Skip to main content

Optimization algorithms for solving penalized non-linear least squares problems

Project description

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.

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-1.0.4.tar.gz (25.5 kB view details)

Uploaded Source

Built Distribution

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

varprox-1.0.4-py3-none-any.whl (25.8 kB view details)

Uploaded Python 3

File details

Details for the file varprox-1.0.4.tar.gz.

File metadata

  • Download URL: varprox-1.0.4.tar.gz
  • Upload date:
  • Size: 25.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.7

File hashes

Hashes for varprox-1.0.4.tar.gz
Algorithm Hash digest
SHA256 f65d1af2c48bf4f0a5920ea55b95e1c58ea63ed8a818a6319376ddd8ac615db2
MD5 03b4f3fc6e96652ffde14b93aa991919
BLAKE2b-256 0bbb6362101bfe70575f5ed309d01bbdd5c2eac9769b17e98504c8aa51060627

See more details on using hashes here.

File details

Details for the file varprox-1.0.4-py3-none-any.whl.

File metadata

  • Download URL: varprox-1.0.4-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-1.0.4-py3-none-any.whl
Algorithm Hash digest
SHA256 ed6131d1e296607f4297d81474cd193e62dc5c241ba3febeae2b694711a5e492
MD5 4d7f648e285cb037aa2b600dff8411c9
BLAKE2b-256 0e7c01029131f57b57056b7387b87d42ae30b6764b3706aecb88014e9f2ec63f

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