dbnR: Dynamic Bayesian Network Learning and Inference
David Quesada · 2020
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) , Santos F.P. and Maciel C.D. (2014) , Quesada D., Bielza C. and Larrañaga P. (2021) . 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.