A Bayesian approach to paired comparison rankings based on a graphical model
A Bayesian approach to paired comparison rankings based on a graphical model
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基于图形模型的配对比较排名的贝叶斯方法
DOI：
10.1016/j.csda.2004.01.002
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发表时间：
2005
期刊：
影响因子：
--
通讯作者：
Hea
中科院分区：
文献类型：
--
作者：
Hea
提出了在K个总体参数的标量函数中寻找最优排序的贝叶斯方法。这是基于成对比较的实验安排，其结果自然可以用完全面向的图形模型来表示。在模型中引入满足强随机传递性条件的后验偏好概率，提出了最优排序准则。给出了该方法所涉及的必要理论和计算方面的一些问题。作为例证，给出了K个多元正态总体的广义方差排序和独立正态均值的乘积排序。
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.