[1]严于鲜,易建华..模型选择中的Bayes方法[J].郑州大学学报(工学版),2003,24(02):93-95.[doi:10.3969/j.issn.1671-6833.2003.02.025]
　Strict than fresh,Yi Jianhua.Bayes method in model selection[J].Journal of Zhengzhou University (Engineering Science),2003,24(02):93-95.[doi:10.3969/j.issn.1671-6833.2003.02.025]

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模型选择中的Bayes方法()

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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:

24

期数:

2003年02期

页码:

93-95

栏目:

出版日期:

1900-01-01

文章信息/Info

Title:

Bayes method in model selection

作者:

严于鲜; 易建华.

西南交通大学理学院,四川,成都,610031, 西南交通大学理学院,四川,成都,610031

Author(s):

Strict than fresh; Yi Jianhua

关键词:

模型选择;  Bayes方法;  不确定性

Keywords:

model selection;  Bayes method;  Uncertainty

DOI:

10.3969/j.issn.1671-6833.2003.02.025

文献标志码:

A

摘要:

在以往关于模型选择的研究中,一般都是先假定选定一个模型,然后对由此模型确定的分布族进行比较,求出最优的分布函数和数值特征,忽略了模型本身的不确定性.介绍了Bayes方法在模型选择中的方法及应用,举例说明了用Bayes方法选择模型,不仅能够减小模型选择中模型不确定性的影响,而且可以根据实际情况和问题认识程度的深化,对模型进行扩展.

Abstract:

In previous studies on model selection, it is generally assumed that a model is selected, and then the distribution family determined by the model is compared to find the optimal distribution function and numerical characteristics, ignoring the uncertainty of the model itself. The method and application of Bayes method in model selection are introduced, and an example is given to show that using Bayes method to select a model can not only reduce the influence of model uncertainty in model selection, but also extend the model according to the actual situation and the deepening of problem understanding.

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