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분야 : 자연과학 > 통계학
발행기관 : 한국통계학회
간행물정보 : CSAM(Communications for Statistical Applications and Methods), 2012 pp.~15 (총 16pages)
 
 
영문초록
In this paper, we introduce a hierarchical Bayesian model to simultaneously estimate the thresholds of each 6 cities. It was noted in the literature there was a dramatic increases in the number of deaths if the mean temperature passes a certain value (that we call a threshold). We estimate the difference of mortality before and after the threshold. For the hierarchical Bayesian analysis, some proper prior distribution of parameters and hyper-parameters are assumed. By combining the Gibbs and Metropolis-Hastings algorithm, we constructed a Markov chain Monte Carlo algorithm and the posterior inference was based on the posterior sample. The analysis shows that the estimates of the threshold are located at 25˚C∼29˚C and the mortality around the threshold changes from-1% to 2∼13%.
 
 
Hierarchical Bayesian model, threshold, Markov chain Monte Carlo algorithm
 
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