PyMC (formerly PyMC3) is a Python package for Bayesian statistical modeling focusing on advanced Markov chain Monte Carlo (MCMC) and variational inference (VI) algorithms. Its flexibility and extensibility make it applicable to a large suite of problems.
Check out the PyMC overview, or one of the many examples! For questions on PyMC, head on over to our PyMC Discourse forum.
x ~ N(0,1)
translates to x = Normal('x',0,1)
To install PyMC on your system, follow the instructions on the installation guide.
Please choose from the following:
We are using discourse.pymc.io as our main communication channel.
To ask a question regarding modeling or usage of PyMC we encourage posting to our Discourse forum under the Questions Category. You can also suggest feature in the Development Category.
You can also follow us on these social media platforms for updates and other announcements:
To report an issue with PyMC please use the issue tracker.
Finally, if you need to get in touch for non-technical information about the project, send us an e-mail.
Please contact us if your software is not listed here.
See Google Scholar for a continuously updated list.
See the GitHub contributor page. Also read our Code of Conduct guidelines for a better contributing experience.
PyMC is a non-profit project under NumFOCUS umbrella. If you want to support PyMC financially, you can donate here.
You can get professional consulting support from PyMC Labs.