Numerical specification of discrete least favorable prior distributions
Numerical specification of discrete least favorable prior distributions
复制标题
离散最不利先验分布的数值规范
DOI：
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发表时间：
1987
期刊：
影响因子：
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通讯作者：
P. Kempthorne
中科院分区：
文献类型：
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作者：
P. Kempthorne
一类广泛的统计决策问题解决的极小极大程序，这是贝叶斯关于离散最不利的先验分布。一个通用的算法，用于指定这样的分布，利用极大极小程序的统计特性。该算法的特点，同时最小化贝叶斯风险和最大风险下不同的损失函数在一个简单的多目标决策问题的程序。
A broad class of statistical decision problems are solved by minimax procedures which are Bayes with respect to discrete least favorable prior distributions. A general algorithm for specifying such distributions is presented which exploits the statistical properties of minimax procedures. The algorithm is demonstrated by characterizing the procedure which simultaneously minimizes a Bayes risk and a maximum risk under different loss functions in a simple multi-objective decision problem.