Preliminary study on Bayesian extreme rainfall analysis: A case study of Alor Setar, Kedah, Malaysia

Statistical modeling of extreme rainfall is essential since the results can often facilitate civil engineers and planners to estimate the ability of building structures to survive under the utmost extreme conditions. Data comprising of annual maximum series (AMS) of extreme rainfall in Alor Setar we...

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Main Authors:	Eli @ Ali, Siti Annazirin, Shaffie, mardhiyyah, Wan Zin, Wan Zawawiah
Format:	Article
Language:	English
Published:	Penerbit UKM 2012
Subjects:	TA Engineering (General). Civil engineering (General)
Online Access:	http://irep.iium.edu.my/29233/ http://irep.iium.edu.my/29233/ http://irep.iium.edu.my/29233/1/Preliminary_Study_on_Bayesian_Extreme_Rainfall_Analysis.pdf

id	iium-29233
recordtype	eprints
spelling	iium-292332013-02-26T07:13:15Z http://irep.iium.edu.my/29233/ Preliminary study on Bayesian extreme rainfall analysis: A case study of Alor Setar, Kedah, Malaysia Eli @ Ali, Siti Annazirin Shaffie, mardhiyyah Wan Zin, Wan Zawawiah TA Engineering (General). Civil engineering (General) Statistical modeling of extreme rainfall is essential since the results can often facilitate civil engineers and planners to estimate the ability of building structures to survive under the utmost extreme conditions. Data comprising of annual maximum series (AMS) of extreme rainfall in Alor Setar were fitted to Generalized Extreme Value (GEV) distribution using method of maximum likelihood (ML) and Bayesian Markov Chain Monte Carlo (MCMC) simulations. The weakness of ML method in handling small sample is hoped to be tackled by means of Bayesian MCMC simulations in this study. In order to obtain the posterior densities, non-informative and independent priors were employed. Performances of parameter estimations were verified by conducting several goodness-of-fit tests. The results showed that Bayesian MCMC method was slightly better than ML method in estimating GEV parameters. Penerbit UKM 2012 Article PeerReviewed application/pdf en http://irep.iium.edu.my/29233/1/Preliminary_Study_on_Bayesian_Extreme_Rainfall_Analysis.pdf Eli @ Ali, Siti Annazirin and Shaffie, mardhiyyah and Wan Zin, Wan Zawawiah (2012) Preliminary study on Bayesian extreme rainfall analysis: A case study of Alor Setar, Kedah, Malaysia. Sains Malaysiana, 41 (11). pp. 1403-1410. ISSN 0126-6039 http://www.ukm.my/jsm/pdf_files/SM-PDF-41-11-2012/09%20Annazirin.pdf
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English
topic	TA Engineering (General). Civil engineering (General)
spellingShingle	TA Engineering (General). Civil engineering (General) Eli @ Ali, Siti Annazirin Shaffie, mardhiyyah Wan Zin, Wan Zawawiah Preliminary study on Bayesian extreme rainfall analysis: A case study of Alor Setar, Kedah, Malaysia
description	Statistical modeling of extreme rainfall is essential since the results can often facilitate civil engineers and planners to estimate the ability of building structures to survive under the utmost extreme conditions. Data comprising of annual maximum series (AMS) of extreme rainfall in Alor Setar were fitted to Generalized Extreme Value (GEV) distribution using method of maximum likelihood (ML) and Bayesian Markov Chain Monte Carlo (MCMC) simulations. The weakness of ML method in handling small sample is hoped to be tackled by means of Bayesian MCMC simulations in this study. In order to obtain the posterior densities, non-informative and independent priors were employed. Performances of parameter estimations were verified by conducting several goodness-of-fit tests. The results showed that Bayesian MCMC method was slightly better than ML method in estimating GEV parameters.
format	Article
author	Eli @ Ali, Siti Annazirin Shaffie, mardhiyyah Wan Zin, Wan Zawawiah
author_facet	Eli @ Ali, Siti Annazirin Shaffie, mardhiyyah Wan Zin, Wan Zawawiah
author_sort	Eli @ Ali, Siti Annazirin
title	Preliminary study on Bayesian extreme rainfall analysis: A case study of Alor Setar, Kedah, Malaysia
title_short	Preliminary study on Bayesian extreme rainfall analysis: A case study of Alor Setar, Kedah, Malaysia
title_full	Preliminary study on Bayesian extreme rainfall analysis: A case study of Alor Setar, Kedah, Malaysia
title_fullStr	Preliminary study on Bayesian extreme rainfall analysis: A case study of Alor Setar, Kedah, Malaysia
title_full_unstemmed	Preliminary study on Bayesian extreme rainfall analysis: A case study of Alor Setar, Kedah, Malaysia
title_sort	preliminary study on bayesian extreme rainfall analysis: a case study of alor setar, kedah, malaysia
publisher	Penerbit UKM
publishDate	2012
url	http://irep.iium.edu.my/29233/ http://irep.iium.edu.my/29233/ http://irep.iium.edu.my/29233/1/Preliminary_Study_on_Bayesian_Extreme_Rainfall_Analysis.pdf
first_indexed	2023-09-18T20:42:53Z
last_indexed	2023-09-18T20:42:53Z
_version_	1777409483215994880

Preliminary study on Bayesian extreme rainfall analysis: A case study of Alor Setar, Kedah, Malaysia

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