标题： 具有贝叶斯决策规则的最优序贯程序 显示英文标题

标题： Optimal sequential procedures with Bayes decision rules

摘要： 本文考虑了一般离散时间随机过程序贯统计推断的一个一般问题。 该问题是在由于错误决策导致的贝叶斯风险不超过某个给定界限的条件下，使平均样本量最小化。 我们刻画了这个问题中最优序贯停止规则的形式。 特别是，当贝叶斯风险包括因错误决策导致的损失和观察的成本时，我们得到了最优序贯决策程序形式的刻画。 显示英文摘要

摘要： In this article, a general problem of sequential statistical inference for general discrete-time stochastic processes is considered. The problem is to minimize an average sample number given that Bayesian risk due to incorrect decision does not exceed some given bound. We characterize the form of optimal sequential stopping rules in this problem. In particular, we have a characterization of the form of optimal sequential decision procedures when the Bayesian risk includes both the loss due to incorrect decision and the cost of observations.