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数据存储量的扩大和计算能力的提升为基于观测数据推断时间序列的因果关系开辟了新途径。在时间序列因果推断的基本性质和研究现状的基础上，系统梳理了5种基于观测数据的时间序列因果推断方法，即Granger因果分析方法、基于信息论的方法、因果网络结构学习算法、基于结构因果模型的方法和基于非线性状态空间模型的方法。然后，根据不同应用场景的数据特点，结合方法的功能和适配性，对基于观测数据的时间序列因果推断方法在经济金融、医疗和生物学、地球系统科学和其他工程领域的典型应用进行了简要介绍。最后，结合时间序列因果推断的重难点问题，比较5种方法的优缺点，分析下一步研究重点，展望未来的研究方向。

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