Thank you Paul, Barry and Patrick. I will do what you recommand (the profiling).
I have heard several times that for example Matlab would be faster than R... This is why I thought of switching to Python, though it is also interpreted. I thought it would be faster. Best, Jean 2009/11/21 Patrick Burns <pbu...@pburns.seanet.com> > One little thing that I think Barry > meant to say. > > If the bottleneck is in your code, you > may be able to improve the situation > enough by merely rewriting the R code > of your function. If that doesn't work, > then you can move to C. > > > > Patrick Burns > patr...@burns-stat.com > +44 (0)20 8525 0696 > http://www.burns-stat.com > (home of "The R Inferno" and "A Guide for the Unwilling S User") > > Barry Rowlingson wrote: > >> On Sat, Nov 21, 2009 at 2:29 PM, Jean Legeande <jean.legea...@gmail.com> >> wrote: >> >>> Dear R users, >>> >>> I would like to make my R code for MCMC faster. It is possible to >>> integrate >>> C code into R but I think C is too complicated for me. I would need a C >>> introduction only for MCMC and I do not know if such a thing exists. >>> >>> I was thinking of Python (and scipy). Where could I read about its >>> integration into R ? How developed are the statistical packages in Python >>> ? >>> I could not find a Python package on the web with functions to simulate >>> Wishart, or multivariate gamma or student distributions. >>> >>> Since I am a little bit lost, I write this message to the R help list. >>> Sorry >>> for these naive questions and thanks for your help. >>> >>> >> Have you done a profile of your MCMC code to see where the bottleneck >> is? Without doing that first any effort could be a total waste of >> time. >> >> R can do a lot of it's calculations at the same level as C, so if 80% >> of your time is spent inverting matrices then converting to Python or >> C (or even assembly language) isn't going to help much since R's >> matrix inversion is done using C code (and quite possibly very >> optimised C code with maybe some assembly language too). >> >> So do a profile (see ?Rprof) and work out the bottleneck. It might be >> one of your functions, in which case just re-writing that in C and >> linking to R (see programmers guide and a good C book) will do the >> job. >> >> My hunch is that Python and R run at about the same speed, and both >> use C libraries for speedups (Python primarily via the numpy package). >> >> You can call the GSL from Python, and there are probably tricks for >> getting the distributions you want: >> >> http://www.mailinglistarchive.com/help-...@gnu.org/msg00096.html >> >> describes how to get samples from a Wishart. >> >> However using the GSL from Python probably wont be much faster than >> using R because again it's all at the C level already. Did I suggest >> you profile your code? >> >> Barry >> >> ______________________________________________ >> 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<http://www.r-project.org/posting-guide.html> >> and provide commented, minimal, self-contained, reproducible code. >> >> [[alternative HTML version deleted]] ______________________________________________ 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.
