This is veering off topic... but to give you something to chase elsewhere...
Bad idea: reference classes in R. R is functional... RC/R6 break that paradigm and reduce re-usability and are difficult to debug. Every time I have done that I have regretted it later. I can't say definitively that you won't come up with a case that justifies itself... but I would recommend learning a bit about functional software architectures before going too far down that road. Existing packages: look at the Bayesian Inference Task View on CRAN. On April 17, 2020 5:16:48 AM PDT, eva lehner <eva-vale...@gmx.at> wrote: > >Hi Jeff, > >thank you for the answer. I did not really consider this option. >Why do you think that translating a reference-based OOP design to R is >a bad idea? >And do you have a recommendation when it comes to existing MCMC >packages (I would need gibbs, metropolis-hastings and reversible jump >samplers)? > >Cheers, >Eva > >Gesendet: Freitag, 10. April 2020 um 17:25 Uhr >Von: "Jeff Newmiller" <jdnew...@dcn.davis.ca.us> >An: rcpp-devel@lists.r-forge.r-project.org, "eva lehner" ><eva-vale...@gmx.at>, "Dirk Eddelbuettel" <e...@debian.org> >Betreff: Re: [Rcpp-devel] Input on code design implementing a MCMC >algorithm in R and improving performance with RcppArmadillo >Translating reference-based OOP designs from other languages into R >seems like a bad idea, and on the surface looks like re-inventing the >wheel. Are you sure this couldn't be done with one of the existing >packages for doing MCMC? > >On April 10, 2020 2:21:13 AM PDT, eva lehner <eva-vale...@gmx.at> >wrote: >>Hi Dirk, >>Below is my question in text format since there were troubles with the >>html formating. >> >>I want to „translate“ a MCMC algorithm written in matlab to R to >>eventually release it in a package. In the matlab version model input, >>state of the chain and chain output is stored in structs. Updating >>different parameters of the underlying model is performed with >>different functions. I already have a very raw R version where these >>structs are implemented as S4 classes and updates are performed with >>generic functions taking both classes as input. I would like to >>increase performance with RcppArmadillo. However, I struggle to choose >>a good approach since I am not very experienced in any of the above >>subjects and have difficulties putting together the different >concepts. >>It would be very helpful if you could give me your thoughts on what I >>think my main options are, tell me in case I misunderstood some >>concepts or point me into a better direction. >> >>Option 1: mainly R >>Keeping R S4 classes (or rewrite them as Reference Classes since I >>think they would have been a better choice for defining a class >storing >>states of a model) and the algorithm written in R and write updating >>functions in RcppArmadillo. These functions can be exposed to R with >>Rcpp modules or attributes. >>+ possibly the easiest version since I only have to rewrite the >>functions in Rcpp >>- Still a lot of R which could come with performance costs >> >>Option2: mainly Rcpp >>Define one Cpp class which stores input and updated parameters as >>member variables and the updating functions as member functions. Then >I >>could write the main MCMC algorithm as a separate function that >creates >>an instance of this class, calls the updating functions and returns a >>list containing the output. I could only expose this main algorithm >>(with Rcpp modules or attributes) to R and avoid exposing the internal >>classes. (Currently I don’t think exposure of the classes is necessary >>and seems more difficult than exposing functions).The part involving >>the class is taken from the Kalman filter example (RcppArmadillo-intro >>vignette) and I imagine the structure of the algorithm function and >>returned list similar to the gallery entry on the EM Algorithm for >>Probit Regressions >>(https://gallery.rcpp.org/articles/EM-algorithm-example/#attempt-1[https://deref-gmx.net/mail/client/Q6JdcN6Rp84/dereferrer/?redirectUrl=https%3A%2F%2Fgallery.rcpp.org%2Farticles%2FEM-algorithm-example%2F%23attempt-1[https://deref-gmx.net/mail/client/Q6JdcN6Rp84/dereferrer/?redirectUrl=https%3A%2F%2Fgallery.rcpp.org%2Farticles%2FEM-algorithm-example%2F%23attempt-1]]). >>+ probably faster >>+ possibly cleaner >>- more difficult and I have very little Cpp experience (especially >with >>classes) >> >>Personally, I aim for a compromise between performance, implementation >>difficulty and the best approach since this is for my master’s thesis >>and I also have to consider the deadline. I think this compromise >would >>be to stay with the main R version but rewrite the S4 classes as >>Reference Class. >>I'm looking forward to hearing your feedback, thoughts and >experiences, >>Eva >> >> >> >>Gesendet: Donnerstag, 09. April 2020 um 14:51 Uhr >>Von: "Dirk Eddelbuettel" <e...@debian.org> >>An: "eva lehner" <eva-vale...@gmx.at> >>Cc: rcpp-devel@lists.r-forge.r-project.org >>Betreff: Re: [Rcpp-devel] Input on code design implementing a MCMC >>algorithm in R and improving performance with RcppArmadillo >>Hi Eva, >> >>My email client doesn't display you html email, possibly a fault at my >>end. >>But text-only email is still a default in most places. Can you maybe >>resend >>text-only please? Thanks! >> >>Cheers, Dirk >> >>-- >>http://dirk.eddelbuettel.com[http://dirk.eddelbuettel.com][http://dirk.eddelbuettel.com[http://dirk.eddelbuettel.com]] >| >>@eddelbuettel | e...@debian.org >>_______________________________________________ >>Rcpp-devel mailing list >>Rcpp-devel@lists.r-forge.r-project.org >>https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel[https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel] > >-- >Sent from my phone. Please excuse my brevity. -- Sent from my phone. Please excuse my brevity. _______________________________________________ Rcpp-devel mailing list Rcpp-devel@lists.r-forge.r-project.org https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel
