Measuring volatility persistence on rainfall records with the hybrid of autoregressive fractional integrated moving average (ARFIMA) - Hidden Markov Model (HMM)
Precarious circumstances related to rainfall events can be due to very intense or persistence of rainfall over a long period of time. Such events may give rise to an exceedence of the capacity of sewer systems resulting to landslides or flooding. One of the conventional ways of measuring such risk a...
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my.utm.593672021-12-15T08:45:52Z http://eprints.utm.my/id/eprint/59367/ Measuring volatility persistence on rainfall records with the hybrid of autoregressive fractional integrated moving average (ARFIMA) - Hidden Markov Model (HMM) Yusof, Fadhilah Kane, Ibrahim Lawal Yusop, Zulkifli QA Mathematics Precarious circumstances related to rainfall events can be due to very intense or persistence of rainfall over a long period of time. Such events may give rise to an exceedence of the capacity of sewer systems resulting to landslides or flooding. One of the conventional ways of measuring such risk associated with persistence in rain is done through studies of long term persistence and volatility persistence. This work investigates the persistence level of Kuantan daily rainfall using the hybrid of autoregressive fractional integrated moving average (ARFIMA) and hidden Markov model (HMM). The result shows that the rainfall variability period returns quickly to its usual variability level which may not have a lasting period of extreme wet, hence relatively stable rainfall behavior is observed in Kuantan rainfall. This will enhance the understanding of the process for the successful development and implementation of water resource tools to assess engineering and environmental problems such as flood control. 2015 Conference or Workshop Item PeerReviewed Yusof, Fadhilah and Kane, Ibrahim Lawal and Yusop, Zulkifli (2015) Measuring volatility persistence on rainfall records with the hybrid of autoregressive fractional integrated moving average (ARFIMA) - Hidden Markov Model (HMM). In: 2nd ISM International Statistical Conference 2014: Empowering the Applications of Statistical and Mathematical Sciences, ISM 2014, 12 August 2014 - 14 August 2014, Kuantan, Pahang. http://dx.doi.org/10.1063/1.4907479 |
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QA Mathematics Yusof, Fadhilah Kane, Ibrahim Lawal Yusop, Zulkifli Measuring volatility persistence on rainfall records with the hybrid of autoregressive fractional integrated moving average (ARFIMA) - Hidden Markov Model (HMM) |
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Precarious circumstances related to rainfall events can be due to very intense or persistence of rainfall over a long period of time. Such events may give rise to an exceedence of the capacity of sewer systems resulting to landslides or flooding. One of the conventional ways of measuring such risk associated with persistence in rain is done through studies of long term persistence and volatility persistence. This work investigates the persistence level of Kuantan daily rainfall using the hybrid of autoregressive fractional integrated moving average (ARFIMA) and hidden Markov model (HMM). The result shows that the rainfall variability period returns quickly to its usual variability level which may not have a lasting period of extreme wet, hence relatively stable rainfall behavior is observed in Kuantan rainfall. This will enhance the understanding of the process for the successful development and implementation of water resource tools to assess engineering and environmental problems such as flood control. |
format |
Conference or Workshop Item |
author |
Yusof, Fadhilah Kane, Ibrahim Lawal Yusop, Zulkifli |
author_facet |
Yusof, Fadhilah Kane, Ibrahim Lawal Yusop, Zulkifli |
author_sort |
Yusof, Fadhilah |
title |
Measuring volatility persistence on rainfall records with the hybrid of autoregressive fractional integrated moving average (ARFIMA) - Hidden Markov Model (HMM) |
title_short |
Measuring volatility persistence on rainfall records with the hybrid of autoregressive fractional integrated moving average (ARFIMA) - Hidden Markov Model (HMM) |
title_full |
Measuring volatility persistence on rainfall records with the hybrid of autoregressive fractional integrated moving average (ARFIMA) - Hidden Markov Model (HMM) |
title_fullStr |
Measuring volatility persistence on rainfall records with the hybrid of autoregressive fractional integrated moving average (ARFIMA) - Hidden Markov Model (HMM) |
title_full_unstemmed |
Measuring volatility persistence on rainfall records with the hybrid of autoregressive fractional integrated moving average (ARFIMA) - Hidden Markov Model (HMM) |
title_sort |
measuring volatility persistence on rainfall records with the hybrid of autoregressive fractional integrated moving average (arfima) - hidden markov model (hmm) |
publishDate |
2015 |
url |
http://eprints.utm.my/id/eprint/59367/ http://dx.doi.org/10.1063/1.4907479 |
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1720436908324028416 |