Skip to main content

A collection of python tools for Bayesian data analysis

Project description


Documentation Status GitHub license PyPI - Downloads PyPI - Python Version DOI

This package provides a set of Python-based tools for Bayesian data analysis which are simple to use, allowing them to applied quickly and easily.

Inference-tools is not a framework for Bayesian modelling (e.g. like PyMC), but instead provides tools to sample from user-defined models using MCMC, and to analyse and visualise the sampling results.


  • Implementations of MCMC algorithms like Gibbs sampling and Hamiltonian Monte-Carlo for sampling from user-defined posterior distributions.

  • Density estimation and plotting tools for analysing and visualising inference results.

  • Gaussian-process regression and optimisation.

Gibbs Sampling 1 Hamiltonian Monte-Carlo 2 Density estimation 3
Matrix plotting 4 Highest-density intervals 5 GP regression 6


inference-tools is available from PyPI, so can be easily installed using pip as follows:

pip install inference-tools


Full documentation is available at

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

inference_tools-0.13.2.tar.gz (7.4 MB view hashes)

Uploaded Source

Built Distribution

inference_tools-0.13.2-py3-none-any.whl (80.6 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page