PyMC: a modern, and comprehensive probabilistic programming framework in Python

Abril, Oriol; Andreani, Virgile; Carroll, Colin; Dong, Larry; Fonnesbeck, Christopher; Kochurov, Maxim; Kumar, Ravin; Lao, Junpeng; C. Luhmann, Christian; A. Martin, Osvaldo; Osthege, Michael; Vieira, Ricardo; V. Wiecki, Thomas; Zinkov, Robert

doi:10.7717/peerj-cs.1516

Public

PyMC: a modern, and comprehensive probabilistic programming framework in Python

Published in PeerJ Computer Science • Sep 1, 2023

Authors:

Oriol Abril

Virgile Andreani

Colin Carroll

Abstract

PyMC is a probabilistic programming library for Python that provides tools for constructing and fitting Bayesian models. It offers an intuitive, readable syntax that is close to the natural syntax statisticians use to describe models. PyMC leverages the symbolic computation library PyTensor, allowin...

Subject

Computer science

Python (programming language)

Probabilistic logic

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