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sdcMicro

sdcMicro is an R-package to anonymize microdata. Most functionalities of the package are also available via an interactive shiny-based graphical user interface.

The online documentation can also be found at sdctools.github.io/sdcMicro.

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Version

Install

install.packages('sdcMicro')

Monthly Downloads

730

Version

5.7.5

License

GPL-2

Issues

Pull Requests

Stars

Forks

Repository

https://github.com/sdcTools/sdcMicro

Maintainer

Matthias Templ

Last Published

January 9th, 2023

Functions in sdcMicro (5.7.5)

Local recoding via Edmond's maximum weighted matching algorithm

Recompute Risk and Frequencies for a sdcMicroObj

argus_microaggregation

argus_microaggregation

Tarragona data set

Adding noise to perturb data

Small Artificial Data set

CASCrefmicrodata

Census data set

overal disclosure risk

RMD based disclosure risk

distributeDraws_cpp

Distribute number of swaps

distributeRandom_cpp

Data-Utility measures

Fast generation of synthetic data

data from the casc project

Frequencies calculation for risk estimation

Additional Information-Loss measures

Generate one strata variable from multiple factors

Dummy Dataset for Record Swapping

extractManipData

Remove certain variables from the data set inside a sdc object.

get.sdcMicroObj

get.sdcMicroObj

Creates new randomized IDs

Join levels of a variables in an object of class sdcMicroObj-class or factor or data.frame

Individual Risk computation

Demo data set from mu-Argus

Global Recoding

Fast and Simple Microaggregation

Microaggregation for numerical and categorical key variables based on a distance similar to the Gower Distance

Calculate information loss after targeted record swapping

Local Suppression

kAnon_violations

kAnon_violations

mergeHouseholdData

Replaces the raw household-level data with the anonymized household-level data in the full dataset for anonymization of data with a household structure (or other hierarchical structure). Requires a matching household ID in both files.

Disclosure Risk for Categorical Variables

microaggregation

Microaggregation

Detection and winsorization of multivariate outliers

Comparison plots

Post Randomization

Global risk using log-linear models.

print.indivRisk

Print method for objects from class indivRisk

Random Sampling

Targeted Record Swapping

print.sdcMicroObj

Print and Extractor Functions for objects of class sdcMicroObj-class

Print method for objects from class freqCalc.

Print method for objects from class modrisk

plot.localSuppression

Plots for localSuppression objects

print.localSuppression

Print method for objects from class localSuppression

plot.sdcMicroObj

Plotfunctions for objects of class sdcMicroObj

localSuppression

Local Suppression to obtain k-anonymity

Print method for objects from class suda2

Print method for objects from class micro

Print method for objects from class pram

sampleDonor_cpp

Random sample for donor records

set.sdcMicroObj

set.sdcMicroObj

selectHouseholdData

Creates a household level file from a dataset with a household structure.

Suda2: Detecting Special Uniques

show,sdcMicroObj-method

subsetMicrodata

subsetMicrodata

Summary method for objects from class micro

sdcMicroObj-class

Class "sdcMicroObj"

summary.freqCalc

Summary method for objects from class freqCalc

Shuffling and EGADP

sdcMicro-package

Statistical Disclosure Control (SDC) for the generation of protected microdata for researchers and for public use.

Define Swap-Levels

Summary method for objects from class pram

Generate an Html-report from an sdcMicroObj

Change the a keyVariable of an object of class sdcMicroObj-class from Numeric to Factor or from Factor to Numeric

A real-world data set on household income and expenditures

Targeted Record Swapping

Remove certain variables from the data set inside a sdc object.

Top and Bottom Coding

Comparison of different microaggregation methods