{"id":23774682,"url":"https://github.com/victoorv/bootstrap_mcmc","last_synced_at":"2026-05-08T17:35:02.722Z","repository":{"id":259240056,"uuid":"876976170","full_name":"VictoorV/Bootstrap_MCMC","owner":"VictoorV","description":"Ce projet estime les paramètres d'un modèle via le maximum de vraisemblance et compare des intervalles de confiance obtenus par bootstrap. Il développe également des outils d'analyse des fréquences de lettres, utilisant un algorithme MCMC pour déchiffrer efficacement un message codé.","archived":false,"fork":false,"pushed_at":"2024-10-22T23:39:57.000Z","size":1294,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-01T06:16:22.739Z","etag":null,"topics":["bootstrap","data-science","language-model","mcmc","monte-carlo-methods","python","r","regression-models","resampling-methods","statistics"],"latest_commit_sha":null,"homepage":"","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/VictoorV.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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":"2024-10-22T21:47:09.000Z","updated_at":"2024-12-26T13:37:24.000Z","dependencies_parsed_at":"2024-10-23T20:06:57.441Z","dependency_job_id":"0fd6da26-1b21-47e6-8597-cb50ff34dd89","html_url":"https://github.com/VictoorV/Bootstrap_MCMC","commit_stats":null,"previous_names":["victoorv/bootstrap_mcmc"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VictoorV%2FBootstrap_MCMC","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VictoorV%2FBootstrap_MCMC/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VictoorV%2FBootstrap_MCMC/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/VictoorV%2FBootstrap_MCMC/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/VictoorV","download_url":"https://codeload.github.com/VictoorV/Bootstrap_MCMC/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239964511,"owners_count":19725952,"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":["bootstrap","data-science","language-model","mcmc","monte-carlo-methods","python","r","regression-models","resampling-methods","statistics"],"created_at":"2025-01-01T06:16:25.409Z","updated_at":"2026-04-04T07:30:20.280Z","avatar_url":"https://github.com/VictoorV.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Bootstrap_MCMC\nLa première partie de projet vise à estimer les paramètres d’un modèle via le maximum de vraisemblance et à construire des intervalles de confiance. Deux approches bootstrap, paramétrique et non paramétrique, sont utilisées pour calculer et comparer les intervalles de confiance et de prédiction, en fonction de la taille de l'échantillon.\nLa deuxième partie de ce projet consiste à développer des outils pour encoder, décoder et analyser les fréquences de lettres dans un corpus. Un algorithme Markov Chain Monte-Carlo a été mis en place pour déchiffrer un message codé de manière efficace.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvictoorv%2Fbootstrap_mcmc","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvictoorv%2Fbootstrap_mcmc","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvictoorv%2Fbootstrap_mcmc/lists"}