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.

Keywords

• Markov chain;
• Bayesian analysis;
• mixed effect model

• 마코프 체인;
• 베이지안 분석;
• 혼합 효과 모델;

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References

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