NIMBLE version 0.6-2 has been released on CRAN and at r-nimble.org. NIMBLE is a system that allows you to:
- Write general hierarchical statistical models in BUGS code and create a corresponding model object to use in R. - Build Markov chain Monte Carlo (MCMC), particle filters, Monte Carlo Expectation Maximization (MCEM), or write generic algorithms that can be applied to any model. - Compile models and algorithms via problem-specific generated C++ that NIMBLE interfaces to R for you. Most people associate BUGS with MCMC, but NIMBLE is about much more than that. It implements and extends the BUGS language as a flexible system for model declaration and lets you do what you want with the resulting models. Some of the cool things you can do with NIMBLE include: - Extend BUGS with functions and distributions you write in R as nimbleFunctions, which will be automatically turned into C++ and compiled into your model. - Program with models written in BUGS code: get and set values of variables, control model calculations, simulate new values, use different data sets in the same model, and more. - Write your own MCMC samplers as nimbleFunctions and use them in combination with NIMBLE’s samplers. - Write functions that use MCMC as one step of a larger algorithm. - Use standard particle filter methods or write your own. - Combine particle filters with MCMC as Particle MCMC methods. - Write other kinds of model-generic algorithms as nimbleFunctions. - Compile a subset of R’s math syntax to C++ automatically, without writing any C++ yourself. Compared to earlier versions, the new version of NIMBLE is faster and more flexible in a lot of ways. Building and compiling models and algorithms could sometimes get bogged down for large models, so we streamlined those steps quite a lot. We’ve generally increased the efficiency of C++ generated by the NIMBLE compiler. We’ve added functionality to what can be compiled to C++ from nimbleFunctions. And we’ve added a bunch of better error-trapping and informative messages, although there is still a good way to go on that. Give us a holler on the nimble-users list (see r-nimble.org) if you run into questions. - Chris Paciorek, for the NIMBLE development team _______________________________________________ R-packages mailing list r-packa...@r-project.org https://stat.ethz.ch/mailman/listinfo/r-packages ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
