Interactions and time shape many aspects of life. Everyday activities -- like conversations, emails, money transfers, citations, and even acts of violence -- are relational events: interactions between a sender and a receiver at a specific moment. At the intersection of event-history analysis and network modelling, relational event models (REMs) offer a powerful framework for studying when and why these events occur. Recent advances have made it possible to express REMs as generalized additive models, allowing researchers to capture complex, non-linear patterns over time. While an essay and a comprehensive review exist, a hands-on tutorial paper on REMs is still missing. This work fills that gap. It provides a practical introduction to REMs, incorporating the latest developments in the field. It demonstrates how to simulate synthetic relational-event data and walks through several empirical applications, comparing different modelling and inference strategies. By bringing together theory, simulation, and application, this tutorial lowers the barrier to entry and makes REMs a more accessible and practical tool.

翻译：互动与时间塑造了生活的方方面面。日常活动——如对话、电子邮件、资金转账、引用行为甚至暴力行为——都是关系事件：在特定时刻发生在发送者与接收者之间的互动。作为事件史分析与网络建模的交叉领域，关系事件模型（REMs）为研究这些事件发生的时间与原因提供了强大的分析框架。近年来的进展使得将关系事件模型表达为广义加性模型成为可能，使研究者能够捕捉随时间变化的复杂非线性模式。尽管已有专题论文和综合性综述，但关于REMs的实践操作教程仍付之阙如。本文填补了这一空白，提供了融合该领域最新发展的REMs实用入门指南。文中演示了如何模拟合成关系事件数据，并通过多个实证应用案例比较不同的建模与推断策略。通过整合理论、模拟与应用，本教程降低了入门门槛，使REMs成为更易用、更具实用价值的分析工具。