Robust Bayesian Bounds for Monetary-Unit Sampling in Auditing
研究了审计中货币单位抽样的Cox和Snell贝叶斯界限，发现保守先验参数可使该界限在多种总体下具有经典置信性质。
Mixture distributions combining a probability mass at zero and a continuous density function for positive outcomes are frequently found in auditing. The Cox and Snell bound for evaluating the results of monetary unit sampling is a Bayesian bound utilizing prior information designed for such mixture distributions. In this paper it is shown that conservative prior parameter values for the Cox and Snell bound can be found such that this bound possesses classical confidence properties in repeated sampling from a wide variety of possible realized populations.