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Systematic sampling is a minimum support design

机译:系统采样是最低的支持设计

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摘要

In order to select a sample in a finite population of N units with given inclusion probabilities, it is possible to define a sampling design on at most N samples that have a positive probability of being selected. Designs defined on minimal sets of samples are called minimum support designs. It is shown that, for any vector of inclusion probabilities, systematic sampling always provides a minimum support design. This property makes it possible to extensively compute the sampling design and the joint inclusion probabilities. Random systematic sampling can be viewed as the random choice of a minimum support design. However, even if the population is randomly sorted, a simple example shows that some joint inclusion probabilities can be equal to zero. Another way of randomly selecting a minimum support design is proposed, in such a way that all the samples have a positive probability of being selected, and all the joint inclusion probabilities are positive.
机译:为了以给定的包含概率选择有限数量的N个单位中的样本,可以在最多N个样本中定义正样本被选择的样本设计。在最小样本集上定义的设计称为最小支持设计。结果表明,对于任何包含概率的向量,系统抽样总是提供最小的支持设计。此属性使得可以广泛地计算采样设计和联合包含概率。随机系统抽样可以看作是最小支持设计的随机选择。但是,即使总体是随机排序的,一个简单的示例也显示某些联合包含概率可以等于零。提出了另一种随机选择最小支撑设计的方式,即所有样本均具有正概率被选择,而所有联合包含概率均为正。

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