One approach used for analyzing extremes is to fit the excesses over a high threshold by a generalized Pareto distribution. For the estimation of the shape and scale parameters in the generalized Pareto distribution, under some restrictions on the value of the scale parameter, maximum likelihood, method of moments and probability weighted moments' estimators are available. However, these are not robust estimators. In this paper we implement a robust estimation procedure known as the method of medians (He and Fung, 1999) to estimate the parameters in the generalized Pareto distribution. The asymptotic distribution of our estimator is normal for any value of the shape parameter except -1.
%0 Journal Article
%1 Peng.Welsh2001
%A Peng, Liang
%A Welsh, A.H.
%D 2001
%I Springer U.S.
%J Extremes
%K estimation parameter statistics
%P 53-65
%R 10.1023/A:1012233423407
%T Robust Estimation of the Generalized Pareto Distribution
%U http://dx.doi.org/10.1023/A:1012233423407
%V 4
%X One approach used for analyzing extremes is to fit the excesses over a high threshold by a generalized Pareto distribution. For the estimation of the shape and scale parameters in the generalized Pareto distribution, under some restrictions on the value of the scale parameter, maximum likelihood, method of moments and probability weighted moments' estimators are available. However, these are not robust estimators. In this paper we implement a robust estimation procedure known as the method of medians (He and Fung, 1999) to estimate the parameters in the generalized Pareto distribution. The asymptotic distribution of our estimator is normal for any value of the shape parameter except -1.
@article{Peng.Welsh2001,
abstract = {One approach used for analyzing extremes is to fit the excesses over a high threshold by a generalized Pareto distribution. For the estimation of the shape and scale parameters in the generalized Pareto distribution, under some restrictions on the value of the scale parameter, maximum likelihood, method of moments and probability weighted moments' estimators are available. However, these are not robust estimators. In this paper we implement a robust estimation procedure known as the method of medians (He and Fung, 1999) to estimate the parameters in the generalized Pareto distribution. The asymptotic distribution of our estimator is normal for any value of the shape parameter except -1.},
added-at = {2011-09-29T20:53:17.000+0200},
author = {Peng, Liang and Welsh, A.H.},
biburl = {https://www.bibsonomy.org/bibtex/2f9a6f759fc992148c12f45924550dc61/poeschko},
description = {SpringerLink - Extremes, Volume 4, Number 1},
doi = {10.1023/A:1012233423407},
interhash = {a3c8b84e4802d72f52a9dbdd1eb529ba},
intrahash = {f9a6f759fc992148c12f45924550dc61},
issn = {1386-1999},
issue = {1},
journal = {Extremes},
keyword = {Mathematics and Statistics},
keywords = {estimation parameter statistics},
pages = {53-65},
publisher = {Springer U.S.},
timestamp = {2011-09-29T20:53:17.000+0200},
title = {Robust Estimation of the Generalized Pareto Distribution},
url = {http://dx.doi.org/10.1023/A:1012233423407},
volume = 4,
year = 2001
}