WinBUGS is no longer under development, and has been superseded by OpenBUGS (www.openbugs.info). Up until now, to use OpenBUGS on a Mac, you needed to run R under Wine and then call OpenBUGS via the BRugs package. Now, the R2WinBUGS package has been updated to work with OpenBUGS and allows R, running on a Mac, to call OpenBUGS using Wine. So far, OpenBUGS seems to run much faster and more efficiently than WinBUGS. Here's how to get it running. 1. If you don't have Wine up and running, follows steps 1-6 on this page. 2. Download OpenBUGS321setup.exe (windows executable) and place it in your default directory for Wine programs (mine is "~/.wine/drive_c") 3. Run the OpenBugs installer by: 4. Test OpenBUGS by opening a new XQuartz Terminal window typing: wine C:\\Program\ Files\\OpenBUGS321\\OpenBUGS.exe 5. Get the R2OpenBUGS source package from here. 6. Install the package.
7. Test OpenBugs by running this R script: #Load the OpenBUGS Package - make sure XQuartz is running library(R2OpenBUGS) #schools data in the R2OpenBUGS library data(schools) #define the model nummodel <- function(){ for (j in 1:J){ y[j] ~ dnorm (theta[j], tau.y[j]) theta[j] ~ dnorm (mu.theta, tau.theta) tau.y[j] <- pow(sigma.y[j], -2)} mu.theta ~ dnorm (0.0, 1.0E-6) tau.theta <- pow(sigma.theta, -2) sigma.theta ~ dunif (0, 1000) } # write the model code out to a file write.model(nummodel, "nummodel.txt") model.file1 = paste(getwd(),"nummodel.txt", sep="/") ## and let's take a look: file.show("nummodel.txt") #prepare the data for input into OpenBUGS J <- nrow(schools) y <- schools$estimate sigma.y <- schools$sd data <- list ("J", "y", "sigma.y") #initialization of variables inits <- function(){ list(theta = rnorm(J, 0, 100), mu.theta = rnorm(1, 0, 100), sigma.theta = runif(1, 0, 100))} #set the WINE working directory and the directory to OpenBUGS - change the OpenBUGS.exe location as necessary WINE="/opt/local/bin/wine" WINEPATH="/opt/local/bin/winepath" OpenBUGS.pgm="/Users/[username]/.wine/drive_c/Program Files/OpenBUGS321/OpenBUGS.exe" #these are the parameters to save parameters = c("theta", "mu.theta", "sigma.theta") #run the model schools.sim <- bugs(data, inits, model.file = model.file1,parameters=parameters,n.chains = 3, n.iter = 1000, OpenBUGS.pgm=OpenBUGS.pgm, WINE=WINE, WINEPATH=WINEPATH,useWINE=T) #R will pause. When model is complete a prompt will reappear print(schools.sim) 7. Output from step 6 should be: Inference for Bugs model at "/Users/bigbird/Documents/Duke/2paper/rcode/nummodel.txt", Current: 3 chains, each with 1000 iterations (first 500 discarded) Cumulative: n.sims = 1500 iterations saved mean sd 2.5% 25% 50% 75% 97.5% Rhat n.eff theta[1] 11.7 7.5 -1.4 7.4 11.5 15.0 29.3 1.1 350 theta[2] 9.0 6.1 -4.2 5.2 10.0 12.4 19.2 1.1 21 theta[3] 7.7 7.2 -9.4 3.2 9.1 12.4 18.8 1.2 18 theta[4] 8.8 6.3 -4.7 4.6 10.0 12.4 20.1 1.1 22 theta[5] 6.8 6.6 -8.8 2.6 8.0 12.0 16.7 1.3 11 theta[6] 7.6 6.6 -7.4 3.1 8.9 12.3 17.4 1.2 13 theta[7] 11.2 6.1 -0.8 7.7 11.5 14.4 24.0 1.1 160 theta[8] 9.7 7.1 -5.0 5.6 10.7 13.1 24.5 1.1 54 mu.theta 8.9 5.1 -1.9 5.9 9.8 12.4 17.2 1.2 15 sigma.theta 5.2 5.3 0.0 0.9 3.6 8.1 17.9 1.7 6 deviance 60.5 2.0 57.1 59.3 60.4 61.4 64.9 1.0 200 For each parameter, n.eff is a crude measure of effective sample size, and Rhat is the potential scale reduction factor (at convergence, Rhat=1). DIC info (using the rule, pD = Dbar-Dhat) pD = 63.0 and DIC = 2.5 DIC is an estimate of expected predictive error (lower deviance is better). |
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Running OpenBUGS on Mac Using Wine |