{"id":15551450,"url":"https://github.com/seatonullberg/kernel-density-estimation","last_synced_at":"2025-04-23T20:14:03.303Z","repository":{"id":61566705,"uuid":"547462841","full_name":"seatonullberg/kernel-density-estimation","owner":"seatonullberg","description":"Kernel density estimation in Rust.","archived":false,"fork":false,"pushed_at":"2024-03-22T20:51:48.000Z","size":238,"stargazers_count":26,"open_issues_count":2,"forks_count":6,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-23T20:13:46.672Z","etag":null,"topics":["kernel-density-estimation","probability-density","statistics"],"latest_commit_sha":null,"homepage":"https://crates.io/crates/kernel-density-estimation","language":"Rust","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/seatonullberg.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","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,"zenodo":null}},"created_at":"2022-10-07T18:20:29.000Z","updated_at":"2025-03-22T10:30:50.000Z","dependencies_parsed_at":"2025-04-17T16:00:41.565Z","dependency_job_id":"dd620db0-286b-4ad7-8183-b641f85fa54e","html_url":"https://github.com/seatonullberg/kernel-density-estimation","commit_stats":{"total_commits":21,"total_committers":1,"mean_commits":21.0,"dds":0.0,"last_synced_commit":"36013d61c9f404672f2494d85cd4d5ce50972187"},"previous_names":[],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/seatonullberg%2Fkernel-density-estimation","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/seatonullberg%2Fkernel-density-estimation/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/seatonullberg%2Fkernel-density-estimation/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/seatonullberg%2Fkernel-density-estimation/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/seatonullberg","download_url":"https://codeload.github.com/seatonullberg/kernel-density-estimation/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":250506141,"owners_count":21441723,"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":["kernel-density-estimation","probability-density","statistics"],"created_at":"2024-10-02T14:05:03.237Z","updated_at":"2025-04-23T20:14:03.286Z","avatar_url":"https://github.com/seatonullberg.png","language":"Rust","funding_links":[],"categories":[],"sub_categories":[],"readme":"# kernel-density-estimation\n![Crates.io](https://img.shields.io/crates/d/kernel-density-estimation)\n![Crates.io](https://img.shields.io/crates/l/kernel-density-estimation)\n![Crates.io](https://img.shields.io/crates/v/kernel-density-estimation)\n\nKernel density estimation in Rust.\n\nKernel density estimation (KDE) is a non-parametric method to estimate the probability\ndensity function of a random variable by taking the summation of kernel functions centered\non each data point. This crate serves three major purposes based on this idea:\n1) Evaluate the probability density function of a random variable.\n2) Evaluate the cumulative distribution function of a random variable.\n3) Sample data points from the probability density function.\n\nAn excellent technical description of the method is available\n[here](https://bookdown.org/egarpor/NP-UC3M/kde-i.html).\n\n__Note:__ Currently only univariate distributions are supported but multivariate is a goal in the future!\n\n## Examples\n\n__[univariate](examples/univariate.rs)__ - This example showcases the core `pdf`, `cdf`, and `sample` functionalities for a univariate distribution.\n```\ncargo run --example univariate\n```\n![Univariate Distribution](assets/univariate.png)\n\n__[kernel](examples/kernel.rs)__ - This example showcases each of the available kernel functions.\n```\ncargo run --example kernel\n```\n![Kernel Functions](assets/kernel.png)\n\n## Roadmap\n\nRefer to the [milestone issues](https://github.com/seatonullberg/kernel-density-estimation/issues) to see the direction the project is headed in future releases or [CHANGELOG.md](./CHANGELOG.md) to see the changes between each release.\n\n## License\n\nDistributed under the MIT License. See [LICENSE](./LICENSE) for more information.\n\n## Acknowledgements\n\n* Notes for Nonparametric Statistics[^citation] - An excellent technical description of nonparametric methods referenced heavily in the development of this project.\n\n[^citation]: García-Portugués, E. (2022). Notes for Nonparametric Statistics.\nVersion 6.5.9. ISBN 978-84-09-29537-1.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fseatonullberg%2Fkernel-density-estimation","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fseatonullberg%2Fkernel-density-estimation","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fseatonullberg%2Fkernel-density-estimation/lists"}