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stat.ME2022
Bayesian sample size determination for causal discovery
Federico Castelletti, Guido Consonni
Graphical models based on Directed Acyclic Graphs (DAGs) are widely used to answer causal questions across a variety of scientific and social disciplines. However, observational da…
stat.ML2022★ 1 cited
BCDAG: An R package for Bayesian structure and Causal learning of Gaussian DAGs
Federico Castelletti, Alessandro Mascaro
Directed Acyclic Graphs (DAGs) provide a powerful framework to model causal relationships among variables in multivariate settings; in addition, through the do-calculus theory, the…