{"id":24775656,"url":"https://github.com/inseefr/btb","last_synced_at":"2025-10-12T00:31:25.410Z","repository":{"id":42128477,"uuid":"407196026","full_name":"InseeFr/btb","owner":"InseeFr","description":"An R package which provides functions dedicated to urban analysis and kernel density estimation.","archived":false,"fork":false,"pushed_at":"2025-03-17T10:17:22.000Z","size":5756,"stargazers_count":16,"open_issues_count":2,"forks_count":8,"subscribers_count":5,"default_branch":"main","last_synced_at":"2025-09-22T05:23:51.456Z","etag":null,"topics":["statistical-package"],"latest_commit_sha":null,"homepage":"https://inseefr.github.io/btb","language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/InseeFr.png","metadata":{"files":{"readme":"README.md","changelog":"NEWS.md","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":"2021-09-16T14:27:15.000Z","updated_at":"2025-04-09T10:19:24.000Z","dependencies_parsed_at":"2025-03-13T13:45:20.690Z","dependency_job_id":null,"html_url":"https://github.com/InseeFr/btb","commit_stats":null,"previous_names":[],"tags_count":8,"template":false,"template_full_name":null,"purl":"pkg:github/InseeFr/btb","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/InseeFr%2Fbtb","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/InseeFr%2Fbtb/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/InseeFr%2Fbtb/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/InseeFr%2Fbtb/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/InseeFr","download_url":"https://codeload.github.com/InseeFr/btb/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/InseeFr%2Fbtb/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279009509,"owners_count":26084609,"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","status":"online","status_checked_at":"2025-10-11T02:00:06.511Z","response_time":55,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":["statistical-package"],"created_at":"2025-01-29T06:55:10.343Z","updated_at":"2025-10-12T00:31:25.405Z","avatar_url":"https://github.com/InseeFr.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Beyond the Border \u003cimg src=\"man/figures/logo.png\" width=200 align=\"right\" /\u003e\n\n\u003c!-- badges: start --\u003e\n  [![R-CMD-check](https://github.com/InseeFr/btb/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/InseeFr/btb/actions/workflows/R-CMD-check.yaml)\n  \u003c!-- badges: end --\u003e\n\n[![CRAN_Status](http://www.r-pkg.org/badges/version/btb)](https://cran.r-project.org/package=btb)\n\n`btb` (\"Beyond the Border - Kernel Density Estimation for Urban Geography\") is an R package which provides functions dedicated to urban analysis and density estimation using the KDE (kernel density estimator) method. \n\nA partial transposition of the package in Python is also available: [btbpy](https://github.com/InseeFrLab/btbpy).\n\n## Description\n\n\nThe `btb_smooth()` function allows you to square and smooth geolocated data. It calculates a classical kernel smoothing (conservative) or a geographically weighted median. There are four major call modes of the function. \n\n- The first call mode is `btb_smooth(obs, epsg, cellsize, bandwidth)` for a classical kernel smoothing and automatic grid.\n- The second call mode is `btb_smooth(obs, epsg, cellsize, bandwidth, quantiles)` for a geographically weighted median and automatic grid.\n- The third call mode is `btb_smooth(obs, epsg, cellsize, bandwidth, centroids)` for a classical kernel smoothing and user grid.\n- The fourth call mode is `btb_smooth(obs, epsg, cellsize, bandwidth, quantiles, centroids)` for a geographically weighted median and user grid.\n\n## Installation\n\n`btb` is available on CRAN and can therefore be readily installed\n```\ninstall.packages(\"btb\")\n```\n\nTo get a bug fix or to use a feature from the development version, you can install the development version of from GitHub :\n\n```\ninstall.packages(\"devtools\")\ndevtools::install_github(\"InseeFr/btb\")\n```\n\n## Usage \n\nDetails on how to use the package can be found in its [documentation](man). Some applications for spatial smoothing are presented in [chapter 8](https://www.insee.fr/en/statistiques/fichier/3635545/imet131-l-chapitre-8.pdf) of the [Handbook of Spatial Analysis](https://www.insee.fr/en/information/3635545) published by Insee. You advise you to start by consulting the [vignette](https://inseefr.github.io/btb/articles/btb.html) of the package\n\n## Contributions\n\nMaintainer: Solène Colin \u003csolene.colin@insee.fr\u003e\n\nCreators, authors and contributors: \n\n- Arlindo DOS SANTOS [aut],\n- François SEMECURBE [aut],\n- Julien PRAMIL [aut]\n- Solène COLIN [cre, ctb],\n- Kim ANTUNEZ [ctb],\n- Auriane RENAUD [ctb],\n- Farida MAROUCHI [ctb]\n- Joachim TIMOTEO [ctb]\n\n\n## References\n\n- Geographically weighted summary statistics : a framework for localised exploratory data analysis, C.Brunsdon \u0026 al., in Computers, Environment and Urban Systems C.Brunsdon \u0026 al. (2002) [doi:10.1016/S0198-9715(01)00009-6](https://doi.org/10.1016/S0198-9715(01)00009-6) \n- Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition, Diggle, pp. 83-86, (2003) [doi:10.1080/13658816.2014.937718](https://doi.org/10.1080/13658816.2014.937718).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finseefr%2Fbtb","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Finseefr%2Fbtb","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Finseefr%2Fbtb/lists"}