approximate bayesian computing with population monte carlo
A Python Approximate Bayesian Computing (ABC) Population Monte Carlo (PMC) implementation based on Sequential Monte Carlo (SMC) with Particle Filtering techniques.
Entirely implemented in Python and easy to extend
Follows Beaumont et al. 2009 PMC algorithm
Parallelized with muliprocessing or message passing interface (MPI)
Extendable with k-nearest neighbour (KNN) or optimal local covariance matrix (OLCM) pertubation kernels (Fillipi et al. 2012)
Detailed examples in IPython notebooks
The full documentation can be generated with Sphinx
- Python 3 support
- Minor fixes
- Improved documentation
- First release
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