https://github.com/jordandeklerk/sieve

Python package for penalized sieve estimation in tensor product spaces for non-parametric regression and classification estimation.
https://github.com/jordandeklerk/sieve

classification-models high-dimensional-statistics multivariate-regression nonparametric-regression nonparametric-statistics penalized-regression sieve tensor-product

Last synced: 8 months ago
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Python package for penalized sieve estimation in tensor product spaces for non-parametric regression and classification estimation.

• Host: GitHub
• URL: https://github.com/jordandeklerk/sieve
• Owner: jordandeklerk
• License: mit
• Created: 2025-05-22T23:28:06.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2025-06-18T13:23:01.000Z (12 months ago)
• Last Synced: 2025-07-03T17:50:06.327Z (11 months ago)
• Topics: classification-models, high-dimensional-statistics, multivariate-regression, nonparametric-regression, nonparametric-statistics, penalized-regression, sieve, tensor-product
• Language: Python
• Homepage:
• Size: 160 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Changelog: CHANGELOG.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

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__sieve__ is a Python package for non-parametric regression using the method of sieves in multivariate tensor product spaces. It implements both least-squares and L1-penalized sieve estimators through orthogonal basis expansions, offering computational efficiency and strong statistical properties for general reproducing kernel Hilbert spaces.




> [!WARNING]

> This package is currently in active development.

## Citation

```bibtex

@article{zhang2022sieve,

  title={Regression in Tensor Product Spaces by the Method of Sieves},

  author={Zhang, Tianyu and Simon, Noah},

  journal={arXiv preprint arXiv:2206.02994},

  year={2022}

}

```