Skip to main content

PyPI pyversions PyPI version Downloads Documentation Status

Nonparametric Inference on Dose-Response Curve and its Derivative

This package implements the proposed integral estimator and a localized derivative estimator for estimating the covariate-adjusted regression function (or the dose-response curve in causal inference) and its derivative. We also document all the code for simulations and real-world case study in our paper here.

Installation guide

npDoseResponse requires Python 3.8+ (earlier version might be applicable) and NumPy. 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.

Metadata

Release files for npDoseResponse 0.0.10

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for npDoseResponse 0.0.10
File Size Uploaded
npdoseresponse-0.0.10.tar.gz 19.2 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for npDoseResponse 0.0.10
File Interpreter ABI Platform
npDoseResponse-0.0.10-py3-none-any.whl Python 3 none any Details

Total release size: 41.9 kB

Release files / npdoseresponse-0.0.10.tar.gz

Download URL npdoseresponse-0.0.10.tar.gz
Size 19.2 kB
Tags Source
SHA-256 checksum
How to use checksums
71f066ac97d51a0137805d7c9fc476ddfb38b11da8d8be7ad0d68c7edc985a1f
BLAKE2b-256 checksum
How to use checksums
c09fde9266ef15d5b1061235167978d76e9b7f0f4a63e380bf8d8940a9cb9df6
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.0.1 CPython/3.10.12

Release files / npDoseResponse-0.0.10-py3-none-any.whl

Download URL npDoseResponse-0.0.10-py3-none-any.whl
Size 22.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
e4fb83aa6d6fb4f7acc1512733a1a07f464518199a34c08843206cb7f7507e92
BLAKE2b-256 checksum
How to use checksums
f2a8f8bf7a8b92effc71e61a56c68ee66e53659659b984f2fe8db1a0edd65850
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.0.1 CPython/3.10.12

Release history Release notifications | RSS feed

This release

0.0.10 This release

2 release files

0.0.9

2 release files

0.0.8

2 release files

0.0.7

2 release files

0.0.6

2 release files

0.0.5

2 release files

0.0.4

2 release files

0.0.3

2 release files

0.0.2

2 release files

0.0.1

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page