A Note on Sampling to Locate Rare Defectives with Strong Prior Evidence
本文用贝叶斯模型计算样本中未发现缺陷品的概率，针对均匀先验和强先验两种情况给出了样本量确定准则，帮助判断是否需要抽样或仅凭先验信息即可。
Inference about the number of defectives in a finite population is considered. Using a Bayesian model for computing the probability of unobserved defectives given the results of the sample, a criterion for sample size determination is introduced for two cases: (i) when there is a uniform prior, and (ii) when there is strong prior information. Depending on the value of the population size N, the savings in terms of a sampling effort rather than a census can be significant. When there is strong prior information, an explicit decision rule is given for determining whether a sample is needed or if the prior information alone is sufficient.