SpatialKDE: Kernel Density Estimation for Spatial Data

Calculate Kernel Density Estimation (KDE) for spatial data. The algorithm is inspired by the tool 'Heatmap' from 'QGIS'. The method is described by: Hart, T., Zandbergen, P. (2014) <doi:10.1108/PIJPSM-04-2013-0039>, Nelson, T. A., Boots, B. (2008) <doi:10.1111/j.0906-7590.2008.05548.x>, Chainey, S., Tompson, L., Uhlig, S.(2008) <doi:10.1057/palgrave.sj.8350066>.

Version: 0.5.0
Imports: Rcpp, sf, dplyr, glue, magrittr, rlang, methods, raster
LinkingTo: Rcpp
Suggests: tmap, sp, knitr, testthat (≥ 2.1.0)
Published: 2019-12-16
Author: Jan Caha ORCID iD [aut, cre]
Maintainer: Jan Caha <jan.caha at outlook.com>
License: MIT + file LICENSE
URL: https://jancaha.github.io/SpatialKDE/index.html, https://github.com/JanCaha/SpatialKDE
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: SpatialKDE results

Downloads:

Reference manual: SpatialKDE.pdf
Vignettes: SpatialKDE quickstart
Package source: SpatialKDE_0.5.0.tar.gz
Windows binaries: r-devel: SpatialKDE_0.5.0.zip, r-devel-gcc8: SpatialKDE_0.5.0.zip, r-release: SpatialKDE_0.5.0.zip, r-oldrel: SpatialKDE_0.5.0.zip
OS X binaries: r-release: SpatialKDE_0.5.0.tgz, r-oldrel: SpatialKDE_0.5.0.tgz

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