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Dynamic Nested Sampling package for computing Bayesian posteriors and evidences

Home Page: https://dynesty.readthedocs.io/

License: MIT License

Python 100.00%

dynesty's Introduction

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dynesty

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 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

If you find the package useful in your research, please cite it together with the papers describing the methods (see the documentation)

dynesty's People

Contributors

segasai avatar joshspeagle avatar kbarbary avatar gregoryashton avatar johannesbuchner avatar cscheffler avatar bacook17 avatar colmtalbot avatar guillochon avatar pcubillos avatar aasensio avatar matthieudartiailh avatar ipashchenko avatar dstndstn avatar bd-j avatar jtmendel avatar ejhigson avatar vandalt avatar tdaylan avatar ruthangus avatar ruskin23 avatar pacargile avatar psheehan avatar mattpitkin avatar mjkirk avatar jrleja avatar eteq avatar dannygoldstein avatar dfm avatar cdeil avatar

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