In this paper, a class of resampling techniques for finite populations under πps sampling design is introduced. The basic idea on which they rest is a two-step procedure consisting in: (i) constructing a "pseudopopulation" on the basis of sample data; (ii) drawing a sample from the predicted population according to an appropriate resampling design. From a logical point of view, this approach is essentially based on the plugin principle by Efron, at the "sampling design level". Theoretical justifications based on large sample theory are provided. New approaches to construct pseudo populations based on various forms of calibrations are proposed. Finally, a simulation study is performed.
Conti, P., Marella, D., Mecatti, F., Andreis, F. (2020). A unified principled framework for resampling based on pseudo-populations: Asymptotic theory. BERNOULLI, 26(2), 1044-1069 [10.3150/19-BEJ1138].
A unified principled framework for resampling based on pseudo-populations: Asymptotic theory
Mecatti, FPenultimo
Membro del Collaboration Group
;
2020
Abstract
In this paper, a class of resampling techniques for finite populations under πps sampling design is introduced. The basic idea on which they rest is a two-step procedure consisting in: (i) constructing a "pseudopopulation" on the basis of sample data; (ii) drawing a sample from the predicted population according to an appropriate resampling design. From a logical point of view, this approach is essentially based on the plugin principle by Efron, at the "sampling design level". Theoretical justifications based on large sample theory are provided. New approaches to construct pseudo populations based on various forms of calibrations are proposed. Finally, a simulation study is performed.File | Dimensione | Formato | |
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