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strength.plot {bnlearn}  R Documentation 
Arc strength plot
Description
Plot a Bayesian network and format its arcs according to the strength of the dependencies they represent. Requires the Rgraphviz package.
Usage
strength.plot(x, strength, threshold, cutpoints, highlight = NULL, groups,
layout = "dot", shape = "circle", fontsize = 12, main = NULL, sub = NULL,
render = TRUE, debug = FALSE)
Arguments
x 
an object of class 
strength 
an object of class 
threshold 
a numeric value. See below. 
cutpoints 
an array of numeric values. See below. 
highlight 
a list, see 
groups 
a list of character vectors, representing groups of node labels of nodes that should be plotted close to each other. 
layout 
a character string, the layout argument that will be passed to Rgraphviz.
Possible values are 
shape 
a character string, the shape of the nodes. Can be 
fontsize 
a positive number, the font size for the node labels. 
main 
a character string, the main title of the graph. It's plotted at the top of the graph. 
sub 
a character string, a subtitle which is plotted at the bottom of the graph. 
debug 
a boolean value. If 
render 
a logical value. If 
Details
The threshold
argument is used to determine which arcs are supported strongly enough by the
data to be deemed significant:

if arc strengths have been computed using conditional independence tests, any strength coefficient (which is the pvalue of the test) lesser than or equal to the threshold is considered significant.

if arc strengths have been computed using network scores, any strength coefficient (which is the increase/decrease of the network score caused by the removal of the arc) lesser than the threshold is considered significant.

if arc strengths have been computed using bootstrap or using Bayes factors, any strength coefficient (which can be interpreted as a probability for inclusion) greater or equal than the threshold is considered significant.
The default value is the value of the strength
attribute of the bn.strength
object passed via the strength
argument.
Nonsignificant arcs are plotted as dashed lines.
The cutpoints
argument is an array of numeric values used to divide the range of the strength
coefficients into intervals. The interval each strength coefficient falls into determines the line width of
the corresponding arc in the plot. The default intervals are delimited by
unique(c(0, threshold/c(10, 5, 2, 1.5, 1), 1))
if the coefficients are computed from conditional independence tests, by
unique(c(0, (1  threshold)/c(10, 5, 2, 1.5, 1), 1))
for bootstrap estimates or by the quantiles
quantile(s[s < threshold], 1  c(0.50, 0.75, 0.90, 0.95, 1))
of the significant differences if network scores are used.
Value
graphviz.plot()
returns invisibly the graph
object produced by Rgraphviz. It can be further modified using the commands present in the graph and Rgraphviz packages, and it contains the arc strengths in the
edge weight attribute.
Author(s)
Marco Scutari
Examples
## Not run:
# plot the network learned by hc().
dag = hc(learning.test)
strength = arc.strength(dag, learning.test, criterion = "x2")
strength.plot(dag, strength)
# add another (nonsignificant) arc and plot the network again.
dag = set.arc(dag, "A", "C")
strength = arc.strength(dag, learning.test, criterion = "x2")
strength.plot(dag, strength)
## End(Not run)
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