A General Pairwise Comparison Model for Extremely Sparse Networks

• Published in: Journal of the American Statistical Association Vol. 118; no. 544; pp. 2422 - 2432
• Main Authors: Han, Ruijian, Xu, Yiming, Chen, Kani
• Format: Journal Article
• Language: English
• Published: Alexandria Taylor & Francis 02.10.2023; Taylor & Francis Ltd
• Subjects: Asymptotic properties; Entry-wise error; Flexibility; Graph topology; Maximum likelihood estimation; Maximum likelihood estimators; Networks; Parameterization; Simulation; Sparsity; statistical analysis; Statistics; Topology; Uniform consistency

Statistical estimation using pairwise comparison data is an effective approach to analyzing large-scale sparse networks. In this article, we propose a general framework to model the mutual interactions in a network, which enjoys ample flexibility in terms of model parameterization. Under this setup,...