Author: Psar Analyse Urbaine Insee - Thierry Cornely, Laure Genebes, Arlindo Dos Santos, Cynthia Faivre, Auriane Renaud and Francois Semecurbe
Maintainer: Arlindo Dos Santos <Arlindo.Dos-Santos@insee.fr>
Description: Kernel density estimation dedicated to urban geography.

Author: Thierry Cornely, Laure Genebes, Arlindo Dos Santos, Cynthia Faivre,
Auriane Renaud, Farida Marouchi and Francois Semecurbe

Author: Psar Analyse Urbaine Insee - Thierry Cornely, Laure Genebes, Arlindo Dos
Santos, Cynthia Faivre, Auriane Renaud and Francois Semecurbe

Imports: methods, Rcpp (>= 0.11.3), sp, sf, RcppParallel
LinkingTo: Rcpp, RcppParallel, BH (>= 1.60.0-1), RcppArmadillo

Title: Beyond the Border - Kernel Density Estimation for Urban
Description: 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, bandwith) for a classical kernel smoothing and automatic grid.
The second call mode is kernelSmoothing(obs, epsg, cellsize, bandwith, quantiles) for a geographically weighted median and automatic grid.
The third call mode is kernelSmoothing(obs, epsg, cellsize, bandwith, centroids) for a classical kernel smoothing and user grid.
The fourth call mode is kernelSmoothing(obs, epsg, cellsize, bandwith, 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>.

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.
Imports: methods, Rcpp (>= 1.0.9), sf, RcppParallel, magrittr
person("Arlindo", "Dos Santos", role = c("aut")),
person("François", "Sémécurbe", role = c("aut")),
person("Julien", "Pramil", role = c("aut")),
person("Kim", "Antunez", role = c("cre", "ctb"), email = "antuki.kim+cran@gmail.com"),
person("Auriane", "Renaud", role = c("ctb")),
person("Farida", "Marouchi", role = c("ctb")),
person("Joachim", "Timotéo", role = c("ctb")),
person("Institut national de la statistique et des études économiques", role = c("cph"))
Institut national de la statistique et des études économiques [cph]