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gboehl committed Jul 23, 2024
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**Differential-Independence Mixture Ensemble ("DIME") MCMC sampling for Python**

This is the Python implementation of the DIME sampler proposed in `Ensemble MCMC Sampling for Robust Bayesian Inference <https://gregorboehl.com/live/dime_mcmc_boehl.pdf>`_ *(Gregor Boehl, 2022, SSRN No. 4250395)*. It provides the ``DIMEMove`` as a drop-in replacement for the great `emcee <https://github.com/dfm/emcee>`_ MCMC package.
This is the Python implementation of the DIME sampler proposed in `DIME MCMC: A Swiss Army Knife for Bayesian Inference <https://gregorboehl.com/live/dime_mcmc_boehl.pdf>`_ *(Gregor Boehl, 2022, SSRN No. 4250395)*. It provides the ``DIMEMove`` as a drop-in replacement for the great `emcee <https://github.com/dfm/emcee>`_ MCMC package.

The sampler has a series of advantages over conventional samplers:

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