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

arXiv: https://arxiv.org/abs/1705.03827 · HTML: https://mlsanity.com/paper/1705.03827/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 May 2017.

## Built on by (most cited first, 1 of 1)

- [Distributional Random Forests for Complex Survey Designs](https://mlsanity.com/paper/2512.08179/) (2025)

## Abstract (arXiv)

In this paper, a class of resampling techniques for finite populations under complex sampling design is introduced. The basic idea on which it rests 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.