抽样方差平滑法在小面积比例估算中的应用

IF 0.5 4区数学 Q4 SOCIAL SCIENCES, MATHEMATICAL METHODS

Journal of Official Statistics Pub Date : 2023-12-10 DOI:10.2478/jos-2023-0026

Yong You, Mike Hidiroglou

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引用次数: 0

摘要

抽样方差平滑是小面积估计中的一个重要课题。本文提出了用于小面积比例估计的抽样方差平滑方法。其中，我们考虑了抽样方差平滑的广义方差函数和设计效应方法。我们通过分析加拿大统计局的调查数据，评估和比较了平滑抽样方差和基于平滑方差估计的小面积估计。真实数据分析和模拟研究的结果表明，所提出的抽样方差平滑方法在小面积估计方面表现非常出色。

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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Application of Sampling Variance Smoothing Methods for Small Area Proportion Estimation

Sampling variance smoothing is an important topic in small area estimation. In this article, we propose sampling variance smoothing methods for small area proportion estimation. In particular, we consider the generalized variance function and design effect methods for sampling variance smoothing. We evaluate and compare the smoothed sampling variances and small area estimates based on the smoothed variance estimates through analysis of survey data from Statistics Canada. The results from real data analysis and simulation study indicate that the proposed sampling variance smoothing methods perform very well for small area estimation.

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来源期刊

Journal of Official Statistics STATISTICS & PROBABILITY-

CiteScore

1.90

自引率

9.10%

发文量

审稿时长

>12 weeks

期刊介绍： JOS is an international quarterly published by Statistics Sweden. We publish research articles in the area of survey and statistical methodology and policy matters facing national statistical offices and other producers of statistics. The intended readers are researchers or practicians at statistical agencies or in universities and private organizations dealing with problems which concern aspects of production of official statistics.