The first two chapters of the 2nd edition of this book are available as a PDF for free. The rest of the book I used the first edition as it is available through my schools library.
This book is an introduction to Bayesian statistics, focussing on providing an applicable education in R. This repository contains my notes; these notes are not a thorough recapitulation of the book, but instead acting as a combination of a reference and a playground for myself.
These notes have been compiled into a simple static website for ease of reference and searching.
This course includes an R packages called ‘rethinking’](). It can be installed as follows.
# Dependencies
install.packages(c("coda", "mvtnorm", "devtools", "loo", "dagitty"))
# Course package
devtools::install_github("rmcelreath/rethinking")Chapter 1. The Golem of Prague
Chapter 2. Small Worlds and Large Worlds
Chapter 3. Sampling the Imaginary
Chapter 5. Multivariate Linear Models
Chapter 6. Overfitting, Regularization, and Information Criteria
Chapter 8. Markov Chain Monte Carlo
Chapter 9. Big Entropy and the Generalized Linear Model
Chapter 10. Counting and Classification
Chapter 11. Monsters and Mixtures
Chapter 13. Adventures in Covariance
Chapter 14. Missing Data and Other Opportunities
Below are some of the common packages for using Baysian statistics in R. The purpose of this collection is to serve as a reference for future work. As I work through their vignettes (and possible other associated tutorals/articles), the markdown files will be linked below.
‘bayetestR’ (part of the ‘easystats’ suite of packages)