The Korean Journal of Applied Statistics (응용통계연구)

The Korean Statistical Society (한국통계학회)
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Comparative Study of Model Selection Using Bayes Factor through Simulation : Poisson vs. Negative Binomial Model Selection and Normal, Double Exponential vs. Cauchy Model Selection

시뮬레이션을 통한 베이즈요인에 의한 모형선택의 비교연구 : 포아송, 음이항모형의 선택과 정규, 이중지수, 코쉬모형의 선택

  • 오미라 (전남대학교 자연과학대학 통계학과) ;
  • 윤소영 (경기통계사무소 경제조사과) ;
  • 심정욱 (전남대학교 자연과학대학 통계학과) ;
  • 손영숙 (전남대학교 자연과학대학 통계학과)
  • Published : 2003.09.01
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Abstract

In this paper, we use Bayesian method for model selection of poisson vs. negative binomial distribution, and normal, double exponential vs. cauchy distribution. The fractional Bayes factor of O'Hagan (1995) was applied to Bayesian model selection under the assumption of noninformative improper priors for all parameters in the models. Through the analyses of real data and simulation data, we examine the usefulness of the fractional Bayes factor in comparison with intrinsic Bayes factors of Berger and Pericchi (1996, 1998).

본 논문에서는 포아송분포 대 음이항분포, 그리고 정규분포, 이중지 수분포 대 코쉬분포에 대한 모형선택을 위하여 베이지안 방법을 사용한다. 각 모수에 대한 사전분포로는 무정보 부적절 사전분포의 가정 하에, 베이지안 모형선택을 위하여 O'Hagan (1995)의 부분적 베 이즈요인을 이용하였다. 실제자료와 모의 실험 자료의 분석을 통하여 부분적 베이즈요인의 유용성을 Berger와 Pericchi (1996, 1998)의 내재적 베이즈요인들과 함께 비교 검토해 본다.

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