Parameter estimation of generalised extreme distribution for rainfall data in Sabah
The purpose of this study is to compare the Generalized Extreme Value (GEV) parameter estimation by using several methods; the Probability weighted moment (PWM), the Maximum likelihood estimation (MLE) and the Penalized maximum likelihood estimation (PMLE). The analysis will be illustrated using an...
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| Format: | Proceedings |
| Language: | English English |
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Faculty of Science and Natural Resources
2020
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| Online Access: | https://eprints.ums.edu.my/id/eprint/21444/1/Parameter%20estimation%20of%20generalised%20extreme%20distribution%20for%20rainfall%20data%20in%20Sabah.pdf https://eprints.ums.edu.my/id/eprint/21444/2/Parameter%20estimation%20of%20generalised%20extreme%20distribution%20for%20rainfall%20data%20in%20Sabah1.pdf |
| _version_ | 1825713563167096832 |
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| author | S.C. Sian Darmesah Gabda |
| author_facet | S.C. Sian Darmesah Gabda |
| author_sort | S.C. Sian |
| collection | UMS |
| description | The purpose of this study is to compare the Generalized Extreme Value (GEV) parameter estimation by using several methods; the Probability weighted moment (PWM), the Maximum likelihood estimation (MLE) and the Penalized maximum likelihood estimation (PMLE). The analysis will be illustrated using an application of GEV to the extreme rainfall in Sabah with small sample size event. As a result, the PMLE has a better estimation compared to other methods. The return level of the rainfall then can be computed using these parameter estimation. |
| first_indexed | 2024-03-06T02:58:31Z |
| format | Proceedings |
| id | ums.eprints-21444 |
| institution | Universiti Malaysia Sabah |
| language | English English |
| last_indexed | 2024-03-06T02:58:31Z |
| publishDate | 2020 |
| publisher | Faculty of Science and Natural Resources |
| record_format | dspace |
| spelling | ums.eprints-214442021-06-17T02:34:29Z https://eprints.ums.edu.my/id/eprint/21444/ Parameter estimation of generalised extreme distribution for rainfall data in Sabah S.C. Sian Darmesah Gabda QA Mathematics QC Physics The purpose of this study is to compare the Generalized Extreme Value (GEV) parameter estimation by using several methods; the Probability weighted moment (PWM), the Maximum likelihood estimation (MLE) and the Penalized maximum likelihood estimation (PMLE). The analysis will be illustrated using an application of GEV to the extreme rainfall in Sabah with small sample size event. As a result, the PMLE has a better estimation compared to other methods. The return level of the rainfall then can be computed using these parameter estimation. Faculty of Science and Natural Resources 2020 Proceedings PeerReviewed text en https://eprints.ums.edu.my/id/eprint/21444/1/Parameter%20estimation%20of%20generalised%20extreme%20distribution%20for%20rainfall%20data%20in%20Sabah.pdf text en https://eprints.ums.edu.my/id/eprint/21444/2/Parameter%20estimation%20of%20generalised%20extreme%20distribution%20for%20rainfall%20data%20in%20Sabah1.pdf S.C. Sian and Darmesah Gabda (2020) Parameter estimation of generalised extreme distribution for rainfall data in Sabah. https://www.ums.edu.my/fssa/wp-content/uploads/2020/12/PROCEEDINGS-BOOK-ST-2020-e-ISSN.pdf |
| spellingShingle | QA Mathematics QC Physics S.C. Sian Darmesah Gabda Parameter estimation of generalised extreme distribution for rainfall data in Sabah |
| title | Parameter estimation of generalised extreme distribution for rainfall data in Sabah |
| title_full | Parameter estimation of generalised extreme distribution for rainfall data in Sabah |
| title_fullStr | Parameter estimation of generalised extreme distribution for rainfall data in Sabah |
| title_full_unstemmed | Parameter estimation of generalised extreme distribution for rainfall data in Sabah |
| title_short | Parameter estimation of generalised extreme distribution for rainfall data in Sabah |
| title_sort | parameter estimation of generalised extreme distribution for rainfall data in sabah |
| topic | QA Mathematics QC Physics |
| url | https://eprints.ums.edu.my/id/eprint/21444/1/Parameter%20estimation%20of%20generalised%20extreme%20distribution%20for%20rainfall%20data%20in%20Sabah.pdf https://eprints.ums.edu.my/id/eprint/21444/2/Parameter%20estimation%20of%20generalised%20extreme%20distribution%20for%20rainfall%20data%20in%20Sabah1.pdf |
| work_keys_str_mv | AT scsian parameterestimationofgeneralisedextremedistributionforrainfalldatainsabah AT darmesahgabda parameterestimationofgeneralisedextremedistributionforrainfalldatainsabah |