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LQ-moments: application to the extreme value type I distribution

The objective of this study is to develop improved LQ-moments that do not impose restrictions on the value of p and α such as the median, trimean or the Gastwirth but we explore an extended class of LQMOM with consideration combinations of p and α values in the range 0 and 0.5. The popular quantil...

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Main Authors: Shabri, Ani, Jemain, Abdul Aziz
Format: Article
Published: Asian Network for Scientific Information 2006
Subjects:
Q Science (General)
Online Access:http://eprints.utm.my/id/eprint/9051/
http://dx.doi.org/10.3923/jas.2006.993.997
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spelling my.utm.90512018-03-22T08:33:46Z http://eprints.utm.my/id/eprint/9051/ LQ-moments: application to the extreme value type I distribution Shabri, Ani Jemain, Abdul Aziz Q Science (General) The objective of this study is to develop improved LQ-moments that do not impose restrictions on the value of p and α such as the median, trimean or the Gastwirth but we explore an extended class of LQMOM with consideration combinations of p and α values in the range 0 and 0.5. The popular quantile estimator namely the Weighted Kernel Quantile (WKQ) estimator will be proposed to estimate the quantile function. The performances of the proposed estimators of the Extreme Values Type 1 (EV1) distribution were compared with the estimators based on conventional LMOM, MOM (method of moments), ML (method of maximum likelihood) and the LQ-moments based on LIQ (linear interpolation quantile) for various sample sizes and return periods. Asian Network for Scientific Information 2006 Article PeerReviewed Shabri, Ani and Jemain, Abdul Aziz (2006) LQ-moments: application to the extreme value type I distribution. Journal of Applied Sciences, 6 (5). pp. 993-997. ISSN 1812-5654 http://dx.doi.org/10.3923/jas.2006.993.997 10.3923/jas.2006.993.997
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 Q Science (General)
spellingShingle Q Science (General)
Shabri, Ani
Jemain, Abdul Aziz
LQ-moments: application to the extreme value type I distribution
description The objective of this study is to develop improved LQ-moments that do not impose restrictions on the value of p and α such as the median, trimean or the Gastwirth but we explore an extended class of LQMOM with consideration combinations of p and α values in the range 0 and 0.5. The popular quantile estimator namely the Weighted Kernel Quantile (WKQ) estimator will be proposed to estimate the quantile function. The performances of the proposed estimators of the Extreme Values Type 1 (EV1) distribution were compared with the estimators based on conventional LMOM, MOM (method of moments), ML (method of maximum likelihood) and the LQ-moments based on LIQ (linear interpolation quantile) for various sample sizes and return periods.
format Article
author Shabri, Ani
Jemain, Abdul Aziz
author_facet Shabri, Ani
Jemain, Abdul Aziz
author_sort Shabri, Ani
title LQ-moments: application to the extreme value type I distribution
title_short LQ-moments: application to the extreme value type I distribution
title_full LQ-moments: application to the extreme value type I distribution
title_fullStr LQ-moments: application to the extreme value type I distribution
title_full_unstemmed LQ-moments: application to the extreme value type I distribution
title_sort lq-moments: application to the extreme value type i distribution
publisher Asian Network for Scientific Information
publishDate 2006
url http://eprints.utm.my/id/eprint/9051/
http://dx.doi.org/10.3923/jas.2006.993.997
_version_ 1643645106185568256
score 13.211869

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