Very nice, thanks. Shige
On Sat, Oct 1, 2011 at 5:16 PM, Whit Armstrong <[email protected]> wrote: > Please have a look here. > > It's a simple linear model using inline and cppbugs: > https://github.com/armstrtw/CppBugs/tree/master/test/r.inline.example > > -Whit > > > On Sat, Oct 1, 2011 at 3:29 PM, Dirk Eddelbuettel <[email protected]> wrote: >> >> On 1 October 2011 at 15:03, Shige Song wrote: >> | Any examples showing how CppBugs and Rcpp work together will be good. >> | I am particularly interested in knowing how GLM models and GLMM models >> | can be estimated that way. >> | >> | Thanks in advance. >> >> Well, maybe you should really try these two things: >> >> i) take the five or six small examples in Whit's git repo, and read up on >> the inline package and its cxxfunction() to wrap them -- given the >> /working example/ I just provided you yesterday, this is not all that >> hard. >> >> ii) take glm / glmm code you and try to make it work with CppBugs in >> standalone mode as per Whit's examples in hit repo. Then revisit i) >> and wrap it too. >> >> Dirk >> >> | Best, >> | Shige >> | >> | On Sat, Oct 1, 2011 at 1:52 PM, Whit Armstrong <[email protected]> >> wrote: >> | > I'm happy to provide more examples of cppbugs with inline and Rcpp. >> | > >> | > Is there something in particular you had in mind? >> | > >> | > -Whit >> | > >> | > >> | > On Sat, Oct 1, 2011 at 7:05 AM, Shige Song <[email protected]> wrote: >> | >> Dear Whit, >> | >> >> | >> I have been playing with other examples you provided in the github >> | >> repository. The one Dirt sent, however, is the only example that I can >> | >> find from the internet showing how CppBugs works with Rcpp (and R). As >> | >> I see it, such a combination has great potential providing a flexible >> | >> yet powerful Bayesian computational tool. >> | >> >> | >> Very nice work, and thanks for the suggestion. >> | >> >> | >> Best, >> | >> Shige >> | >> >> | >> On Fri, Sep 30, 2011 at 10:06 PM, Whit Armstrong >> | >> <[email protected]> wrote: >> | >>> Shige, >> | >>> >> | >>> That example is quite dated at this point. The CppBugs api has >> | >>> changed a lot since then and is likely to change more in the near >> | >>> future. >> | >>> >> | >>> Please git pull the latest from github, and ping me if you have any >> issues. >> | >>> >> | >>> There are also quite a few pure c++ examples the the 'test' dir to get >> | >>> you started. >> | >>> >> | >>> In the next major release of CppBugs you will be able to declare the >> | >>> objects directly in R, but give me a few months to get that working. >> | >>> >> | >>> -Whit >> | >>> >> | >>> >> | >>> On Fri, Sep 30, 2011 at 9:40 PM, Shige Song <[email protected]> >> wrote: >> | >>>> Dear Dirk, >> | >>>> >> | >>>> Thank you very much for the suggestions and the upated file. Your file >> | >>>> actually works flawlessly on my system. It looks really interesting >> | >>>> and educational. >> | >>>> >> | >>>> Thanks also for the great work on Rcpp, really amazing piece of >> | >>>> software you got there. >> | >>>> >> | >>>> Best, >> | >>>> Shige >> | >>>> >> | >>>> On Fri, Sep 30, 2011 at 9:11 PM, Dirk Eddelbuettel <[email protected]> >> wrote: >> | >>>>> >> | >>>>> Shige, >> | >>>>> >> | >>>>> There is no way to sugarcoat this: you have to learn to live with, >> and learn >> | >>>>> from, the compiler errors and relate them to the actual code. Using >> Rcpp >> | >>>>> still means programming in the context of a C++ compiler. >> | >>>>> >> | >>>>> >> | >>>>> You also need Whit's CppBugs repo from github _installed somewhere_ >> so that >> | >>>>> >> | >>>>> #include <cppbugs/cppbugs.hpp> >> | >>>>> >> | >>>>> works. Plus the same for Conrad's Armadillo as we have >> | >>>>> >> | >>>>> #include <armadillo> >> | >>>>> >> | >>>>> And to top it all off, you probably need a bunch of Boost installed >> as >> | >>>>> CppBugs uses it. If all that is a given, then you can run the >> attached file >> | >>>>> 'whit.r' as I do below. This file served as in example in the Rcpp >> workshop >> | >>>>> in April and I just fetched it from my sources. The version posted >> then is >> | >>>>> likely a little outdated. But this one works: >> | >>>>> >> | >>>>> $ r whit.R >> | >>>>> Loading required package: methods >> | >>>>> user system elapsed >> | >>>>> 0.220 0.020 0.236 >> | >>>>> $b >> | >>>>> [1] -0.3303790 0.5276294 >> | >>>>> >> | >>>>> $ar >> | >>>>> [1] 0 >> | >>>>> >> | >>>>> $ >> | >>>>> >> | >>>>> Whether you use Rscript or r (from littler) does not matter. The >> updated >> | >>>>> whit.r is attached. It builds and runs, I have no idea if it makes >> any >> | >>>>> sense... I think it regresses y ~ X with both being noise so there. >> | >>>>> >> | >>>>> Hope this helps, Dirk >> | >>>>> >> | >>>>> >> | >>>>> >> | >>>>> >> | >>>>> -- >> | >>>>> New Rcpp master class for R and C++ integration is scheduled for >> | >>>>> San Francisco (Oct 8), more details / reg.info available at >> | >>>>> >> http://www.revolutionanalytics.com/products/training/public/rcpp-master-class.php >> | >>>>> >> | >>>>> >> | >>>> _______________________________________________ >> | >>>> Rcpp-devel mailing list >> | >>>> [email protected] >> | >>>> >> https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel >> | >>> >> | >> >> | > >> | _______________________________________________ >> | Rcpp-devel mailing list >> | [email protected] >> | https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel >> -- >> New Rcpp master class for R and C++ integration is scheduled for >> San Francisco (Oct 8), more details / reg.info available at >> http://www.revolutionanalytics.com/products/training/public/rcpp-master-class.php >> > _______________________________________________ Rcpp-devel mailing list [email protected] https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel
