This package aims to provide 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 building Bayesian/probabilistic models - instead it provides tools to characterise arbitrary posterior distributions (given a function which maps model parameters to a log-probability) via MCMC sampling.
This type of 'black-box' functionality allows for inference without the requirement of first implementing the problem within a modelling framework.
Additionally, the package provides tools for analysing and plotting sampling results, as well as implementations of some useful applications of Gaussian processes.
Requests for features/improvements can be made via the issue tracker. If you have questions or are interested in getting involved with the development of this package, please contact me at chris.bowman.physics@gmail.com.
getting_started mcmc distributions pdf gp approx plotting