Linear Polytree Structural Equation Models: Structural Learning and Inverse Correlation Estimation. (arXiv:2107.10955v2 [stat.ML] UPDATED)

We are interested in the problem of learning the directed acyclic graph (DAG)
when data are generated from a linear structural equation model (SEM) and the
causal structure can be characterized by a polytree. Under the Gaussian
polytree models, we study sufficient conditions on the sample sizes for the
well-known Chow-Liu algorithm to exactly recover both the skeleton and the
equivalence class of the polytree, which is uniquely represented by a CPDAG. On
the other hand, necessary conditions on the …

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