We introduce a family of parsimonious network models that are intended to generalize the configuration model to temporal settings. We present consistent estimators for the model parameters and perform numerical simulations to illustrate the properties of the estimators on finite samples. We also develop analytical solutions for basic and effective reproductive numbers for the early stage of discrete-time SIR spreading process. We apply three distinct temporal configuration models to empirical student proximity networks and compare their performance.

翻译：我们提出了一类简约的网络模型，旨在将配置模型推广至时间动态场景。我们给出了模型参数的一致性估计量，并通过数值模拟展示了有限样本下估计量的性质。针对离散时间SIR传播过程的早期阶段，我们推导了基本再生数与有效再生数的解析解。我们将三种不同的时间配置模型应用于实证学生邻近网络，并比较了它们的性能表现。