# -------------------------------------------- # CITATION file created with {cffr} R package # See also: https://docs.ropensci.org/cffr/ # -------------------------------------------- cff-version: 1.2.0 message: 'To cite package "btb" in publications use:' type: software license: GPL-2.0-or-later title: 'btb: Beyond the Border - Kernel Density Estimation for Urban Geography' version: 0.2.0 doi: 10.32614/CRAN.package.btb abstract: '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) , Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition, Diggle, pp. 83-86, (2003) .' authors: - family-names: Dos Santos given-names: Arlindo - family-names: Sémécurbe given-names: François - family-names: Pramil given-names: Julien - family-names: Antunez given-names: Kim email: antuki.kim+cran@gmail.com repository: https://cranhaven.r-universe.dev repository-code: https://github.com/InseeFr/btb commit: 0728caafe66e1bf2f1f4f544dbeff10ccd95757e url: https://inseefr.github.io/btb/ date-released: '2022-10-24' contact: - family-names: Antunez given-names: Kim email: antuki.kim+cran@gmail.com