npostpred: Take Posterior Predictive Draws for Functions of Networks

In sna: Tools for Social Network Analysis

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 [e-mail]

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))

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