Evaluation of Synthetic Small-area Estimators Using Design-based Methods
Evaluation of Synthetic Small-area Estimators Using Design-based Methods
复制标题
使用基于设计的方法评估综合小面积估计器
DOI：
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发表时间：
2019
影响因子：
0.6
通讯作者：
S. Pramanik
中科院分区：
文献类型：
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作者：
P. Lahiri;S. Pramanik
使用特定区域的设计为基础的均方误差（MSE）来衡量与合成和直接估计的不确定性是有吸引力的，因为相同的无模型的标准。然而，小样本量往往是一个困难，在获得一个可靠的估计特定区域的设计为基础的MSE。此外，基于特定区域设计的均方误差估计量在某些情况下可能会产生不期望的负值。现有的解决方案，以克服小样本量的问题是考虑平均设计为基础的MSE，平均是在可用的小面积。这可能无法解决负MSE的另一个问题。提出了一种基于平均设计的均方误差估计器，它总是产生正估计。仿真结果表明，这种估计比现有的平均设计为基础的MSE更好，因为它总是产生积极的估计和帐户的偏差分量通常存在于合成估计。
The use of area-specific design-based mean squared error (MSE) to measure the uncertainty associated with synthetic and direct estimators is appealing since the same model-free criterion is applied. However, the small sample size is often a difficulty in obtaining a reliable estimator of the area-specific design-based MSE. Moreover, the area-specific design-based mean squared error estimator might yield undesirable negative values under certain circumstances. The existing solution to overcome the problem of small sample size is to consider average design-based MSE, average being taken over the available small areas. This may not solve the other problem of negative MSE. An alternative average design-based mean squared error estimator is proposed which always produces positive estimates. Simulation shows that this estimator performs better than the existing average design-based MSEs as it always produces positive estimates and accounts for the bias component usually present in synthetic estimators.