plot.bbnam: Plotting for bbnam Objects

In sna: Tools for Social Network Analysis

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 bbnam object
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 plot

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 [e-mail]

References

Butts, C.T. (1999). “Informant (In)Accuracy and Network Estimation: A Bayesian Approach.” CASOS Working Paper, Carnegie Mellon University.

See Also

bbnam

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)

sna documentation built on Feb. 16, 2023, 9:52 p.m.