distributions 2.0.6

Primitives for Bayesian MCMC inference

# Distributions [](https://travis-ci.org/forcedotcom/distributions)

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 Salesforce.com.

## Installation

distributions with pip:

pip install distributions

For help with other builds, see [the installation documentation](http://distributions.readthedocs.org/en/latest/installation.html).

## Documentation

The official documentation lives at http://distributions.readthedocs.org/.

Branch-specific documentation lives at

• [Overview](/doc/overview.rst)

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

## Authors (alphabetically)

• Jonathan Glidden <https://twitter.com/jhglidden>

• Eric Jonas <https://twitter.com/stochastician>

• Fritz Obermeyer <https://github.com/fritzo>

• Cap Petschulat <https://github.com/cap>

## License

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

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