Installation of brms/stan packages

This installation instruction shows you how to install brms/stan packages in R version 4.0.1.

Start R with required dependencies

Within a terminal in a VNC session, do

$ module load R/4.0.1
$ module load jdk

Check if the gcc compiler is pointed to /opt/gcc/7.2.0/bin/gcc:

$ which gcc
/opt/gcc/7.2.0/bin/gcc

If you prefer using R in a text console, submit an interactive job with more than 4GB memory, e.g.

$ qsub -I -l walltime=1:00:00,mem=4gb

once the job is started, run R in the terminal.

If you prefer using rstudio, simply type rstudio in the terminal and use the dialog to set the job requirement, submit the job and wait for the rstudio window to pop up.

Install rstan/brms

Once you are in a R session (either in the console or in rstudio), run the following three R commands to install rstan/brms and their dependencies:

> install.packages("V8", dependencies = TRUE)
> install.packages("rstan", dependencies = TRUE)
> install.packages("brms", dependencies = TRUE)

Test installation

With a successful installation, you should be able to load the rstan package by running

> library(rstan)

It is recommended that you also test with the simple Eight Schools example from the rstan wiki. You could follow the instruction at this link, or use the simplified instruction below:

In a VNC session, open a terminal and run the commands below to download the R script and data:

$ cd
$ wget https://github.com/Donders-Institute/hpc-wiki-v2/raw/master/docs/cluster_howto/exercise_R/rstan_eightschools.tgz
$ tar xvzf rstan_eightschools.tgz
$ ls rstan_workspace
rstan_test_eightschools.R  schools.stan

Run rstudio in the terminal with more than 4 GB memory; wait for the rstudio to start.
Within the rstudio, open the R script ~/rstan_workspace/rstan_test_eightschools.R and run it interactively. You sould see the resulting plot in the plots panel of rstudio, like the one below: