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BayesNetBP (version 1.3.0)

Bayesian Network Belief Propagation

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 .

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Install

install.packages('BayesNetBP')

Monthly Downloads

266

Version

1.3.0

License

GPL-2

Issues

0

Pull Requests

0

Stars

20

Forks

3

Maintainer

Han Yu

Last Published

February 16th, 2018

Functions in BayesNetBP (1.3.0)

LocalModelCompile

Model compilation
ComputeKLDs

Compute signed and symmetric Kullback-Leibler divergence
SummaryMarginals

Summary a continuous marginal distribution
AbsorbEvidence

Absorb evidence into the model
ClusterTree-class

An S4 class of the cluster tree.
FactorQuery

Queries of discrete variable distributions
GetValue

Possible values of a discrete variable
bn_to_graphNEL

Convert a bn object to graphNEL object
chest

A simulated data from the Chest Clinic example
emission

A ClusterTree Example of Emission Model
PlotTree

Plot the cluster tree
yeast

Saccharomyces Cerevisiae eQTL data from Kruglak et. al. (2005)
Initializer

Initialize a ClusterTree object
liver

Mus Musculus HDL QTL data from Leduc et. al. (2012)
Propagate

Propagate the cluster tree
runBayesNetApp

Launch the BayesNetBP Shiny App
toytree

A ClusterTree Example of Liver Model
ElimTreeInitialize

Initialize the elimination tree
PlotMarginals

Plot the marginal distributions
PlotCGBN

Plot the Bayesian network
Marginals

Obtain marginal distributions
ClusterTreeCompile

Compile the cluster tree
Sampler

Sampling from the Bayesian network