Well, it appears that many people had the same idea: See https://github.com/karlines/ccSolve/ which does something similar for Fortran, and C code - and also extends some base R functions to support compiled code. Karline -----Original Message----- From: R-sig-dynamic-models [mailto:r-sig-dynamic-models-bounces at r-project.org] On Behalf Of Tim Keitt Sent: vrijdag 17 april 2015 23:45 To: r-sig-dynamic-models at r-project.org Subject: [R-sig-dyn-mod] New R package I've recently been using Rcpp + ODEINT for some projects where I needed a lot of speed and flexibility in model specification (variable dimensions, mixing discrete and continuous time functions). It gave me the idea to write a small R package that allows one to specify the ODE system in a C++ snippet, which is combined with boilerplate code and compiled using Rcpp. Have a look: https://github.com/thk686/odeintr THK -- http://www.keittlab.org/ _______________________________________________ R-sig-dynamic-models mailing list R-sig-dynamic-models at r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-dynamic-models
[R-sig-dyn-mod] New R packages supporting compiled code
3 messages · Karline Soetaert, Tim Keitt, Daniel Kaschek
Nice. I'll check it out. THK On Sat, Apr 18, 2015 at 3:52 AM, Karline Soetaert <Karline.Soetaert at nioz.nl> wrote:
Well, it appears that many people had the same idea: See https://github.com/karlines/ccSolve/ which does something similar for Fortran, and C code - and also extends some base R functions to support compiled code. Karline -----Original Message----- From: R-sig-dynamic-models [mailto: r-sig-dynamic-models-bounces at r-project.org] On Behalf Of Tim Keitt Sent: vrijdag 17 april 2015 23:45 To: r-sig-dynamic-models at r-project.org Subject: [R-sig-dyn-mod] New R package I've recently been using Rcpp + ODEINT for some projects where I needed a lot of speed and flexibility in model specification (variable dimensions, mixing discrete and continuous time functions). It gave me the idea to write a small R package that allows one to specify the ODE system in a C++ snippet, which is combined with boilerplate code and compiled using Rcpp. Have a look: https://github.com/thk686/odeintr THK -- http://www.keittlab.org/ [[alternative HTML version deleted]]
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Dear Karline, I had a look at your ccSolve package and it looks very nice. I would like to comment on two things: 1. Jacobians: When implementing my first BVPs with compiled code I found it especially tedious to compute and implement the jacobian of the system. Therefore, I implemented a function jacobianSymb() in my cOde package that symbolically computes the jacobian for a function defined as character vector. If you had plans to implement something similar, you might just have a look at my code and use it if you like. 2. Parameter estimation in ODEs: Our group has been working on this topic for many years now. In our experience, optimization with derivatives computed from finite differences of the model solutions is quite unstable and time consuming. Optimization is improved a lot when you compute the sensitivities along with the model states. In http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0074335 you find a comparison of different optimization stategies (deterministic vs. stochastic, finite differences vs. sensitivities), Figures 5, 6 and 7. Best regards, Daniel --------------------------------- Daniel Kaschek Institute of Physics Freiburg University Room: 210 Phone: +49 761 2038531 On Sa, Apr 18, 2015 at 10:52 , Karline Soetaert
<Karline.Soetaert at nioz.nl> wrote:
Well, it appears that many people had the same idea: See https://github.com/karlines/ccSolve/ which does something similar for Fortran, and C code - and also extends some base R functions to support compiled code. Karline -----Original Message----- From: R-sig-dynamic-models [mailto:r-sig-dynamic-models-bounces at r-project.org] On Behalf Of Tim Keitt Sent: vrijdag 17 april 2015 23:45 To: r-sig-dynamic-models at r-project.org Subject: [R-sig-dyn-mod] New R package I've recently been using Rcpp + ODEINT for some projects where I needed a lot of speed and flexibility in model specification (variable dimensions, mixing discrete and continuous time functions). It gave me the idea to write a small R package that allows one to specify the ODE system in a C++ snippet, which is combined with boilerplate code and compiled using Rcpp. Have a look: https://github.com/thk686/odeintr THK -- http://www.keittlab.org/ [[alternative HTML version deleted]]
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