R: Speeding things up

June 9, 2011

(This article was first published on The Data Monkey, and kindly contributed to R-bloggers)

R is many things, but it’s not exactly speedy like a Patas Monkey. In fact, while it is much faster than many other solutions, R is notably slower than Stata (even inspiring talks that it should be rewritten from scratch!).

Fortunately, Radford Neal has been hard at work speeding R up, and has released some new patches to play with if you find it too slow. You can also try writing key sections in C++, or using Revolution Analytics’ offerings (free for academics).

For extreme speed needs, however, R can’t be beat, as it has long offered graphics-card based extreme parallelism that commercial solutions are only beginning to match.

Of course, for more prosaic needs, focusing on vectorizing key operations can solve speed troubles. And it’s worth noting that the $1,000+ per copy that Stata costs can buy an awful lot of extra processing power to throw at the problem.

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