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Causal Analysis of Air Pollution Based on Mixed Relation Index

Yuming Zhang, Mingwei Li, Nan Zhang

Abstract

Granger causality theory is widely used in data-driven analysis. In multivariable systems, unique, redundant, synergistic and mixed information structures may lead to distorted or complex causality. Based on mutual information and Granger causality theory, this paper decomposed multivariate information structure, and proposed Average Granger causality index and mixed relation index to reduce the data dimension and computational complexity. The experiments examine the causality of air pollutants in Beijing and its surrounding cities, and the results show that the method is feasible.

Keywords

Granger Causality; Redundancy; Synergy; Information Structure Decomposition; Air Pollution

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References

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DOI: https://doi.org/10.18686/pes.v5i1.1603

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