Spatially Balanced Sampling: A Review and A Reappraisal
Spatially Balanced Sampling: A Review and A Reappraisal
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DOI：
10.1111/insr.12216
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发表时间：
2017-12-01
影响因子：
2
通讯作者：
Postiglione, Paolo
中科院分区：
文献类型：
--
作者：
Benedetti, Roberto;Piersimoni, Federica;Postiglione, Paolo
空间分布的数据表现出在设计空间单元调查时应考虑的特殊特征。不幸的是，传统的抽样设计通常不考虑空间特征，即使在抽样设计中通常希望使用与空间相关性有关的信息。本文回顾和比较了最近发展起来的几种随机空间抽样方法，并以没有替换的简单随机抽样作为比较基准。所采取的方法是以设计为基础的，用来证实关于有必要明确地将空间相关性纳入抽样调查理论的直观论点。为选择合适的空间抽样设计提供了一些指导，并以两个数据集为例，给出了使用这些设计对空间总体的收益的一些经验证据。
Spatially distributed data exhibit particular characteristics that should be considered when designing a survey of spatial units. Unfortunately, traditional sampling designs generally do not allow for spatial features, even though it is usually desirable to use information concerning spatial dependence in a sampling design. This paper reviews and compares some recently developed randomised spatial sampling procedures, using simple random sampling without replacement as a benchmark for comparison. The approach taken is design-based and serves to corroborate intuitive arguments about the need to explicitly integrate spatial dependence into sampling survey theory. Some guidance for choosing an appropriate spatial sampling design is provided, and some empirical evidence for the gains from using these designs with spatial populations is presented, using two datasets as illustrations.