Statistical Rethinking is an incredible good introductory book to Bayesian Statistics, its follows a Jaynesian and practical approach with very good examples and clear explanations.
In this repository we ported the codes (originally in R and Stan) in the book to PyMC3. We are trying to keep the examples as close as possible to those in the book, while at the same time trying to express them in the most Pythonic and PyMC3onic way we can.
View Jupyter notebooks in nbviewer
All contributions are welcome!
Feel free to send PR to fix errors, improve the code or made comments that could help the user of this repository and readers of the book.
You can also join the discussion on Gitter
To install the dependencies to run these notebooks, you can use Anaconda. Once you have installed Anaconda, run:
conda env create -f environment.yml
to install all the dependencies into an isolated environment. You can switch to this environment by running:
source activate stat-rethink-pymc3
Statistical Rethinking with Python and PyMC3 by All Contributors is licensed under a Creative Commons Attribution 4.0 International License.
