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:Edwin de Jonge [aut, cre], Peter-Paul de Wolf [aut], Douwe Hut [ctb], Sapphire Han [ctb]

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sdcSpatial/json (API)
NEWS

# Install sdcSpatial in R:
install.packages('sdcSpatial', repos = c('https://edwindj.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/edwindj/sdcspatial/issues

Datasets:

On CRAN:

16 exports 6 stars 1.25 score 5 dependencies 149 downloads

Last updated 7 months agofrom:33a6c46054

Exports:disclosure_riskis_sensitiveis_sensitive_atmask_gridmask_randommask_sensitivemask_voronoimask_weighted_randomplot_sensitiveprotect_neighborhoodprotect_quadtreeprotect_smoothremove_sensitivesdc_rastersensitivity_scoresmooth_raster

Dependencies:latticerasterRcppspterra

Introduction sdcSpatial: privacy protected density maps

Rendered fromsdcSpatial.Rmdusingknitr::rmarkdownon Jun 29 2024.

Last update: 2023-12-13
Started: 2022-03-23