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

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

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Abstract

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.

Item Type:	Article (Journal)
Additional Information:	4945/29233
Uncontrolled Keywords:	Annual maximum series; Bayesian MCMC; extreme rainfall analysis; extreme value distribution; generalized maximum likelihood
Subjects:	T Technology > TA Engineering (General). Civil engineering (General)
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering
Depositing User:	Nur' Aini Abu Bakar
Date Deposited:	26 Feb 2013 15:13
Last Modified:	26 Feb 2013 15:13
URI:	http://irep.iium.edu.my/id/eprint/29233

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