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Article

A unified principled framework for resampling based on pseudo-populations: Asymptotic theory

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Citation

Conti PL, Marella D, Mecatti F & Andreis F (2020) A unified principled framework for resampling based on pseudo-populations: Asymptotic theory. Bernoulli, 26 (2), pp. 1044-1069. https://doi.org/10.3150/19-bej1138

Abstract
In this paper, a class of resampling techniques for finite populations under ¦Ðps sampling design is introduced. The basic idea on which they rest is a two-step procedure consisting in: (i) constructing a ¡°pseudo-population¡± 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 plug-in 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.

Keywords
¦Ðps sampling designs; bootstrap; calibration; confidence intervals; finite populations; resampling; variance estimation

Journal
Bernoulli: Volume 26, Issue 2

StatusPublished
Publication date31/12/2020
Publication date online31/01/2020
Date accepted by journal28/06/2019
URL
ISSN1350-7265

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