PlotCGBN {BayesNetBP} | R Documentation |
Plot the Bayesian network
Description
Plot and compare two Bayesian networks with different evidence(s) absorbed and propagated.
Usage
PlotCGBN(
tree.1,
tree.2,
fontsize = NULL,
pbar = FALSE,
plotting = TRUE,
epsilon = 10^-6
)
Arguments
tree.1 |
|
tree.2 |
|
fontsize |
font size for the node labels |
pbar |
|
plotting |
|
epsilon |
|
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. This function requires Rgraphviz
package.
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.
Yu H, Moharil J, Blair RH (2020). BayesNetBP: An R Package for Probabilistic Reasoning in Bayesian
Networks. Journal of Statistical Software, 94(3), 1-31. <doi:10.18637/jss.v094.i03>.
Examples
## Not run:
library("Rgraphviz")
data(toytree)
tree.post <- AbsorbEvidence(toytree, c("Nr1i3"), list(1))
PlotCGBN(tree.1=toytree, tree.2=tree.post)
## End(Not run)