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Tuesday, June 28 • 10:48am - 11:06am
Compiling parts of R using the NIMBLE system for programming algorithms

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The NIMBLE R package provides a flexible system for programming statistical algorithms for hierarchical models specified using the BUGS language. As part of the system, we compile R code for algorithms and seamlessly link the compiled objects back into R, with our focus being on mathematical operations. Our compiler first generates C++, including Eigen code for linear algebra, before the usual compilation process. The NIMBLE compiler was written with extensibility in mind, such that adding new operations for compilation requires only a few well-defined additions to the code base. We'll describe how one can easily write functions in R and automatically compile them, as well as how the compiler operates behind the scenes. Functions can be stand-alone functions or can be functions that interact with hierarchical models written in BUGS code, which NIMBLE converts to a set of functions and data structures that are also compiled via C++. Finally, we'll show how the system has been used to build a full suite of MCMC and sequential Monte Carlo algorithms that can be used on any hierarchical model.

avatar for Ben Goodrich

Ben Goodrich

Lecturer in the Discipline of Political Science, Columbia University
Ben Goodrich is a core developer of Stan, which is a collection of statistical software for Bayesian estimation of models, and is the maintainer of the corresponding rstan and rstanarm R packages. He teaches in the political science department and in the Quantitative Methods in the Social Sciences master's program at Columbia University.


Christopher J. Paciorek

Department of Statistics, UC Berkeley

Attendees (29)