Thread by @DaniRabaiotti

So folks, what package would you recommend for paralellising code in R?

I thought this would be simple based on previous experience with parallelising code but I am quickly realising it is not going to be simple. Blargh.

I have had a total turnaround and now think I do not need the paralell package.

I hope you are all enjoying this live commentary on the realities of science.

I'm also so stressed about this I have managed to spell parallel wrong twice in a very short space of time.

My conundrum quite nicely illustrates the frustrations of R. I *could* open 12 R windows and run 1/12th of my runs in each. It would achieve exactly what I am trying to do. Instead I will spend the next few days wrangling with code because it will be more useful in future #rstats

So far I have managed to make my model, and whole computer run really slowly using the future package #winning #rstats

Everything is bad.

Wait I think I am getting somewhere

So I can run my function using foreach....now I need to work out how to get different runs to use different input variables

I HAVE PARALLELISED IT IN FOREACH. But I don't know how to get each run to use a different variable help?! #rstats #babysteps

I have one solution courtesy of @statsforbios who is a total hero, but am keen to get it working using foreach and doapply as well. If anyone knows about cycling through numbers using iter() let me know #rstats. It keeps telling me an argument is missing *grumble*