Measuring the uncertainty of coupling
1 School of Economics and Management, Beijing Jiaotong University - Beijing 100044, PRC
2 Department of Mathematics, School of Science, Beijing Jiaotong University - Beijing 100044, PRC
Received: 16 November 2014
Accepted: 26 June 2015
A new information-theoretic measure, called coupling entropy, is proposed here to detect the causal links in complex systems by taking into account the inner composition alignment of temporal structure. It is a permutation-based asymmetric association measure to infer the uncertainty of coupling between two time series. The coupling entropy is found to be effective in the analysis of Hénon maps, where different noises are added to test its accuracy and sensitivity. The coupling entropy is also applied to analyze the relationship between unemployment rate and CPI change in the U.S., where the CPI change turns out to be the driving variable while the unemployment rate is the responding one.
PACS: 05.45.Tp – Time series analysis / 89.20.-a – Interdisciplinary applications of physics / 89.75.-k – Complex systems
© EPLA, 2015