Univariate-Guided Interaction Modeling
Project description
uniPairs
Univariate–guided interaction modeling in Python.
uniPairs implements procedures for discovering and estimating pairwise interactions in high-dimensional generalized linear models, built on top of the adelie library.
The package provides:
- UniLasso
- Lasso / GLM wrappers over
adelie.grpnetfor Gaussian, binomial and Cox models - UniPairs (one-stage and two-stage) interaction models:
- support for Gaussian, logistic, and Cox regression
Installation
pip install uniPairs
## Citation
If you use this package in your research, please cite:
```bibtex
@article{echarghaoui2025univariate,
title={Univariate-Guided Interaction Modeling},
author={Echarghaoui, Aymen and Tibshirani, Robert},
journal={arXiv preprint arXiv:2512.14413},
year={2025}
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
unipairs-0.1.4.tar.gz
(19.6 kB
view details)
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
unipairs-0.1.4-py3-none-any.whl
(19.1 kB
view details)
File details
Details for the file unipairs-0.1.4.tar.gz.
File metadata
- Download URL: unipairs-0.1.4.tar.gz
- Upload date:
- Size: 19.6 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.10.14
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
eb8fb90f6f436fdd3f134f0cf7361efea5a9771a19874a13aace552139829f04
|
|
| MD5 |
e0b2415a5e2d8611326e8f212c7eedf2
|
|
| BLAKE2b-256 |
990c858019262a6a62c97bc35efc2bc57f9b68da75f21508321809603fb27169
|
File details
Details for the file unipairs-0.1.4-py3-none-any.whl.
File metadata
- Download URL: unipairs-0.1.4-py3-none-any.whl
- Upload date:
- Size: 19.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.10.14
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
20479e43ef30276de17ce338a67b7fa28c8b6dc1058c19a16236519f717f3df2
|
|
| MD5 |
373b8327ec2c173556c6096e270e78ab
|
|
| BLAKE2b-256 |
2087c1d7ee8dfd8904be3d6250bdaad35f7c124645cb46614c4424931a1b907e
|