R: Take Posterior Predictive Draws for Functions of Networks

npostpred {sna} | R Documentation

## Take Posterior Predictive Draws for Functions of Networks

### Description

`npostpred` takes a list or data frame, `b`, and applies the function `FUN` to each element of `b`'s `net` member.

### Usage

    npostpred(b, FUN, ...)

### Arguments

`b` | A list or data frame containing posterior network draws; these draws must take the form of a graph stack, and must be the member of `b` referenced by "`net`"
`FUN` | Function for which posterior predictive is to be estimated
`...` | Additional arguments to `FUN`

### Details

Although created to work with `bbnam`, `npostpred` is quite generic. The form of the posterior draws will vary with the output of `FUN`; since invocation is handled by `apply`, check there if unsure.

### Value

A series of posterior predictive draws

### Author(s)

Carter T. Butts buttsc@uci.edu

### References

Gelman, A.; Carlin, J.B.; Stern, H.S.; and Rubin, D.B. (1995). Bayesian Data Analysis. London: Chapman and Hall.

### 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)
    #Plot a summary of the posterior predictive of reciprocity
    hist(npostpred(b,grecip))

[Package sna version 2.4 Index]