Bayesian Structure and Causal Learning of Gaussian Directed Graphs R package BCDAG version 1.1.3 A collection of functions for structure learning of causal networks and estimation of joint causal effects from observational Gaussian data. Main algorithm consists of a Markov chain Monte Carlo scheme for posterior inference of causal structures, parameters and causal effects between variables. References: F. Castelletti and A. Mascaro (2021) <doi:10.1007/s10260-021-00579-1>, F. Castelletti and A. Mascaro (2022) <doi:10.48550/arXiv.2201.12003>. Software Depends: R (>= 2.10) Imports: graph, graphics, gRbase, Rgraphviz, grDevices, lattice, methods, mvtnorm, stats, utils Suggests: rmarkdown, knitr, testthat (>= 3.0.0) Alessandro Mascaro <alessandro.mascaro@upf.edu> Comprehensive R Archive Network (CRAN) Federico Castelletti [aut], Alessandro Mascaro [aut, cre, cph] MIT + file LICENSE (https://CRAN.R-project.org/package=BCDAG/LICENSE) 2025-02-28 application/tgz https://CRAN.R-project.org/package=BCDAG doi:10.32614/CRAN.package.BCDAG