The properties of the cross-match estimate and split sampling

• 成果类型: Article
• 署名作者: Kong, A; Liu, JS; Wong, WH
• 署名单位: University of Chicago; Stanford University; University of California System; University of California Los Angeles
• 刊物名称: ANNALS OF STATISTICS
• ISSN/ISSBN: 0090-5364
• 发表日期: 1997
• 页码: 2410-2432
• 关键词: STATISTICS

摘要

By noting the connection with h-sample U-statistics, we find a simple decomposition of the variance of the cross-match estimate, which can be regarded as a generalization of Efron and Stein. We apply the decomposition in assessing efficiencies of several plans of using the weighted samples from an importance scheme. The applications of the formula to multiple imputations lead to a method of crossing jointly imputed data to gain more accuracy.