Beyond the Border - Kernel Density Estimation for Urban Geography R package btb version 0.2.2 The kernelSmoothing() 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. The first call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth) for a classical kernel smoothing and automatic grid. The second call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth, quantiles) for a geographically weighted median and automatic grid. The third call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth, centroids) for a classical kernel smoothing and user grid. The fourth call mode is kernelSmoothing(obs, epsg, cellsize, bandwidth, quantiles, centroids) for a geographically weighted median and user grid. Geographically weighted summary statistics : a framework for localised exploratory data analysis, C.Brunsdon & al., in Computers, Environment and Urban Systems C.Brunsdon & al. (2002) <doi:10.1016/S0198-9715(01)00009-6>, Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition, Diggle, pp. 83-86, (2003) <doi:10.1080/13658816.2014.937718>. Software Depends: R (>= 3.3.0), dplyr, mapsf Imports: methods, Rcpp (>= 1.0.9), sf, RcppParallel, magrittr LinkingTo: Rcpp, RcppParallel, BH (>= 1.60.0-1), RcppArmadillo Suggests: knitr, rmarkdown, testthat (>= 3.0.0), Solène Colin <solene.colin@insee.fr> Comprehensive R Archive Network (CRAN) Arlindo Dos Santos [aut], François Sémécurbe [aut], Julien Pramil [aut], Solène Colin [cre, ctb], Kim Antunez [ctb], Auriane Renaud [ctb], Farida Marouchi [ctb], Joachim Timotéo [ctb], Institut national de la statistique et des études économiques [cph] GPL (>= 2) 2026-01-20 application/tgz https://CRAN.R-project.org/package=btb doi:10.32614/CRAN.package.btb