Score Driven Generalized Fitness Model for Sparse and Weighted Temporal Networks
稀疏加权时变网络的得分驱动广义适应度模型
While the vast majority of the literature on models for temporal networks focuses on binary graphs, often one can associate a weight to each link. In such cases the data are better described by a weighted, or valued, network. An important well known fact is that real world weighted networks are typically sparse. We propose a novel time varying parameter model for sparse and weighted temporal networks as a combination of the fitness model, appropriately extended, and the…