{"id":19015885,"url":"https://github.com/o-laurent/multivariate-ks-test","last_synced_at":"2025-07-03T05:01:43.842Z","repository":{"id":185108996,"uuid":"673011032","full_name":"o-laurent/multivariate-ks-test","owner":"o-laurent","description":"Python implementation of an extension of the Kolmogorov-Smirnov test for multivariate samples","archived":false,"fork":false,"pushed_at":"2023-08-06T09:01:11.000Z","size":9,"stargazers_count":12,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-07T06:42:21.058Z","etag":null,"topics":["kolmogorov-smirnov","kolmogorov-smirnov-tests","multivariate","python","statistical-tests"],"latest_commit_sha":null,"homepage":"","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/o-laurent.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-07-31T17:01:19.000Z","updated_at":"2025-01-23T10:42:09.000Z","dependencies_parsed_at":"2024-11-08T19:51:47.995Z","dependency_job_id":null,"html_url":"https://github.com/o-laurent/multivariate-ks-test","commit_stats":null,"previous_names":["o-laurent/multivariate-ks-test"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/o-laurent/multivariate-ks-test","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/o-laurent%2Fmultivariate-ks-test","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/o-laurent%2Fmultivariate-ks-test/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/o-laurent%2Fmultivariate-ks-test/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/o-laurent%2Fmultivariate-ks-test/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/o-laurent","download_url":"https://codeload.github.com/o-laurent/multivariate-ks-test/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/o-laurent%2Fmultivariate-ks-test/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":263264641,"owners_count":23439246,"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":["kolmogorov-smirnov","kolmogorov-smirnov-tests","multivariate","python","statistical-tests"],"created_at":"2024-11-08T19:40:05.587Z","updated_at":"2025-07-03T05:01:42.455Z","avatar_url":"https://github.com/o-laurent.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Multivariate extension of the Kolmogorov-Smirnov test\n\nThis repository implements the extension of the KS test proposed by Michael Naaman in \n[On the tight constant in the multivariate Dvoretzky–Kiefer–Wolfowitz inequality](https://www.sciencedirect.com/science/article/pii/S016771522100050X/pdf)\nin the one and two-sample cases.\n\nThis package was translated from the original MATLAB code provided by the author.\n\nPlease feel free to open an issue if you have any problems or questions.\n\n## Installation\n\nClone the repository and install it with pip:\n\n```bash\n\ncd multivariate-ks-test \u0026\u0026 pip install .\n```\n\nPlease raise an issue if you want to install it from PyPI.\n\n## Usage example\n\n```python\nimport numpy as np\n\nfrom mks_test import mkstest\n\n# Generate two samples from a 5D Normal distribution\nn = 100\nd = 5\nmu = np.zeros(d)\nsigma = np.eye(d)\nX = np.random.multivariate_normal(mu, sigma, n)\nY = np.random.multivariate_normal(mu, sigma, n)\n\n# Compute the test statistic\nmkstest(X, Y, alpha=0.05, verbose=True)\n# returns False - you can't reject that the two samples are drawn from the same distribution\n```\n\n## Reference\n\nIf you find this code useful, you may cite the following paper:\n\n```latex\n@article{naaman2021tight,\n  title={On the tight constant in the multivariate Dvoretzky--Kiefer--Wolfowitz inequality},\n  author={Naaman, Michael},\n  journal={Statistics \\\u0026 Probability Letters},\n  year={2021},\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fo-laurent%2Fmultivariate-ks-test","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fo-laurent%2Fmultivariate-ks-test","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fo-laurent%2Fmultivariate-ks-test/lists"}