{"id":22463730,"url":"https://github.com/poissonconsulting/universals","last_synced_at":"2025-08-02T05:32:28.910Z","repository":{"id":37067644,"uuid":"234643049","full_name":"poissonconsulting/universals","owner":"poissonconsulting","description":"An R package of S3 generic methods for Bayesian analyses that generate MCMC samples","archived":false,"fork":false,"pushed_at":"2023-10-24T15:03:24.000Z","size":517,"stargazers_count":4,"open_issues_count":0,"forks_count":1,"subscribers_count":5,"default_branch":"main","last_synced_at":"2024-06-11T17:12:02.672Z","etag":null,"topics":["cran","generics","model-fitting","rstats","s3"],"latest_commit_sha":null,"homepage":"https://poissonconsulting.github.io/universals/","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/poissonconsulting.png","metadata":{"files":{"readme":"README.Rmd","changelog":null,"contributing":".github/CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":".github/CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2020-01-17T21:53:16.000Z","updated_at":"2022-07-27T21:48:36.000Z","dependencies_parsed_at":"2022-06-24T21:40:21.189Z","dependency_job_id":null,"html_url":"https://github.com/poissonconsulting/universals","commit_stats":null,"previous_names":[],"tags_count":13,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/poissonconsulting%2Funiversals","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/poissonconsulting%2Funiversals/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/poissonconsulting%2Funiversals/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/poissonconsulting%2Funiversals/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/poissonconsulting","download_url":"https://codeload.github.com/poissonconsulting/universals/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":228439452,"owners_count":17920026,"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":["cran","generics","model-fitting","rstats","s3"],"created_at":"2024-12-06T09:13:55.350Z","updated_at":"2025-08-02T05:32:28.891Z","avatar_url":"https://github.com/poissonconsulting.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"---\noutput: github_document\n---\n\n\u003c!-- README.md is generated from README.Rmd. Please edit that file --\u003e\n\n```{r, include = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\u003e\",\n  fig.path = \"man/figures/README-\",\n  out.width = \"100%\"\n)\n```\n\n# universals \u003cimg src=\"man/figures/logo.png\" align=\"right\" /\u003e\n\n\u003c!-- badges: start --\u003e\n[![Lifecycle: stable](https://img.shields.io/badge/lifecycle-stable-brightgreen.svg)](https://lifecycle.r-lib.org/articles/stages.html#stable)\n[![R-CMD-check](https://github.com/poissonconsulting/universals/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/poissonconsulting/universals/actions/workflows/R-CMD-check.yaml)\n[![codecov](https://codecov.io/gh/poissonconsulting/universals/branch/main/graph/badge.svg?token=iSrKzkDv8E)](https://app.codecov.io/gh/poissonconsulting/universals)\n[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](https://opensource.org/license/mit/)\n[![CRAN status](https://www.r-pkg.org/badges/version/universals)](https://cran.r-project.org/package=universals)\n![CRAN downloads](https://cranlogs.r-pkg.org/badges/universals)\n\n\u003c!-- badges: end --\u003e\n\n`universals` provides S3 generic methods and some default implementations\nfor Bayesian analyses that generate Markov Chain Monte Carlo (MCMC) samples.\n\nThe purpose of `universals` is to reduce package dependencies and conflicts. \n\n## Philosophy\n\nThe methods are primarily designed to be used for Bayesian analyses that generate Markov Chain Monte Carlo (MCMC) samples but many can also be used for Maximum Likelihood (ML) and other types of analyses.\n\nThe names of the functions are based on the following definitions/concepts:\n\n- A `term` is a single real or integer `value`.\n- A `par` (short for parameter) is a numeric object of terms.\n- An MCMC object is a collection of MCMC samples that refer to a set of terms.\n- The samples are arranged in one or more `chains` of the same length (number of `iterations`).\n- The number of `simulations` is the product of the number of iterations and the number of chains.\n- The number of `samples` is the product of the number of simulations and the number of `terms`.\n\nThe 'nlist' package implements many of the methods for its 'nlists' class.\n\n## Usage\n\n`universals` is designed to be used by package developers.\n\nIt is recommended to import and re-export the generics of interest. For example, to provide a method for the S3 `pars()` method, use the following `roxygen2` code:\n\n``` {r, eval = FALSE}\n#' @importFrom universals pars\n#' @export\nuniversals::pars\n```\n\n## Installation\n\n### Release\n\nTo install the release version from [CRAN](https://CRAN.R-project.org/package=universals).\n```r\ninstall.packages(\"universals\")\n```\n\nThe website for the release version is at \u003chttps://poissonconsulting.github.io/universals/\u003e.\n\n### Development\n\nTo install the development version from [r-universe](https://poissonconsulting.r-universe.dev/universals).\n```r\ninstall.packages(\"universals\", repos = c(\"https://poissonconsulting.r-universe.dev\", \"https://cloud.r-project.org\"))\n```\n\nor from [GitHub](https://github.com/poissonconsulting/universals)\n```r\n# install.packages(\"remotes\")\nremotes::install_github(\"poissonconsulting/universals\")\n```\n\n\n## Inspiration\n\n- [r-lib/generics](https://github.com/r-lib/generics)\n\n## Contribution\n\nPlease report any [issues](https://github.com/poissonconsulting/universals/issues).\n\n[Pull requests](https://github.com/poissonconsulting/universals/pulls) are always welcome.\n\n## Code of Conduct\n\nPlease note that the universals project is released with a [Contributor Code of Conduct](https://contributor-covenant.org/version/2/0/CODE_OF_CONDUCT.html). \nBy contributing to this project, you agree to abide by its terms.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpoissonconsulting%2Funiversals","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpoissonconsulting%2Funiversals","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpoissonconsulting%2Funiversals/lists"}