文章基本信息

标题：synthpop: Bespoke Creation of Synthetic Data in R
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作者：Beata Nowok ; Gillian M. Raab ; Chris Dibben 等
期刊名称：Journal of Statistical Software
印刷版ISSN：1548-7660
电子版ISSN：1548-7660
出版年度：2016
卷号：74
期号：1
页码：1-26
语种：English
出版社：University of California, Los Angeles
摘要：In many contexts, confidentiality constraints severely restrict access to unique and valuable microdata. Synthetic data which mimic the original observed data and preserve the relationships between variables but do not contain any disclosive records are one possible solution to this problem. The synthpop package for R, introduced in this paper, provides routines to generate synthetic versions of original data sets. We describe the methodology and its consequences for the data characteristics. We illustrate the package features using a survey data example.
关键词：synthetic data;disclosure control;CART;R;UK longitudinal studies