elfi | ELFI - Engine for Likelihood-Free Inference | Analytics library

elfi is a Python library typically used in Analytics applications. elfi has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

[DOI] . ELFI is a statistical software package written in Python 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. ELFI features an easy to use generative modeling syntax and supports parallelized inference out of the box. Currently implemented LFI methods: - ABC Rejection sampler - Sequential Monte Carlo ABC sampler - SMC-ABC sampler with [adaptive threshold selection] - SMC-ABC sampler with [adaptive distance] - [Bayesian Optimization for Likelihood-Free Inference (BOLFI)] - [Robust Optimisation Monte Carlo (ROMC)] - [Bayesian Optimization for Likelihood-Free Inference by Ratio Estimation (BOLFIRE)] Other notable included algorithms and methods: - Bayesian Optimization - [No-U-Turn-Sampler] a Hamiltonian Monte Carlo MCMC sampler. ELFI also integrates tools for visualization, model comparison, diagnostics and post-processing. See examples under [notebooks] to get started. Full documentation can be found at Limited user-support may be asked from elfi-support.at.hiit.fi, but the [Gitter chat] is preferable.