A Bayesian Approach to Some Best Population Problems
A Bayesian Approach to Some Best Population Problems
复制标题
一些最佳总体问题的贝叶斯方法
DOI：
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发表时间：
1964
期刊：
影响因子：
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通讯作者：
G. Tiao
中科院分区：
文献类型：
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作者：
I. Guttman;G. Tiao
翻译后摘要：采用贝叶斯方法的某些最佳人口问题进行了调查。这种方法的一个主要优点是，满意的决策过程中，可以得到滋扰参数的存在。贝叶斯定理的使用允许人们从许多角度分析最佳人口问题。最佳人口问题的一般描述概述。“最佳”的标准被认为是统计学家的“效用”函数。然后采用的决策程序是基于最大化后验期望效用的原则。讨论了该方法在正态总体和指数总体抽样中的应用。定义最佳总体的标准是在某个给定区间内考虑的总体的覆盖率。这些程序是一致的。给出了考虑准则后分布的决策分析。这一扩展使其他决策程序提出可能是更合适的，在某些情况下比后期望效用最大化的原则。
Abstract : Certain best population problems adopting a Bayesian approach were investigated. One main advantage of such an approach is that satisfactory decision procedures can be obtained in the presence of nuisance parameters. The use of Bayes' theorem allows one to analyze best population problems from many points of view. A general description of best population problems is outlined. The criterion for 'bestness' is regarded as a 'utility' function of the statistician. The decision procedure then adopted is based upon the principle of maximizing posterior expected utility. The application of this procedure when sampling from normal populations and exponential populations was discussed. The criterion defining the best population is taken to be the coverage of the population considered in a certain given interval. The procedures are shown to be consistent. The decision analysis by considering the pos terior distribution of the criterion is presented. This extension enables other decision procedures to be proposed which may be more appropriate in certain situations than that resulting from the principle of maximizing posterior expected utility.