Tabular Data Suppression using Gaussian Elimination

A statistical disclosure control tool to protect tables by suppression using the Gaussian elimination secondary suppression algorithm (Langsrud, 2024) . A suggestion is to start by working with functions SuppressSmallCounts() and SuppressDominantCells(). These functions use primary suppression functions for the minimum frequency rule and the dominance rule, respectively. Novel functionality for targeted attribute disclosure protection is also included. See Langsrud (2026) and references therein. General primary suppression functions can be supplied as input to the general working horse function, GaussSuppressionFromData(). Suppressed frequencies can be replaced by synthetic decimal numbers as described in Langsrud (2019) . This approach can also be used as a flexible tool for suppression of post-published tabular data (Langsrud and Bøvelstad, 2022) .


Reference manual

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install.packages("GaussSuppression")

1.3.2 by Øyvind Langsrud, a day ago


https://github.com/statisticsnorway/ssb-gausssuppression, https://statisticsnorway.github.io/ssb-gausssuppression/


Report a bug at https://github.com/statisticsnorway/ssb-gausssuppression/issues


Browse source code at https://github.com/cran/GaussSuppression


Authors: Øyvind Langsrud [aut, cre] (ORCID: , Daniel Lupp [aut] , Hege Bøvelstad [ctb] , Vidar Norstein Klungre [rev] (ORCID: , Jonas Lindblad [ctb] , Statistics Norway [cph]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports SSBtools, RegSDC, stats, methods, utils, Matrix, ellipsis, rlang

Suggests formattable, kableExtra, knitr, rmarkdown, testthat, lpSolve, Rsymphony, Rglpk, slam, highs, data.table


See at CRAN