Materials for the virtual NIMBLE workshop, May 26-28 2021.

To prepare for the workshop:

• Install NIMBLE (see below)
• Install additional packages (see below)
• Join our Slack workspace (highly recommended but not required; see information in email)
• Download these materials (and check back before the workshop on Wednesday for updates)
• See email for Zoom invitation.

All materials for the workshop will be in this GitHub repository. 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 (https://htmlpreview.github.io/?https://github.com/nimble-training/nimble-virtual-2021/blob/master/overview.html), including links to the content modules in order.

Time: 8 am - 1 pm California time (GMT-8); 11 am - 4 pm Eastern US time.

Location: Zoom (see email) and Slack.

Please see [this document (https://docs.google.com/document/d/1hhm6Eco0KevM30aDGdpo0n-gYDcT7IPbw7_vTrb-BVQ/edit?usp=sharing) for discussion of how to use Zoom and Slack during the workshop.

All times are California time. If we need to modify the start times of units, we'll try to announce in advance on the Slack #general channel.

Day 1 (Wednesday May 26):

1. (8 am - 8:45 am) Introduction to NIMBLE: Basic concepts and workflows
2. (9 am - 10 am) Working with NIMBLE models and converting from WinBUGS/JAGS
3. (10:30 am - 11:45 pm) Comparing and customizing MCMC methods in NIMBLE
4. (12 pm - 1 pm) Strategies for improving MCMC

Day 2 (Thursday May 27):

5. (8 am - 9 am) Writing your own functions and distributions
6. (9:15 am - 10:00 am) The basics of programming algorithms in NIMBLE
7. (10:30 pm - 1 pm with a 15 minute break) Spatial modeling

Day 3 (Friday May 28):

8. (8 am - 9:30 am) Model selection and Bayesian nonparametrics
9. (9:45 am - 1 pm with breaks) Special topics breakouts
   • (a) Ecological models
   • (b) Programming in NIMBLE, including writing your own MCMC sampler and calling out to R and C++

Our user manual is here.

We have a 'cheatsheet' here.

For those of you who are not already familiar with writing models in WinBUGS, JAGS, or NIMBLE, you may want to look through the first module (Introduction to NIMBLE) or Section 5.2 of our user manual in advance.

We're happy to answer questions about writing models as we proceed through the workshop, but if you have no experience with it, reviewing in advance will greatly lessen the odds you feel lost right at the beginning.

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 [email protected] directly if you can't get things going.

In general we encourage you to update to the most recent version of NIMBLE, 0.11.0.

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")

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", "coda"))

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

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

Windows users will probably need to use this invocation:

library(remotes)
install_github("nimble-dev/compareMCMCs", subdir = "compareMCMCs", INSTALL_opts = "--no-multiarch")

Attendees to the ecological modeling session (9a) should install nimbleEcology and nimbleSCR to run relevant code:

install.packages(c("nimbleEcology", "nimbleSCR"))