Uncertainty Analysis of Parameters of Spatial Statistical Model Using Bayesian Method for Estimating Spatial Distribution of Probability Rainfall

확률강우량의 공간분포추정에 있어서 Bayesian 기법을 이용한 공간통계모델의 매개변수 불확실성 해석

  • Seo, Young-Min (Department of Civil Engineering, Yeungnam University) ;
  • Park, Ki-Bum (Department of Construction Information Andong Science College) ;
  • Kim, Sung-Won (Department of Railroad Civil Engineering, Dongyang University)
  • 서영민 (영남대학교 건설시스템공학과) ;
  • 박기범 (안동과학대학 건설정보과) ;
  • 김성원 (동양대학교 철도토목학과)
  • Received : 2011.06.21
  • Accepted : 2011.12.07
  • Published : 2011.12.31


This study applied the Bayesian method for the quantification of the parameter uncertainty of spatial linear mixed model in the estimation of the spatial distribution of probability rainfall. In the application of Bayesian method, the prior sensitivity analysis was implemented by using the priors normally selected in the existing studies which applied the Bayesian method for the puppose of assessing the influence which the selection of the priors of model parameters had on posteriors. As a result, the posteriors of parameters were differently estimated which priors were selected, and then in the case of the prior combination, F-S-E, the sizes of uncertainty intervals were minimum and the modes, means and medians of the posteriors were similar to the estimates using the existing classical methods. From the comparitive analysis between Bayesian and plug-in spatial predictions, we could find that the uncertainty of plug-in prediction could be slightly underestimated than that of Bayesian prediction.


Probability rainfall;Spatial distribution;Parameter uncertainty;Spatial linear mixed model;Bayesian inference


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