https://github.com/zhangyk8/npdoseresponse

Python and R packages for "Nonparametric Inference on Dose-Response Curves Without the Positivity Condition"
https://github.com/zhangyk8/npdoseresponse

derivative-estimation dose-response-function kernel-smoothing nonparametric-bootstrap

Last synced: 6 days ago
JSON representation

Python and R packages for "Nonparametric Inference on Dose-Response Curves Without the Positivity Condition"

• Host: GitHub
• URL: https://github.com/zhangyk8/npdoseresponse
• Owner: zhangyk8
• License: mit
• Created: 2024-05-04T16:39:12.000Z (about 2 years ago)
• Default Branch: main
• Last Pushed: 2026-03-11T17:27:01.000Z (4 months ago)
• Last Synced: 2026-03-11T22:37:14.966Z (4 months ago)
• Topics: derivative-estimation, dose-response-function, kernel-smoothing, nonparametric-bootstrap
• Language: Jupyter Notebook
• Homepage:
• Size: 122 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE
  • Citation: citation.bib

Awesome Lists containing this project

README

          
[![PyPI pyversions](https://img.shields.io/pypi/pyversions/npDoseResponse.svg)](https://pypi.python.org/pypi/npDoseResponse/)

[![PyPI version](https://badge.fury.io/py/npDoseResponse.svg)](https://badge.fury.io/py/NPDoseResponse)

[![Downloads](https://static.pepy.tech/badge/npDoseResponse)](https://pepy.tech/project/npDoseResponse)

[![Documentation Status](https://readthedocs.org/projects/npdoseresponse/badge/?version=latest)](http://npdoseresponse.readthedocs.io/?badge=latest)

# Nonparametric Inference on Dose-Response Curve and its Derivative

This package provides the implementation of estimating and conducting valid inference on the covariate-adjusted regression function (or the dose-response curve in causal inference) and its derivative through the proposed integral estimator and a localized derivative estimator in [[1]](#npdoseresponse). It also implements the regression adjustment (RA), inverse probability weighting (IPW) and doubly robust (DR) estimators of the dose-response curve and its derivative function with and without the positivity condition in [[2]](#npdrderiv). All the code for simulations and real-world applications in our papers are documented in [Paper 1](https://github.com/zhangyk8/NPDoseResponse/tree/main/Paper_Code) and [Paper 2](https://github.com/zhangyk8/npDRDeriv).

* Free software: MIT license

* Python Package Documentation: [https://npdoseresponse.readthedocs.io](https://npdoseresponse.readthedocs.io).

* We also provide an R package [npDoseResponse](https://cran.r-project.org/package=npDoseResponse) for those estimators in [[1]](#npdoseresponse), though the Python package will be numerically stabler.

Installation guide

--------

```npDoseResponse``` requires Python 3.8+ (earlier version might be applicable) and [NumPy](http://www.numpy.org/). To install the latest version of ```npDoseResponse``` from this repository, run:

```

python setup.py install

```

To pip install a stable release, run:

```

pip install npDoseResponse

```

References

--------

[1] Y. Zhang, Y.-C. Chen, and A. Giessing (2024+) Nonparametric Inference on Dose-Response Curves Without the Positivity Condition [arXiv:2405.09003](https://arxiv.org/abs/2405.09003).

[2] Y. Zhang and Y.-C. Chen (2025+) Doubly Robust Inference on Causal Derivative Effects for Continuous Treatments [arXiv:2501.06969](http://arxiv.org/abs/2501.06969).