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Bayesian Networks
book

Bayesian Networks

by Marco Scutari, Jean-Baptiste Denis
June 2014
Intermediate to advanced content levelIntermediate to advanced
241 pages
6h 20m
English
CRC Press
Content preview from Bayesian Networks
Theory and Algorithms for Bayesian Networks 95
It is also easy, for the sake of the example, to perform moralisation man-
ually. First, we ide ntify the v-structures in the DAG and we link the parents
within each v-structure with an undirected arc (e.g., an edge).
> mg2 <- dag
> vs <- vstructs(dag)
> for (i in seq(nrow(vs)))
+ mg2 <- set.edge(mg2, from = vs[i, "X"], to = vs[i, "Y"],
+ check.cycles = FALSE)
This step appears to introduce potential cycles in the resulting PDAG. How-
ever, we can safely ignore them since we are going to construct the undirected
graph underlying mg2, thus replacing each directed arc with an undirected
one.
> mg2 <- skeleton(mg2) ...
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Publisher Resources

ISBN: 9781482225587