The Bayesian method for causal discovery of latent-variable models from a mixture of experimental and observational data

DOI10.1016/j.csda.2012.01.010zbMath1252.62032OpenAlexW1982904558WikidataQ98649297 ScholiaQ98649297MaRDI QIDQ693221

Changwon Yoo

Publication date: 7 December 2012

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7441591

zbMATH Keywords

Bayesian networksknowledge discovery from data bases

Mathematics Subject Classification ID

Bayesian inference (62F15) Learning and adaptive systems in artificial intelligence (68T05)

Related Items (1)

Large-scale local causal inference of gene regulatory relationships

Uses Software

• TETRAD

Cites Work

• Learning Bayesian networks for discrete data
• Causation, prediction, and search
• A Bayesian method for the induction of probabilistic networks from data
• Efficient approximations for the marginal likelihood of Bayesian networks with hidden variables
• Statistical challenges in functional genomics. (With comments and a rejoinder).
• Learning Bayesian networks: The combination of knowledge and statistical data
• Marginal Likelihood from the Gibbs Output
• Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
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