Skip to main content
Join the official Python Developers Survey 2018 and win valuable prizes: Start the survey!

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.

Project details


Release history Release notifications

This version
History Node

0.0.1

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
kcbo-0.0.1.tar.gz (8.4 kB) Copy SHA256 hash SHA256 Source None Aug 3, 2014

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page