LQ-moment : application to the generalized extreme valueÂ
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 effeciency of the Weighted Kemal Quantile(WKQ), HD(Harrell and Davis) quantile the weighted HD qualities estimators compared with the Linear Interpolation Qu...
| Main Authors: | , |
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| Format: | Article |
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Asian Network for Scientific Information
2007
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| Online Access: | http://eprints.utm.my/8793/ |
| _version_ | 1848891768138891264 |
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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 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 effeciency of the Weighted Kemal Quantile(WKQ), HD(Harrell and Davis) quantile the weighted HD qualities 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. |
| first_indexed | 2025-11-15T21:03:13Z |
| format | Article |
| id | utm-8793 |
| institution | Universiti Teknologi Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T21:03:13Z |
| publishDate | 2007 |
| publisher | Asian Network for Scientific Information |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utm-87932018-03-07T21:04:39Z http://eprints.utm.my/8793/ 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 effeciency of the Weighted Kemal Quantile(WKQ), HD(Harrell and Davis) quantile the weighted HD qualities 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 Article PeerReviewed Shabri, Ani and Jemain, Abdul Aziz (2007) LQ-moment : application to the generalized extreme valueÂ. Journal of Applied Sciences, 7 (1). pp. 115-120. ISSN 1812-5654 http://dx.doi.org/10.3923/jas.2007.115.120 doi : 10.3923/jas.2007.115.120 |
| spellingShingle | QA Mathematics Shabri, Ani Jemain, Abdul Aziz LQ-moment : application to the generalized extreme value |
| title | 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_short | LQ-moment : application to the generalized extreme value |
| title_sort | lq-moment : application to the generalized extreme valueâ |
| topic | QA Mathematics |
| url | http://eprints.utm.my/8793/ http://eprints.utm.my/8793/ http://eprints.utm.my/8793/ |