EES 4891-06/5891-01

Tools

Software Tools

This course will use R statistical analysis software. We will use several specialized Bayesian analysis packages written for R

Installing Tools

Installing

  • Download R version 4.5.2 from https://cran.rstudio.com/
    • Windows:
    • MacOS:
    • Linux:
      • You should be able to install R from your Linux distribution’s package manager:
        • sudo apt-get install r-base r-base-dev for Debian or Ubuntu
        • sudo yum install R or sudo dnf install git for Fedora, Red Hat, and related distributions.
        • If you are using Ubuntu, there are advanced instructions for configuring the package management system to use the very latest versions of R and its associated packages at https://cran.rstudio.com/bin/linux/ubuntu/fullREADME.html . This is optional and the default version of R should be fine for this class, as long as it is version 4.5 or higher.
  • If you have a version of R older than 4.5, you should update it to 4.5 or higher.

Installing RStudio

RStudio is a free editing and software development environment that makes it much easier to work with R. I strongly recommend that you install RStudio for this course.

  • Go to the download page for the free desktop edition of RStudio at https://posit.co/download/rstudio-desktop/ and download the installer for your operating system. Windows, MacOS, and the Debian, Ubuntu, Fedora, RedHat, and openSUSE editions of Linux are all supported.

    There are other versions of RStudio (an expensive professional edition and a server edition). You want the free desktop edition. As of January 2026, the latest version is RStudio Desktop version 2025.09.2+418 “Cucumberleaf Sunflower”.

  • Run the installer.

  • After the installer finishes running, run RStudio .

    • When RStudio starts up, the lower left part of the screen should have a window that displays the R version, saying something like this:

      R version 4.5.2 (2025-10-31 ucrt) -- "[Not] Part in a Rumble"    
Copyright (C) 2025 The R Foundation for Statistical 
Computing Platform: x86_64-w64-mingw32/x64

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

  Natural language support but running in an English locale

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

      The details will be different depending on your operating system, but if you see something like this, RStudio correctly found R on your computer.

    • Configuring RStudio for additional optional software. There are a few other pieces of software that you may want to use this semester, but these are not required.

      If have installed the Git revision control system or the typesetting software, you should configure RStudio to use them:

    • If will use Git for software revision control with R, you should open the “Tools” menu, and click on the “Global Options” choice.

      • Go to the “Git/SVN” tab and click “enable version control interface for RStudio projects”. If RStudio can find the git program on your computer, it will appear in the “git executable” field. If RStudio can’t find it, you can help it by browsing to the git program.

    • If you have installed on your computer, click on the SWeave tab, and select “knitr” for weaving .Rnw files, and choose pdfLaTeX for typesetting files into PDF.

R Packages:

After you have R and RStudio installed, you will need to install a number of software packages that extend R for Bayesian data analysis.

  • Cmdstanr

    The trickiest package to install is cmdstanr. I recommend that you follow the detailed installation instructions on the cmdstanr web site.

    After you install cmdstanr, you will need to use it to install the cmdstan software. For this, you will need to install a C++

    compiler and related tools before you can install cmdstan.

    (Don’t worry, you won’t need to do any programming in C++ . Stan writes the C++ code for you, based on your description of the statistical problem.)

    Follow the instructions at the cmdstan web page, https://mc-stan.org/docs/cmdstan-guide/installation.html . There are instructions for installing the C++ toolchain for Windows, MacOS, and Linux. If you are using Windows, the simplest thing to do is install the Rtools4.5 software from the same place you installed R, or from https://cran.rstudio.org/bin/windows/Rtools/rtools45/rtools.html

    After you’ve done this, you can go to the main cmdstanr installation instructions and continue from there.

    The basic steps are to do the following at the R console in RStudio:

    #. First, check whether the C++ toolchain is set up correctly:

    library(cmdstanr)

check_cmdstan_toolchain()

    #. If you get an error message, then run

    check_cmdstan_toolchain(fix = TRUE)

    to fix the toolchain configuration

    #. Next, install cmdstan

    options(mc.cores = parallel::detectCores() / 2 - 1)
install_cmdstan()

    The line beginning options(... is optional. It tells R to use multiple processor cores to install cmdstan, which can speed up the installation considerably if you have a powerful processor in your computer.

    If you run into difficulty, let me know and I will help you.

    If you are having trouble installing cmdstan, don’t worry. We won’t use cmdstan until late in the semester, so go ahead and install the other things, and there will be plenty of time for me to help you get cmdstan installed and working on your computer.

