nonlinear-causal v1.0

I’m thrilled to announce the launch of our newest Python library, "nonlinear-causal v1.0" nonlinear-causal is a Python module for nonlinear causal inference, including hypothesis testing and confidence interval for causal effect, built on top of instrument variables and Two-Stage least squares.

nonlinear-causal primary implements Two-Stage Least Squares (2SLS) and Two-Stage Inverse Regression (2SIR) based on Instrumental Variable (IV) regression.

PS: 2SIR is the method proposed in our paper, which was just accepted in PMLR@CLeaR.

You can access the library via github and find its documentation on doc. We sincerely look forward to your valuable expertise and insights.

Cheer!

nonlinear-causal v0.3

• fix circular import issues
• readthedoc v1 -> v2

nonlinear-causal v0.1

nonlinear-causal - Version 0.1 - Initial Release

We are excited to announce the release of our new software on causal inference, nonlinear-causal Version 1.0

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 (2SLS and 2SIR).

We hope you enjoy using nl_causal! This release is an important step in our journey. As we continue to innovate and improve, we look forward to delivering an enhanced version. Thank you for your support!