nimble-virtual-2020

Materials for the virtual NIMBLE workshop, June 3-5 2020.

To prepare for the workshop:

• Install NIMBLE (see below)
• Install additional packages (see below and check back for updates)
• Download these materials [UNDER CONSTRUCTION]
• (Optional) Join a slack workspace for the workshop [UNDER CONSTRUCTION]

All materials for the workshop are here [UNDER CONSTRUCTION]. If you're familiar with Git/Github, you already know how to get all the materials on your computer. If you're not, simply click here.

There is some overview information here, including links to the content modules in order.

Location: Zoom (URL TBD) Time: 9 am - 2 pm California time (noon - 5 pm EDT)

Approximate schedule

Day 1 (Wednesday):

1. Introduction to NIMBLE: Basic concepts and workflows
2. Working with NIMBLE models and converting from WinBUGS/JAGS
3. Comparing and customizing MCMC methods in NIMBLE
4. Strategies for improving MCMC

Day 2 (Thursday):

5. Writing your own functions and distributions
6. Writing your own MCMC samplers
7. Spatial modeling (part 1)

Day 3 (Friday):

8. Spatial modeling (part 2)
9. Model selection and Bayesian nonparametrics
10. Special topics breakouts a. Ecological models b. Sequential Monte Carlo and maximum likelihood methods

Installing NIMBLE

NIMBLE is an R package on CRAN, so in general it will be straightforward to install as with any R package, but you do need a compiler and related tools on your system.

In summary, here are the steps.

1. Install compiler tools on your system. https://r-nimble.org/download has more details on how to install Rtools on Windows and how to install the command line tools of Xcode on a Mac. Note that if you have packages requiring a compiler (e.g., Rcpp) on your computer, you should already have the compiler tools installed.

2. Install the nimble package from CRAN in the usual fashion for an R package. More details (including troubleshooting tips) can also be found in Section 4 of the NIMBLE manual.

3. To test that things are working please run the following code in R:

library(nimble)
code <- nimbleCode({
  y ~ dnorm(0,1)
})
model <- nimbleModel(code)
cModel <- compileNimble(model)

If that runs without error, you're all set. If not, please see the troubleshooting tips and email nimble.stats@gmail.com directly if you can't get things going.

In general we encourage you to update to the most recent version of NIMBLE, 0.9.1.

IMPORTANT: for those of you using R 4.0 under Windows, you MUST use version 0.9.1.

(Not required) Development version(s) of NIMBLE

Sometimes we make an update or new feature available on a github branch before it is released. In the event a need arises to install from a branch, you can do so as follows (for branch "devel"):

library(remotes)
install_github("nimble-dev/nimble", ref = "devel", subdir = "packages/nimble")

Installing additional packages

Some of the packages we will use (beyond those automatically installed with nimble) can be installed as follows:

install.packages(c("mcmcplots", "CARBayesdata", "sp", "spdep", "classInt"))

compareMCMCs is a package in development that is not yet on CRAN:

library(remotes)
install_github("nimble-dev/compareMCMCs", subdir = "compareMCMCs")