Foundations of structural causal models with cycles and latent variables

DOI10.1214/21-AOS2064zbMath1486.62176arXiv1611.06221OpenAlexW3214040448MaRDI QIDQ2054537

Patrick Forré, Stephan Bongers, Jonas Peters, Joris M. Mooij

Publication date: 3 December 2021

Published in: The Annals of Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1611.06221

zbMATH Keywords

counterfactualssolvabilitycyclesinterventionsmarginalizationMarkov propertiescausal graphstructural causal models

Mathematics Subject Classification ID

Knowledge representation (68T30) Reasoning under uncertainty in the context of artificial intelligence (68T37) Graphical methods in statistics (62A09) Probabilistic graphical models (62H22)

Related Items (6)

Causal structure learning: a combinatorial perspective ⋮ Reasoning about causality in games ⋮ Discovering agents ⋮ From statistical to causal learning ⋮ Unnamed Item ⋮ A survey on causal discovery: theory and practice

Uses Software

• TETRAD
• JCI
• CausalKinetiX

Cites Work

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• On the Validity of the Markov Interpretation of Path Diagrams of Gaussian Structural Equations Systems with Correlated Errors
• The Statistical Implications of a System of Simultaneous Equations

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