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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: |
0.5.2 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
raster, methods |
| Suggests: |
testthat, knitr, rmarkdown, sp, sf, FNN |
| Published: |
2022-03-24 |
| DOI: |
10.32614/CRAN.package.sdcSpatial |
| Author: |
Edwin de Jonge 
[aut, cre],
Peter-Paul de Wolf [aut],
Douwe Hut [ctb],
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 |
| Materials: |
NEWS |
| In views: |
OfficialStatistics |
| CRAN checks: |
sdcSpatial results |
Documentation:
Downloads:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=sdcSpatial
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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