Probabilistic programming in Python using PyMC3

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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Bibliographic Details
Published in:PeerJ Computer Science
Main Authors: John Salvatier, Thomas V. Wiecki, Christopher Fonnesbeck
Format: Article
Language:English
Published: PeerJ Inc. 2016-04-01
Subjects:
Bayesian statistic
Probabilistic Programming
Python
Markov chain Monte Carlo
Statistical modeling
Online Access:https://peerj.com/articles/cs-55.pdf

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https://peerj.com/articles/cs-55.pdf

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