BANFF (version 1.1)

plot.Networks.STD: Plotting Bayesian Network Discovery using a Standard MCMC Algorithm

Description

plot method for class "Networks.STD"

Usage

"plot"(x, ...)

Arguments

x

An object of class "Networks.STD" resulting of a call to Networks.STD.

...

other arguments

See Also

Networks.STD.

Examples

library(igraph)
###Creating the network of 10X10 image
g <- graph.lattice(length=10,dim=2)
net=as(get.adjacency(g,attr=NULL),"matrix")##this is the input of argument 'net'
##Assign the signal elements with signal intention 
##as normal distribution N(1,0.2). While noise is set as N(0,0.2)
newz=rep(0,100)
for (i in 3:7)
{
 newz[(i*10+3):(i*10+7)]=1
}
testcov<-0
for(i in 1:100){
 if(newz[i]==0){
   testcov[i]<-rnorm(1,mean=0,sd=0.2)

 }else{
  testcov[i]<-rnorm(1,mean=1,sd=0.2)

 }
}
##The profile of the image
image(matrix(testcov,10,10),col=gray(seq(0,1,length=255)))
##Transform the signals into pvalue form and begin identification
pvalue=pnorm(-testcov)
total=Networks.STD(pvalue,net,iter=3,nburns=1,
piall=c(0.8, 0.85, 0.9, 0.95),rhoall=c(0.5,1,5,10,15))

######plot the object of class "Networks.STD"
plot(total)