sdcSpatial: Statistical Disclosure Control for Spatial Data

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 ORCID iD [aut, cre], Peter-Paul de Wolf [aut], Sapphire Han [ctb]
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
CRAN checks: sdcSpatial results

Downloads:

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
OS X binaries: r-release: sdcSpatial_0.1.1.tgz, r-oldrel: not available
Old sources: sdcSpatial archive

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