Probabilistic programming allows for flexible specification of Bayesian statistical models in code. PyMC3 is a new, open-source probabilistic programmer framework with an intuitive, readable and concise, yet powerful, syntax that is close to the natural notation statisticians use to describe models. It features next-generation fitting techniques, such as the No U-Turn Sampler, that allow fitting complex models with thousands of parameters without specialized knowledge of fitting algorithms.
PyMC3 has recently seen rapid development. With the addition of two new major features: automatic transforms and missing value imputation, PyMC3 has become ready for wider use. PyMC3 is now refined enough that adding features is easy, so we don't expect adding features in the future will require drastic changes. It has also become user friendly enough for a broader audience. Automatic transformations mean NUTS and find_MAP work with less effort, and friendly error messages mean its easy to diagnose problems with your model.
Thus, Thomas, Chris and I are pleased to announce that PyMC3 is now in Beta.
- Transforms now automatically applied to constrained distributions
- Transforms now specified with a
transform=
argument on Distributions.model.TransformedVar
is gone. - Transparent missing value imputation support added with MaskedArrays or pandas.DataFrame NaNs.
- Bad default values now ignored
- Profile theano functions using
model.profile(model.logpt)
- A. Flaxman [email protected]
- Andrea Zonca [email protected]
- Andreas Klostermann [email protected]
- Andrew Clegg [email protected]
- AustinRochford [email protected]
- Benjamin Edwards [email protected]
- Brian Naughton [email protected]
- Chad Heyne [email protected]
- Chris Fonnesbeck [email protected]
- Corey Farwell [email protected]
- John Salvatier [email protected]
- Karlson Pfannschmidt [email protected]
- Kyle Bishop [email protected]
- Kyle Meyer [email protected]
- Mack Sweeney [email protected]
- Osvaldo Martin [email protected]
- Raymond Roberts [email protected]
- Rodrigo Benenson [email protected]
- Thomas Wiecki [email protected]
- Zach Ploskey [email protected]
- maahnman [email protected]
- paul sorenson [email protected]
- zenourn [email protected]