| 带有反馈的因果模型中的独立性识别 |
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| 引用本文： | 郑忠国,孙丽丽.带有反馈的因果模型中的独立性识别[J].应用数学学报,2000,23(2):299-310. |
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| 作者姓名： | 郑忠国 孙丽丽 |
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| 作者单位： | 北京大学概率统计系,北京,100871 |
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| 基金项目： | 国家自然科学基金基金(#19871003,#39930160)和博士点基金(#97000139)资助项目. |
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| 摘 要： | 在本文中，直接利用计算要概率分布的办法证明了在史包含离散变量４ 反馈系统产生的因果图中的条件独立关系可以由ｄ－分离识别出．
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| 关 键 词： | 有向图 d－分离 反馈系统 因果模型 独立性识别 |
IDENTIFYING INDEPENDENCIES IN CAUSAL MODELS WITH FEEDBACK |
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| ZHENG ZHONGGUO,SUN LILI.IDENTIFYING INDEPENDENCIES IN CAUSAL MODELS WITH FEEDBACK[J].Acta Mathematicae Applicatae Sinica,2000,23(2):299-310. |
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| Authors: | ZHENG ZHONGGUO SUN LILI |
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| Abstract: | It is well known that d-separation can identify conditional independence in Bayesian network. Pearl J, Dechter R~6] proved d-separation criteria is sound in causal graphs with feedback assuming V is discrete variable set and the state space of V is finite. In this paper it is shown that their conclusion is valid only under certain constraints on the causal equations and under the same constraints, their conclusion is generalized by computing the probability distriubution to the situation in which the range of V is in the discrete but infinite state space. Counterexamples show when the above constraints does not hold or V is continuous, the d-separation criteria is not valid any more. |
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| Keywords: | Bayesian network directed acyclic grab directed graph d-separation |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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