Package: sdcSpatial 0.6.0.9000
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>.
Authors:
sdcSpatial_0.6.0.9000.tar.gz
sdcSpatial_0.6.0.9000.zip(r-4.5)sdcSpatial_0.6.0.9000.zip(r-4.4)sdcSpatial_0.6.0.9000.zip(r-4.3)
sdcSpatial_0.6.0.9000.tgz(r-4.4-any)sdcSpatial_0.6.0.9000.tgz(r-4.3-any)
sdcSpatial_0.6.0.9000.tar.gz(r-4.5-noble)sdcSpatial_0.6.0.9000.tar.gz(r-4.4-noble)
sdcSpatial_0.6.0.9000.tgz(r-4.4-emscripten)sdcSpatial_0.6.0.9000.tgz(r-4.3-emscripten)
sdcSpatial.pdf |sdcSpatial.html✨
sdcSpatial/json (API)
NEWS
| # Install 'sdcSpatial' in R: |
| install.packages('sdcSpatial', repos = c('https://edwindj.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/edwindj/sdcspatial/issues
- dwellings - Simulated dwellings data set
- enterprises - Simulated data set with enterprise locations.
Last updated 1 years agofrom:33a6c46054. Checks:OK: 5 NOTE: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 26 2024 |
| R-4.5-win | NOTE | Nov 26 2024 |
| R-4.5-linux | NOTE | Nov 26 2024 |
| R-4.4-win | OK | Nov 26 2024 |
| R-4.4-mac | OK | Nov 26 2024 |
| R-4.3-win | OK | Nov 26 2024 |
| R-4.3-mac | OK | Nov 26 2024 |
Exports:disclosure_riskis_sensitiveis_sensitive_atmask_gridmask_randommask_sensitivemask_voronoimask_weighted_randomplot_sensitiveprotect_neighborhoodprotect_quadtreeprotect_smoothremove_sensitivesdc_rastersensitivity_scoresmooth_raster
