{"id":21872184,"url":"https://github.com/ardiad/admit","last_synced_at":"2025-04-15T00:05:01.810Z","repository":{"id":56934114,"uuid":"59887530","full_name":"ArdiaD/AdMit","owner":"ArdiaD","description":"Adaptive Mixture of Student-t distributions","archived":false,"fork":false,"pushed_at":"2022-02-07T23:48:42.000Z","size":5446,"stargazers_count":2,"open_issues_count":0,"forks_count":2,"subscribers_count":3,"default_branch":"master","last_synced_at":"2024-10-28T17:24:18.130Z","etag":null,"topics":["adaptive","distribution","fitting","mcmc","mixture","mixture-model"],"latest_commit_sha":null,"homepage":null,"language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ArdiaD.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"COPYING","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2016-05-28T09:38:49.000Z","updated_at":"2024-04-24T18:13:41.000Z","dependencies_parsed_at":"2022-08-21T00:40:28.067Z","dependency_job_id":null,"html_url":"https://github.com/ArdiaD/AdMit","commit_stats":null,"previous_names":[],"tags_count":2,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ArdiaD%2FAdMit","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ArdiaD%2FAdMit/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ArdiaD%2FAdMit/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ArdiaD%2FAdMit/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ArdiaD","download_url":"https://codeload.github.com/ArdiaD/AdMit/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":226868305,"owners_count":17694895,"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":["adaptive","distribution","fitting","mcmc","mixture","mixture-model"],"created_at":"2024-11-28T06:19:28.548Z","updated_at":"2024-11-28T06:19:29.048Z","avatar_url":"https://github.com/ArdiaD.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# AdMit\n\n`AdMit` ([Ardia et al., 2009a](https://doi.org/10.18637/jss.v029.i03)) is an R package which provides \nflexible functions to approximate a certain target distribution and to efficiently generate a sample of \nrandom draws from it, given only a kernel of the target density function. The core \nalgorithm fits an adaptive mixture of Student-t distributions to the density of interest, and then, \nimportance sampling or the independence chain Metropolis-Hastings algorithm is used to obtain \nquantities of interest for the target density, using the fitted mixture as the importance or \ncandidate density. The estimation procedure is fully automatic and thus avoids the \ntime-consuming and difficult task of tuning a sampling algorithm.\nFull description of the algorithm and numerous applications are available in [Ardia et al. (2009a)](https://doi.org/10.18637/jss.v029.i03) and [Ardia et al. (2009b)](https://doi.org/10.32614/RJ-2009-003).\n\n## Please cite the package in publications!\n\nBy using `AdMit` you agree to the following rules: \n\n1) You must cite [Ardia et al. (2009a)](https://doi.org/10.18637/jss.v029.i03) in working papers and published papers that use `AdMit`.\n2) You must place the following URL in a footnote to help others find `AdMit`: [https://CRAN.R-project.org/package=AdMit](https://CRAN.R-project.org/package=AdMit). \n3) You assume all risk for the use of `AdMit`.\n\nArdia, D., Hoogerheide, L., van Dijk, H.K. (2009a).    \nAdaptive mixture of Student-t distributions as a flexible candidate \ndistribution for efficient simulation: The R package AdMit.    \n_Journal of Statistical Software_, 29(3), 1-32.     \n[https://doi.org/10.18637/jss.v029.i03](https://doi.org/10.18637/jss.v029.i03)  \n\nArdia, D., Hoogerheide, L., van Dijk, H.K. (2009b).    \nAdMit: Adaptive mixture of Student-t distributions.   \n_R Journal_, 1(1), 25-30.     \n[https://doi.org/10.32614/RJ-2009-003](https://doi.org/10.32614/RJ-2009-003)  \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fardiad%2Fadmit","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fardiad%2Fadmit","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fardiad%2Fadmit/lists"}