Small area estimation - New developments and directions
Small area estimation - New developments and directions
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DOI：
10.1111/j.1751-5823.2002.tb00352.x
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发表时间：
2002-04-01
影响因子：
2
通讯作者：
Pfeffermann, D
中科院分区：
文献类型：
--
作者：
Pfeffermann, D
本文对近年来小区域估计(SAE)方法的主要进展进行了综述。我们还讨论了一些早期的发展，这是新研究的必要背景。综述了模型依赖方法，特别强调目标区域数量的点预测和均方误差评估。所考虑的新模型是用于离散测量的模型、时间序列模型和在信息抽样下产生的模型。对用于表示小区域目标量的不可解释变化的小区域随机效应之间的相关性进行了建模，研究了可能的收益。关于早期用于SAE的方法的审查和评价，见Ghosh Rao(1994)。
The purpose of this paper is to provide a critical review of the main advances in small area estimation (SAE) methods in recent years. We also discuss some of the earlier developments, which serve as a necessary background for the new studies. The review focuses on model dependent methods with special emphasis on point prediction of the target area quantities, and mean square error assessments. The new models considered are models used for discrete measurements, time series models and models that arise under informative sampling. The possible gains from modeling the correlations among small area random effects used to represent the unexplained variation of the small area target quantities are examined. For review and appraisal of the earlier methods used for SAE, see Ghosh Rao (1994).