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路径抽样法在贝叶斯模型选择中的应用
引用本文:郝志峰,王宁宁. 路径抽样法在贝叶斯模型选择中的应用[J]. 华南理工大学学报(自然科学版), 2004, 32(10): 90-92
作者姓名:郝志峰  王宁宁
作者单位:华南理工大学,数学科学学院,广东,广州,510640;华南理工大学,数学科学学院,广东,广州,510640
摘    要:为采用贝叶斯分析方法解决模型选择问题,针对传统的Box-Cox模型线性与非线性的选择问题,将路径抽样法应用于贝叶斯因子的计算,引进一个连续的路径参数并且假定它满足一定的概率分布,利用该路径参数连接待选择的模型,使计算贝叶斯因子的工作主要集中于马尔可夫链蒙特卡洛(MCMC)抽样上,从而简化了使用贝叶斯分析方法的计算过程,实现了路径抽样法在模型选择中的具体应用.

关 键 词:贝叶斯因子  模型选择  路径抽样  Box-Cox模型
文章编号:1000-565X(2004)10-0090-03
修稿时间:2003-10-09

Application of the Path Sampling to the Model Selection by Means of Bayesian Method
Hao Zhi-feng Wang Ning-ning. Application of the Path Sampling to the Model Selection by Means of Bayesian Method[J]. Journal of South China University of Technology(Natural Science Edition), 2004, 32(10): 90-92
Authors:Hao Zhi-feng Wang Ning-ning
Abstract:In order to solve the problem of model selection by means of Bayesian method and in view of the selection of the traditional linear Box-Cox model and the nonlinear Box-Cox model, the method of path sampling was adopted to calculate the Bayesian factors, A continuous path parameter with a certain assumed probability distribution was then introduced to connect different models to be selected. Thus, the main calculation of the Bayesian factors was focused on the sampling of Markov Chain Monte Carlo (MCMC) and the calculation in the analytical process by means of Bayesian method was simplified. It is concluded that the method of path sampling can be applied to model selection in practice.
Keywords:Bayesian factor  model selection  path sampling  Box-Cox model
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