Annazirin Eli, and Mardhiyyah Shaffie, and Wan Zawiah Wan Zin, (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
![]()
|
PDF
560kB |
Official URL: http://www.ukm.my/jsm/
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 |
---|---|
Keywords: | Annual maximum series; Bayesian MCMC; extreme rainfall analysis; extreme value distribution; generalized maximum likelihood |
Journal: | Sains Malaysiana |
ID Code: | 5576 |
Deposited By: | Mr Azam |
Deposited On: | 18 Oct 2012 02:54 |
Last Modified: | 14 Dec 2016 06:38 |
Repository Staff Only: item control page