  • Other R packages

    This will be a lot easier. Open RStudio, go to the “Console” window in RStudio, and type

    install.packages(c("devtools", "pacman"))
library(pacman)
for (p in c("tidyverse", "ape", "bayesplot", "brms", 
  "broom", "coda", "dagitty", "flextable", 
  "ggdag", "ggformula", "ggmcmc", "ggrepel",  
  "ggthemes", "knitr", "loo", "mvtnorm", 
  "patchwork", "posterior", "psych", 
  "rcartocolor", "Rcpp", "rmarkdown", 
  "rprojroot", "sf", "shiny", "shinystan",
  "statebins", "tidybayes", "viridis", 
  "viridisLite", "wesanderson")) {
    p_install(p, character.only = TRUE, force = FALSE)
  }
remotes::install_github("rmcelreath/rethinking")
remotes::install_github("mjskay/tidybayes.rethinking")

    Now you should be good to go.

Optional Tools:

Installing the tinytex package

It is optional to install the tinytex package. You will be able to do all the work for the labs without it, but if you do install it, it will give you the option to produce nicely formatted PDF output from your RMarkdown files (for lab reports, presentations, etc.).

The R tinytex package installs a sophisticated typesetting system called LaTeX on your computer. RMarkdown uses this system to generate PDF output.

The tinytex package needs to download a lot of files from the internet, and it can take 10 minutes or more to do so, even on a fast connection. So it’s a good idea to wait until you can let your computer run for a while, and until you’re connected to a good fast internet connection, preferably one that doesn’t charge you for data.

To install tinytex, go to the RStudio console, and you type the following:

install.packages('tinytex')
tinytex::install_tinytex()

If you want to uninstall tinytex later, you can just type this command at the RStudio console:

tinytex::uninstall_tinytex()`

Installing

Git is software for managing revisions as you develop software. You will not need it for this course, but it may be useful if you plan to develop complicated scripts for data analysis in the future.

If you have a Mac or Linux you may already have git installed. Test it by opening up a terminal window and typing which git. If you get a response like /usr/bin/git then it’s installed. If there is no response, then you need to install git.

  • Windows:
    • Download and install git from https://git-scm.com
      • Choose the default options for the installer.
    • Optionally, you might want to also install Tortoise Git, which integrates git into the Windows explorer, so you can execute git commands from the context menu when you right-click on files or directories in the explorer. You can download Tortoise Git from https://tortoisegit.org/
  • MacOS:
    • If git is not already installed on your computer, you can download and install it from https://git-scm.com
  • Linux:
    • If git is not already installed, you can install it from your distribution’s package manager:
      • sudo apt-get install git for Debian or Ubuntu
      • sudo yum install git or sudo dnf install git for Fedora, Red Hat, and related distributions.

Introducing Youself to

Whatever operating system you’re using, after you install git you will need to introduce yourself to git (you only need to do this once). It is important for git to knows your name and email address so it can keep track of who is editing files when you are working collaboratively and so it gives you credit for the files you have authored and edited.

  1. Open a terminal prompt:

    • On Windows, open a “git bash” window (git will give you the option to do this when it finishes installing) or you can do so from the Windows Start menu, under “Git”.
    • On MacOS or Linux, open a regular terminal window (on MacOS, you can use Finder to find the terminal application in the “applications” folder).

  2. Type the following at the terminal prompt:

    git config --global user.name "Your Name"
git config --global user.email your.name@vanderbilt.edu

    using your real name and email.

You only need to introduce yourself to git one time after you install it. Then it will remember who you are every time you use it.

Getting an account on GitHUB

If you will be using Git, you may want to create a free account on the GitHub website. This will allow you to use GitHub to store your work in the cloud, so you can get access it from other computers and have a backup in case your computer dies.

  • Go to https://github.com and register for a free account
  • After you have set up your account, go to GitHub Education and register your account for the free extras you can get as a student.

Resources for Learning More

and RStudio Resources

and GitHUB Resources

  • There is a lot of free documentation about git at the git-scm website, including a full Git reference manual and a free online book, Pro Git
  • Professor Jenny Bryan at the University of British Columbia, has written a lot of helpful tutorial material specifically about using git and GitHub with R and RStudio at Happy Git and GitHub for the useR . tutorial on using Git and GitHub with R and RStudio") at the RStudio Webinars and Videos page . This tutorial walks you through all the steps of setting up git with RStudio and how to use it to keep track of your edits and revisions, and synchronize your work with GitHub (this serves three functions: backing up your data to the cloud, sharing your data with other people, and collaborating on writing code or documents with other people).

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Copyright 2022--2026, Jonathan Gilligan.

Based on ESPM 157, by Carl Boettiger.