A Bayesian data analysis library in Python
Project description
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.*
The Bayesian philosophy and framework provide an excellent structure for both asking and answering questions. Bayesian statistics allow us to ask questions in a more natural manner and derive incredibly powerful solutions.
Researchers and analysts shouldn't 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. Software should take care of that computing and researchers should take care of producing insights.
The world is ready for a good, clean, and easy to use Bayesian framework. The goal of KCBO is to provide that framework.
====
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.*
The Bayesian philosophy and framework provide an excellent structure for both asking and answering questions. Bayesian statistics allow us to ask questions in a more natural manner and derive incredibly powerful solutions.
Researchers and analysts shouldn't 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. Software should take care of that computing and researchers should take care of producing insights.
The world is ready for a good, clean, and easy to use Bayesian framework. The goal of KCBO is to provide that framework.
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