1

I am running a single network model in R. I want to utilize parallel processing in R to run it. I see examples online but they are usually for multiple operations. 

model.2 <- ergmm(network.M.CS ~ euclidean(d=2, G=2)+
                  nodematch("Party", diff = F) + 
                  nodematch("State", diff = F) + 
                  absdiff("Ideology")+
                  edgecov(Donor.Network), 
                response = "Norm.Num.Bill.CS", 
                family = c("Bernoulli"),
                control=ergmm.control(burnin=20000, sample.size= 4000,interval=10),
                verbose=T)
summary(model.2)

As an example, this is the model I would like to run. Any tips you can offer that would allow me to use parallel processing on this single model would be much appreciated. Thank you!

Krantz
  • 1,424
  • 1
  • 12
  • 31
Sharif Amlani
  • 1,138
  • 1
  • 11
  • 25
  • https://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example – Krantz Mar 30 '19 at 20:47
  • 1
    I am not sure if it is applicable, but you could try to implement “software alchemy”: https://www.jstatsoft.org/article/view/v071i04 – Ralf Stubner Mar 31 '19 at 08:49

0 Answers0