Estimation of the extreme value type I Distribution by the method of LQ-Moments

The study evaluated the effectiveness of the various quantile estimators of the LQ-moments method for estimating parameters of the Extreme Value Type 1 (EV1) distribution. Approach: The performances of the LQ-moments were analyzed and compared against a widely used method of L-moments by using simul...

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Main Authors: Shabri, Ani, Jemain, Abdul Aziz
Format: Article
Language:English
Published: Science Publications 2009
Subjects:
Online Access:http://eprints.utm.my/2638/
http://eprints.utm.my/2638/1/AniShabri2009_EstimationoftheExtremeValueType.pdf
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author Shabri, Ani
Jemain, Abdul Aziz
author_facet Shabri, Ani
Jemain, Abdul Aziz
author_sort Shabri, Ani
building UTeM Institutional Repository
collection Online Access
description The study evaluated the effectiveness of the various quantile estimators of the LQ-moments method for estimating parameters of the Extreme Value Type 1 (EV1) distribution. Approach: The performances of the LQ-moments were analyzed and compared against a widely used method of L-moments by using simulated samples of both EV1 and generalized Lambda distribution, focusing on small and moderate sample sizes. Results: The analysis results showed that LQMOM method wais more efficient in many cases especially for the upper tails of the distribution and for various sample sizes. Conclusion: This study demonstrated that conventional LMOM was not optimal for the estimation of the EV1 distribution
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spelling utm-26382010-10-13T04:45:22Z http://eprints.utm.my/2638/ Estimation of the extreme value type I Distribution by the method of LQ-Moments Shabri, Ani Jemain, Abdul Aziz QA Mathematics The study evaluated the effectiveness of the various quantile estimators of the LQ-moments method for estimating parameters of the Extreme Value Type 1 (EV1) distribution. Approach: The performances of the LQ-moments were analyzed and compared against a widely used method of L-moments by using simulated samples of both EV1 and generalized Lambda distribution, focusing on small and moderate sample sizes. Results: The analysis results showed that LQMOM method wais more efficient in many cases especially for the upper tails of the distribution and for various sample sizes. Conclusion: This study demonstrated that conventional LMOM was not optimal for the estimation of the EV1 distribution Science Publications 2009 Article PeerReviewed application/pdf en http://eprints.utm.my/2638/1/AniShabri2009_EstimationoftheExtremeValueType.pdf Shabri, Ani and Jemain, Abdul Aziz (2009) Estimation of the extreme value type I Distribution by the method of LQ-Moments. Journal of Mathematics and Statistics, 5 (4). pp. 298-304. ISSN 1549-3644 http://www.scipub.org/fulltext/jms2/jms254298-304.pdf
spellingShingle QA Mathematics
Shabri, Ani
Jemain, Abdul Aziz
Estimation of the extreme value type I Distribution by the method of LQ-Moments
title Estimation of the extreme value type I Distribution by the method of LQ-Moments
title_full Estimation of the extreme value type I Distribution by the method of LQ-Moments
title_fullStr Estimation of the extreme value type I Distribution by the method of LQ-Moments
title_full_unstemmed Estimation of the extreme value type I Distribution by the method of LQ-Moments
title_short Estimation of the extreme value type I Distribution by the method of LQ-Moments
title_sort estimation of the extreme value type i distribution by the method of lq-moments
topic QA Mathematics
url http://eprints.utm.my/2638/
http://eprints.utm.my/2638/
http://eprints.utm.my/2638/1/AniShabri2009_EstimationoftheExtremeValueType.pdf