plot.bbnam {sna} | R Documentation |
Plotting for bbnam Objects
Description
Generates various plots of posterior draws from the bbnam
model.
Usage
## S3 method for class 'bbnam'
plot(x, mode="density", intlines=TRUE, ...)
Arguments
x |
A |
mode |
“density” for kernel density estimators of posterior marginals; otherwise, histograms are used |
intlines |
Plot lines for the 0.9 central posterior probability intervals? |
... |
Additional arguments to |
Details
plot.bbnam
provides plots of the estimated posterior marginals for the criterion graph and error parameters (as appropriate). Plotting may run into difficulties when dealing with large graphs, due to the problem of getting all of the various plots on the page; the routine handles these issues reasonably intelligently, but there is doubtless room for improvement.
Value
None
Author(s)
Carter T. Butts buttsc@uci.edu
References
Butts, C.T. (1999). “Informant (In)Accuracy and Network Estimation: A Bayesian Approach.” CASOS Working Paper, Carnegie Mellon University.
See Also
Examples
#Create some random data
g<-rgraph(5)
g.p<-0.8*g+0.2*(1-g)
dat<-rgraph(5,5,tprob=g.p)
#Define a network prior
pnet<-matrix(ncol=5,nrow=5)
pnet[,]<-0.5
#Define em and ep priors
pem<-matrix(nrow=5,ncol=2)
pem[,1]<-3
pem[,2]<-5
pep<-matrix(nrow=5,ncol=2)
pep[,1]<-3
pep[,2]<-5
#Draw from the posterior
b<-bbnam(dat,model="actor",nprior=pnet,emprior=pem,epprior=pep,
burntime=100,draws=100)
#Print a summary of the posterior draws
summary(b)
#Plot the result
plot(b)