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dbnR  

Dynamic Bayesian Network Learning and Inference
View on CRAN: Click here


Download and install dbnR package within the R console
Install from CRAN:
install.packages("dbnR")

Install from Github:
library("remotes")
install_github("cran/dbnR")

Install by package version:
library("remotes")
install_version("dbnR", "0.7.8")



Attach the package and use:
library("dbnR")
Maintained by
David Quesada
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-03-20
Latest Update: 2022-10-05
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) , Santos F.P. and Maciel C.D. (2014) , Quesada D., Bielza C. and Larra
How to cite:
David Quesada (2020). dbnR: Dynamic Bayesian Network Learning and Inference. R package version 0.7.8, https://cran.r-project.org/web/packages/dbnR
Previous versions and publish date:
0.3.3 (2020-03-20 12:20), 0.3.4 (2020-03-25 14:50), 0.4.5 (2020-06-11 10:40), 0.5.2 (2020-10-08 13:50), 0.5.3 (2020-10-13 10:40), 0.7.1 (2021-09-29 13:00), 0.7.5 (2022-03-14 15:20)
Other packages that cited dbnR R package
View dbnR citation profile
Other R packages that dbnR depends, imports, suggests or enhances
Functions, R codes and Examples using the dbnR R package
Some associated functions: AIC.dbn.fit . AIC.dbn . BIC.dbn.fit . BIC.dbn . Causlist . Particle . Position . PsoCtrl . Velocity . acc_successions . add_attr_to_fit . all.equal.dbn.fit . all.equal.dbn . approx_prediction_step . approximate_inference . as.character.dbn . as_named_vector . bn_translate_exp . calc_mu . calc_mu_cpp . calc_sigma . calc_sigma_cpp . cash-set-.dbn.fit . check_time0_formatted . cl_to_arc_matrix_cpp . coef.dbn.fit . create_blacklist . create_causlist_cpp . create_natcauslist_cpp . crop_names_cpp . cte_times_vel_cpp . degree.bn.fit . degree.bn . degree.dbn.fit . degree.dbn . degree . dmmhc . dynamic_ordering . exact_inference . exact_inference_backwards . exact_prediction_step . expand_time_nodes . filter_same_cycle . filtered_fold_dt . fit_dbn_params . fitted.dbn.fit . fold_dt . fold_dt_rec . forecast_ts . generate_random_network_exp . init_cl_cpp . init_list_cpp . initialize_cl_cpp . learn_dbn_struc . logLik.dbn.fit . logLik.dbn . mean.dbn.fit . merge_nets . motor . mvn_inference . natCauslist . natParticle . natPosition . natPsoCtrl . natPsoho . natVelocity . nat_cl_to_arc_matrix_cpp . nat_cte_times_vel_cpp . nat_pos_minus_pos_cpp . nat_pos_plus_vel_cpp . nat_vel_plus_vel_cpp . node_levels . nodes-set-.bn.fit . nodes-set-.bn . nodes-set-.dbn.fit . nodes-set-.dbn . nodes-set . nodes.bn.fit . nodes.bn . nodes.dbn.fit . nodes.dbn . nodes . nodes_gen_exp . one_hot . one_hot_cpp . ordering_gen_exp . plot.dbn.fit . plot.dbn . plot_dynamic_network . plot_static_network . pos_minus_pos_cpp . pos_plus_vel_cpp . predict.dbn.fit . predict_bn . predict_dt . print.dbn.fit . print.dbn . psoho . randomize_vl_cpp . rbn.dbn.fit . recount_arcs_exp . reduce_freq . rename_nodes_cpp . residuals.dbn.fit . score.bn . score.dbn . score . shift_values . sigma.dbn.fit . smooth_ts . sub-subset-.dbn.fit . time_rename . trunc_geom . vel_plus_vel_cpp . 
Some associated R codes: RcppExports.R . Rcpp_init.R . bnlearn_compat.R . dbn_inference.R . dbn_learn.R . dbn_visualization.R . dt_modification.R . gauss_transform.R . init.R . motor_data.R . mvn_exact_inference.R . security_checks.R . structure_learning_dmmhc.R . structure_learning_natpsoho.R . structure_learning_psoho.R . utils.R .  Full dbnR package functions and examples
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