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Every LWF and AMP Chain Graph Originates from a Set of Causal Models

机译:每个LWF和AMP链图都源自一组因果模型

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This paper aims at justifying LWF and AMP chain graphs by showing that they do not represent arbitrary independence models. Specifically, we show that every chain graph is inclusion optimal wrt the intersection of the independence models represented by a set of directed and acyclic graphs under conditioning. This implies that the independence model represented by the chain graph can be accounted for by a set of causal models that are subject to selection bias, which in turn can be accounted for by a system that switches between different regimes or configurations.
机译:本文旨在通过证明LWF和AMP链图不代表任意独立性模型来证明它们的合理性。具体而言,我们表明在条件下,由一组有向图和无环图表示的独立模型的相交处,每个链图都是包含最优的。这意味着链图表示的独立性模型可以由一组因果模型来解释,这些因果模型会受到选择偏见的影响,而因果关系模型又可以由在不同状态或配置之间切换的系统来解释。

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