Nonparametric Estimation of the Number of Drug Users in Hong Kong Using Repeated Multiple Lists

作     者：Huggins, Richard M. Yip, Paul S. F. Stoklosa, Jakub 

作者机构：Univ Melbourne Dept Math & Stat Melbourne Vic 3010 Australia Univ Hong Kong Dept Social Work & Social Adm Hong Kong Hong Kong Peoples R China Univ New S Wales Sch Math & Stat Sydney NSW 2052 Australia Univ New S Wales Evolut & Ecol Res Ctr Sydney NSW 2052 Australia 

出 版 物：《AUSTRALIAN & NEW ZEALAND JOURNAL OF STATISTICS》 (澳大利亚与新西兰统计学杂志)

年 卷 期：2016年第58卷第1期

页      面：1-13页

核心收录：

学科分类：0202[经济学-应用经济学] 02[经济学] 020208[经济学-统计学] 07[理学] 0714[理学-统计学（可授理学、经济学学位）] 

主　　题：log-linear models model selection population size estimation smoothing splines 

摘      要：We update a previous approach to the estimation of the size of an open population when there are multiple lists at each time point. Our motivation is 35years of longitudinal data on the detection of drug users by the Central Registry of Drug Abuse in Hong Kong. We develop a two-stage smoothing spline approach. This gives a flexible and easily implemented alternative to the previous method which was based on kernel smoothing. The new method retains the property of reducing the variability of the individual estimates at each time point. We evaluate the new method by means of a simulation study that includes an examination of the effects of variable selection. The new method is then applied to data collected by the Central Registry of Drug Abuse. The parameter estimates obtained are compared with the well known Jolly-Seber estimates based on single capture methods.