Hurdle Network Model With Latent Dynamic Shrinkage For Enhanced Edge Prediction in Zero-Inflated Directed Network Time Series
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潜在动态收缩障碍网络模型：零膨胀有向网络时间序列的边预测
- 研究问题
- 如何同时建模贸易关系是否存在及贸易量，刻画时变网络依赖，并处理只在发生贸易时才能观察到的边信息？
- 方法与思路
- 作者提出动态障碍网络模型，以二元和连续分量共享节点潜在结构，结合动态收缩与广义 logistic 链接联合建模。
- 材料陈述的贡献
- 摘要称模型能够结合协变量与多类依赖，在模拟和服装业双边贸易应用中，相较静态或独立模型改善估计与预测。
- 阅读关注点
- 应核对未发生贸易时潜在贸易量的处理、共享潜在结构的识别，以及动态收缩设定和预测评估中的时间划分。
- 阅读边界
- 所给版本为 arXiv 预印本，同行评审或期刊接收未核实；摘要未说明先验细节、缺失机制假设及性能改善幅度。
原文摘要
This article aims to model international trade relationships among 29 countries in the apparel industry between 1994 and 2013. Bilateral trade flows can be represented as a directed network, where nodes correspond to countries and directed edges indicate trade flows (i.e., whether one country exported to another in a given year). Additionally, node (e.g., GDP) and edge-specific (e.g., labor provision) covariates are also available. The study focuses on two key challenges: (1) capturing multiple forms of temporal and network dependence, and dependence on covariates; and (2) accounting for potential trade volume as an important but partially observed edge-specific covariate, which is only available for country pairs that engaged in trade. To address these challenges, we introduce the dynamic hurdle network model (Hurdle-Net) for zero-inflated directed network time series that incorporates several novel features. First, it represents the time series as a paired binary and continuous time series and utilizes a hurdle model that effectively handles sparsity in edge occurrence. Second, the model captures evolving network dependencies using node-specific latent variables governed by a dynamic shrinkage process. Third, it leverages a shared latent structure across the binary and continuous components, reflecting the fact that both networks involve the same nodes. Finally, the model employs a generalized logistic link function to relate edge occurrence to edge weight, allowing for a parsimonious and coherent hierarchical Bayesian framework that jointly models both network components. Compared to static or independent models, Hurdle-Net provides improved model selection, estimation, and prediction performance for analyzing international trade patterns. Its effectiveness is demonstrated through simulation studies and an application to bilateral trade flow data.