PlotCGBN: Plot the Bayesian network

Description Usage Arguments Details Value Author(s) References Examples

Description

Plot and compare two Bayesian networks with different evidence(s) absorbed and propagated.

Usage

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PlotCGBN(tree.1, tree.2, fontsize = NULL, pbar = FALSE, plotting = TRUE)

Arguments

tree.1

a ClusterTree

tree.2

a ClusterTree

fontsize

font size for the node labels

pbar

logical(1) whether to show progress bar

plotting

logical(1) whether to output plot

Details

Network visualization of the node-specific differences between Bayesian Networks with the same topology, but evidence that has been absorbed and propagated. The change of marginal distribution of each node is measured by signed and symmetric Kullback-Leibler divergence. The sign indicates the direction of change, with tree.1 considered as the baseline. The magnitude of the change is reflected by the value. Nodes that are white are d-separated from the evidence.

Value

a plot of Bayesian network

a vector of signed symmetric Kullback-Leibler divergence

Author(s)

Han Yu

References

Cowell, R. G. (2005). Local propagation in conditional Gaussian Bayesian networks. Journal of Machine Learning Research, 6(Sep), 1517-1550.

Examples

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## Not run: 
data(toytree)
tree.post <- AbsorbEvidence(toytree, c("Nr1i3"), list(1))
PlotCGBN(tree.1=toytree, tree.2=tree.post)

## End(Not run)

BayesNetBP documentation built on May 2, 2019, 3:43 p.m.