A unified principled framework for resampling based on\n pseudo-populations: asymptotic theory

2017/05/10 by Pier Luigi Conti, Daniela Marella, Conti, Pier Luigi +5 · 1 citation
Computer Science · Mathematics · #Bayesian Methods and Mixture Models #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Distribution Estimation and Applications #Survey Sampling and Estimation Techniques

paper · pdf · doi:10.48550/arxiv.1705.03827

openalex publication_date 2017/05/10 · openalex created_date 2022/10/06 · openalex updated_date 2026/07/28

Abstract

In this paper, a class of resampling techniques for finite populations under\ncomplex sampling design is introduced. The basic idea on which it rests is a\ntwo-step procedure consisting in : (i) constructing a pseudo-population on the\nbasis of sample data; (ii) drawing a sample from the predicted population\naccording to an appropriate resampling design. From a logical point of view,\nthis approach is essentially based on the plug-in principle by Efron, at the\n"sampling design level". Theoretical justifications based on large sample\ntheory are provided. New approaches to construct pseudo-populations based on\nvarious forms of calibrations are proposed. Finally, a simulation study is\nperformed.\n

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