A Comparison of Small Area and Calibration Estimators Via Simulation
A Comparison of Small Area and Calibration Estimators Via Simulation
复制标题
通过仿真对小面积估计器和校准估计器进行比较
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
V. Estevao
中科院分区：
文献类型：
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作者：
M. Hidiroglou;V. Estevao
摘要通常使用直接或修改的直接校准估计器来获得域估计。如果它们严格使用感兴趣领域内的数据，则它们是直接的。如果它们同时使用感兴趣的域内和域外的数据，则直接对其进行修改。产生这些估算值的另一种方法是通过小面积程序。在本文中，我们通过仿真对这两种方法的性能进行了比较。使用既包括区域效应又包括单位水平随机误差的分层模型来生成总体。种群由不同大小的相互排斥的域组成，从少量的单元到大量的单元不等。我们从总体中选择许多固定大小的独立的简单随机样本，并利用可用的辅助信息计算每个样本的各种估计。模拟计算的估计值包括Horvitz-Thompson估计值、合成估计值(间接估计值)、校准估计值和基于单位水平的估计值(小区域估计值)。根据它们基于设计的性质总结了这些估值器的性能。
Abstract Domain estimates are typically obtained using calibration estimators that are direct or modified direct. They are direct if they strictly use data within the domain of interest. They are modified direct if they use both data within and outside the domain of interest. An alternative way of producing these estimates is through small area procedures. In this article, we compare the performance of these two approaches via a simulation. The population is generated using a hierarchical model that includes both area effects and unit level random errors. The population is made up of mutually exclusive domains of different sizes, ranging from a small number of units to a large number of units. We select many independent simple random samples of fixed size from the population and compute various estimates for each sample using the available auxiliary information. The estimates computed for the simulation included the Horvitz-Thompson estimator, the synthetic estimator (indirect estimate), calibration estimators, and unit level based estimators (small area estimate). The performance of these estimators is summarized based on their design-based properties.