{"id":32203830,"url":"https://github.com/mpascariu/ungroup","last_synced_at":"2026-02-19T08:35:38.646Z","repository":{"id":49102839,"uuid":"114939659","full_name":"mpascariu/ungroup","owner":"mpascariu","description":"Estimating Smooth Distributions from Coarsely Binned Data - R Package","archived":false,"fork":false,"pushed_at":"2024-01-29T15:00:30.000Z","size":8246,"stargazers_count":16,"open_issues_count":3,"forks_count":10,"subscribers_count":2,"default_branch":"master","last_synced_at":"2026-02-01T12:40:35.008Z","etag":null,"topics":["distributions","glm","smoothing","ungrouping"],"latest_commit_sha":null,"homepage":"","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/mpascariu.png","metadata":{"files":{"readme":"README.md","changelog":"NEWS","contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":"CODE_OF_CONDUCT.md","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":"2017-12-20T23:12:30.000Z","updated_at":"2025-09-11T02:03:45.000Z","dependencies_parsed_at":"2025-04-14T17:32:23.749Z","dependency_job_id":null,"html_url":"https://github.com/mpascariu/ungroup","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/mpascariu/ungroup","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mpascariu%2Fungroup","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mpascariu%2Fungroup/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mpascariu%2Fungroup/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mpascariu%2Fungroup/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mpascariu","download_url":"https://codeload.github.com/mpascariu/ungroup/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mpascariu%2Fungroup/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29541119,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-17T08:11:05.436Z","status":"ssl_error","status_checked_at":"2026-02-17T08:09:38.860Z","response_time":100,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":["distributions","glm","smoothing","ungrouping"],"created_at":"2025-10-22T04:46:24.967Z","updated_at":"2026-02-19T08:35:38.640Z","avatar_url":"https://github.com/mpascariu.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"# \u003cimg src=\"inst/figures/ungroup_logo.png\" align=\"right\" width=\"150\" height=\"150\" /\u003e Penalized Composite Link Model for Efficient Estimation of Smooth Distributions from Coarsely Binned Data \n[![CRAN_Version](https://www.r-pkg.org/badges/version/ungroup)](https://cran.r-project.org/package=ungroup)\n[![codecov](https://codecov.io/github/mpascariu/ungroup/branch/master/graphs/badge.svg)](https://app.codecov.io/github/mpascariu/ungroup)\n[![issues](https://img.shields.io/github/issues-raw/mpascariu/ungroup.svg)](https://github.com/mpascariu/ungroup/issues)\n[![DOI](http://joss.theoj.org/papers/10.21105/joss.00937/status.svg)](https://doi.org/10.21105/joss.00937)\n\n[![lifecycle](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://lifecycle.r-lib.org/articles/stages.html)\n[![license](https://img.shields.io/badge/License-GPL%20v3-blue.svg)](https://github.com/mpascariu/ungroup/blob/master/LICENSE)\n[![CRAN_Download_Badge1](https://cranlogs.r-pkg.org/badges/grand-total/ungroup)](https://CRAN.R-project.org/package=ungroup)\n[![CRAN_Download_Badge2](https://cranlogs.r-pkg.org/badges/ungroup)](https://CRAN.R-project.org/package=ungroup)\n\nThis repository contains a versatile method for ungrouping histograms (binned count data) assuming that counts are Poisson distributed and that the underlying sequence on a fine grid to be estimated is smooth. The method is based on the composite link model and estimation is achieved by maximizing a penalized likelihood. Smooth detailed sequences of counts and rates are so estimated from the binned counts. Ungrouping binned data can be desirable for many reasons: Bins can be too coarse to allow for accurate analysis; comparisons can be hindered when different grouping approaches are used in different histograms; and the last interval is often wide and open-ended and, thus, covers a lot of information in the tail area. Age-at-death distributions grouped in age classes and abridged life tables are examples of binned data. Because of modest assumptions, the approach is suitable for many demographic and epidemiological applications. For a detailed description of the method and applications see Rizzi et al. (2015).\n\n## Installation\n\n1. Make sure you have the most recent version of R\n2. Run the following code in your R console \n\n   ```R\n   install.packages(\"ungroup\")\n   ```\n\n## Updating to the latest version of `ungroup` package\n\nYou can track (and contribute to) the development of `ungroup` at https://github.com/mpascariu/ungroup. To install it:\n\n1. Install the release version of `devtools` from CRAN with `install.packages(\"devtools\")`.\n\n2. Make sure you have a working development environment.\n    * **Windows**: Install [Rtools](https://CRAN.R-project.org/bin/windows/Rtools/).\n    * **Mac**: Install `Xcode` from the Mac App Store.\n    * **Linux**: Install a compiler and various development libraries (details vary across different flavours of Linux).\n\n3. Install the development version of `ungroup`.\n\n   ```R\n   devtools::install_github(\"mpascariu/ungroup\")\n   ```\n\n## Intro\nGet started with `ungroup` by checking the vignette\n ```R\n browseVignettes(package = \"ungroup\") \n ```\n\n## Contributing\nThis software is an academic project. We welcome any issues and pull requests.\n* If `ungroup` is malfunctioning, please report the case by submitting an issue on GitHub.\n* If you wish to contribute, please submit a pull request following the guidelines in [CONTRIBUTING.md](https://github.com/mpascariu/ungroup/blob/master/CONTRIBUTING.md).\n\n\n## References\nRizzi S, Gampe J and Eilers PHC. 2015. [Efficient Estimation of Smooth Distributions From Coarsely Grouped Data.](https://doi.org/10.1093/aje/kwv020) American Journal of Epidemiology, Volume 182, Issue 2, Pages 138-147.\n\nEilers PHC. 2007. [Ill-posed problems with counts, the composite link model and penalized likelihood.](https://doi.org/10.1177/1471082X0700700302) Statistical Modelling, Volume 7, Issue 3, Pages 239-254.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmpascariu%2Fungroup","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmpascariu%2Fungroup","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmpascariu%2Fungroup/lists"}