Adaptive Sampling

自适应抽样设计是这样一种设计，在这种设计中，选择包括在样本中的单位的程序可能取决于在调查期间所做的观察。对于某些人群，与同等样本量的传统设计相比，适应性策略在估计精度上产生了实质性的提高。本研究探讨了自适应设计和推理程序的新类别，并发展了所需的基础理论。该研究将基于设计和基于模型的方法相结合，研究了自适应聚类抽样、自适应分配、自适应图抽样、最优抽样策略、自适应抽样中的多变量方法（包括快速评估策略）和自适应抽样中的非抽样误差。有了自适应抽样设计，可以在调查期间根据观察到的总体模式改变选择样本的程序。例如，在对一种稀有、濒危动物物种的调查中，只要发现该物种的成员，就可以在邻近的地点进行额外的观察。在环境污染评估研究中，适应性计划允许在观测到的“热点”附近进行额外的观测。同样，在对难以接近的人群进行调查时，个体之间的社会联系可能会自适应地用于获取样本。这种设计与传统的调查设计形成鲜明对比，在传统的调查设计中，可以在进行任何观察或获得任何回应之前确定将被纳入样本的地点或人员。适应性采样研究在环境研究中有许多重要的应用，包括对濒危物种、自然资源和环境污染物的调查，以及对隐藏或难以接近的人群的科学研究。自适应采样策略的优点包括在给定的采样努力量下获得更好的种群数量估计的潜力。例如，对于分布非常不均匀的抽样群体，自适应集群抽样设计已被证明比传统设计更高效。适应性设计可以显著提高样本的“产量”，例如，可以观察到更多稀有物种的动物，同时允许对种群中动物总数等数量进行无偏估计。自适应设计可用于增加找到调查人员最感兴趣的值的概率，例如污染物的最高浓度。在许多对隐藏或难以接近的人群的科学研究中，自适应联系追踪设计提供了获得足够大的研究样本的唯一实际手段，因此，从这些样本中进行估计的有效方法至关重要。*** DMS 9626102汤普森自适应抽样设计是指选择包括在样本中的单位的程序可能取决于在调查期间所做的观察的设计。对于某些人群，与同等样本量的传统设计相比，适应性策略在估计精度上产生了实质性的提高。本研究探讨了自适应设计和推理程序的新类别，并发展了所需的基础理论。该研究将基于设计和基于模型的方法相结合，研究了自适应聚类抽样、自适应分配、自适应图抽样、最优抽样策略、自适应抽样中的多变量方法（包括快速评估策略）和自适应抽样中的非抽样误差。采用自适应抽样设计，可以在调查期间根据在总体中观察到的模式改变选择样本的程序。例如，在对一种稀有、濒危动物物种的调查中，只要发现该物种的成员，就可以在邻近的地点进行额外的观察。在环境污染评估研究中，适应性计划允许在观测到的“热点”附近进行额外的观测。同样，在对难以接近的人群进行调查时，个体之间的社会联系可能会自适应地用于获取样本。这种设计与传统的调查设计形成鲜明对比，在传统的调查设计中，可以在进行任何观察或获得任何回应之前确定将被纳入样本的地点或人员。适应性采样研究在环境研究中有许多重要的应用，包括对濒危物种、自然资源和环境污染物的调查，以及对隐藏或难以接近的人群的科学研究。自适应抽样策略的优点包括在给定的抽样努力量下获得更好的总体数量估计的潜力。例如，对于分布非常不均匀的抽样群体，自适应集群抽样设计已被证明比传统设计更高效。适应性设计可以显著提高样本的“产量”，例如，可以观察到更多稀有物种的动物，同时允许对种群中动物总数等数量进行无偏估计。自适应设计可用于增加找到调查人员最感兴趣的值的概率，例如污染物的最高浓度。在许多对隐藏或难以接近的人群的科学研究中，自适应联系追踪设计提供了获得足够大的研究样本的唯一实际手段，因此，从这些样本中进行估计的有效方法至关重要。* * *

DMS 9626102 Thompson Adaptive sampling designs are designs in which the procedure for selecting the units to include in the sample may depend on observations made during the survey. For some populations, adaptive strategies produce substantial increases in precision of estimates compared to conventional designs with equivalent sample sizes. The research investigates new classes of adaptive designs and inference procedures and develops the needed basic theory. The research involves a combination of design-based and model-based approaches, and includes investigations in adaptive cluster sampling, adaptive allocation, adaptive graph sampling, optimal sampling strategies, multivariate methods in adaptive sampling including rapid-assessment strategies, and nonsampling errors in adaptive sampling. With adaptive sampling designs, the procedure for selecting the sample can be changed during a survey in response to observed patterns in the population. For example, in a survey of a rare, endangered animal species, whenever members of the species are detected, additional observations may be made at neighboring sites. In environmental pollution assessment studies, an adaptive plan allows additional observations to be made in the vicinity of observed "hot spots." Similarly, in surveys of hard-to-access human populations, social links between individuals may be adaptively used in obtaining the sample. Such designs are in marked contrast to conventional survey designs, in which the sites or people to be included in the sample can be determined prior to making any observations or obtaining any responses. Research in adaptive sampling has many important applications in environmental studies, including surveys of endangered species, natural resources, and environmental pollutants, as well as for scientific studies of hidden or hard-to-access human populations. Advantages of adaptive sampling strategies include the potential for obtaining better estimates of popu lation quantities with a given amount of sampling effort. Adaptive cluster sampling designs, for example, have been shown to be highly efficient relative to conventional designs