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-0.5.3-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 4ea14476543a28d1941040ba15b8e6b0126e26be5fca66251f30693f75c74286 |
|
MD5 | 5eb7a440ac43b19ba1a537f1653682bf |
|
BLAKE2b-256 | cade416e4ba30b353cd36dea2a92391462a14852582f15265403a2cf2dcc2622 |