Take Posterior Predictive Draws for Functions of Networks
npostpred takes a list or data frame, b, and applies the function FUN to each element of b's net member.
npostpred(b, FUN, ...)
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 |
FUN |
Function for which posterior predictive is to be estimated |
... |
Additional arguments to |
A series of posterior predictive draws
Carter T. Butts buttsc@uci.edu
Gelman, A.; Carlin, J.B.; Stern, H.S.; and Rubin, D.B. (1995). Bayesian Data Analysis. London: Chapman and Hall.
#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))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.