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首页> 外文期刊>The American statistician >Teaching Decision Theory Proof Strategies Using a Crowdsourcing Problem
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Teaching Decision Theory Proof Strategies Using a Crowdsourcing Problem

机译:使用众包问题的教学决策理论证明策略

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摘要

Teaching how to derive minimax decision rules can be challenging because of the lack of examples that are simple enough to be used in the classroom. Motivated by this challenge, we provide a new example that illustrates the use of standard techniques in the derivation of optimal decision rules under the Bayes and minimax approaches. We discuss how to predict the value of an unknown quantity,theta.epsilon {0, 1}, given the opinions of n experts. An important example of such crowdsourcing problem occurs in modern cosmology, where theta indicates whether a given galaxy is merging or not, and Y-1,..., Y-n are the opinions from n astronomers regarding theta We use the obtained prediction rules to discuss advantages and disadvantages of the Bayes andminimax approaches to decision theory. The material presented here is intended to be taught to first- year graduate students.
机译:由于缺少足够简单的示例以供课堂使用,因此教授如何导出极小极大决策规则可能会具有挑战性。受这一挑战的激励,我们提供了一个新的示例,该示例说明了在贝叶斯和最小极大值方法下推导最佳决策规则时使用标准技术的情况。我们讨论了如何根据n位专家的意见预测未知量theta.epsilon {0,1}的值。这样的众包问题的一个重要例子发生在现代宇宙学中,其中theta指示给定星系是否正在合并,Y-1,...,Yn是n个天文学家关于theta的观点。我们使用获得的预测规则来讨论贝叶斯方法的优缺点和决策理论的极小极大方法。这里介绍的材料旨在教授一年级研究生。

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