文章基本信息

标题：Bayesian Bootstrap in Multiple Frames
本地全文：下载
作者：Daniela Cocchi ; Lorenzo Marchi ; Riccardo Ievoli 等
期刊名称：Stats
电子版ISSN：2571-905X
出版年度：2022
卷号：5
期号：2
页码：561-571
DOI：10.3390/stats5020034
语种：English
出版社：MDPI AG
摘要：Multiple frames are becoming increasingly relevant due to the spread of surveys conducted via registers. In this regard, estimators of population quantities have been proposed, including the multiplicity estimator. In all cases, variance estimation still remains a matter of debate. This paper explores the potential of Bayesian bootstrap techniques for computing such estimators. The suitability of the method, which is compared to the existing frequentist bootstrap, is shown by conducting a small-scale simulation study and a case study.