Distributed, likelihood-free ABC-SMC inference


Keywords
likelihood-free, inference, abc, approximate, bayesian, computation, sge, distributed, approximate-bayesian-inference, likelihood-free-inference, parameter-inference
License
BSD-3-Clause
Install
pip install pyabc==0.10.13

Documentation

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Massively parallel, distributed and scalable ABC-SMC (Approximate Bayesian Computation - Sequential Monte Carlo) for parameter estimation of complex stochastic models. Provides numerous state-of-the-art algorithms for efficient, accurate, robust likelihood-free inference, described in the documentation and illustrated in example notebooks. Written in Python with support for especially R and Julia.