• Corpus ID: 238531458

Uncertainty quantification in the Bradley-Terry-Luce model

@inproceedings{Gao2021UncertaintyQI,
  title={Uncertainty quantification in the Bradley-Terry-Luce model},
  author={Chao Gao and Yandi Shen and Anderson Y. Zhang},
  year={2021}
}
  • Chao Gao, Yandi Shen, Anderson Y. Zhang
  • Published 8 October 2021
  • Mathematics
The Bradley-Terry-Luce (BTL) model is a benchmark model for pairwise comparisons between individuals. Despite recent progress on the first-order asymptotics of several popular procedures, the understanding of uncertainty quantification in the BTL model remains largely incomplete, especially when the underlying comparison graph is sparse. In this paper, we fill this gap by focusing on two estimators that have received much recent attention: the maximum likelihood estimator (MLE) and the spectral… 

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