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Interval Estimation Approach to Counting by Weighing: A Sequential Scheme

机译：称重计数的区间估计方法：一种顺序方案

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Considerable time and energy involved in complete counting of large, but pre-specified, batch of N_s items could be saved by using weights of items. This article considers the case when the underlying distribution of weights, and its mean and variance are unknown. The problem is then reduced to that of finding an estimator of the mean and an optimal (small) sample size based on which a number N_n of items in the batch can be determined. Using a fixed-width interval criterion, Nickerson [Nickerson, D.M. Another look at counting by weighing. Commun. Statist. Simula. 1993, 22 (2), 323-343] derived an optimal sample size, but it depends on the unknown coefficient of variation. For this case, we propose a batch-type sequential sampling scheme which requires substantially fewer sampling operations and no prior knowledge of the coefficient of variation, but performs as well as Nickerson's and other available procedures in the literature. This shows that a little bit of sampling using substantially fewer sampling operations can significantly reduce the effort of complete counting.
机译：通过使用项目权重，可以完全节省大量但预先指定的N_s个项目的批处理所花费的大量时间和精力。本文考虑了权重的基础分布及其均值和方差未知的情况。然后将问题简化为寻找均值的估计量和最佳（小）样本量，由此可以确定批次中N_n个项目。使用固定宽度间隔标准，尼克森[Nickerson，D.M.再看一下称重计数。公社统计员。 Simula。 [1993，22（2），323-343]得出了最佳样本量，但这取决于未知的变异系数。对于这种情况，我们提出了一种批处理类型的顺序采样方案，该方案所需的采样操作少得多，并且无需先验变异系数，但其性能与尼克森的方法和文献中的其他可用方法一样好。这表明使用少得多的采样操作进行一点采样可以显着减少完成计数的工作量。

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