A dynamic nested sampling package for computing Bayesian posteriors and evidences.
Project description
dynesty
A Dynamic Nested Sampling package for computing Bayesian posteriors and evidences. Pure Python. MIT license.
Documentation
Documentation can be found here.
Installation
The most stable release of dynesty can be installed
through pip via
pip install dynesty
The current (less stable) development version can be installed by running
python setup.py install
from inside the repository.
Demos
Several Jupyter notebooks that demonstrate most of the available features of the code can be found here.
Attribution
Please cite Speagle (2019) if you find the package useful in your research, along with any relevant papers on the citations page.
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