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https://github.com/fehiepsi/rethinking-numpyro
Statistical Rethinking (2nd ed.) with NumPyro
https://github.com/fehiepsi/rethinking-numpyro
bayesian-statistics causal-inference laplace-approximation markov-chain-monte-carlo numpy python variational-inference
Last synced: about 7 hours ago
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Statistical Rethinking (2nd ed.) with NumPyro
- Host: GitHub
- URL: https://github.com/fehiepsi/rethinking-numpyro
- Owner: fehiepsi
- License: mit
- Created: 2019-10-27T06:24:25.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2024-02-16T11:55:46.000Z (12 months ago)
- Last Synced: 2025-01-25T14:08:49.569Z (7 days ago)
- Topics: bayesian-statistics, causal-inference, laplace-approximation, markov-chain-monte-carlo, numpy, python, variational-inference
- Language: Jupyter Notebook
- Homepage: https://fehiepsi.github.io/rethinking-numpyro/
- Size: 160 MB
- Stars: 450
- Watchers: 13
- Forks: 75
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
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# Statistical Rethinking (2nd ed.) with NumPyro
I am a fan of the book [*Statistical Rethinking*](https://xcelab.net/rm/statistical-rethinking/), so I port the codes of [its second edition](https://github.com/rmcelreath/rethinking) to [NumPyro](https://github.com/pyro-ppl/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.
## How to read the notebooks
+ Read on the site: https://fehiepsi.github.io/rethinking-numpyro/
+ Use GitHub's renderer: https://github.com/fehiepsi/rethinking-numpyro/tree/master/notebooks/
+ Use Jupyter's nbviewer: https://nbviewer.jupyter.org/github/fehiepsi/rethinking-numpyro/tree/master/notebooks/
## Installation
The following tools are used for some analysis and visualizations: [arviz](https://arviz-devs.github.io/arviz/) for [posteriors](https://en.wikipedia.org/wiki/Posterior_probability), [networkx](https://networkx.org/) and [daft](https://docs.daft-pgm.org/en/latest/) for [causal graphs](https://en.wikipedia.org/wiki/Causal_graph), and (optional) [ete3](http://etetoolkit.org/) for [phylogenetic trees](https://en.wikipedia.org/wiki/Phylogenetic_tree).
```sh
pip install numpyro arviz daft networkx
```
## Excercises
If you need help solving the exercises with numpyro, there are resolutions from chapter 2 and 3 [here](https://github.com/felipeffm/statistical-rethinking-resolutions).
## Acknowledgements
[Kapil Sachdeva](https://github.com/ksachdeva) and [Manuel A. Vázquez](https://github.com/manuvazquez) has helped fix many code and plot mismatches since the release. Many thanks!