plot.bbnam {sna} | R Documentation

## Plotting for bbnam Objects

### Description

Generates various plots of posterior draws from the `bbnam` model.

### Usage

    plot.bbnam(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 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

`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)

[Package sna version 1.1 Index]