Article ID: | iaor2007539 |
Country: | Netherlands |
Volume: | 171 |
Issue: | 1 |
Start Page Number: | 39 |
End Page Number: | 52 |
Publication Date: | May 2006 |
Journal: | European Journal of Operational Research |
Authors: | Castro Jordi |
Keywords: | programming: linear, programming: quadratic, statistics: general |
National Statistical Agencies routinely release large amounts of tabular information. Prior to dissemination, tabular data need to be processed to avoid the disclosure of individual confidential information. One widely used class of methods is based on the modification of the table cells values. However, previous approaches were not able to preserve the values of the marginal cells and the additivity relations for a general table of any dimension, size and structure. This void was recently filled by the controlled tabular adjustment and one of its variants, the quadratic minimum-distance controlled perturbation method. Although independently developed, both approaches rely on the same strategy: given a set of tables to be protected, they find the minimum-distance values to the original cells that make the released information safe. Controlled tabular adjustment uses the