Statistical inference from finite population samples: A critical review of frequentist and Bayesian approaches

Pub Date : 2022-07-27 DOI:10.1002/cjs.11717
Jean-François Beaumont, David Haziza
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引用次数: 1

Abstract

In survey sampling, data are obtained on a subset of a finite population by probability or nonprobability sampling procedures. These data are used to compute point estimates of finite population parameters along with their associated variance estimates and confidence intervals. Methods to conduct inferences and evaluate the properties of sampling and estimation procedures have been the subject of discussion and debate in the second half of the 20th century. In this article, we propose a critical review of three inferential approaches in a finite population context: the design-based approach, the frequentist model-based approach, and the Bayesian approach.

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有限总体样本的统计推断:频率论和贝叶斯方法综述
在调查抽样中,数据是通过概率或非概率抽样程序在有限总体的子集上获得的。这些数据用于计算有限总体参数的点估计值及其相关的方差估计值和置信区间。在20世纪下半叶,对抽样和估计程序的性质进行推断和评估的方法一直是讨论和争论的主题。在这篇文章中,我们对有限总体背景下的三种推理方法进行了批判性的回顾:基于设计的方法、基于频繁度模型的方法和贝叶斯方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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