标题： 布拉德利-特里模型的约束识别的渐近比较 显示英文标题

标题： Asymptotic comparison of identifying constraints for Bradley-Terry models

摘要： 布拉德利-特雷模型广泛用于成对比较数据分析。本文分析了布拉德利-特雷模型在逻辑参数化下最大似然估计量的渐近行为，适用于一类广义线性可识别约束条件。我们证明了要求所有被比较对象的布拉德利-特雷得分总和为零的约束条件可以最小化估计得分方差之和，并建议在实际应用中使用该约束条件。 显示英文摘要

摘要： 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.