Package: dbnR 0.7.9
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.
Authors:
dbnR_0.7.9.tar.gz
dbnR_0.7.9.zip(r-4.5)dbnR_0.7.9.zip(r-4.4)
dbnR_0.7.9.tgz(r-4.5-x86_64)dbnR_0.7.9.tgz(r-4.5-arm64)dbnR_0.7.9.tgz(r-4.4-x86_64)dbnR_0.7.9.tgz(r-4.4-arm64)
dbnR_0.7.9.tar.gz(r-4.5-noble)dbnR_0.7.9.tar.gz(r-4.4-noble)
dbnR_0.7.9.tgz(r-4.4-emscripten)
dbnR.pdf |dbnR.html✨
dbnR/json (API)
NEWS
# Install 'dbnR' in R: |
install.packages('dbnR', repos = c('https://dkesada.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/dkesada/dbnr/issues
- motor - Multivariate time series dataset on the temperature of an electric motor
bayesian-networksdynamic-bayesian-networksforecastinginferencetime-seriescpp
Last updated 9 months agofrom:f8745ceac1. Checks:9 OK. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 16 2025 |
R-4.5-win-x86_64 | OK | Mar 16 2025 |
R-4.5-mac-x86_64 | OK | Mar 16 2025 |
R-4.5-mac-aarch64 | OK | Mar 16 2025 |
R-4.5-linux-x86_64 | OK | Mar 16 2025 |
R-4.4-win-x86_64 | OK | Mar 16 2025 |
R-4.4-mac-x86_64 | OK | Mar 16 2025 |
R-4.4-mac-aarch64 | OK | Mar 16 2025 |
R-4.4-linux-x86_64 | OK | Mar 16 2025 |
Exports:calc_mucalc_sigmadegreefilter_same_cyclefiltered_fold_dtfit_dbn_paramsfold_dtforecast_tsgenerate_random_network_explearn_dbn_strucmvn_inferencenodesnodes<-plot_dynamic_networkplot_static_networkpredict_bnpredict_dtrbn.dbn.fitreduce_freqscoreshift_valuessmooth_tstime_rename