A collection of python tools for Bayesian data analysis
Project description
inference-tools
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
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Implementations of MCMC algorithms like Gibbs sampling and Hamiltonian Monte-Carlo for sampling from user-defined posterior distributions.
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Density estimation and plotting tools for analysing and visualising inference results.
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Gaussian-process regression and optimisation.
| Gibbs Sampling |
Hamiltonian Monte-Carlo |
Density estimation |
| Matrix plotting |
Highest-density intervals |
GP regression |
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.
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