How to write efficient R code
You may also be interested in reading the latest article on artima.com (http://www.artima.com/intv/abstreffi.html) where Bjarne Stroustrup (the creator of C++) discusses some of the benefits and costs of abstraction, as well as premature vs. prudent optimisation. It is important to remember that the key to improving execution speeds is profiling your running code - we're not good at anticipating what parts of a program will be slow. It's much better to run the program and see. Hadley
Lennart.Borgman at astrazeneca.com wrote:
I have been lurking in this list a while and searching in the archives to find out how one learns to write fast R code. One solution seems to be to write part of the code not in R but in C. However after finding a benchmark article (http://www.sciviews.org/other/benchmark.htm) I have been more interested in making the R code itself more efficient. I would like to find more info about this. I have tried to mail the contact person for the benchmark, but I have so recieved no reply. I am not an R programmer (or statistican) so I do not know R well. I am looking for some advice about writing fast R code. What about the different data types for example? Is there some good place to start to look for more info about this? Thanks for any pointers Lennart