Installation

Installing R and RStudio

For this course, you will be using your own computer on which you have installed or updated R (version 4.2.1 for Unix systems and version 4.1.3 for Windows) and the RStudio user interface: https://www.rstudio.com/products/rstudio/.

Installing brms and rstan

We’ll also be using Stan via the brms and rstan packages. You’ll find all the info you need to install brms on your platform here: https://learnb4ss.github.io/learnB4SS/articles/install-brms.html.1

Please note that this step can be quite long and complex, depending on your platform (especially on Windows), so make sure you don’t do it at the last minute, and that everything’s up and running at the start of the course.

Installing imsb

The rest of the packages, along with the data used in the exercises and a few useful functions, can be installed together as a “companion” package to the workshop, the imsb package. To install it, you first need to install the remotes and tidyverse packages, then install imsb from Github.2

install.packages(pkgs = c("remotes", "tidyverse") )
options(timeout = 240) # allowing more time to download the package
remotes::install_github(repo = "lnalborczyk/IMSB2022/_imsb", dependencies = TRUE)

The datasets used during the workshop are contained in this package. You can import them using the function open_data().

library(imsb)
open_data(robot)

Reminder regarding the pre-requisites

Although a good knowledge of R is a pre-requisite for registration, you will find here a short introduction to the basics of the language, which will be necessary to fully understand the examples covered during the course.

Footnotes

  1. In case of problems, see also: https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started.↩︎

  2. Yeah, the imsb acronym comes from the French name of the course I am teaching, hence the loose correspondence with this course’s acronym.↩︎