The best fitting distribution of annual maximum rainfall in Peninsular Malaysia based on methods of L-moment and LQ-moment
Abstract The main objective of this study is to determine the best fitting distribution to describe the annual series of maximum daily rainfall from 1975 to 2004 for 50 rain gauge stations in Peninsular Malaysia based on L-moment and LQ-moment. Five three-parameter extreme-value distributions which...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Wan Zin, Wan Zawiah [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2008 |
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| Schlagwörter: |
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| Systematik: |
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| Anmerkung: |
© Springer-Verlag 2008 |
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| Übergeordnetes Werk: |
Enthalten in: Theoretical and applied climatology - Springer Vienna, 1986, 96(2008), 3-4 vom: 17. Juli, Seite 337-344 |
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| Übergeordnetes Werk: |
volume:96 ; year:2008 ; number:3-4 ; day:17 ; month:07 ; pages:337-344 |
| Links: |
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| DOI / URN: |
10.1007/s00704-008-0044-2 |
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| Katalog-ID: |
OLC2048442439 |
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| 520 | |a Abstract The main objective of this study is to determine the best fitting distribution to describe the annual series of maximum daily rainfall from 1975 to 2004 for 50 rain gauge stations in Peninsular Malaysia based on L-moment and LQ-moment. Five three-parameter extreme-value distributions which are considered are generalized extreme value (GEV), generalized Pareto (GP), generalized logistic (GL), lognormal (LN3) and Pearson (P3) distributions. The estimation of parameters of these distributions is determined using the L-moment and LQ-moment. The adequacy of the distributions based on parameter estimates computed using the two methods are evaluated using goodness-of-fit tests. When the goodness-of-fit results for these distributions are compared, it is found that, on the average, the performance of L-moment is better than the performance of LQ-moment. Although the best fitting distribution may vary according to the method of estimation and stations considered, in most cases, data for the majority of the stations are found to follow the generalized logistic distribution. | ||
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10.1007/s00704-008-0044-2 doi (DE-627)OLC2048442439 (DE-He213)s00704-008-0044-2-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn RA 1000 VZ rvk Wan Zin, Wan Zawiah verfasserin aut The best fitting distribution of annual maximum rainfall in Peninsular Malaysia based on methods of L-moment and LQ-moment 2008 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2008 Abstract The main objective of this study is to determine the best fitting distribution to describe the annual series of maximum daily rainfall from 1975 to 2004 for 50 rain gauge stations in Peninsular Malaysia based on L-moment and LQ-moment. Five three-parameter extreme-value distributions which are considered are generalized extreme value (GEV), generalized Pareto (GP), generalized logistic (GL), lognormal (LN3) and Pearson (P3) distributions. The estimation of parameters of these distributions is determined using the L-moment and LQ-moment. The adequacy of the distributions based on parameter estimates computed using the two methods are evaluated using goodness-of-fit tests. When the goodness-of-fit results for these distributions are compared, it is found that, on the average, the performance of L-moment is better than the performance of LQ-moment. Although the best fitting distribution may vary according to the method of estimation and stations considered, in most cases, data for the majority of the stations are found to follow the generalized logistic distribution. Malaysia Generalize Extreme Value Extreme Rainfall Generalize Extreme Value Distribution Extreme Rainfall Event Jemain, Abdul Aziz aut Ibrahim, Kamarulzaman aut Enthalten in Theoretical and applied climatology Springer Vienna, 1986 96(2008), 3-4 vom: 17. Juli, Seite 337-344 (DE-627)129958808 (DE-600)405799-5 (DE-576)01552857X 0177-798X nnns volume:96 year:2008 number:3-4 day:17 month:07 pages:337-344 https://doi.org/10.1007/s00704-008-0044-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO GBV_ILN_40 GBV_ILN_70 GBV_ILN_381 GBV_ILN_2003 GBV_ILN_2006 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4306 GBV_ILN_4311 GBV_ILN_4313 RA 1000 AR 96 2008 3-4 17 07 337-344 |
