A Bayesian Copula Approach for Flood Analysis


Kamaruzaman, Izzat Fakhruddin and Wan Zin, Wan Zawiah and Mohd Ariff, Noratiqah (2021) A Bayesian Copula Approach for Flood Analysis. Malaysian Journal of Fundamental and Applied Sciences, 17 (4). pp. 354-364. ISSN 2289-5981, 2289-599X

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This study aims to provide joint modelling of rainfall characteristics in Peninsular Malaysia using two-dimensional copula. Two commonly regarded as important variables in the field of hydrology, namely rainfall severity and duration were derived using the Standard Precipitation Index (SPI) and their univariate marginal distributions are further identified by fitting into several distributions. The paper uses a Bayesian framework to estimate the parameter values in the marginal and copula model. The approximation of the posterior distribution by random sampling has been done by Monte Carlo Markov Chain (MCMC). Next, the authors compared these findings with those based on the classical procedure. The results indicated that the Bayesian approach can be substantially more reliable in parameter estimation for small samples.

Item Type: Article
Uncontrolled Keywords: Bayesian statistical decision theory, Bayesian analysis, copula, MCMC, rainfall modelling
Subjects: Q Science > QA Mathematics > QA273-280 Probabilities. Mathematical statistics
Divisions: Faculty of Business (FOB)
Depositing User: Ms Nurul Iqtiani Ahmad
Date Deposited: 03 Oct 2021 14:19
Last Modified: 03 Oct 2021 14:19
URII: http://shdl.mmu.edu.my/id/eprint/9603


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