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BayesNetBP (version 1.2.1)

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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Version

Install

install.packages('BayesNetBP')

Monthly Downloads

247

Version

1.2.1

License

GPL-2

Maintainer

Han Yu

Last Published

June 6th, 2017

Functions in BayesNetBP (1.2.1)

ElimTreeInitialize

Initialize the elimination tree

FactorQuery

Queries of discrete variable distributions

Marginals

Obtain marginal distributions

PlotCGBN

Plot the Bayesian network

ClusterTreeCompile

Compile the cluster tree

ComputeKLDs

Compute signed and symmetric Kullback-Leibler divergence

GetValue

Possible values of a discrete variable

LocalModelCompile

Model compilation

PlotMarginals

Plot the marginal distributions

PlotTree

Plot the cluster tree

chest

A simulated data from the Chest Clinic example by Dethlefsen and Hojsgaard

liver

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

yeast

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

PropagateDBN

Propagate the cluster tree

SummaryMarginals

Summary a continuous marginal distribution

AbsorbEvidence

Absorb evidence into the model

ClusterTree-class

An S4 class of the cluster tree.

runBayesNetApp

Launch the BayesNetBP Shiny App

toytree

A synthetic toy dataset