University of Pittsburgh

Scoring Ancestral Graphs

graduate student
Friday, March 22, 2019 - 1:00pm - 1:30pm

Maximal ancestral graph (MAGs) provide a natural extension to directed acyclic graphs in the case where a subset of the vertices are latent. Accordingly, MAGs may be used to model and perform causal reasoning on systems with latent (confounding) variables. In this work, we introduce m-connected sets, a novel representation of MAGs with several nice theoretical properties. Using m-connected sets, we derive a consistent, score equivalent, and computationally efficient score for MAGs and illustrate the practicality of the score on learning MAGs from data with a simulation study.


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