Statistical Disclosure Control Methods for Anonymization of Microdata and Risk Estimation

Data from statistical agencies and other institutions are mostly confidential. This package can be used for the generation of anonymized (micro)data, i.e. for the creation of public- and scientific-use files. In addition, various risk estimation methods are included. Note that the package includes a graphical user interface that allows to use various methods of this package.

Readme for R-Package sdcMicro



  • IHSN SDC guidelines as vignette
  • cat. key variables returned as factors in extractManipData


  • show method for sdcMicroObj


  • pram bug fix


  • bug fix mafasts


  • only small bug fixes


  • new IHSN SDC Guidelines included
  • new implementation of freqCalc. Computation time is now linear with data size. Gains a lot of speed for large data sets.
  • localSuppression, measure_risk and createSdcJobj make use of new implementation of freqCalc
  • C++-Level glpk and R-Level Rglpk removed for better compatiblity with Mac
  • configure,cleanup removed and Makevars and rewritten according to Rcpp documentation
  • function microaggrGower added: microaggregation for numerical and categorical variables based on Gower distance
  • completely new report facility (knitr and brew instead of R2HTML), new class 'reportObj' which stores all info for reporting and is generate by calcReportData
  • new slot in class sdcObj for manipPramVars

Reference manual

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5.0.4 by Matthias Templ, 3 months ago

Browse source code at

Authors: Matthias Templ, Alexander Kowarik, Bernhard Meindl

Documentation:   PDF Manual  

Task views: Official Statistics & Survey Methodology

GPL-2 license

Imports utils, stats, graphics, car, rmarkdown, knitr, data.table, xtable, robustbase, cluster, MASS, e1071, tools, Rcpp, methods, sets, ggplot2, shiny, haven, rhandsontable, DT, shinyBS, prettydoc, VIM

Suggests laeken, testthat

Linking to Rcpp

See at CRAN