Encoding: UTF-8
Package: btb
Type: Package
Title: Beyond the Border - Kernel Density Estimation for Urban
        Geography
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, 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>.
Version: 0.2.0
License: GPL (>= 2)
Date: 2022-10-24
Imports: methods, Rcpp (>= 1.0.9), sf, RcppParallel, magrittr
Suggests: knitr, rmarkdown, testthat (>= 3.0.0),
Depends: R (>= 3.3.0), dplyr, mapsf
Authors@R: c( 
    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"))
  )
Maintainer: Kim Antunez <antuki.kim+cran@gmail.com>
LinkingTo: Rcpp, RcppParallel, BH (>= 1.60.0-1), RcppArmadillo
LazyData: true
URL: https://github.com/InseeFr/btb, https://inseefr.github.io/btb/
BugReports: https://github.com/InseeFr/btb/issues
RoxygenNote: 7.2.1
Config/testthat/edition: 3
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2022-10-24 13:53:57 UTC; onyxia
Author: Arlindo Dos Santos [aut],
  François Sémécurbe [aut],
  Julien Pramil [aut],
  Kim Antunez [cre, ctb],
  Auriane Renaud [ctb],
  Farida Marouchi [ctb],
  Joachim Timotéo [ctb],
  Institut national de la statistique et des études économiques [cph]
Repository: CRAN
Date/Publication: 2022-10-24 15:25:11 UTC
Built: R 4.2.3; x86_64-w64-mingw32; 2024-04-24 02:27:46 UTC; windows
ExperimentalWindowsRuntime: ucrt
Archs: x64
