Coloured Gaussian directed acyclic graphical models

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Local and global Markov properties characterize the coloured DAG models.
A new greedy equivalence search algorithm is proposed for learning BPEC-DAGs from synthetic data.
Coloured DAGs improve causal insights by clustering direct causes into communities.
Findings support the use of coloured models in statistical inference for causal analysis.

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Analysis uncovers structural identifiability in coloured Gaussian models, suggesting improvements in causal discovery techniques.

Boege et al. (2025) studied this question.

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