Parameter estimation for generalized extreme value distribution of extreme rainfall in Johor

Analysis of extreme rainfall events is essential since the results beneficial for civil engineers and planners to estimate the ability of building structures to survive under the utmost extreme conditions. The annual maximum series (AMS) data of daily rainfall in Johor were fitted to Generalized Ext...

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Main Author:	Nazmi, Nurhazimah
Format:	Thesis
Language:	English
Published:	2014
Subjects:	QA Mathematics
Online Access:	http://eprints.utm.my/id/eprint/38866/1/NurhazimahNazmiMFS2014.pdf
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id	my-utm-ep.38866
record_format	uketd_dc
spelling	my-utm-ep.388662017-09-11T04:39:36Z Parameter estimation for generalized extreme value distribution of extreme rainfall in Johor 2014-01 Nazmi, Nurhazimah QA Mathematics Analysis of extreme rainfall events is essential since the results beneficial for civil engineers and planners to estimate the ability of building structures to survive under the utmost extreme conditions. The annual maximum series (AMS) data of daily rainfall in Johor were fitted to Generalized Extreme Value (GEV) distribution. A study was conducted to determine the best method to estimate parameters of GEV distribution by using method of moments (MOM), maximum likelihood estimators (MLE) and Bayesian Markov Chain Monte Carlo (MCMC) simulations. Previous study show that parameter estimation using MOM was a better method than MLE since MLE method had problem in handling small sample. However, some researchers identified that the performance of parameter estimation of MLE method can be improved when adopting Bayesian MCMC. The performances of parameter estimations by using MOM, MLE and Bayesian MCMC were compared by conducting Relative Root Mean Square Error (RRMSE) and Relative Absolute Square Error (RASE). The results showed that Bayesian MCMCmethod was better than MOM and MLEmethod in estimating GEVparameters.Bayesian also had the maximum value return level for 10, 25, 50 and 100 years for most of stations. Therefore, it can be concluded that Bayesian MCMC is the best method to estimate the distribution parameters of extreme daily rainfall amount in Johor. 2014-01 Thesis http://eprints.utm.my/id/eprint/38866/ http://eprints.utm.my/id/eprint/38866/1/NurhazimahNazmiMFS2014.pdf application/pdf en public masters Universiti Teknologi Malaysia, Faculty of Science Faculty of Science
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QA Mathematics
spellingShingle	QA Mathematics Nazmi, Nurhazimah Parameter estimation for generalized extreme value distribution of extreme rainfall in Johor
description	Analysis of extreme rainfall events is essential since the results beneficial for civil engineers and planners to estimate the ability of building structures to survive under the utmost extreme conditions. The annual maximum series (AMS) data of daily rainfall in Johor were fitted to Generalized Extreme Value (GEV) distribution. A study was conducted to determine the best method to estimate parameters of GEV distribution by using method of moments (MOM), maximum likelihood estimators (MLE) and Bayesian Markov Chain Monte Carlo (MCMC) simulations. Previous study show that parameter estimation using MOM was a better method than MLE since MLE method had problem in handling small sample. However, some researchers identified that the performance of parameter estimation of MLE method can be improved when adopting Bayesian MCMC. The performances of parameter estimations by using MOM, MLE and Bayesian MCMC were compared by conducting Relative Root Mean Square Error (RRMSE) and Relative Absolute Square Error (RASE). The results showed that Bayesian MCMCmethod was better than MOM and MLEmethod in estimating GEVparameters.Bayesian also had the maximum value return level for 10, 25, 50 and 100 years for most of stations. Therefore, it can be concluded that Bayesian MCMC is the best method to estimate the distribution parameters of extreme daily rainfall amount in Johor.
format	Thesis
qualification_level	Master's degree
author	Nazmi, Nurhazimah
author_facet	Nazmi, Nurhazimah
author_sort	Nazmi, Nurhazimah
title	Parameter estimation for generalized extreme value distribution of extreme rainfall in Johor
title_short	Parameter estimation for generalized extreme value distribution of extreme rainfall in Johor
title_full	Parameter estimation for generalized extreme value distribution of extreme rainfall in Johor
title_fullStr	Parameter estimation for generalized extreme value distribution of extreme rainfall in Johor
title_full_unstemmed	Parameter estimation for generalized extreme value distribution of extreme rainfall in Johor
title_sort	parameter estimation for generalized extreme value distribution of extreme rainfall in johor
granting_institution	Universiti Teknologi Malaysia, Faculty of Science
granting_department	Faculty of Science
publishDate	2014
url	http://eprints.utm.my/id/eprint/38866/1/NurhazimahNazmiMFS2014.pdf
_version_	1747816532404076544

Parameter estimation for generalized extreme value distribution of extreme rainfall in Johor

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