[R-sig-ME] glmmTMB and foreach parallel adaptor

[Sophia Kyriakou]

Dear members,

I am trying to set some code running on Windows, which calculates and
returns the Laplace-based maximum likelihood estimates of a generalized
linear mixed model.
Both glmer and glmmTMB functions work on R 3.3.3 when the code is executed
sequentially.
However, when I use the parallel algorithm, then glmer still works, but
glmmTMB does not.
The error I get is Error in { : task 1 failed - "object 'dat' not found" ,
where dat is the simulated dataset in each replication.

Any ideas on how to tackle this error? I am interested in using glmmTMB
instead of lme4, because I need some of glmmTMB output components.

Below is a sample code that illustrates the above:


library(doParallel)
library(glmmTMB)
library(lme4)

simSamples <- matrix(sample(0:6,300,replace=TRUE),30,10)

## Sequential version
LA <- LA2 <- matrix(NA,3,10)
for (i in 1:10){
dat <-
data.frame(subject=rep(1:15,each=2),x=-14:15,m=rep(6,30),y=simSamples[,i],yprop=simSamples[,i]/6)
fitLA <- glmmTMB(yprop ~ x +(1|subject),family=binomial,weights=m,data=dat)
LA[,i] <- fitLA$fit$par
fitLA2 <- glmer(cbind(y,6-y) ~ x +(1|subject),family=binomial,data=dat)
LA2[,i] <- c(fixef(fitLA2),sqrt(unlist(VarCorr(fitLA2))))
}


## Parallel version
cl <- makeCluster(3)
registerDoParallel(cl)
TMBfit <- foreach(i=1:10, .combine= cbind, .packages=c("glmmTMB")) %dopar% {
dat <-
data.frame(subject=rep(1:15,each=2),x=-14:15,m=rep(6,30),yprop=simSamples[,i]/6)
fitLA <- glmmTMB(yprop ~ x +(1|subject),family=binomial,weights=m,data=dat)
fitLA$fit$par
}
stopCluster(cl)


cl <- makeCluster(3)
registerDoParallel(cl)
LME4fit <- foreach(i=1:10, .combine= cbind, .packages=c("lme4")) %dopar% {
dat <-
data.frame(subject=rep(1:15,each=2),x=-14:15,m=rep(6,30),y=simSamples[,i])
fitLA <- glmer(cbind(y,6-y) ~ x +(1|subject),family=binomial,data=dat)
c(fixef(fitLA),sqrt(unlist(VarCorr(fitLA))))
}
stopCluster(cl)

Any help is much appreciated.
Thanks in advance!
Sophia

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