A Review of Composite Sampling Methods
混合采样方法综述AI 解读 ↓
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混合采样方法综述
- 研究问题
- 将多个样本单位混合后测量，会失去单位层面的信息但降低测量成本；如何梳理不同学科的方法及其估计用途？
- 方法与思路
- 作者综述混合采样、分组筛查、合并测量和称量设计相关文献，并以同时具有混合及单位层面测量的汞污染数据展示应用。
- 材料陈述的贡献
- 摘要称，论文整合分散在不同学科的原创方法与应用，并展示一种数值正则化用途，利用双层测量数据评估混合采样估计。
- 阅读关注点
- 核对综述纳入范围、样本混合及测量机制，关注单位信息损失与成本节约的权衡，以及正则化应用的具体估计目标。
- 阅读边界
- 仅据 OpenAlex 索引摘要，稿件版本未注明；这是综述及应用展示，摘要未给出成本节约或估计误差数值，不能推断普遍收益。
原文摘要
A composite is formed by collecting multiple sample units and combining them in their entirety or in part, to form a new sample. The sample units that make up the composite may retain their integrity or be homogenized through physical processes such as ball milling, sieving, shaking, or centrifuging. One or more subsequent measurements are taken on the composite and the information on the sample units is lost. This counterintuitive loss of information has fueled opposition to composite sampling, while the methodology's adherents find their motivation in its ability to reduce measurement costs for many classes of problems. This article reviews the scientific literature related to the development of composite sampling methods. The literature on compositing exists only as a compendium derived from disparate disciplines in which terms such as compositing, group screening, pooling, and weighing designs are used. The goal of this review is to synthesize this body of literature. The articles reviewed are limited to those that offer original applications or methodologies. A novel application in numerical regularization, is illustrated using data from an environmental investigation into mercury contamination at a waste disposal site in New Mexico. What is unusual about these data is the existence of measurements at both the composite and sample unit levels, thus allowing an opportunity to evaluate estimates based on composite sampling methods.