We will use the MCMCvis
package
to manipulate and visualize JAGS output. The package
vignette nicely outlines its capabilities.
We will use JAGS (Just Another Gibbs Sampler) and the rjags package for most of our MCMC computations. Detailed instructions for installing them are found in the JAGS Primer. See the link on Day 4 of the course. It is not necessary that you download them before the course, but it will save you a bit of time for the Day 4 session if you do. Don’t worry if you have any problems, just give us a heads up and we will be ready to trouble shoot at the start of the Day 4 lab.
Here are some conventions for statistical notation that you might find helpful.
BayesNSF
We have prepared an R package that contains all the data you will need to complete our lab exercises. The package is part of the course materials that you now have on your local machine. You will need to do an initial install of this package and do periodic updates throughout the course. For both the install and update the commands are the same.
Download the course R package BayeNSF ver. 1.1 to your computer.
Open R or RStudio run the following line of code to install the
BayesNSF
package from source. Remember to change the path
to wherever files you download from the web are saved locally on your
computer.
install.packages("<YOU_SPECIFY_THE_PATH_HERE>/BayesNSF_1.1.tar.gz", repos = NULL, type = "source")
library(BayesNSF)
BayesNSF
type in
R, bu the usual (?BayesNSF) doesn’t work. Instead, go to R studio Help,
click on packages, and click on BayesNSF All material on this website is licensed under GPLv3.