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

[Sophia Kyriakou]

Thanks João, indeed the scoping assignment works.
All the best,
Sophia

On Fri, Mar 17, 2017 at 1:09 AM, João Veríssimo <jl.verissimo at gmail.com>
wrote:

> Hi Sophia,
>
> Not sure why this happens, but using <<- assignment seems to work.
> (i.e., dat <<- ..., rather than dat <- ...)
>
> João
>
> On Fri, 2017-03-17 at 00:34 +0200, Sophia Kyriakou wrote:
> > 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
> >
> >       [[alternative HTML version deleted]]
> >
> > _______________________________________________
> > R-sig-mixed-models at r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models
>
>
>

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