causal-hub: A Package for Causal Data Science

A package for Causal Data Science.

Table of Contents

• Overview
• Documentation
• Changelog
• Contributing
• Citation
• License
• Versioning

Overview

Causal inference is the process of identifying and estimating the causal effect of a given treatment for a chosen outcome. To formally describe the relationship between a cause and its effect, a causal model must be constructed from the available data and the experts' prior knowledge in a process called causal discovery. This library is intended to collect, organize and exploit state of the art methodology to enable causal data science.

To use this software, run the following cargo command in your project directory:

cargo add causal-hub

Or add the following lines to your Cargo.toml:

[dependencies]
causal-hub = "^0.1"

Documentation

The official documentation is available here.

Changelog

All notable changes to this project will be documented in the CHANGELOG.

Contributing

To contribute to this software refer to CONTRIBUTING.

Citation

To cite this software refer to CITATION or click on Cite this repository in the GitHub repository. Read more.

License

This software is distributed under the terms of both the Apache License (Version 2.0) and the MIT license.

See LICENSE-APACHE and LICENSE-MIT for details.

Versioning

This software follows the SemVer specification.