Posted by Chris Fonnesbeck on behalf of the PyMC development team This week featured the release of PyMC 3.7, which includes a slew of bug fixes and enhancements to help make building and fitting Bayesian models easier and more robust than ever. …

Posted by Chris Fonnesbeck on behalf of the PyMC development team The PyMC development team is proud to announce the release of version 3.5 today. This version features several usability enhancements, so we recommend this update to all users. The implementation of parallel sampling has been refactored to be more…

PyMC3 is an open-source library for Bayesian statistical modeling and inference in Python, implementing gradient-based Markov chain Monte Carlo, variational inference, and other approximation methods. These algorithms currently rely on Theano for computation, specifically for providing gradients. Posted by Chris Fonnesbeck on behalf of the PyMC development team Since the…