We’ll be giving a two-hour tutorial on NIMBLE, sponsored by the environmental Bayes (enviBayes) section of ISBA (The International Society for Bayesian Analysis), on Thursday November 18, from 11 am to 1 pm US Eastern time.
NIMBLE (r-nimble.org) is a system for fitting and programming with hierarchical models in R that builds on (a new implementation of) the BUGS language for declaring models. NIMBLE provides analysts with a flexible system for using MCMC, sequential Monte Carlo, MCEM, and other techniques on user-specified models. It provides developers and methodologists with the ability to write algorithms in an R-like syntax that can be easily disseminated to users. C++ versions of models and algorithms are created for speed, but these are manipulated from R without any need for analysts or algorithm developers to program in C++. While analysts can use NIMBLE as a nearly drop-in replacement for WinBUGS or JAGS, NIMBLE provides enhanced functionality in a number of ways.
This workshop will demonstrate how one can use NIMBLE to:
- flexibly specify an MCMC for a specific model, including choosing samplers and blocking approaches (and noting the potential usefulness of this for teaching);
- tailor an MCMC to a specific model using user-defined distributions, user-defined functions, and vectorization;
- write your own MCMC sampling algorithms and use them in combination with samplers from NIMBLE’s library of samplers;
- develop and disseminate your own algorithms, building upon NIMBLE’s existing algorithms; and
- use specialized model components such as Dirichlet processes, conditional auto-regressive (CAR) models, and reversible jump for variable selection.
The tutorial will assume working knowledge of hierarchical models and some familiarity with MCMC. Given the two-hour time frame, we’ll focus on demonstrating some of the key features of NIMBLE, without going into a lot of detail on any given topic.
To attend, please register here.