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本页整理公开书目信息,不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成,未完成全文核验,可能有误;具体假设、证明与结论请核对原文。摘要保留来源文本,未经模型改写。

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AI 根据所提供的论文材料归类:摘要讨论跨学科的混合采样与测量成本,没有明确对应所列经济计量细分领域,故暂不归类。

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混合采样方法综述

研究问题
将多个样本单位合并测量,会损失单位层面的信息;研究关注这种做法如何降低测量成本,以及如何利用混合样本进行估计。
方法与思路
作者综述不同学科中的混合采样、分组筛查与合并测量方法,并用同时具有混合样本和单位测量的数据展示数值正则化应用。
材料陈述的贡献
摘要称,文章整合了分散在不同学科中的原创方法与应用,并借助新墨西哥州汞污染调查数据评估混合采样估计。
阅读关注点
应核对混合过程如何改变观测信息、各类方法估计的目标,以及同时具有两层测量的数据如何用于评价估计结果。
阅读边界
仅据版本未注明的 OpenAlex 索引摘要;成本节约幅度、估计条件和评价结果未说明,不能推断其他版本变化。

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.

笔记与分组
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