Distributed, likelihood-free ABC-SMC inference
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.
- Documentation: https://pyabc.readthedocs.io
- Contact: https://pyabc.readthedocs.io/en/latest/about.html
- Source: https://github.com/icb-dcm/pyabc
- Bug reports: https://github.com/icb-dcm/pyabc/issues
Release history Release notifications | RSS feed
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size pyabc-0.10.0-py3-none-any.whl (156.7 kB)||File type Wheel||Python version py3||Upload date||Hashes View|