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.

Bayesian Bootstrap in Multiple Frames

Daniela Cocchi
Methodology
;
Lorenzo Marchi
Software
;
Riccardo Ievoli
Methodology
2022

Abstract

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.
2022
Daniela Cocchi , Lorenzo Marchi , Riccardo Ievoli
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/905866
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