{"id":13857129,"url":"https://github.com/timothyb0912/pylogit","last_synced_at":"2025-10-21T20:07:44.694Z","repository":{"id":5779122,"uuid":"53904800","full_name":"timothyb0912/pylogit","owner":"timothyb0912","description":"A python package for estimating conditional logit models.","archived":false,"fork":false,"pushed_at":"2022-07-12T12:30:01.000Z","size":2918,"stargazers_count":193,"open_issues_count":31,"forks_count":106,"subscribers_count":14,"default_branch":"master","last_synced_at":"2025-07-01T07:53:47.999Z","etag":null,"topics":["discrete-choice"],"latest_commit_sha":null,"homepage":"https://pypi.org/project/pylogit/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/timothyb0912.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.rst","contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2016-03-15T01:29:46.000Z","updated_at":"2025-04-19T20:28:37.000Z","dependencies_parsed_at":"2022-08-07T02:30:11.842Z","dependency_job_id":null,"html_url":"https://github.com/timothyb0912/pylogit","commit_stats":null,"previous_names":[],"tags_count":7,"template":false,"template_full_name":null,"purl":"pkg:github/timothyb0912/pylogit","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/timothyb0912%2Fpylogit","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/timothyb0912%2Fpylogit/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/timothyb0912%2Fpylogit/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/timothyb0912%2Fpylogit/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/timothyb0912","download_url":"https://codeload.github.com/timothyb0912/pylogit/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/timothyb0912%2Fpylogit/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":265199639,"owners_count":23726691,"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":["discrete-choice"],"created_at":"2024-08-05T03:01:26.886Z","updated_at":"2025-10-21T20:07:39.644Z","avatar_url":"https://github.com/timothyb0912.png","language":"Python","funding_links":[],"categories":["Python"],"sub_categories":[],"readme":"![PyLogit Logo](./images/PyLogit_Final-small-04.png)\n\n![Tests](https://github.com/timothyb0912/pylogit/workflows/Testing/badge.svg)\n\n# PyLogit\nPyLogit is a Python package for performing maximum likelihood estimation of conditional logit models and similar discrete choice models.\n\n## Main Features\n- It supports\n   - Conditional Logit (Type) Models\n     - Multinomial Logit Models\n     - Multinomial Asymmetric Models\n        - Multinomial Clog-log Model\n        - Multinomial Scobit Model\n        - Multinomial Uneven Logit Model\n        - Multinomial Asymmetric Logit Model\n   - Nested Logit Models\n   - Mixed Logit Models (with Normal mixing distributions)\n- It supports datasets where the choice set differs across observations\n- It supports model specifications where the coefficient for a given variable may be\n   - completely alternative-specific   \n   (i.e. one coefficient per alternative, subject to identification of the coefficients),\n   - subset-specific  \n   (i.e. one coefficient per subset of alternatives, where each alternative belongs to only one subset, and there are more than 1 but less than J subsets, where J is the maximum number of available alternatives in the dataset),\n   - completely generic  \n   (i.e. one coefficient across all alternatives).\n\n## Installation\nAvailable from [PyPi](https://pypi.python.org/pypi/pylogit):\n```\npip install pylogit\n```\n\nAvailable through [Anaconda](https://anaconda.org/conda-forge/pylogit):\n```\nconda install -c conda-forge pylogit\n```\n\nor\n\n```\nconda install -c timothyb0912 pylogit\n```\n\n## Usage\nFor Jupyter notebooks filled with examples, see [examples](./examples/).\n\n\n## For More Information\nFor more information about the asymmetric models that can be estimated with PyLogit, see the following paper\n\n\u003e Brathwaite, T., \u0026 Walker, J. L. (2018). Asymmetric, closed-form, finite-parameter models of multinomial choice. Journal of Choice Modelling, 29, 78–112. https://doi.org/10.1016/j.jocm.2018.01.002\n\nA free and better formatted version is available at [ArXiv](http://arxiv.org/abs/1606.05900).\n\n## Attribution\nIf PyLogit (or its constituent models) is useful in your research or work, please cite this package by citing the paper above.\n\n## License\nModified BSD (3-clause). See [here](./LICENSE.txt).\n\n## Changelog\nSee [here](./CHANGELOG.rst).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftimothyb0912%2Fpylogit","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftimothyb0912%2Fpylogit","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftimothyb0912%2Fpylogit/lists"}