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Extensions of the Re-identification Risk Measures Based on Log-Linear Models

机译:基于对数线性模型的重新识别风险措施的扩展

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摘要

A global measure of the re-identification risk in microdata files is analyzed. Two extensions of the log-linear models are presented. The first methodology considers the weights in the analysis of contingency tables. The results of several tests performed on real data are presented. In the framework of statistical disclosure control, the second methodology proposes a maximum penalized likelihood approach to the computation of smooth estimates.
机译:分析了Microdata文件中重新识别风险的全局衡量标准。呈现了对数线性模型的两个扩展。第一种方法考虑了应急表分析中的权重。介绍了对实际数据执行的几种测试的结果。在统计公开控制的框架中,第二种方法提出了最大惩罚似然方法来计算平滑估计。

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