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
[EMAIL PROTECTED] 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
______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
