Overview

I am a fan of the book Statistical Rethinking, so I port the codes of its second edition to NumPyro. I hope that the book and this translation will be helpful not only for NumPyro/Pyro users but also for ones who are willing to do Bayesian statistics in Python.

Contents

• Preface

• Chapter 1. The Golem of Prague

• Chapter 2. Small Worlds and Large Worlds

• Chapter 3. Sampling the Imaginary

• Chapter 4. Geocentric Models

• Chapter 5. The Many Variables & The Spurious Waffles

• Chapter 6. The Haunted DAG & The Causal Terror

• Chapter 7. Ulysses’ Compass

• Chapter 8. Conditional Manatees

• Chapter 9. Markov Chain Monte Carlo

• Chapter 10. Big Entropy and the Generalized Linear Model

• Chapter 11. God Spiked the Integers

• Chapter 12. Monsters and Mixtures

• Chapter 13. Models With Memory

• Chapter 14. Adventures in Covariance

• Chapter 15. Missing Data and Other Opportunities

• Chapter 16. Generalized Linear Madness

• Chapter 17. Horoscopes

Installation

Data and notebooks can be found at my github repository.

The following tools are used for some analysis and visualizations: arviz for posteriors, causalgraphicalmodels and daft for causal graphs, and (optional) ete3 for phylogenetic trees.

pip install numpyro arviz causalgraphicalmodels daft