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Preserving confidentiality of high-dimensional tabulated data: Statistical and computational issues
Authors:Dobra  Adrian  Karr  Alan F  Sanil  Ashish P
Institution:(1) National Institute of Statistical Sciences, Research Triangle Park, NC 27709-4006, USA
Abstract:Dissemination of information derived from large contingency tables formed from confidential data is a major responsibility of statistical agencies. In this paper we present solutions to several computational and algorithmic problems that arise in the dissemination of cross-tabulations (marginal sub-tables) from a single underlying table. These include data structures that exploit sparsity to support efficient computation of marginals and algorithms such as iterative proportional fitting, as well as a generalized form of the shuttle algorithm that computes sharp bounds on (small, confidentiality threatening) cells in the full table from arbitrary sets of released marginals. We give examples illustrating the techniques.
Keywords:branch and bound  contingency tables  disclosure limitation  integer programming  marginal bounds  shuttle algorithm
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