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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
80 Bayesian Networks: With Examples in R
TR = 1
1.0 1.5 2.0 2.5 3.0
0.0 0.5 1.0 1.5
PR
0.0 0.4 0.8
0.0 1.0 2.0
CL
0 5 10 15 20
0.00 0.10 0.20
G1
0 50 100 150
0.000 0.010 0.020
G2
0 20 40 60 80
0.00 0.02 0.04 0.06
LO
Figure 3.9
Marginal distributions of the nodes when conditioning on TR=1.
although the frequency of treated crops is greater, the loss is greater than for
the cases where treatment was not applied.
For the moment, we based our inference just on the marginal distributions
of the nodes conditional on a single node. In fact, many other configurations
are possible, such as fixing several nodes and considering simultaneously the
marginal or joint distributions ...
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Publisher Resources

ISBN: 9781482225587