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Distributed, likelihood-free ABC-SMC inference

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Massively parallel, distributed and scalable ABC-SMC (Approximate Bayesian Computation - Sequential Monte Carlo) for parameter estimation of complex stochastic models. Implemented in Python with support of the R language.


Many examples are available as Jupyter Notebooks in the examples directory and also for download and for online inspection in the example section of the documentation.

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