Jeff Newmiller <jdnewmil <at> dcn.davis.ca.us> writes: > Nope. Most users get speed by using vectorized calculations. If you > have already identified how to get correct answers, the next step is > something like Rcpp or linking to a shared library written in your > language of choice.
> But seriously, vectorizing is enough for most applications, and > making sure the answer is right doesn't usually require compiled > code. > Gregory Propf <gregorypropf <at> yahoo.com> wrote: > > >Simple question: is there a way to compile R scripts to native code? > >�If not is there anything else that might improve speed? �I'm not even > >sure that R compiles internally to byte code or not. �I assume it does > >since all modern languages seem to do this. �Maybe there's a JIT > >compiler? �Yes, I have searched Google and get lots of stuff that's > >seems confusing. �I just want to know what packages to install and how > >to use them to generate binaries if they exist. > > [[alternative HTML version deleted]] Note that there is a fairly recently introduced byte-compiler for R (library("compiler"); ?compile). There's also http://www.milbo.users.sonic.net/ra/ , which looks a little out of date by now (last release August 2011), but it might be worht comparing. As Jeff said, though, there is usually room for lots of speed improvement via vectorizing (or using add-on packages such as data.table ). I *believe* typical speed-ups from the built-in compiler are on the order of three-fold. Porting to compiled languages (most popularly via Rcpp) can give much higher speed-ups. For more information we'd really need to know what you are trying to do. You might try searching Stack Overflow for "[r] speed up" ... ______________________________________________ R-help@r-project.org mailing list 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.