A Stochastic Model For Auditing
本文提出一个贝叶斯模型，通过平衡抽样成本与未发现重大错误的风险来确定审计中的样本量，并探讨了用连续搜索替代离散抽样的方法以得到更明确的解。
Auditing is based on random sampling from the records of a company. This paper considers a Bayesian model for determining the sample sizes by finding a balance between the cost of sampling and the risk of leaving major faults undiscovered. It leads to a dynamic programming problem which involves substantial computations, but a slightly different approach in which discrete sampling is replaced by a continuous search for faults produces more explicit solutions.