plot.bdgraph {BDgraph}

Plot function for S3 class "bdgraph"

Description

Visualizes structure of the selected graphs which could be a graph with links for which their estimated posterior probabilities are greater than 0.5 or graph with the highest posterior probability.

Usage

 ## S3 method for class 'bdgraph'
plot( x, cut = 0.5, number.g = NULL, main = NULL, 
           layout = igraph::layout_with_fr, vertex.size = 2, vertex.color = "orange", 
           vertex.frame.color = "orange", vertex.label = NULL, vertex.label.dist = 0.5, 
           vertex.label.color = "blue", edge.color = "lightblue", ... ) 

Arguments

x

object of S3 class "bdgraph", from function bdgraph.

cut

threshold for including the links in the selected graph based on the estimated posterior probabilities of the links; See the examples.

number.g

number of graphs with the highest probabilities. This option works for the case running function bdgraph() with option save = TRUE; See the examples.

main

Graphical parameter (see plot).

layout

vertex placement which is according to R package igraph; For different layouts, see layout of R package igraph.

vertex.size

vertex size which is according to R package igraph.

vertex.color

vertex color which is according to R package igraph.

vertex.frame.color

vertex frame color which is according to R package igraph.

vertex.label

vertex label. The default vertex labels are the vertex ids.

vertex.label.dist

vertex label distance which is according to R package igraph.

vertex.label.color

vertex label color which is according to R package igraph.

edge.color

edge color which is according to R package igraph.

...

additional plotting parameters. For the complete list, see igraph.plotting of R package igraph.

Author(s)

Reza Mohammadi [e-mail] and Ernst Wit

References

Mohammadi, R. and Wit, E. C. (2019). BDgraph: An R Package for Bayesian Structure Learning in Graphical Models, Journal of Statistical Software, 89(3):1-30, doi:10.18637/jss.v089.i03

See Also

bdgraph, bdgraph.mpl

Examples

## Not run: 
set.seed( 100 )

# Generating multivariate normal data from a 'random' graph
data.sim <- bdgraph.sim( n = 100, p = 15, graph = "random", prob = 0.2, vis = TRUE )
   
bdgraph.obj <- bdgraph( data = data.sim )
   
plot( bdgraph.obj )
   
bdgraph.obj <- bdgraph( data = data.sim, save = TRUE )
   
plot( bdgraph.obj, cut = 0.5 )

plot( bdgraph.obj, number.g = 4 )

## End(Not run)