Probabilistic programming in Python using PyMC3
Published in PeerJ Inc. • Apr 1, 2016
Authors:,,
John Salvatier
Thomas V. Wiecki
Christopher Fonnesbeck
Abstract
Probabilistic programming allows for automatic Bayesian inference on user-defined probabilistic models. Recent advances in Markov chain Monte Carlo (MCMC) sampling allow inference on increasingly complex models. This class of MCMC, known as Hamiltonian Monte Carlo, requires gradient information whic...
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