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A collection of python tools for Bayesian data analysis

Project description

inference-tools

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.

Features

  • 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

Installation

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

pip install inference-tools

Documentation

Full documentation is available at inference-tools.readthedocs.io.

Project details


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