importProblem

path

<p>reads an sdcProblem with code that has been exported within <code><a rd-options="" href="/link/sdcApp?package=sdcMicro&version=5.5.1" data-mini-rdoc="sdcMicro::sdcApp">sdcApp</a></code>.</p>

Data from statistical agencies and other institutions are mostly
confidential. This package (see also 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 anonymisation methods are included. Note that the package
includes a graphical user interface (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

importProblem function

<p>reads an sdcProblem with code that has been exported within <code><a rd-options='' href='sdcApp'>sdcApp</a></code>.</p>

importProblem: importProblem

Description

Usage

Arguments

Value