https://github.com/nicolossus/pylfi

pyLFI is a Python toolbox using likelihood-free inference (LFI) methods for estimating the posterior distributions of model parameters.
https://github.com/nicolossus/pylfi

bayesian-inference likelihood-free-inference simulation-based-inference

Last synced: 3 months ago
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pyLFI is a Python toolbox using likelihood-free inference (LFI) methods for estimating the posterior distributions of model parameters.

• Host: GitHub
• URL: https://github.com/nicolossus/pylfi
• Owner: nicolossus
• License: mit
• Created: 2021-04-15T00:08:16.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2021-12-04T00:00:00.000Z (over 3 years ago)
• Last Synced: 2025-01-14T01:34:38.566Z (4 months ago)
• Topics: bayesian-inference, likelihood-free-inference, simulation-based-inference
• Language: Python
• Homepage: https://pylfi.readthedocs.io
• Size: 9.31 MB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# pyLFI

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[![GitHub license](https://img.shields.io/github/license/nicolossus/pylfi)](https://github.com/nicolossus/pylfi/blob/pylfi/LICENSE)

`pyLFI` is a Python toolbox for Bayesian parameter estimation in models with intractable likelihood functions. By using *Likelihood-Free Inference* (LFI) schemes, in particular *Approximate Bayesian Computation* (ABC), `pyLFI` estimates the posterior distributions over model parameters.

## Overview

`pyLFI` presently includes the following methods:

* Rejection ABC

* MCMC ABC

* Post-sampling regression adjustment.

`pyLFI` was created as a part of the author's [Master thesis](https://github.com/nicolossus/Master-thesis).

## Installation instructions

### Install with pip

`pyLFI` can be installed directly from [PyPI](https://pypi.org/project/pylfi/):

    $ pip install pylfi

## Requirements

* `Python` >= 3.8

## Documentation

Documentation can be found at [pylfi.readthedocs.io](https://pylfi.readthedocs.io/).

## Getting started

Check out the [Examples gallery](https://pylfi.readthedocs.io/en/latest/auto_examples/index.html) in the documentation.

## Automated build and test

The repository uses continuous integration (CI) workflows to build and test the project directly with GitHub Actions. Tests are provided in the [`tests`](tests) folder. Run tests locally with `pytest`:

    $ python -m pytest tests -v