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-0.13.2-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 2df0c96cb716462f292e26e8f7f89c9813204d689b176bcf34d9205b79e405ab |
|
MD5 | fdea69b56a36cc0663b33a5bbe400e6c |
|
BLAKE2b-256 | 5aa47d0ea56d63972e5ef855b7702f048d3b4b47fc954fc5fdb2f4eaa93cd82e |