sdcHierarchies - Create and (Interactively) Modify Nested Hierarchies

Provides functionality to generate, (interactively) modify (by adding, removing and renaming nodes) and convert nested hierarchies between different formats. These tree like structures can be used to define for example complex hierarchical tables used for statistical disclosure control.

Last updated 1 years ago

cpp

5.70 score 2 stars 3 dependents 28 scripts 743 downloads

STATcubeR - R Interface for the 'STATcube' REST API and Open Government Data

Import data from the 'STATcube' REST API or from the open data portal of Statistics Austria. This package includes a client for API requests as well as parsing utilities for data which originates from 'STATcube'. Documentation about 'STATcubeR' is provided by several vignettes included in the package as well as on the public 'pkgdown' page at <https://statistikat.github.io/STATcubeR/>.

Last updated 3 months ago

apidatabaseogdopen-datasdmx

5.03 score 18 stars 9 scripts 546 downloads

sdcTable - Methods for Statistical Disclosure Control in Tabular Data

Methods for statistical disclosure control in tabular data such as primary and secondary cell suppression as described for example in Hundepol et al. (2012) <doi:10.1002/9781118348239> are covered in this package.

Last updated 2 years ago

glpkcpp

3.18 score 1 stars 2 dependents 25 scripts 871 downloads

cellKey - Consistent Perturbation of Statistical Frequency- And Magnitude Tables

Data from statistical agencies and other institutions often need to be protected before they can be published. This package can be used to perturb statistical tables in a consistent way. The main idea is to add - at the micro data level - a record key for each unit. Based on these keys, for any cell in a statistical table a cell key is computed as a function on the record keys contributing to a specific cell. Values that are added to the cell in order to perturb it are derived from a lookup-table that maps values of cell keys to specific perturbation values. The theoretical basis for the methods implemented can be found in Thompson, Broadfoot and Elazar (2013) <https://unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.46/2013/Topic_1_ABS.pdf> which was extended and enhanced by Giessing and Tent (2019) <https://unece.org/fileadmin/DAM/stats/documents/ece/ces/ge.46/2019/mtg1/SDC2019_S2_Germany_Giessing_Tent_AD.pdf>.

Last updated 1 years ago

2.70 score 7 scripts 301 downloads