nonlinear-causal 0.1

nonlinear-causal is a Python module for nonlinear causal inference built on top of Two-stage methods.

🧬 nonlinear-causal

nonlinear-causal is a Python module for nonlinear causal inference, including hypothesis testing and confidence interval for causal effect, built on top of two-stage methods.

• GitHub repo: https://github.com/nl-causal/nonlinear-causal

• PyPi: https://pypi.org/project/nl-causal
• Open Source: MIT license

The proposed model is:

• : marginal causal effect from X -> Y;
• : nonlinear causal link;

What We Can Do:

• Estimate and .
• Hypothesis testing (HT) and confidence interval (CI) for marginal causal effect $\beta$.
• Estimate nonlinear causal link .

Installation

Dependencies

nonlinear-causal requires:

Python>=3.8	numpy	pandas	sklearn	scipy	sliced

User installation

Install nonlinear-causal using pip

pip install nl_causal
pip install git+https://github.com/nl-causal/nonlinear-causal

Source code

You can check the latest sources with the command::

git clone https://github.com/nl-causal/nonlinear-causal

Examples and notebooks

• User Guide

• Simulation for HT and CI with standard setup

• Simulation for HT and CI with invalid IVs

• Simulation for HT and CI with categorical IVs

• Real application