Parameter estimate for three-parameter kappa distribution using LH-moments approach

The method of higher-order L-moments (LH-moment) was proposed as a more robust alternative compared to classical L-moments to characterize extreme events. The new derivation will be done for Mielke-Johnson's Kappa and Three-Parameters Kappa Type-II (K3D-II) distributions based on the LHmoments...

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Main Authors: Zahrahtul Amani, Zakaria, Ali, Jarah Moath Suleiman, Wan Nur Syahidah, Wan Yusoff
Format: Article
Language:English
Published: Institute of Advanced Science Extension (IASE) 2022
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/33581/1/Parameter%20estimate%20for%20three-parameter%20kappa%20distribution%20using%20LH-moments%20approach.pdf
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author Zahrahtul Amani, Zakaria
Ali, Jarah Moath Suleiman
Wan Nur Syahidah, Wan Yusoff
author_facet Zahrahtul Amani, Zakaria
Ali, Jarah Moath Suleiman
Wan Nur Syahidah, Wan Yusoff
author_sort Zahrahtul Amani, Zakaria
collection UMP
description The method of higher-order L-moments (LH-moment) was proposed as a more robust alternative compared to classical L-moments to characterize extreme events. The new derivation will be done for Mielke-Johnson's Kappa and Three-Parameters Kappa Type-II (K3D-II) distributions based on the LHmoments approach. The data of maximum monthly rainfall for Embong station in Terengganu were used as a case study. The analyses were conducted using the classical L-moments method with η = 0 and LHmoments methods with η = 1, η = 2, η = 3 and η = 4 for a complete data series and upper parts of the distributions. The most suitable distributions were determined based on the Mean Absolute Deviation Index (MADI), Mean Square Deviation Index (MSDI), and Correlation (r). Also, L-moment and LHmoment ratio diagrams were used to represent visual proofs of the results. The analysis showed that LH-moments methods at a higher order of K3D-II distribution best fit the data of maximum monthly rainfalls for the Embong station for the upper parts of the distribution compared to L-moments. The results also proved that whenever η increases, LH-moments reflect more and more characteristics of the upper part of the distribution. This seems to suggest that LH-moments estimates for the upper part of the distribution events are superior to L-moments in fitting the data of maximum monthly rainfalls.
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spelling UMPir335812022-04-15T07:20:34Z http://umpir.ump.edu.my/id/eprint/33581/ Parameter estimate for three-parameter kappa distribution using LH-moments approach Zahrahtul Amani, Zakaria Ali, Jarah Moath Suleiman Wan Nur Syahidah, Wan Yusoff GB Physical geography Q Science (General) QA Mathematics The method of higher-order L-moments (LH-moment) was proposed as a more robust alternative compared to classical L-moments to characterize extreme events. The new derivation will be done for Mielke-Johnson's Kappa and Three-Parameters Kappa Type-II (K3D-II) distributions based on the LHmoments approach. The data of maximum monthly rainfall for Embong station in Terengganu were used as a case study. The analyses were conducted using the classical L-moments method with η = 0 and LHmoments methods with η = 1, η = 2, η = 3 and η = 4 for a complete data series and upper parts of the distributions. The most suitable distributions were determined based on the Mean Absolute Deviation Index (MADI), Mean Square Deviation Index (MSDI), and Correlation (r). Also, L-moment and LHmoment ratio diagrams were used to represent visual proofs of the results. The analysis showed that LH-moments methods at a higher order of K3D-II distribution best fit the data of maximum monthly rainfalls for the Embong station for the upper parts of the distribution compared to L-moments. The results also proved that whenever η increases, LH-moments reflect more and more characteristics of the upper part of the distribution. This seems to suggest that LH-moments estimates for the upper part of the distribution events are superior to L-moments in fitting the data of maximum monthly rainfalls. Institute of Advanced Science Extension (IASE) 2022-02 Article PeerReviewed pdf en cc_by_nc_nd_4 http://umpir.ump.edu.my/id/eprint/33581/1/Parameter%20estimate%20for%20three-parameter%20kappa%20distribution%20using%20LH-moments%20approach.pdf Zahrahtul Amani, Zakaria and Ali, Jarah Moath Suleiman and Wan Nur Syahidah, Wan Yusoff (2022) Parameter estimate for three-parameter kappa distribution using LH-moments approach. International Journal of Advanced and Applied Sciences, 9 (2). pp. 104-108. ISSN 2313-626X. (Published) https://doi.org/10.21833/IJAAS.2022.02.011 https://doi.org/10.21833/IJAAS.2022.02.011
spellingShingle GB Physical geography
Q Science (General)
QA Mathematics
Zahrahtul Amani, Zakaria
Ali, Jarah Moath Suleiman
Wan Nur Syahidah, Wan Yusoff
Parameter estimate for three-parameter kappa distribution using LH-moments approach
title Parameter estimate for three-parameter kappa distribution using LH-moments approach
title_full Parameter estimate for three-parameter kappa distribution using LH-moments approach
title_fullStr Parameter estimate for three-parameter kappa distribution using LH-moments approach
title_full_unstemmed Parameter estimate for three-parameter kappa distribution using LH-moments approach
title_short Parameter estimate for three-parameter kappa distribution using LH-moments approach
title_sort parameter estimate for three parameter kappa distribution using lh moments approach
topic GB Physical geography
Q Science (General)
QA Mathematics
url http://umpir.ump.edu.my/id/eprint/33581/1/Parameter%20estimate%20for%20three-parameter%20kappa%20distribution%20using%20LH-moments%20approach.pdf
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