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distributions 2.0.22

Primitives for Bayesian MCMC inference

Latest Version: 2.2.1

# Distributions [![Build Status](]( [![Code Quality](]( [![Latest Version](](

Distributions provides low-level primitives for Bayesian MCMC inference in Python and C++ including:

  • special numerical functions,
  • samplers and density functions from a variety of distributions,
  • conjugate component models (e.g., gamma-Poisson, normal-inverse-chi-squared),
  • clustering models (e.g., CRP, Pitman-Yor), and
  • efficient wrappers for mixture models.

Distributions powered a machine-learning-as-a-service for Prior Knowledge Inc., and now powers machine learning infrastructure at

## Installation

distributions with pip:

pip install distributions

For help with other builds, see [the installation documentation](

## Documentation

The official documentation lives at

Branch-specific documentation lives at

  • [Overview](/doc/overview.rst)
  • [Installation](/doc/installation.rst)

## Authors (alphabetically)

## License

Copyright (c) 2014, Inc. All rights reserved.

Licensed under the Revised BSD License. See [LICENSE.txt](LICENSE.txt) for details.

File Type Py Version Uploaded on Size
distributions-2.0.22.tar.gz (md5) Source 2014-08-12 12MB