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BCDAG

Bayesian Structure and Causal Learning of Gaussian Directed Graphs

v1.1.3 · Feb 28, 2025 · MIT + file LICENSE

Description

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>.

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14 OK
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r-devel-linux-x86_64-fedora-clang OK
r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
r-devel-windows-x86_64 OK
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r-patched-linux-x86_64 OK
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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 10, 2026

Dependency Network

Dependencies Reverse dependencies graph gRbase Rgraphviz lattice mvtnorm BCDAG

Version History

new 1.1.3 Mar 10, 2026
updated 1.1.3 ← 1.1.2 diff Feb 27, 2025
updated 1.1.2 ← 1.1.1 diff Jan 29, 2025
updated 1.1.1 ← 1.1.0 diff Jun 13, 2024
updated 1.1.0 ← 1.0.0 diff Feb 9, 2024
new 1.0.0 Mar 14, 2022