[igraph] Random Walk Sample

[Thomas]

I'm creating a sample of nodes according to the random walk procedure  
described in Section 3.3.3 of:

http://www.stat.cmu.edu/~fienberg/Stat36-835/Leskovec-sampling-kdd06.pdf

The following R code samples no less than 300 nodes, although it might  
sample the same node twice but it runs really slowly. Does anyone know  
why it might be going so slow? Is there any better way to do this?

Thank you,

Thomas

#Random Walk Sample of nodes from network g
#Read graph g in as UNDIRECTED

 A <- sample(1:length(degree(g)), 1)
 oput <- c()
 oput <- c(oput, A)
 flag <- FALSE
 count <- 1

 while(count <= 300)
 {
 node1 <- A
 while(flag==FALSE)
 {
 node2 <- sample(neighbors(g,node1),1)
 oput <- c(oput, node2)
 count <- count + 1
 node1 <- node2
 if(rbinom(1,1,0.15)==1){flag=TRUE}
 }#end of while flag loop
 }#end of while count loop
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