The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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A Bayesian Threshold Model for Ordered Categorical Traits

순서범주형자료 분석을 위한 베이지안 분계점 모형

  • Choi Byangsu (School of Computer Engineering, Hansung University) ;
  • Lee Seung-Chun (Department of Statistics, Hanshin University)
  • 최병수 (한성대학교 컴퓨터공학부) ;
  • 이승천 (한신대학교 정보통계학과)
  • Published : 2005.03.01
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Abstract

A Bayesian threshold model is considered to analyze binary or ordered categorical traits. Gibbs sampler for making full Bayesian inferences about the category probability as well as the regression coefficients is described. The model can be regarded as an alternative to the ordered logit regression model. Numerical examples are shown to demonstrate the efficiency of the model.

순서를 갖는 범주형자료의 분석을 위한 중요한 통계적 방법인 순위로짓모형의 대안으로 무정보 사전분포에 의한 베이지안 분계점 모형을 정의하고, 실증 자료분석을 통해 베이지안 모형의 유용성을 살펴보았다.

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References

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