# pymc-examples

**Repository Path**: mirrors_pymc-devs/pymc-examples

## Basic Information

- **Project Name**: pymc-examples
- **Description**: Examples of PyMC models, including a library of Jupyter notebooks.
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 1
- **Created**: 2020-12-16
- **Last Updated**: 2026-01-24

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

.. image:: https://cdn.rawgit.com/pymc-devs/pymc/main/docs/logos/svg/PyMC_banner.svg
    :height: 100px
    :alt: PyMC logo
    :align: center

PyMC Examples
==============

Supporting examples and tutorials for PyMC, the Python package for Bayesian 
statistical modeling and Probabilistic Machine Learning!

Check out the 
`getting started guide <https://www.pymc.io/projects/docs/en/latest/learn.html>`__,
or interact with live examples using Binder! 
Each notebook in 
`PyMC examples gallery <https://www.pymc.io/projects/examples/en/latest/gallery.html>`__ 
has a binder badge.
For questions on PyMC, head on over to our 
`PyMC Discourse <https://discourse.pymc.io/>`__ forum.


Contributing
============

If you are interested in contributing to the example notebooks hosted here, 
please read the
`contributing guide <https://github.com/pymc-devs/pymc-examples/blob/main/CONTRIBUTING.md>`__
Also read our 
`Code of Conduct <https://github.com/pymc-devs/pymc-examples/blob/main/CODE_OF_CONDUCT.md>`__ 
guidelines for a better contributing experience.


Contact
=======

We are using `discourse.pymc.io <https://discourse.pymc.io/>`__ as our main 
communication channel. You can also follow us on 
`Twitter @pymc_devs <https://twitter.com/pymc_devs>`__ 
for updates and other announcements.

To ask a question regarding modeling or usage of PyMC we encourage posting to 
our Discourse forum under the 
`“Questions” Category <https://discourse.pymc.io/c/questions>`__. 
You can also suggest feature in the 
`“Development” Category <https://discourse.pymc.io/c/development>`__.

To report an issue, please use the following:

-  `PyMC Examples - Issue Tracker <https://github.com/pymc-devs/pymc-examples/issues>`__. 
   For issues about the example notebooks, errors in the example codes, outdated 
   information, improvement suggestions...
-  `PyMC - Issue Tracker <https://github.com/pymc-devs/pymc/issues>`__. For 
   issues, bugs or feature requests related to the PyMC library itself.

Finally, if you need to get in touch for non-technical information about the 
project, `send us an e-mail <pymc.devs@gmail.com>`__.


Getting started
===============

If you already know about Bayesian statistics:
----------------------------------------------


-  `API quickstart guide <https://www.pymc.io/projects/examples/en/latest/howto/api_quickstart.html>`__
-  The `PyMC tutorial <https://www.pymc.io/projects/docs/en/stable/learn/core_notebooks/pymc_overview.html>`__
-  `PyMC examples <https://www.pymc.io/projects/examples/en/latest/gallery.html>`__ 
   and the `API reference <https://www.pymc.io/projects/docs/en/stable/api.html>`__

Learn Bayesian statistics with a book together with PyMC:
----------------------------------------------------------

-  `Probabilistic Programming and Bayesian Methods for Hackers <https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers>`__ 
   by Cameron Davidson-Pilon: Fantastic book with many applied code examples.
-  `Doing Bayesian Data Analysis <https://github.com/aloctavodia/Doing_bayesian_data_analysis>`__ 
   by John Kruschke, as well as the `second edition <https://github.com/JWarmenhoven/DBDA-python>`__: 
   Principled introduction to Bayesian data analysis.
-  `Statistical Rethinking: A Bayesian Course with Examples in R and Stan <https://github.com/pymc-devs/resources/tree/master/Rethinking>`__ 
   by Richard McElreath: Comprehensive text on modeling choices and interpretations.
-  `Bayesian Cognitive Modeling <https://github.com/pymc-devs/resources/tree/master/BCM>`__ 
   by Michael Lee and EJ Wagenmakers: Focused on using Bayesian statistics in cognitive modeling.
-  `Bayesian Analysis with Python <https://www.packtpub.com/big-data-and-business-intelligence/bayesian-analysis-python-second-edition>`__ 
   (second edition) by Osvaldo Martin: Great introductory book. 
   (`code <https://github.com/aloctavodia/BAP>`__ and errata).

PyMC talks
-----------

There are also several talks on PyMC which are gathered in this 
`YouTube playlist <https://www.youtube.com/playlist?list=PL1Ma_1DBbE82OVW8Fz_6Ts1oOeyOAiovy>`__
and as part of `PyMCon 2020 <https://discourse.pymc.io/c/pymcon/2020talks/15>`__

Installation
------------

To install PyMC on your system, see its 
`installation section here <https://www.pymc.io/projects/docs/en/stable/installation.html>`__

Citing PyMC
============

* To cite the PyMC software, use:

  Salvatier J., Wiecki T.V., Fonnesbeck C. (2016) Probabilistic programming
  in Python using PyMC3. PeerJ Computer Science 2:e55
  `DOI: 10.7717/peerj-cs.55 <https://doi.org/10.7717/peerj-cs.55>`__.

* To cite specific guides from this collection, use |zenodo|. You'll find page specific
  citation instructions at the bottom of each page.

Papers citing PyMC
-------------------

See `Google Scholar <https://scholar.google.de/scholar?oi=bibs&hl=en&authuser=1&cites=6936955228135731011>`__ 
for a continuously updated list.


Support
=======

PyMC is a non-profit project under NumFOCUS umbrella. If you want to support 
PyMC financially, you can donate 
`here <https://numfocus.salsalabs.org/donate-to-pymc3/index.html>`__.


Sponsors
========

|NumFOCUS|

|PyMCLabs|

.. |zenodo| image:: https://zenodo.org/badge/321449673.svg
   :target: https://zenodo.org/badge/latestdoi/321449673
.. |NumFOCUS| image:: https://www.numfocus.org/wp-content/uploads/2017/03/1457562110.png
   :target: http://www.numfocus.org/
.. |PyMCLabs| image:: https://raw.githubusercontent.com/pymc-devs/pymc/main/docs/logos/sponsors/pymc-labs.png
   :target: https://pymc-labs.io