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.

Abstract
 1. 서 론
 2. Bayesian 기법을 이용한 모델 매개변수 추정
  2.1. 공간선형혼합모델
  2.2. 모델 매개변수에 대한 Bayesian 추정
 3. 적용 분석
  3.1. 적용유역 및 분석개요
  3.2. 사전분포 민감도 분석
  3.3. 모델 매개변수에 대한 불확실성 정량화 및 공간예측비교
 4. 결 론
 참 고 문 헌

• 서영민(영남대학교 건설시스템공학과) | Young-Min Seo (Department of Civil Engineering, Yeungnam University)
• 박기범(안동과학대학 건설정보과) | Ki-Bum Park (Department of Construction Information Andong Science College) Corresponding Author
• 김성원(동양대학교 철도토목학과) | Sungwon Kim (Department of Railroad Civil Engineering, Dongyang University)