A dynamic nested sampling package for computing Bayesian posteriors and evidences.
Project description
A dynamic nested sampling package for computing Bayesian posteriors and evidences. Pure Python. MIT license. Beta release.
### Documentation Documentation can be found [here](https://dynesty.readthedocs.io). Warning: The documentation is currently somewhat out of date.
### Installation dynesty can be installed through [pip](https://pip.pypa.io/en/stable) via ` pip install dynesty ` It can also 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](https://github.com/joshspeagle/dynesty/tree/master/demos).
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