In this article, we extend the statistical detection performance evaluation of linear connectivity from Sameshima et al. (in: Slezak et al. (eds.) Lecture Notes in Computer Science, 2014) via brand new Monte Carlo simulations of three widely used toy models under different data record lengths for a classic time domain multivariate Granger causality test, information partial directed coherence, information directed transfer function, and include conditional multivariate Granger causality whose behaviour was found to be anomalous.

中文翻译：

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关于格兰杰因果连通性估计量的统计性能。

在本文中，我们扩展了Sameshima等人对线性连通性的统计检测性能评估。（in：Slezak et al。（eds。）Computer Science in Computer Science，2014）通过全新的蒙特卡洛模拟对三种广泛使用的玩具模型在不同的数据记录长度下进行的经典时域多元Granger因果关系检验，信息部分有针对性的相干性，信息定向传递函数，并包括条件多元Granger因果关系，其行为被发现是异常的。