本质上是ML ASN-Minimax双重抽样计划
Essentially ML ASN-Minimax double sampling plans
摘要：
本文研究了具有未知标准差和双侧规格限的正态分布质量特性的ASN-Minimax（AM）双重抽样方案。基于不合格率p的估计量p*，即最大似然（ML）估计量，分别利用首样和合并样的随机变量p* 1和p* p，计算AM-双重抽样方案。给定p_1、p_2、α和β，基于相同估计量的AM-双重抽样方案都不具有平均样本量的下最大值，同时满足经典的两点条件。
英文摘要：
Subject of this paper is ASN-Minimax (AM) double sampling plans by variables for a normally distributed quality characteristic with unknown standard deviation and two-sided specification limits. Based on the estimator p* of the fraction defective p, which is essentially the Maximum-Likelihood (ML) estimator, AM-double sampling plans are calculated by using the random variables p*_1 and p*_p relating to the first and pooled samples, respectively. Given p_1, p_2, α, and β, no other AM-double sampling plans based on the same estimator feature a lower maximum of the average sample number (ASN) while fulfilling the classical two-point condition on the corresponding operation characteristic (OC).
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
