Skip to main content

Optimization algorithms for solving penalized non-linear least squares problems

Project description

https://zenodo.org/badge/575338202.svg

The Package varprox is designed for solving penalized separable non-linear least squares problems. It extends the standard variable projection method by adding regularization on the non-linear variable. More details can be found in the documentation.

Package features

  • Methods for minimizing separable non-linear least squares problems with penalizations and box constraints on variables.

  • Non linear model fitting in engineering.

  • Applications to the statistical inference for stochastic processes.

Installation from sources

The package source can be downloaded from the repository.

The package can be installed through PYPI with

pip install varprox

Communication to the author

varprox is developed and maintained by Arthur Marmin and Frédéric Richard. For feed-back, contributions, bug reports, contact directly the author, or use the discussion facility.

Licence

varprox is under licence GNU GPL, version 3.

Citation

When using varprox, please cite the papers

  1. Escande, P. and Richard, F. Full inference for the anisotropic fractional Brownian field. Journal of Probability Theory and Mathematical Statistics, 110:13–29, 2024. doi:10.1090/tpms/1204.

  2. Marmin, A. and Richard, F. Varprox: a primal-dual variable projection method for the minimization of penalized separable non-linear least squares. Inverse Problems, 2025. doi:10.1088/1361-6420/ae0e48.

Credits

Varprox is written and maintained by Arthur Marmin and Frederic Richard, Aix-Marseille University, France.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

varprox-1.0.7.tar.gz (25.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

varprox-1.0.7-py3-none-any.whl (25.8 kB view details)

Uploaded Python 3

File details

Details for the file varprox-1.0.7.tar.gz.

File metadata

  • Download URL: varprox-1.0.7.tar.gz
  • Upload date:
  • Size: 25.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.7

File hashes

Hashes for varprox-1.0.7.tar.gz
Algorithm Hash digest
SHA256 91e122124a4f1761daa621cc21517e03de4a9f29e4632b72e1950f2305cd7294
MD5 53ef53218b82bce4a3f299120e7133d2
BLAKE2b-256 819d9c19fccb5c550c4581744792fb0379abfb6cf163c01ba637a2d758875458

See more details on using hashes here.

File details

Details for the file varprox-1.0.7-py3-none-any.whl.

File metadata

  • Download URL: varprox-1.0.7-py3-none-any.whl
  • Upload date:
  • Size: 25.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.7

File hashes

Hashes for varprox-1.0.7-py3-none-any.whl
Algorithm Hash digest
SHA256 2cb3c94ae1ff46b9d1064177185bdf1cd02fd34f1be64b3b47d718fbaf2ec086
MD5 e59374c2f38021365f380108a613c524
BLAKE2b-256 2fa598fb59638af4e079c2c88643227d7589029a390500ebea2411fc313b09e8

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page