因果影响分析是一种统计方法，通过比较观察数据与反事实场景来估计干预措施的因果效应，使用结构时间序列模型和吉布斯采样技术。
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因果影响分析（CausalImpact Analysis）是一种统计方法，旨在通过将观察到的数据与反事实场景进行比较来估计干预措施的因果效应——即在没有干预的情况下会发生什么。此分析利用结构时间序列（Structural Time Series, STS）模型来捕捉潜在的数据生成过程，并通过吉布斯采样（Gibbs Sampling）这一贝叶斯推断技术推导出模型参数的后验分布。
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