plotAbn: Plot an ABN graphic

In abn: Modelling Multivariate Data with Additive Bayesian Networks

Plot an ABN graphic

Description

Plot an ABN DAG using formula statement or a matrix in using Rgraphviz through the graphAM class.

Usage

plotAbn(dag, data.dists=NULL, markov.blanket.node=NULL, fitted.values=NULL,
               digits=2, edge.strength=NULL, edge.strength.lwd=5, edge.direction="pc",
               edge.color="black", edge.linetype="solid", edge.arrowsize=0.6,
               edge.fontsize=node.fontsize, node.fontsize=12,
               node.fillcolor=c("lightblue", "brown3", "chartreuse3"),
               node.fillcolor.list=NULL,
               node.shape=c("circle", "box", "ellipse", "diamond"),
               plot=TRUE , ...)

Arguments

dag	a matrix or a formula statement (see details for format) defining the network structure, a Directed Acyclic Graph (DAG). Note that rownames must be set or given in data.dists.
data.dists	a named list giving the distribution for each node in the network, see details.
markov.blanket.node	name of variables to display its Markov blanket.
fitted.values	modes or coefficents outputted from fitAbn.
digits	number of digits to display the fitted.values.
edge.strength	a named matrix containing evaluations of edge strength which will change the arcs width (could be Mutual information, p-values, number of bootstrap retrieve samples or the outcome of the linkStrength).
edge.strength.lwd	maximum line width for edge.strength.
edge.direction	character giving the direction in which arcs should be plotted, pc (parent to child) or cp (child to parent) or undirected.
edge.color	the colour of the edge.
edge.linetype	the linetype of the edge. Defaults to "solid". Valid values are the same as for the R's base graphic parameter lty.
edge.arrowsize	the thickness of the arrows. Not relevant if arc.strength is provided.
edge.fontsize	the font size of the arcs fitted values.
node.fontsize	the font size of the nodes names.
node.fillcolor	the colour of the node. Second and third element is used for the Markov blanket and node of the Markov blanket.
node.fillcolor.list	the list of node that should be coloured.
node.shape	the shape of the nodes according the Gaussian, binomial, Poisson and multinomial distributions.
plot	logical variable, if set to TRUE then the graph is plotted.
...	arguments passed to the plotting function.

Details

By default binomial nodes are squares, multinoial nodes are empty, Gaussian nodes are circles and poison nodes are ellipses.

The dag can be provided using a formula statement (similar to glm). A typical formula is ~ node1|parent1:parent2 + node2:node3|parent3.

The construction is based on the graph package. Properties of the graph can be changend after the construction, see ‘Examples’.

Value

A rendered graph, if plot=TRUE. The graphAM object is returned invisibly.

See Also

graphAM-class, edgeRenderInfo

Examples

#Define distribution list
dist <- list(a="gaussian", b="gaussian", c="gaussian", d="gaussian", e="binomial", f="binomial")

#Define a matrix formulation
edge.strength <- matrix(c(0,0.5,0.5,0.7,0.1,0,
                          0,0,0.3,0.1,0,0.8,
                          0,0,0,0.35,0.66,0,
                          0,0,0,0,0.9,0,
                          0,0,0,0,0,0.8,
                          0,0,0,0,0,0),nrow = 6L, ncol = 6L, byrow = TRUE)

## Naming of the matrix
colnames(edge.strength) <- rownames(edge.strength) <- names(dist)

## Plot form a matrix
plotAbn(dag = edge.strength, data.dists = dist)

## Edge strength
plotAbn(dag = ~a|b:c:d:e+b|c:d:f+c|d:e+d|e+e|f, data.dists = dist, edge.strength = edge.strength)

## Plot from a formula for a different DAG!
plotAbn(dag = ~a|b:c:e+b|c:d:f+e|f, data.dists = dist)

## Markov blanket
plotAbn(dag = ~a|b:c:e+b|c:d:f+e|f, data.dists = dist, markov.blanket.node = "e")

## Change col for all edges
tmp <- plotAbn(dag = ~a|b:c:e+b|c:d:f+e|f, data.dists = dist, plot=FALSE)
graph::edgeRenderInfo(tmp) <- list(col="blue")
Rgraphviz::renderGraph(tmp)

## Change lty for individual ones. Named vector is necessary
tmp <- plotAbn(dag = ~a|b:c:e+b|c:d:f+e|f, data.dists = dist, plot=FALSE)
edgelty <- rep(c("solid","dotted"), c(6,1))
names(edgelty) <- names( graph::edgeRenderInfo(tmp, "col"))
graph::edgeRenderInfo(tmp) <- list(lty=edgelty)
Rgraphviz::renderGraph(tmp)

abn documentation built on Nov. 3, 2023, 5:08 p.m.