Bayesian Approach to Single Variable Sampling Plans
针对多项式损失函数下的变量抽样问题，提出贝叶斯框架下的简单有限算法来确定最优单次抽样方案，并针对对称双侧决策函数给出近似解法。
In this paper, we develop a model of sampling plans for variables with a polynomial loss function, in which the decision function is either one-sided or two-sided. Based on a Bayesian approach, we suggest a simple finite algorithm for the determination of the optimal single sampling plan. Furthermore, for the case of a symmetric two-sided decision function, we propose an approximate method for determining its optimal single sampling plan.