{"id":13689013,"url":"https://github.com/vnmabus/dcor","last_synced_at":"2025-04-04T19:11:43.620Z","repository":{"id":37406202,"uuid":"103399569","full_name":"vnmabus/dcor","owner":"vnmabus","description":"Distance correlation and related E-statistics in Python","archived":false,"fork":false,"pushed_at":"2024-08-31T19:11:14.000Z","size":346,"stargazers_count":148,"open_issues_count":16,"forks_count":27,"subscribers_count":5,"default_branch":"develop","last_synced_at":"2025-03-28T18:13:34.147Z","etag":null,"topics":["distance-correlation","python","python2","python3","statistics"],"latest_commit_sha":null,"homepage":"https://dcor.readthedocs.io","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/vnmabus.png","metadata":{"files":{"readme":"README.rst","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2017-09-13T12:53:50.000Z","updated_at":"2025-03-22T10:30:22.000Z","dependencies_parsed_at":"2024-12-01T07:48:47.223Z","dependency_job_id":null,"html_url":"https://github.com/vnmabus/dcor","commit_stats":{"total_commits":269,"total_committers":6,"mean_commits":"44.833333333333336","dds":0.09665427509293678,"last_synced_commit":"d53c4b98b41fa6c4be96315e56df7706b5d3413f"},"previous_names":[],"tags_count":19,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vnmabus%2Fdcor","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vnmabus%2Fdcor/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vnmabus%2Fdcor/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vnmabus%2Fdcor/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/vnmabus","download_url":"https://codeload.github.com/vnmabus/dcor/tar.gz/refs/heads/develop","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247234922,"owners_count":20905854,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["distance-correlation","python","python2","python3","statistics"],"created_at":"2024-08-02T15:01:30.491Z","updated_at":"2025-04-04T19:11:43.597Z","avatar_url":"https://github.com/vnmabus.png","language":"Python","funding_links":[],"categories":["Python"],"sub_categories":[],"readme":"dcor\n====\n\n|tests| |docs| |coverage| |repostatus| |versions| |pypi| |conda| |zenodo|\n\ndcor: distance correlation and energy statistics in Python.\n\nE-statistics are functions of distances between statistical observations\nin metric spaces.\n\nDistance covariance and distance correlation are\ndependency measures between random vectors introduced in [SRB07]_ with\na simple E-statistic estimator.\n\nThis package offers functions for calculating several E-statistics\nsuch as:\n\n- Estimator of the energy distance [SR13]_.\n- Biased and unbiased estimators of distance covariance and\n  distance correlation [SRB07]_.\n- Estimators of the partial distance covariance and partial\n  distance covariance [SR14]_.\n\nIt also provides tests based on these E-statistics:\n\n- Test of homogeneity based on the energy distance.\n- Test of independence based on distance covariance.\n\nInstallation\n============\n\ndcor is on PyPi and can be installed using :code:`pip`:\n\n.. code::\n\n   pip install dcor\n   \nIt is also available for :code:`conda` using the :code:`conda-forge` channel:\n\n.. code::\n\n   conda install -c conda-forge dcor\n   \nPrevious versions of the package were in the :code:`vnmabus` channel. This\nchannel will not be updated with new releases, and users are recommended to\nuse the :code:`conda-forge` channel.\n\nRequirements\n------------\n\ndcor is available in Python 3.8 or above in all operating systems.\nThe package dcor depends on the following libraries:\n\n- numpy\n- numba \u003e= 0.51\n- scipy\n- joblib\n\nCiting dcor\n===========\n\nPlease, if you find this software useful in your work, reference it citing the following paper:\n\n.. code-block::\n  \n  @article{ramos-carreno+torrecilla_2023_dcor,\n    author = {Ramos-Carreño, Carlos and Torrecilla, José L.},\n    doi = {10.1016/j.softx.2023.101326},\n    journal = {SoftwareX},\n    month = {2},\n    title = {{dcor: Distance correlation and energy statistics in Python}},\n    url = {https://www.sciencedirect.com/science/article/pii/S2352711023000225},\n    volume = {22},\n    year = {2023},\n  }\n\nYou can additionally cite the software repository itself using:\n\n.. code-block::\n\n  @misc{ramos-carreno_2022_dcor,\n    author = {Ramos-Carreño, Carlos},\n    doi = {10.5281/zenodo.3468124},\n    month = {3},\n    title = {dcor: distance correlation and energy statistics in Python},\n    url = {https://github.com/vnmabus/dcor},\n    year = {2022}\n  }\n\nIf you want to reference a particular version for reproducibility, check the version-specific DOIs available in Zenodo.\n\nDocumentation\n=============\nThe documentation can be found in https://dcor.readthedocs.io/en/latest/?badge=latest\n\nReferences\n==========\n\n.. [SR13] Gábor J. Székely and Maria L. Rizzo. Energy statistics: a class of\n           statistics based on distances. Journal of Statistical Planning and\n           Inference, 143(8):1249 – 1272, 2013.\n           URL:\n           http://www.sciencedirect.com/science/article/pii/S0378375813000633,\n           doi:10.1016/j.jspi.2013.03.018.\n.. [SR14]  Gábor J. Székely and Maria L. Rizzo. Partial distance correlation\n           with methods for dissimilarities. The Annals of Statistics,\n           42(6):2382–2412, 12 2014.\n           doi:10.1214/14-AOS1255.\n.. [SRB07] Gábor J. Székely, Maria L. Rizzo, and Nail K. Bakirov. Measuring and\n           testing dependence by correlation of distances. The Annals of\n           Statistics, 35(6):2769–2794, 12 2007.\n           doi:10.1214/009053607000000505.\n\n.. |tests| image:: https://github.com/vnmabus/dcor/actions/workflows/main.yml/badge.svg\n    :alt: Tests\n    :scale: 100%\n    :target: https://github.com/vnmabus/dcor/actions/workflows/main.yml\n\n.. |docs| image:: https://readthedocs.org/projects/dcor/badge/?version=latest\n    :alt: Documentation Status\n    :scale: 100%\n    :target: https://dcor.readthedocs.io/en/latest/?badge=latest\n    \n.. |coverage| image:: http://codecov.io/github/vnmabus/dcor/coverage.svg?branch=develop\n    :alt: Coverage Status\n    :scale: 100%\n    :target: https://codecov.io/gh/vnmabus/dcor/branch/develop\n    \n.. |repostatus| image:: https://www.repostatus.org/badges/latest/active.svg\n   :alt: Project Status: Active – The project has reached a stable, usable state and is being actively developed.\n   :target: https://www.repostatus.org/#active\n   \n.. |versions| image:: https://img.shields.io/pypi/pyversions/dcor\n   :alt: PyPI - Python Version\n   :scale: 100%\n    \n.. |pypi| image:: https://badge.fury.io/py/dcor.svg\n    :alt: Pypi version\n    :scale: 100%\n    :target: https://pypi.python.org/pypi/dcor/\n    \n.. |conda| image:: https://img.shields.io/conda/vn/conda-forge/dcor\n    :alt: Available in Conda\n    :scale: 100%\n    :target: https://anaconda.org/conda-forge/dcor\n    \n.. |zenodo| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.3468124.svg\n    :alt: Zenodo DOI\n    :scale: 100%\n    :target: https://doi.org/10.5281/zenodo.3468124","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvnmabus%2Fdcor","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvnmabus%2Fdcor","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvnmabus%2Fdcor/lists"}