论文标题
Bradley-Terry模型识别约束的渐近比较
Asymptotic comparison of identifying constraints for Bradley-Terry models
论文作者
论文摘要
Bradley-Terry模型被广泛用于成对比较数据分析。在本文中，我们根据一般的线性可识别性约束，在其逻辑参数化中分析了Bradley-Terry模型的最大似然估计量的渐近行为。我们表明，所有比较对象的约束需要Bradley-terry得分，以零以最小化估计分数的差异之和，并建议在实践中使用此约束。
The Bradley-Terry model is widely used for pairwise comparison data analysis. In this paper, we analyze the asymptotic behavior of the maximum likelihood estimator of the Bradley-Terry model in its logistic parameterization, under a general class of linear identifiability constraints. We show that the constraint requiring the Bradley-Terry scores for all compared objects to sum to zero minimizes the sum of the variances of the estimated scores, and recommend using this constraint in practice.