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10.1007/s00704-008-0044-2 doi (DE-627)OLC2048442439 (DE-He213)s00704-008-0044-2-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn RA 1000 VZ rvk Wan Zin, Wan Zawiah verfasserin aut The best fitting distribution of annual maximum rainfall in Peninsular Malaysia based on methods of L-moment and LQ-moment 2008 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2008 Abstract The main objective of this study is to determine the best fitting distribution to describe the annual series of maximum daily rainfall from 1975 to 2004 for 50 rain gauge stations in Peninsular Malaysia based on L-moment and LQ-moment. Five three-parameter extreme-value distributions which are considered are generalized extreme value (GEV), generalized Pareto (GP), generalized logistic (GL), lognormal (LN3) and Pearson (P3) distributions. The estimation of parameters of these distributions is determined using the L-moment and LQ-moment. The adequacy of the distributions based on parameter estimates computed using the two methods are evaluated using goodness-of-fit tests. When the goodness-of-fit results for these distributions are compared, it is found that, on the average, the performance of L-moment is better than the performance of LQ-moment. Although the best fitting distribution may vary according to the method of estimation and stations considered, in most cases, data for the majority of the stations are found to follow the generalized logistic distribution. Malaysia Generalize Extreme Value Extreme Rainfall Generalize Extreme Value Distribution Extreme Rainfall Event Jemain, Abdul Aziz aut Ibrahim, Kamarulzaman aut Enthalten in Theoretical and applied climatology Springer Vienna, 1986 96(2008), 3-4 vom: 17. Juli, Seite 337-344 (DE-627)129958808 (DE-600)405799-5 (DE-576)01552857X 0177-798X nnns volume:96 year:2008 number:3-4 day:17 month:07 pages:337-344 https://doi.org/10.1007/s00704-008-0044-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO GBV_ILN_40 GBV_ILN_70 GBV_ILN_381 GBV_ILN_2003 GBV_ILN_2006 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4306 GBV_ILN_4311 GBV_ILN_4313 RA 1000 AR 96 2008 3-4 17 07 337-344 |
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10.1007/s00704-008-0044-2 doi (DE-627)OLC2048442439 (DE-He213)s00704-008-0044-2-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn RA 1000 VZ rvk Wan Zin, Wan Zawiah verfasserin aut The best fitting distribution of annual maximum rainfall in Peninsular Malaysia based on methods of L-moment and LQ-moment 2008 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2008 Abstract The main objective of this study is to determine the best fitting distribution to describe the annual series of maximum daily rainfall from 1975 to 2004 for 50 rain gauge stations in Peninsular Malaysia based on L-moment and LQ-moment. Five three-parameter extreme-value distributions which are considered are generalized extreme value (GEV), generalized Pareto (GP), generalized logistic (GL), lognormal (LN3) and Pearson (P3) distributions. The estimation of parameters of these distributions is determined using the L-moment and LQ-moment. The adequacy of the distributions based on parameter estimates computed using the two methods are evaluated using goodness-of-fit tests. When the goodness-of-fit results for these distributions are compared, it is found that, on the average, the performance of L-moment is better than the performance of LQ-moment. Although the best fitting distribution may vary according to the method of estimation and stations considered, in most cases, data for the majority of the stations are found to follow the generalized logistic distribution. Malaysia Generalize Extreme Value Extreme Rainfall Generalize Extreme Value Distribution Extreme Rainfall Event Jemain, Abdul Aziz aut Ibrahim, Kamarulzaman aut Enthalten in Theoretical and applied climatology Springer Vienna, 1986 96(2008), 3-4 vom: 17. Juli, Seite 337-344 (DE-627)129958808 (DE-600)405799-5 (DE-576)01552857X 0177-798X nnns volume:96 year:2008 number:3-4 day:17 month:07 pages:337-344 https://doi.org/10.1007/s00704-008-0044-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO GBV_ILN_40 GBV_ILN_70 GBV_ILN_381 GBV_ILN_2003 GBV_ILN_2006 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4306 GBV_ILN_4311 GBV_ILN_4313 RA 1000 AR 96 2008 3-4 17 07 337-344 |
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10.1007/s00704-008-0044-2 doi (DE-627)OLC2048442439 (DE-He213)s00704-008-0044-2-p DE-627 ger DE-627 rakwb eng 550 VZ 14 ssgn RA 1000 VZ rvk Wan Zin, Wan Zawiah verfasserin aut The best fitting distribution of annual maximum rainfall in Peninsular Malaysia based on methods of L-moment and LQ-moment 2008 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer-Verlag 2008 Abstract The main objective of this study is to determine the best fitting distribution to describe the annual series of maximum daily rainfall from 1975 to 2004 for 50 rain gauge stations in Peninsular Malaysia based on L-moment and LQ-moment. Five three-parameter extreme-value distributions which are considered are generalized extreme value (GEV), generalized Pareto (GP), generalized logistic (GL), lognormal (LN3) and Pearson (P3) distributions. The estimation of parameters of these distributions is determined using the L-moment and LQ-moment. The adequacy of the distributions based on parameter estimates computed using the two methods are evaluated using goodness-of-fit tests. When the goodness-of-fit results for these distributions are compared, it is found that, on the average, the performance of L-moment is better than the performance of LQ-moment. Although the best fitting distribution may vary according to the method of estimation and stations considered, in most cases, data for the majority of the stations are found to follow the generalized logistic distribution. Malaysia Generalize Extreme Value Extreme Rainfall Generalize Extreme Value Distribution Extreme Rainfall Event Jemain, Abdul Aziz aut Ibrahim, Kamarulzaman aut Enthalten in Theoretical and applied climatology Springer Vienna, 1986 96(2008), 3-4 vom: 17. Juli, Seite 337-344 (DE-627)129958808 (DE-600)405799-5 (DE-576)01552857X 0177-798X nnns volume:96 year:2008 number:3-4 day:17 month:07 pages:337-344 https://doi.org/10.1007/s00704-008-0044-2 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-GEO SSG-OPC-GGO GBV_ILN_40 GBV_ILN_70 GBV_ILN_381 GBV_ILN_2003 GBV_ILN_2006 GBV_ILN_4012 GBV_ILN_4029 GBV_ILN_4306 GBV_ILN_4311 GBV_ILN_4313 RA 1000 AR 96 2008 3-4 17 07 337-344 |
