argus_microaggregation

calls microaggregation code from mu-argus. In case only one variable should be
microaggregated and <code>useOptimal</code> is <code>TRUE</code>, Hansen-Mukherjee polynomial exact method
is applied. In any other case, the Mateo-Domingo method is used.

Data from statistical agencies and other institutions are mostly
confidential. This package, introduced in Templ, Kowarik and Meindl (2017) <doi:10.18637/jss.v067.i04>, can be used for the generation of anonymized
(micro)data, i.e. for the creation of public- and scientific-use files.
The theoretical basis for the methods implemented can be found in Templ (2017) <doi:10.1007/978-3-319-50272-4>.
Various risk estimation and anonymization methods are included. Note that the package
includes a graphical user interface published in Meindl and Templ (2019) <doi:10.3390/a12090191> that allows to use various methods of this
package.

Matthias Templ

sdcMicro

Statistical Disclosure Control Methods for Anonymization of Data
and Risk Estimation

Bernhard Meindl

Alexander Kowarik

Johannes Gussenbauer

Organisation For Economic Co-Operation And Development 

Statistics Netherlands 

Pascal Heus 

argus_microaggregation function

<dl><dt>df</dt>
<dd>a <code>data.frame</code> with only numerical columns</dd>
<dt>k</dt>
<dd>required group size</dd>
<dt>useOptimal</dt>
<dd>(logical) should optimal microaggregation be applied (ony possible in
in case of one variable)</dd></dl>

Arguments

argus_microaggregation — argus_microaggregation

<dl>

<dt>df</dt>
<dd>a <code>data.frame</code> with only numerical columns</dd>


<dt>k</dt>
<dd>required group size</dd>


<dt>useOptimal</dt>
<dd>(logical) should optimal microaggregation be applied (ony possible in
in case of one variable)</dd>

</dl>

argus_microaggregation: argus_microaggregation

Description

Usage

Value

Arguments

See Also

Examples