{"id":17331906,"url":"https://github.com/ocramz/splitmix-distributions","last_synced_at":"2025-07-22T20:34:58.357Z","repository":{"id":56878753,"uuid":"363862549","full_name":"ocramz/splitmix-distributions","owner":"ocramz","description":"Sampling procedures for some common random variables based on splitmix","archived":false,"fork":false,"pushed_at":"2025-02-08T16:36:07.000Z","size":28,"stargazers_count":2,"open_issues_count":1,"forks_count":0,"subscribers_count":2,"default_branch":"master","last_synced_at":"2025-06-18T08:51:03.010Z","etag":null,"topics":["random-generation","random-sampling","splitmix","statistics"],"latest_commit_sha":null,"homepage":"","language":"Haskell","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/ocramz.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":"2021-05-03T08:21:11.000Z","updated_at":"2025-02-08T16:36:11.000Z","dependencies_parsed_at":"2025-04-14T18:05:05.491Z","dependency_job_id":"1f682c0d-f667-4de1-aeb9-8448d450603a","html_url":"https://github.com/ocramz/splitmix-distributions","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/ocramz/splitmix-distributions","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ocramz%2Fsplitmix-distributions","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ocramz%2Fsplitmix-distributions/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ocramz%2Fsplitmix-distributions/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ocramz%2Fsplitmix-distributions/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ocramz","download_url":"https://codeload.github.com/ocramz/splitmix-distributions/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ocramz%2Fsplitmix-distributions/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":265893151,"owners_count":23845120,"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":["random-generation","random-sampling","splitmix","statistics"],"created_at":"2024-10-15T14:56:00.908Z","updated_at":"2025-07-22T20:34:58.309Z","avatar_url":"https://github.com/ocramz.png","language":"Haskell","readme":"# splitmix-distributions\n\n[![Haskell CI](https://github.com/ocramz/splitmix-distributions/actions/workflows/ci.yaml/badge.svg)](https://github.com/ocramz/splitmix-distributions/actions/workflows/ci.yaml)\n\nRandom samplers for some common distributions, as well as a convenient interface for composing them, based on `splitmix`.\n\n\n## Usage\n\nCompose your random sampler out of simpler ones thanks to the Applicative and Monad interface, e.g. this is how you would declare and sample a binary mixture of Gaussian random variables:\n\n\n    import Control.Monad (replicateM)\n    import System.Random.SplitMix.Distributions (Gen, sample, bernoulli, normal)\n\n    process :: Gen Double\n    process = do\n        coin \u003c- bernoulli 0.7\n        if coin\n        then\n            normal 0 2\n        else\n            normal 3 1\n\n    dataset :: [Double]\n    dataset = sample 1234 $ replicateM 20 process\n\n\nand sample your data in a pure (`sample`) or monadic (`sampleT`) setting.\n\n## Implementation details\n\nThe library is built on top of `splitmix`, so the caveats on safety and performance that apply there are relevant here as well.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Focramz%2Fsplitmix-distributions","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Focramz%2Fsplitmix-distributions","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Focramz%2Fsplitmix-distributions/lists"}