More of a general query, but looking to see if others have successfully used something like the foreach package (or other parallel style functions) with certain functions that minimize likelihood or objective functions (e.g., optim/nlminb).
I have had great success with embarrassingly parallel problems and my R packages have benefited greatly. However, optimization doesn't fit as nicely within that context as the values at iteration t depend on the values found at iteration t-1 and such. So, I'm assuming the cost of splitting and combining might be more expensive in this context that simply doing minimization on a single core. If others have experiences or even possibly R-specific resources that implement this that I would be able to study, I would appreciate seeing how this might be implemented. Regards Harold ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