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The best fitting distribution of annual maximum rainfall in Peninsular Malaysia based on methods of L-moment and LQ-moment |
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The best fitting distribution of annual maximum rainfall in Peninsular Malaysia based on methods of L-moment and LQ-moment |
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Wan Zin, Wan Zawiah |
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Theoretical and applied climatology |
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2008 |
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Wan Zin, Wan Zawiah Jemain, Abdul Aziz Ibrahim, Kamarulzaman |
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10.1007/s00704-008-0044-2 |
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the best fitting distribution of annual maximum rainfall in peninsular malaysia based on methods of l-moment and lq-moment |
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The best fitting distribution of annual maximum rainfall in Peninsular Malaysia based on methods of L-moment and LQ-moment |
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Abstract The main objective of this study is to determine the best fitting distribution to describe the annual series of maximum daily rainfall from 1975 to 2004 for 50 rain gauge stations in Peninsular Malaysia based on L-moment and LQ-moment. Five three-parameter extreme-value distributions which are considered are generalized extreme value (GEV), generalized Pareto (GP), generalized logistic (GL), lognormal (LN3) and Pearson (P3) distributions. The estimation of parameters of these distributions is determined using the L-moment and LQ-moment. The adequacy of the distributions based on parameter estimates computed using the two methods are evaluated using goodness-of-fit tests. When the goodness-of-fit results for these distributions are compared, it is found that, on the average, the performance of L-moment is better than the performance of LQ-moment. Although the best fitting distribution may vary according to the method of estimation and stations considered, in most cases, data for the majority of the stations are found to follow the generalized logistic distribution. © Springer-Verlag 2008 |
| abstractGer |
Abstract The main objective of this study is to determine the best fitting distribution to describe the annual series of maximum daily rainfall from 1975 to 2004 for 50 rain gauge stations in Peninsular Malaysia based on L-moment and LQ-moment. Five three-parameter extreme-value distributions which are considered are generalized extreme value (GEV), generalized Pareto (GP), generalized logistic (GL), lognormal (LN3) and Pearson (P3) distributions. The estimation of parameters of these distributions is determined using the L-moment and LQ-moment. The adequacy of the distributions based on parameter estimates computed using the two methods are evaluated using goodness-of-fit tests. When the goodness-of-fit results for these distributions are compared, it is found that, on the average, the performance of L-moment is better than the performance of LQ-moment. Although the best fitting distribution may vary according to the method of estimation and stations considered, in most cases, data for the majority of the stations are found to follow the generalized logistic distribution. © Springer-Verlag 2008 |
| abstract_unstemmed |
Abstract The main objective of this study is to determine the best fitting distribution to describe the annual series of maximum daily rainfall from 1975 to 2004 for 50 rain gauge stations in Peninsular Malaysia based on L-moment and LQ-moment. Five three-parameter extreme-value distributions which are considered are generalized extreme value (GEV), generalized Pareto (GP), generalized logistic (GL), lognormal (LN3) and Pearson (P3) distributions. The estimation of parameters of these distributions is determined using the L-moment and LQ-moment. The adequacy of the distributions based on parameter estimates computed using the two methods are evaluated using goodness-of-fit tests. When the goodness-of-fit results for these distributions are compared, it is found that, on the average, the performance of L-moment is better than the performance of LQ-moment. Although the best fitting distribution may vary according to the method of estimation and stations considered, in most cases, data for the majority of the stations are found to follow the generalized logistic distribution. © Springer-Verlag 2008 |
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The best fitting distribution of annual maximum rainfall in Peninsular Malaysia based on methods of L-moment and LQ-moment |
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