论文标题
部分定向连贯性和矢量自回归建模神话和警告
Partial Directed Coherence and the Vector Autoregressive Modelling Myth and a Caveat
论文作者
论文摘要
在这里，我们消除了挥之不去的神话，即部分定向的连贯性是矢量自回归（VAR）建模依赖性概念。实际上，我们的示例表明，它的核心是频谱分解，而var建模仅是一种非常有效和方便的设备。这通常适用于Granger因果关系估计程序，还包括瞬时Granger效应。但是，必须对通过非最低相机制生成的多元数据之间的连通性进行护理，因为可能会错误捕获。
Here we dispel the lingering myth that Partial Directed Coherence is a Vector Autoregressive (VAR) Modelling dependent concept. In fact, our examples show that it is spectral factorization that lies at its heart, for which VAR modelling is a mere, albeit very efficient and convenient, device. This applies to Granger Causality estimation procedures in general and also includes instantaneous Granger effects. Care, however, must be exercised for connectivity between multivariate data generated through nonminimum phase mechanisms as it may possibly be incorrectly captured.
