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A dynamic nested sampling package for computing Bayesian posteriors and evidences.

Project description


dynesty in action

A Dynamic Nested Sampling package for computing Bayesian posteriors and evidences. Pure Python. MIT license.


Documentation can be found here.


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 install

from inside the repository.


Several Jupyter notebooks that demonstrate most of the available features of the code can be found here.


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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