plotBNLearn: A custom plotting function for the BNlearn graphs...

In ddgraph: Distinguish direct and indirect interactions with Graphical Modelling

Description

A custom plotting function for the BNlearn graphs

Usage

plotBNLearn(d, bnlearn.function.name="hc", alpha=0.05, test="mc-mi",
    make.plot=FALSE, blacklist, B, restart=0, scale=1.5,
    class.label="target", use.colors=TRUE, score="bic")

Arguments

d	an object of type DDDataSet
bnlearn.function.name	the bnlearn reconstruction algorithm to use (default: hc)
alpha	the alpha value of conditional independence tests (if applicable)
test	the type of conditional independence test (if applicable)
make.plot	if to make a plot or just return the network (default: FALSE)
blacklist	a data frame with two columns (optionally labeled "from" and "to"), containing a set of arcs not to be included in the graph.
B	the number of bootstrap runs of permutations (for iamb and such algorithms)
restart	the number of random restarts for score-based algorithms
scale	the color scaling
class.label	the label to use for the class variable
use.colors	if to color code the results
score	the scoring penalization metric to use (when applicable)

Value

an object of class "bn" representing the inferred network

Examples

data(mesoBin)
# use hill-climbing to make the causal network and plot with enrichment colours
plotBNLearn(mesoBin$Meso, make.plot=TRUE)

ddgraph documentation built on Nov. 17, 2017, 10:50 a.m.