How to speed up your R code with virtually no effort

One way to speed up your R code is to convert the speed critical components to C or some other language. But this takes time and effort. In this informal talk, I’ll suggest a four step approach for speeding up your R code with virtually no effort. For step one I’ll talk about the avoidance of slow implementations in the initial coding stage. For step two I’ll discuss profiling your code using the Rprof function. For step three I’ll look at parallelized implementations using the parallel and foreach packages. And finally, in step four I’ll spend a couple of dollars of my hard earned cash to demonstrate the use of R Studio Server on Amazon EC2 in order to access computing power that I couldn’t otherwise afford.

Alec Stephenson (https://www.meetup.com/MelbURN-Melbourne-Users-of-R-Network/members/12865295/) is a Research Scientist, a former Assistant Professor at the National University of Singapore and a former post-doc at Macquarie University. Alec is a mathematician, statistician and programmer, and wrote several R packages when he was a PhD student at Lancaster University, U.K., following undergraduate training at Warwick and Oxford. He is now an Australian citizen, and has given all his publicly available software away to others who are younger and cleverer. He recently won a couple of Kaggle competitions on credit scoring and rating chess players.