Model Comparison In Bayesian Computation
Compa-ABC is a Python package for performing model comparison in Bayesian Computation. It enables you to do Bayesian model comparison between models for which a likelihood function is not available. In contrast to previous approaches that are mainly based on variants of rejection sampling, this is a density estimation method that approximates the posterior over models in parametric form using a mixture-density network.
Clone the repository. Then, in the repository root folder, run
python setup.py install --user
to install all required packages. Alternatively, you install it via pip using
pip install git+https://github.com/williamqzy/compaABC --process-dependency-links
To test whether everything worked out fine, run
nosetests tests/
in the repository root folder.
You find a jupyter notebook in the examples folder presenting the methods on a tractable
example problem: Bayesian model comparison between a Poisson model and a negative binomial model.
More examples will follow soon.