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

机译:每个LWF和AMP链条图起源于一组因果模型

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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:本文旨在通过表明它们不代表任意独立模型来证明LWF和AMP链条图。具体地,我们表明每个链图是包含在调节下一组定向和非环状图所示的独立模型的交叉点。这意味着链图所示的独立模型可以由一组因果模型进行计入,该模型可能会受到选择偏差,这又可以由在不同的制度或配置之间切换的系统来计算。

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