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Multivariate Counterfactual Systems And Causal Graphical Models

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 نشر من قبل Ilya Shpitser
 تاريخ النشر 2020
  مجال البحث الاحصاء الرياضي
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Among Judea Pearls many contributions to Causality and Statistics, the graphical d-separation} criterion, the do-calculus and the mediation formula stand out. In this chapter we show that d-separation} provides direct insight into an earlier causal model originally described in terms of potential outcomes and event trees. In turn, the resulting synthesis leads to a simplification of the do-calculus that clarifies and separates the underlying concepts, and a simple counterfactual formulation of a complete identification algorithm in causal models with hidden variables.

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