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, 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>.
Version: 0.1.30.3
Depends: R (>= 3.3.0)
Date: 2020-06-03
License: GPL (>= 2)
Imports: methods, Rcpp (>= 0.11.3), sp, sf, RcppParallel
Suggests: cartography
LinkingTo: Rcpp, RcppParallel, BH (>= 1.60.0-1), RcppArmadillo
NeedsCompilation: yes
Packaged: 2020-06-03 15:50:00 UTC; ripley
RoxygenNote: 5.0.1
LazyData: true
Repository: CRAN
Date/Publication: 2020-06-03 14:20:06 UTC
Author: Arlindo Dos Santos [cre],
  Francois Semecurbe [drt, aut],
  Auriane Renaud [ctb],
  Cynthia Faivre [ctb],
  Thierry Cornely [ctb],
  Farida Marouchi [ctb],
  Farida Marouchi [ctb]
Maintainer: Arlindo Dos Santos <Arlindo.Dos-Santos@insee.fr>
Built: R 3.6.3; x86_64-w64-mingw32; 2020-08-05 05:57:56 UTC; windows
Archs: i386, x64
