Estimation of a linear model under microaggregation by individual ranking

被引：0
|
作者：
Schmid M. [1 ]
机构：
[1] Department of Statistics, University of Munich, 80539 Munich
来源：
Allgemeines Statistisches Archiv | 2006年 / 90卷 / 3期
关键词：
Asymptotic variance; Consistent estimation; Disclosure control; Individual ranking; Linear model; Microaggregation;
D O I：
10.1007/s10182-006-0243-z
中图分类号：
学科分类号：
摘要：
Microaggregation by individual ranking is one of themost commonly applied disclosure control techniques for continuous microdata. The paper studies the effect of microaggregation by individual ranking on the least squares estimation of a multiple linear regression model. It is shown that the traditional least squares estimates are asymptotically unbiased. Moreover, the least squares estimates asymptotically have the same variances as the least squares estimates based on the original (non-aggregated) data. Thus, asymptotically, microaggregation by individual ranking does not result in a loss of efficiency in the least squares estimation of a multiple linear regression model. © Physica-Verlag 2006.
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收藏
页码：419 / 438
页数：19
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