for sampling populations that are very unevenly distributed. Adaptive designs can significantly increase the "yield" of the sample, so that, for example, more animals of the rare species are observed, while at the same time permitting unbiased estimation of quantities such as the total number of the animals in the population. Adaptive designs can be used to increase the probability of finding the values of most interest to investigators, such as the highest concentrations of a pollutant. In many scientific studies of hidden or hard-to-access human populations, adaptive link-tracing designs provide the only practical means for obtaining a sample large enough for study, so that effective methods for making estimates from such samples are vitally important. *** DMS 9626102 Thompson Adaptive sampling designs are designs in which the procedure for selecting the units to include in the sample may depend on observations made during the survey. For some populations, adaptive strategies produce substantial increases in precision of estimates compared to conventional designs with equivalent sample sizes. The research investigates new classes of adaptive designs and inference procedures and develops the needed basic theory. The research involves a combination of design-based and model-based approaches, and includes investigations in adaptive cluster sampling, adaptive allocation, adaptive graph sampling, optimal sampling strategies, multivariate methods in adaptive sampling including rapid-assessment strategies, and nonsampling errors in adaptive sampling. %%% With adaptive sampling designs, the procedure for selecting the sample can be changed during a survey in response to observed patterns in the population. For example, in a survey of a rare, endangered animal species, whenever members of the species are detected, additional observations may be made at neighboring sites. In environmental pollution assessment studies, an adaptive plan allows additional observations to be made in the vicinity of observed "hot spots." Similarly, in surveys of hard-to-access human populations, social links between individuals may be adaptively used in obtaining the sample. Such designs are in marked contrast to conventional survey designs, in which the sites or people to be included in the sample can be determined prior to making any observations or obtaining any responses. Research in adaptive sampling has many important applications in environmental studies, including surveys of endangered species, natural resources, and environmental pollutants, as well as for scientific studies of hidden or hard-to-access human populations. Advantages of adaptive sampling strategies include the potential for obtaining better estimates of population quantities with a given amount of sampling effort. Adaptive cluster sampling designs, for example, have been shown to be highly efficient relative to conventional designs for sampling populations that are very unevenly distributed. Adaptive designs can significantly increase the "yield" of the sample, so that, for example, more animals of the rare species are observed, while at the same time permitting unbiased estimation of quantities such as the total number of the animals in the population. Adaptive designs can be used to increase the probability of finding the values of most interest to investigators, such as the highest concentrations of a pollutant. In many scientific studies of hidden or hard-to-access human populations, adaptive link-tracing designs provide the only practical means for obtaining a sample large enough for study, so that effective methods for making estimates from such samples are vitally important. ***