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  • 标题:Bayesian Bootstrap in Multiple Frames
  • 本地全文:下载
  • 作者:Daniela Cocchi ; Lorenzo Marchi ; Riccardo Ievoli
  • 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.
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