processTableHITAS {sdcTable} | R Documentation |
HITAS - algorithm for secondary cell suppression using optimal suppression algorithm.
processTableHITAS (fullData, ub=NULL, lb=NULL, UPLPerc=35, LPLPerc=25, weight="values")
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. |
Have a look at the links given below.
Manipulated data.
processTableHITAS() protects hierarchical tabular data using the HiTaS approach.
Bernhard Meindl
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.
## Not run: data(exampleFullData) erg <- processTableHITAS(exampleFullData, UPLPerc=15, LPLPerc=15) summary(erg) ## End(Not run)