Bayesian subset selection approach to ranking normal means
Bayesian subset selection approach to ranking normal means
复制标题
对正态平均值进行排序的贝叶斯子集选择方法
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
J. Stamey
中科院分区：
文献类型：
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作者：
Cody Hamilton;T. L. Bratcher;J. Stamey
在本文中，我们考虑一种贝叶斯方法来解决正态分布总体均值的排序问题，这是生物科学中一个常见的问题。我们使用一种决策理论方法以及一个简单的损失函数来确定一组候选排序。这个损失函数使研究人员能够在不包含正确排序的风险和增加所选排序数量的风险之间进行权衡。我们将我们的新方法应用于一个关于锌对硅藻物种多样性影响的实例。
In this, article we consider a Bayesian approach to the problem of ranking the means of normal distributed populations, which is a common problem in the biological sciences. We use a decision-theoretic approach with a straightforward loss function to determine a set of candidate rankings. This loss function allows the researcher to balance the risk of not including the correct ranking with the risk of increasing the number of rankings selected. We apply our new procedure to an example regarding the effect of zinc on the diversity of diatom species.