View source: R/A6_ClusterTreeCompile.R
ClusterTreeCompile | R Documentation |
Get the cluster sets and strong semi-elimination tree from the Bayesian network
ClusterTreeCompile(dag, node.class)
dag |
a |
node.class |
a named |
This function forms the cluster sets and the semi-elimination tree graph from the Bayesian network. The procedures include acquiring the elimination order, moralization, triangulation, obtaining cluster sets, forming strong elimination tree and strong semi-elimination tree. The cluster sets and the semi-elimination tree are required to initialize the cluster tree.
tree.graph
a graphNEL
object of semi-elimination tree.
dag
a graphNEL
object of original Bayesian network.
cluster.sets
a list
of members of each cluster.
node.class
a named vector
of logical
values, TRUE
if node
is discrete, FASLE
if otherwise
elimination.order
a vector
of node names sorted by the elimination order.
Han Yu
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>.
ElimTreeInitialize
data(liver) cst <- ClusterTreeCompile(dag=liver$dag, node.class=liver$node.class)
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