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
