Asymptotic expansions for the location invariant moment-type estimator

被引：1
作者：
Peng Zuoxiang [2 ]
Liu Miaomiao [2 ]
Nadarajah, Saralees [1 ]
机构：
[1] Univ Manchester, Sch Math, Manchester M60 1QD, Lancs, England
[2] Southwest Univ, Sch Math & Stat, Chongqing 400715, Peoples R China
来源：
MATHEMATICS AND COMPUTERS IN SIMULATION | 2010年 / 80卷 / 05期
关键词：
Asymptotic expansion; Asymptotic normality; Consistency; Extreme value index; EXTREME-VALUE THEORY; VALUE-AT-RISK; INFERENCE; INDEX;
D O I：
10.1016/j.matcom.2009.12.002
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
In this paper, based on moment-type and location invariant Hill estimators, a new kind of location invariant moment-type extreme value index estimator is proposed. The weak and strong consistency of the estimator are discussed. The asymptotic expansion of the estimator and its distribution are also considered under second order regularly varying conditions. The asymptotic normality is employed to construct the confidence interval. Monte Carlo simulations are performed to compare the Hill estimator and the moment estimator in terms of mean squared error. (C) 2009 IMACS. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码：982 / 998
页数：17
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