Motivated by a study of United Nations voting behaviors, we introduce a regression model for a series of networks that are correlated over time. Our model is a dynamic extension of the additive and multiplicative effects network model (AMEN) of Hoff (2019). In addition to incorporating a temporal structure, the model accommodates two types of missing data thus allows the size of the network to vary over time. We demonstrate via simulations the necessity of various components of the model. We apply the model to the United Nations General Assembly voting data from 1983 to 2014 (Voeten (2013)) to answer interesting research questions regarding international voting behaviors. In addition to finding important factors that could explain the voting behaviors, the model-estimated additive effects, multiplicative effects, and their movements reveal meaningful foreign policy positions and alliances of various countries.

翻译：受联合国投票行为研究的启发，我们针对一系列随时间相关的网络引入了一个回归模型。该模型是Hoff（2019）提出的加性和乘性效应网络模型（AMEN）的动态扩展。除了纳入时间结构外，该模型还适应了两种缺失数据类型，从而允许网络规模随时间变化。我们通过模拟论证了模型各组成部分的必要性。我们将该模型应用于1983年至2014年的联合国大会投票数据（Voeten（2013）），以回答有关国际投票行为的有趣研究问题。除了揭示能够解释投票行为的重要因素外，模型估计的加性效应、乘性效应及其变化趋势还揭示了不同国家有意义的外交政策立场与联盟关系。