
zbMATH Keywords: MSE
zbMATH Keywords: Hill estimator
MaRDI profile type: Publication
description: scientific article; zbMATH DE number 1995752