LQ-moment: application to the generalized extreme value

LQ-moment: application to the generalized extreme value

The LQ-moments are analogous to L-moments, found always exists, easier to compute and have the same potential as L-moment were re-visited. The efficiency of the Weighted Kernal Quantile (WKQ), HD (Harrell and Davis) quantile the weighted HD quantiles estimators compared with the Linear Interpolation...

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Main Authors: Shabri, Ani, Jemain, Abdul Aziz
Format: Article
Published: Asian Network for Scientific Information 2007
Subjects:
QA Mathematics
Online Access:http://eprints.utm.my/id/eprint/7645/
http://dx.doi.org/10.3923/jas.2007.115.120
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Institution: Universiti Teknologi Malaysia
id my.utm.7645
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spelling my.utm.76452009-05-12T07:06:44Z http://eprints.utm.my/id/eprint/7645/ LQ-moment: application to the generalized extreme value Shabri, Ani Jemain, Abdul Aziz QA Mathematics The LQ-moments are analogous to L-moments, found always exists, easier to compute and have the same potential as L-moment were re-visited. The efficiency of the Weighted Kernal Quantile (WKQ), HD (Harrell and Davis) quantile the weighted HD quantiles estimators compared with the Linear Interpolation Quantile (LIQ) estimator to estimate the sample of the LQ-moments. In this study we discuss of the quantile estimator of the LQ-moments method to estimate the parameters of the Generalized Extreme Value (GEV) distribution. In order to determine which quantile estimator is the most suitable for the LQ-moment, the Monte Carlo simulation was considered. The result shows that the WKQ is considered as the best quantile estimator compared with the HDWQ, HDQ and LIQ estimator. Asian Network for Scientific Information 2007-01-01 Article PeerReviewed Shabri, Ani and Jemain, Abdul Aziz (2007) LQ-moment: application to the generalized extreme value. Journal of Applied Sciences, 7 (1). pp. 115-120. ISSN 1812-5654 http://dx.doi.org/10.3923/jas.2007.115.120 10.3923/jas.2007.115.120
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA Mathematics
spellingShingle QA Mathematics
Shabri, Ani
Jemain, Abdul Aziz
LQ-moment: application to the generalized extreme value
description The LQ-moments are analogous to L-moments, found always exists, easier to compute and have the same potential as L-moment were re-visited. The efficiency of the Weighted Kernal Quantile (WKQ), HD (Harrell and Davis) quantile the weighted HD quantiles estimators compared with the Linear Interpolation Quantile (LIQ) estimator to estimate the sample of the LQ-moments. In this study we discuss of the quantile estimator of the LQ-moments method to estimate the parameters of the Generalized Extreme Value (GEV) distribution. In order to determine which quantile estimator is the most suitable for the LQ-moment, the Monte Carlo simulation was considered. The result shows that the WKQ is considered as the best quantile estimator compared with the HDWQ, HDQ and LIQ estimator.
format Article
author Shabri, Ani
Jemain, Abdul Aziz
author_facet Shabri, Ani
Jemain, Abdul Aziz
author_sort Shabri, Ani
title LQ-moment: application to the generalized extreme value
title_short LQ-moment: application to the generalized extreme value
title_full LQ-moment: application to the generalized extreme value
title_fullStr LQ-moment: application to the generalized extreme value
title_full_unstemmed LQ-moment: application to the generalized extreme value
title_sort lq-moment: application to the generalized extreme value
publisher Asian Network for Scientific Information
publishDate 2007
url http://eprints.utm.my/id/eprint/7645/
http://dx.doi.org/10.3923/jas.2007.115.120
_version_ 1643644819681050624

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