For this week's workshop we have Ian Laga presenting on RStan. Ian says "It is the easiest and best way to do Bayesian computing!"

Before the workshop, please install RStan on your computer. You should be using an R version at least 3.4.0 or later, and it's best to use RStudio version 1.2 or later. RStan is slightly different than more common packages because it relies on running C++ code, which requires Rcpp and Rtools. These should be installed automatically if you are using RStudio though.

Install RStan using:

install.packages("rstan", repos = "https://cloud.r-project.org/", dependencies = TRUE)

This should install dependencies, including Rtools (if you are using Rstudio). If it does not install Rtools, you can install this directly via https://cran.r-project.org/bin/windows/Rtools/history.html

There are known problems with running rstan on Catalina OS for Macs, so if you are running Catalina, sometimes you might have errors. Hopefully this is fixed soon. For more detailed (and slightly different) instructions, you can follow this GitHub link:

https://github.com/stan-dev/rstan/wiki/RStan-Getting-Started