格兰杰因果影响较大的方向是否与信息流的方向相同?

Praveen Venkatesh, P. Grover
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引用次数: 10

摘要

格兰杰因果关系是一个随机过程X对另一个过程y的“因果影响”的既定统计度量。随着其最近的推广-定向信息-格兰杰因果关系已广泛用于神经科学,以及一般复杂的相互关联系统,以推断统计因果影响。最近,许多作品沿着正向和反向链接(从X到Y和从Y到X)比较格兰杰因果关系指标,并将更大因果影响的方向解释为“信息流的方向”。在本文中,我们质疑通过比较格兰杰因果关系或有向信息沿正向和反向链接所得到的方向是否总是与信息流的方向相同。我们使用两个简单的理论实验来探索这个问题,其中信息流的真正方向(“基础真相”)是通过设计知道的。实验基于一个带有反馈通道的通信系统,并采用了一种受Schalkwijk和Kailath工作启发的策略。我们表明,在这些实验中,信息流的方向可以与更大的格兰杰因果影响或定向信息的方向相反。我们还提供了信息理论的直觉,说明为什么这样的反例并不令人惊讶,以及为什么基于格兰杰因果关系的信息流推断只会在更大的网络中变得更加脆弱。我们的结论是,不能使用格兰杰因果关系的比较/差异来推断信息流的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Is the direction of greater Granger causal influence the same as the direction of information flow?
Granger causality is an established statistical measure of the “causal influence” that one stochastic process X has on another process Y. Along with its more recent generalization - Directed Information - Granger Causality has been used extensively in neuroscience, and in complex interconnected systems in general, to infer statistical causal influences. More recently, many works compare the Granger causality metrics along forward and reverse links (from X to Y and from Y to X), and interpret the direction of greater causal influence as the “direction of information flow”. In this paper, we question whether the direction yielded by comparing Granger Causality or Directed Information along forward and reverse links is always the same as the direction of information flow. We explore this question using two simple theoretical experiments, in which the true direction of information flow (the “ground truth”) is known by design. The experiments are based on a communication system with a feedback channel, and employ a strategy inspired by the work of Schalkwijk and Kailath. We show that in these experiments, the direction of information flow can be opposite to the direction of greater Granger causal influence or Directed Information. We also provide information-theoretic intuition for why such counterexamples are not surprising, and why Granger causality-based information-flow inferences will only get more tenuous in larger networks. We conclude that one must not use comparison/difference of Granger causality to infer the direction of information flow.
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