dbnR - Dynamic Bayesian Network Learning and Inference

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 Larrañaga 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., Larrañaga P. and Bielza C. (2025) <doi:10.18637/jss.v115.i06>.