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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
200 Bayesian Networks: With Examples in R
2. Plot the DAG again, highlighting the nodes and the arcs
that are part of one or more v-structures.
3. Plot the DAG one more time, highlighting the path leading
from Age to Occupation.
4. Plot the conditional probability table of Education.
5. Compare graphically the distributions of Education for
male and female interviewees.
1. > graphviz.plot(dag)
2. > vs <- vstructs(dag, arcs = TRUE)
> hl <- list(nodes = unique(as.character(vs)), arcs = vs)
> graphviz.plot(dag, highlight = hl)
3. > hl <- matrix(c("A", "E", "E", "O"), nc = 2,
+ byrow = TRUE)
> graphviz.plot(dag, highlight = list(arcs = hl))
4. > bn.fit.barchart(bn$E) ...
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Publisher Resources

ISBN: 9781482225587