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BayesNetBP  

Bayesian Network Belief Propagation
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("BayesNetBP", "1.6.1")



Attach the package and use:
library("BayesNetBP")
Maintained by
Han Yu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2017-05-09
Latest Update: 2022-05-08
Description:
Belief propagation methods in Bayesian Networks to propagate evidence through the network. The implementation of these methods are based on the article: Cowell, RG (2005). Local Propagation in Conditional Gaussian Bayesian Networks . For details please see Yu et. al. (2020) BayesNetBP: An R Package for Probabilistic Reasoning in Bayesian Networks . The optional 'cyjShiny' package for running the Shiny app is available at . Please see the example in the documentation of 'runBayesNetApp' function for installing 'cyjShiny' package from GitHub.
How to cite:
Han Yu (2017). BayesNetBP: Bayesian Network Belief Propagation. R package version 1.6.1, https://cran.r-project.org/web/packages/BayesNetBP. Accessed 09 Oct. 2026.
Previous versions and publish date:
1.0.1 (2017-05-09 00:17), 1.2.1 (2017-06-07 00:14), 1.3.0 (2018-02-16 16:22), 1.4.0 (2018-08-22 23:06), 1.5.2 (2020-04-14 11:00), 1.5.5 (2020-06-25 17:40), 1.5.9 (2021-06-01 17:50), (2026-07-09 07:58)
Other packages that cited BayesNetBP R package
View BayesNetBP citation profile
Other R packages that BayesNetBP depends, imports, suggests or enhances
Complete documentation for BayesNetBP
Functions, R codes and Examples using the BayesNetBP R package
Some associated functions: AbsorbEvidence . ClusterTree-class . ClusterTreeCompile . ComputeKLDs . ElimTreeInitialize . FactorQuery . GetValue . Initializer . LocalModelCompile . Marginals . PlotCGBN . PlotMarginals . PlotTree . Propagate . Sampler . SummaryMarginals . bn_to_graphNEL . chest . emission . emission1000 . liver . qtlnet_to_graphNEL . runBayesNetApp . toytree . yeast . 
Some associated R codes: A1_EliminationOrder.R . A2_Moralize.R . A2_Triangulate.R . A3_ClusterSets.R . A4_SemiEliminationTree.R . A5_StrongEliminationTree.R . A6_ClusterTreeCompile.R . A7_Initialization_helpers.R . A8_qtlnet_to_graphNEL.R . B1_ModelCompileData.R . B2_LocalModelCompile.R . B3_bn_to_graphNEL.R . C1_ElimTreeInitialize.R . C2_Initializer.R . D1_ExchangeOperation.R . D2_AbsorbEvidence.R . D3_Propagate.R . D4_PropagateWorker.R . D5_Absorb_helpers.R . D6_FactorOperations.R . E1_Marginals.R . E2_DiscreteMarginal.R . E3_PushMarginal.R . E4_FactorQuery.R . E5_CrossClusterQuery.R . E6_GetValues.R . E7_Sampler.R . F1_ComputeKLDs.R . F2_SummaryMarginal.R . F3_Summary_helpers.R . G1_PlotCGBN.R . G2_PlotMarginals.R . G3_PlotContinuous.R . G4_PlotDiscrete.R . G5_PlotTree.R . H1_runBayesNetApp.R . R1_data_chest.R . R2_data_yeast.R . R3_data_toytree.R . R4_data_liver.R . R5_data_emission.R . R6_data_emission1000.R . S4_1_LPPotential.R . S4_2_ClusterTree.R .  Full BayesNetBP package functions and examples
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