Causal inference from noisy time-series data - Testing the Convergent Cross-Mapping algorithm in the presence of noise and external influence

Abstract

Convergent Cross-Mapping (CCM) has shown high potential to perform causal inference in the absence of detailed models. This has implications for the understanding of complex information systems, as well as complex systems more generally. This article assesses the strengths and weaknesses of the CCM algorithm by varying coupling strength and noise levels in… (More)
DOI: 10.1016/j.future.2016.12.009

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