Overview
Alec L. Robitaille
Introduction
Learning bayesian data analysis with the Statistical Rethinking textbook and online lectures. The original version followed the 2019 lectures, and I am in the progress of working through the 2022 lectures and associated homework with the statistical rethinking colearning 2022 group.
Approach
For Chapters 1-4, I use quap
from the rethinking
package, following
along with the book and solutions. For Chapters 5-10, I use cmdstanr
and
stantargets
to benefit from the incredible targets
package. All wrapped
up with bookdown
. Thanks to Richard McElreath for the book and providing
lectures available online. And thanks to all the package and Stan developers.
See the full references for all packages.
Links
- Course: https://github.com/rmcelreath/statrethinking_winter2019
-
targets
: https://books.ropensci.org/targets/ -
cmdstanr
: https://mc-stan.org/cmdstanr/ -
stantargets
: https://docs.ropensci.org/stantargets/ -
bookdown
: https://bookdown.org/home/
Adaptations
Stan+R: https://vincentarelbundock.github.io/rethinking2/
tidy+rethinking: https://david-salazar.github.io/2020/04/19/statistical-rethinking-week-1/
brms+tidy: https://bookdown.org/content/4857/
Julia+Turing: https://github.com/StatisticalRethinkingJulia/TuringModels.jl