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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

1,339

Version

5.7.8

License

GPL-2

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Repository

https://github.com/sdcTools/sdcMicro

Maintainer

Last Published

March 11th, 2024

Functions in sdcMicro (5.7.8)

extractManipData

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

distributeDraws_cpp

Distribute number of swaps

overal disclosure risk

distributeRandom_cpp

Dummy Dataset for Record Swapping

Creates new randomized IDs

Data-Utility measures

RMD based disclosure risk

data from the casc project

Fast generation of synthetic data

Global Recoding

get.sdcMicroObj

get.sdcMicroObj

Demo data set from mu-Argus

Generate one strata variable from multiple factors

Frequencies calculation for risk estimation

Additional Information-Loss measures

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

Calculate information loss after targeted record swapping

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

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.

Fast and Simple Microaggregation

Individual Risk computation

localSuppression

Local Suppression to obtain k-anonymity

Local Suppression

microaggregation

Microaggregation

Disclosure Risk for Categorical Variables

Detection and winsorization of multivariate outliers

Comparison plots

plot.localSuppression

Plots for localSuppression objects

plot.sdcMicroObj

Plotfunctions for objects of class sdcMicroObj

Post Randomization

Global risk using log-linear models.

print.indivRisk

Print method for objects from class indivRisk

Print method for objects from class freqCalc.

Random Sampling

print.sdcMicroObj

Print and Extractor Functions for objects of class sdcMicroObj-class

Targeted Record Swapping

Print method for objects from class modrisk

Print method for objects from class pram

print.localSuppression

Print method for objects from class localSuppression

Print method for objects from class micro

Print method for objects from class suda2

Targeted Record Swapping

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

sampleDonor_cpp

Random sample for donor records

selectHouseholdData

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

set.sdcMicroObj

set.sdcMicroObj

sdcMicro-package

sdcMicro: Statistical Disclosure Control Methods for Anonymization of Data and Risk Estimation

Generate an Html-report from an sdcMicroObj

sdcMicroObj-class

Class "sdcMicroObj"

subsetMicrodata

subsetMicrodata

Suda2: Detecting Special Uniques

summary.freqCalc

Summary method for objects from class freqCalc

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

Summary method for objects from class micro

show,sdcMicroObj-method

A real-world data set on household income and expenditures

Top and Bottom Coding

Summary method for objects from class pram

Shuffling and EGADP

Define Swap-Levels

Comparison of different microaggregation methods

Recompute Risk and Frequencies for a sdcMicroObj

argus_microaggregation

argus_microaggregation

Small Artificial Data set

Adding noise to perturb data

Tarragona data set

CASCrefmicrodata

Census data set

Local recoding via Edmond's maximum weighted matching algorithm