The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Bayesian Hierarchical Mixed Effects Analysis of Time Non-Homogeneous Markov Chains

계층적 베이지안 혼합 효과 모델을 사용한 비동차 마코프 체인의 분석

  • Received : 2013.12.21
  • Accepted : 2014.02.19
  • Published : 2014.04.30
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Abstract

The present study used a hierarchical Bayesian approach was used to develop a mixed effect model to describe the transitional behavior of subjects in time nonhomogeneous Markov chains. The posterior distributions of model parameters were not in analytically tractable forms; subsequently, a Gibbs sampling method was used to draw samples from full conditional posterior distributions. The proposed model was implemented with real data.

본 연구에서는 비동차 마코프 체인에서 개체들의 전이 행태를 분석하기 위한 계층적 베이지안 방법론을 사용하여 혼합 효과 모델을 소개 하였다. 모델의 모수들에 대한 사후분포가 분석적으로 구해질 수 없는 형태를 가지기 때문에 깁스(Gibbs) 샘플링 시뮬레이션 방법을 사용하여 조건부 사후확률로부터 샘플이 추출되었고, 실제 자료분석을 예를 사용하였다.

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References

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