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Jun, 2024
使用高阶 Markov 切换模型识别非平稳因果结构
Identifying Nonstationary Causal Structures with High-Order Markov Switching Models
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Carles Balsells-Rodas, Yixin Wang, Pedro A. M. Mediano, Yingzhen Li
TL;DR
通过建立高阶马尔可夫切换模型的可辨识性，我们提出了基于制度依赖因果关系的发现方法，并通过实证研究展示了该方法在高阶制度依赖结构估计上的可扩展性，并对脑活动数据的适用性进行了说明。
Abstract
causal discovery
in
time series
is a rapidly evolving field with a wide variety of applications in other areas such as climate science and neuroscience. Traditional approaches assume a stationary causal graph, wh
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