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BayesNetBP (version 1.0.1)

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

310

Version

1.0.1

License

GPL-2

Maintainer

Han Yu

Last Published

May 8th, 2017

Functions in BayesNetBP (1.0.1)

LocalModelCompile

Model compilation

Marginals

Obtain marginal distributions

PlotCGBN

Plot the Bayesian network

PlotMarginals

Plot the marginal distributions

chest

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

clustertree

A Cluster Tree class

ElimTreeInitialize

Initialize the elimination tree

FactorQuery

Queries of discrete variable distributions

PlotTree

Plot the cluster tree

PrintTree

Print the cluster tree

ClusterTreeCompile

Compile the cluster tree

ComputeKLDs

Compute signed and symmetric Kullback-Leibler divergence

PropagateDBN

Propagate the cluster tree

SummaryMarginals

Summary a continuous marginal distribution

AbsorbEvidence

Absorb evidence into the model

ClusterSetTree-class

An S4 class to represent a cluster tree node.

toytree

A synthetic toy dataset

yeast

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

liver

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

runBayesNetApp

Launch the BayesNetBP Shiny App