Metadata-Version: 2.0
Name: elfi
Version: 0.7
Summary: Modular ABC inference framework for python
Home-page: http://elfi.readthedocs.io
Author: ELFI authors
Author-email: elfi-support@hiit.fi
License: BSD
Description-Content-Type: UNKNOWN
Keywords: abc likelihood-free statistics
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.5
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: BSD License
Requires-Dist: GPy (>=1.0.9)
Requires-Dist: ipyparallel (>=6)
Requires-Dist: matplotlib (>=1.1)
Requires-Dist: networkX (>=1.11,<2.0)
Requires-Dist: numpy (>=1.12.1)
Requires-Dist: scikit-learn (>=0.18.1)
Requires-Dist: scipy (>=0.19)
Requires-Dist: toolz (>=0.8)
Provides-Extra: doc
Requires-Dist: Sphinx; extra == 'doc'
Provides-Extra: graphviz
Requires-Dist: graphviz (>=0.7.1); extra == 'graphviz'

ELFI is a statistical software package for likelihood-free inference (LFI) such as
Approximate Bayesian Computation (ABC_). The term LFI refers to a family of inference
methods that replace the use of the likelihood function with a data generating simulator
function. Other names or related approaches to LFI include simulator-based inference,
approximate Bayesian inference, indirect inference, etc.

ELFI features an easy to use syntax and supports parallelized inference out of the box.

.. _ABC: https://en.wikipedia.org/wiki/Approximate_Bayesian_computation


