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A Bayesian approach to paired comparison rankings based on a graphical model

机译:基于图形模型的配对比较排名的贝叶斯方法

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摘要

A Bayesian method for finding an optimal ranking in scalar functions of K population parameters is developed. This is based on the paired comparison experimental arrangement whose results can naturally be represented by a completely oriented graphical model. Introducing posterior preference probabilities satisfying a strong stochastic transitivity condition to the model, a criterion for the optimal ranking is suggested. Necessary theories involved in the method and some computational aspects are provided. As illustrated examples, ranking in generalized variances of K multivariate normal populations and in products of independent normal means are given.
机译:提出了一种贝叶斯方法,用于找到K总体参数的标量函数的最佳排序。这是基于配对的比较实验安排,其结果自然可以由完全定向的图形模型表示。将满足强随机传递性条件的后验概率引入模型,提出了最优排序的准则。提供了该方法涉及的必要理论和一些计算方面。如图所示,给出了K个多元正态总体的广义方差和独立正态平均值乘积中的排名。

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