Network models for complementary cell suppression
Network models for complementary cell suppression
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DOI：
10.2307/2291538
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发表时间：
1995-12-01
影响因子：
3.7
通讯作者：
Cox, LH
中科院分区：
文献类型：
--
作者：
Cox, LH
补充细胞抑制是一种在数据以表格形式呈现时保护与个别应答者有关的数据免遭统计披露的方法。统计文献中提出了几种互补抑制的数学方法；有些已由国家统计机构在大规模数据处理环境中实施。每种方法都有理论上或计算上的局限性。本文提出了基于数学网络线性优化的互补细胞抑制问题的解决方案。这些方法被证明对某些问题是最优的，并提供理论和实践上的优势，包括全面性、可理解性和计算效率。
Complementary cell suppression is a method for protecting data pertaining to individual respondents from statistical disclosure when the data are presented in tabular form. Several mathematical methods for complementary suppression have been proposed in the statistical literature; some have been implemented in large-scale data processing environments by national statistical agencies. Each method has either theoretical or computational limitations. This article presents solutions to the complementary cell suppression problem based on linear optimization over a mathematical network. These methods are shown to be optimal for certain problems and to offer theoretical and practical advantages, including comprehensiveness, comprehensibleness, and computational efficiency.