imclab / kcbo

A Bayesian testing framework written in Python.

kcbo

A Bayesian testing framework written in Python.

KCBO Philosophy

The goal of KCBO is to provide an easy to use, Bayesian framework to the masses. We feel that the Bayesian philosophy is an incredibly powerful one which will yield insightful and intuitive results.

The Bayesian philosophy and framework provide an excellent structure for both asking and answering questions. Bayesian testing allows us to answer questions in a more intuitive way than traditional NHST's do – instead of answering questions in terms of fail to reject or fail to accept, we answer questions as the most probable answer given the data we've observed.

Researchers and analysts don't want to spend hours reading academic papers and finding which conjugate priors they need, which type of sampler their MCMC should have, or when to use MC or MCMC.

The world is ready for a good, clean, and easy to use Bayesian framework. The goal of KCBO is to provide that framework.