articlePeerJ Computer ScienceSep 1, 2023GOLD OA

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

Boston University · Google (United States) · +12 more institutions

PubMed
Indexed incrossrefdoajpubmed

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, allowing it to be compiled into a variety of computational backends, such as C, JAX, and Numba, which in turn offer access to different computational architectures including CPU, GPU, and TPU. Being a general modeling framework, PyMC supports a variety of models including generalized hierarchical linear regression and classification, time series, ordinary differential equations (ODEs), and non-parametric models such as…

Citation impact

765
total citations
FWCI
92.97
Percentile
100%
References
67
Citations per year

Authors

14

Topics & keywords

Keywords
  • Computer science
  • Python (programming language)
  • Probabilistic logic
  • Programming language
  • Syntax
  • Theoretical computer science
  • Statistical model
  • Variety (cybernetics)
UN Sustainable Development Goals
  • Life in Land
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