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25 April 2024 |
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Article overview
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Continuity scaling: A rigorous framework for detecting and quantifying causality accurately | | Xiong Ying
; Si-Yang Leng
; Huan-Fei Ma
; Qing Nie
; Ying-Cheng Lai
; Wei Lin
; | | Date: |
26 Mar 2022 | | Abstract: | Data based detection and quantification of causation in complex, nonlinear
dynamical systems is of paramount importance to science, engineering and
beyond. Inspired by the widely used methodology in recent years, the
cross-map-based techniques, we develop a general framework to advance towards a
comprehensive understanding of dynamical causal mechanisms, which is consistent
with the natural interpretation of causality. In particular, instead of
measuring the smoothness of the cross map as conventionally implemented, we
define causation through measuring the {it scaling law} for the continuity of
the investigated dynamical system directly. The uncovered scaling law enables
accurate, reliable, and efficient detection of causation and assessment of its
strength in general complex dynamical systems, outperforming those existing
representative methods. The continuity scaling based framework is rigorously
established and demonstrated using datasets from model complex systems and the
real world. | | Source: | arXiv, 2203.14006 | | Services: | Forum | Review | PDF | Favorites | |
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