processTableHITAS {sdcTable}R Documentation

processTableHITAS

Description

HITAS - algorithm for secondary cell suppression using optimal suppression algorithm.

Usage

processTableHITAS (fullData, ub=NULL, lb=NULL, UPLPerc=35, LPLPerc=25, weight="values")

Arguments

fullData object from class fullData.
ub probably known upper bounds for cell values. If not specified, cellvalue * 100 is assumed.
lb probably known lower bounds for cell values. If not specified, 0 is assumed for each cell (non-negative table).
UPLPerc percentage of (upper) protection for each cell. Maximum possible value calculated for any sensitive cell must be greater or equal the cell value plus ULPPerc %.
LPLPerc percentage of (lower) protection for each cell. Minimum possible value calculated for any sensitive cell must be less or equal the cell value minus LPLPerc %.
weight parameter to use for objective function. Possible choices are values and logs.

Details

Have a look at the links given below.

Value

Manipulated data.

Note

processTableHITAS() protects hierarchical tabular data using the HiTaS approach.

Author(s)

Bernhard Meindl

References

de Wolf, P.P (2002). HiTaS: A Heuristic Approach to Cell Suppression in Hierarchical Tables. In: Domingo-Ferrer, J. (Hrsg.): Inference Control in Statistical Databases. Vol. 2316. \ Fischetti, M., Salazar, J.J. (2000). Models and Algorithms for Optimizing Cell Suppression in Tabular Data with Linear Constraints. In: Journal of the American Statistical Association 95, 916-928.

Examples

        ## Not run: 
                data(exampleFullData)
                erg <- processTableHITAS(exampleFullData, UPLPerc=15, LPLPerc=15)
                summary(erg)
        
## End(Not run)

[Package sdcTable version 0.0.2 Index]