摘要
文章将Poisson-Poisson项目计数法进行推广,提出零浮动Poisson项目计数法,其中,非敏感辅助变量来自于一个参数已知的零浮动Poisson分布。并给出了该模型下敏感参数极大似然估计的EM算法以及构造其置信区间的bootstrap方法。此外,还对该模型保护受访者隐私的能力加以讨论,发现该模型的隐私保护要优于Poisson-Poisson项目计数法。最后,从随机模拟的结果表明在该模型下利用本文所介绍的分析方法可以得到敏感参数的较为准确的估计。
This paper extends the Poisson-Poisson item count technique to the zero-inflated Poisson item count technique,where the non-sensitive auxiliary variable comes from a zero-inflated Poisson distribution with known parameters.The paper also provides the EM algorithm to calculate the maximum likelihood estimate for the sensitive parameter as well as the bootstrap method in constructing confidence intervals.Furthermore,the paper discusses the ability of privacy protection of the proposed model and finds out that it performs better than that of the Poisson-Poisson item count approach.Finally,the results of the stochastic simulation show that a more accurate estimate of the sensitive parameters can be obtained by using the analytical method described in the paper.
作者
刘寅
吴琴
Liu Yin;Wu Qin(School of Statistics and Mathematics,Zhongnan University of Economics and Law,Wuhan 430074,China;School of Mathematics,South China Normal University,Guangzhou 510631,China)
出处
《统计与决策》
CSSCI
北大核心
2020年第1期29-32,共4页
Statistics & Decision
基金
国家自然科学基金资助项目(11601524
11401226)
中南财经政法大学青年教师资助项目(31721811206)
关键词
零浮动Poisson项目计数法
敏感数据抽样调查
EM算法
隐私保护度
zero-inflated Poisson item count technique
sample surveys with sensitive characteristics
EM algorithm
degree of privacy protection