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
-
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 | 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.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for inference_tools-0.9.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | a300ef8749fdb6c456dacdd24c23c240dcc9b1092c95cf444f00fcd5251b8e21 |
|
MD5 | f4ed1fd58c02ee1e210e7307d9d57bbf |
|
BLAKE2b-256 | 807d27eb9adeb0fc4d461df520b808aec030206cf83c8b7bcdd87a557784d472 |