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Two-phase adaptive cluster sampling with circular field plots
Environmetrics ( IF 1.7 ) Pub Date : 2022-05-18 , DOI: 10.1002/env.2729
Wilmer Prentius 1 , Anton Grafström 1
Affiliation  

Adaptive cluster sampling (ACS) is extended to the case when the primary sampling units consist of circular field plots. When conducting field work for environmental monitoring, circular field plots are often preferred as they are easily set up by field workers. ACS was developed by tessellating the area frame into square plots. By using a two-phase sampling procedure, a first-phase sample of circular field plots can be established as the primary sampling units, from which ACS can be performed. However, the two-phase approach introduces some additional complexity in estimation. We derive estimators and conservative variance estimators for two-phase ACS using circular field plots. For some populations, ACS may produce a highly variable sample size. To deal with this issue, we provide a way to reduce the maximal possible sample size. By using simulated populations, we compare the efficiencies of two-phase methods with ordinary simple random sampling. The simulations show that the two-phase approach is a competitive alternative to regular ACS, and that adding a restriction to the maximal possible sample size makes ACS a viable alternative for a larger set of populations.

中文翻译:

具有圆形场图的两阶段自适应聚类采样

自适应整群抽样 (ACS) 扩展到主要抽样单元由圆形场图组成的情况。在进行环境监测的现场工作时,通常首选圆形场地,因为它们很容易由现场工作人员设置。ACS 是通过将区域框架细分为方形图而开发的。通过使用两阶段采样程序,可以建立圆形场图的第一阶段样本作为主要采样单元,从中可以执行 ACS。然而,两阶段方法在估计中引入了一些额外的复杂性。我们使用圆形场图推导出两相 ACS 的估计量和保守方差估计量。对于某些人群,ACS 可能会产生高度可变的样本量。为了解决这个问题,我们提供了一种减少最大可能样本量的方法。通过使用模拟总体,我们比较了两阶段方法与普通简单随机抽样的效率。模拟表明,两阶段方法是常规 ACS 的竞争替代方案,并且对最大可能样本量增加限制使得 ACS 成为更大群体的可行替代方案。
更新日期:2022-05-18
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