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dbnR

Dynamic Bayesian Network Learning and Inference

v0.8.0 · Jan 13, 2026 · GPL-3

Description

Learning and inference over dynamic Bayesian networks of arbitrary Markovian order. Extends some of the functionality offered by the 'bnlearn' package to learn the networks from data and perform exact inference. It offers three structure learning algorithms for dynamic Bayesian networks: Trabelsi G. (2013) <doi:10.1007/978-3-642-41398-8_34>, Santos F.P. and Maciel C.D. (2014) <doi:10.1109/BRC.2014.6880957>, Quesada D., Bielza C. and LarraƱaga P. (2021) <doi:10.1007/978-3-030-86271-8_14>. It also offers the possibility to perform forecasts of arbitrary length. A tool for visualizing the structure of the net is also provided via the 'visNetwork' package. Further detailed information and examples can be found in our Journal of Statistical Software paper Quesada D., LarraƱaga P. and Bielza C. (2025) <doi:10.18637/jss.v115.i06>.

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r-devel-linux-x86_64-fedora-gcc OK
r-devel-macos-arm64 OK
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r-oldrel-windows-x86_64 OK
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r-release-windows-x86_64 OK
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Check History

OK 14 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026

Dependency Network

Dependencies Reverse dependencies bnlearn data.table Rcpp magrittr R6 MASS dbnR

Version History

new 0.8.0 Mar 9, 2026