Privacy protected raster maps can be created from spatial point data. Protection methods include smoothing of dichotomous variables by de Jonge and de Wolf (2016) <doi:10.1007/978-3-319-45381-1_9>, continuous variables by de Wolf and de Jonge (2018) <doi:10.1007/978-3-319-99771-1_23>, suppressing revealing values and a generalization of the quad tree method by Suñé, Rovira, Ibáñez and Farré (2017) <doi:10.2901/EUROSTAT.C2017.001>.
Version: | 0.1.1 |
Depends: | R (≥ 2.10) |
Imports: | raster, methods |
Suggests: | testthat, knitr, rmarkdown, sp, sf |
Published: | 2019-07-19 |
Author: | Edwin de Jonge |
Maintainer: | Edwin de Jonge <edwindjonge at gmail.com> |
BugReports: | https://github.com/edwindj/sdcSpatial/issues |
License: | GPL-2 |
URL: | https://github.com/edwindj/sdcSpatial |
NeedsCompilation: | no |
In views: | OfficialStatistics |
CRAN checks: | sdcSpatial results |
Reference manual: | sdcSpatial.pdf |
Vignettes: |
Introduction sdcSpatial: privacy protected density maps |
Package source: | sdcSpatial_0.1.1.tar.gz |
Windows binaries: | r-devel: sdcSpatial_0.1.1.zip, r-release: sdcSpatial_0.1.1.zip, r-oldrel: sdcSpatial_0.1.1.zip |
macOS binaries: | r-release: sdcSpatial_0.1.1.tgz, r-oldrel: sdcSpatial_0.1.1.tgz |
Old sources: | sdcSpatial archive |
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