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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 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 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](

Project details

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