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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Recurrence measure of conditional dependence and applications

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Ramos, Antonio M. T. ; Builes-Jaramillo, Alejandro ; Poveda, German ; Goswami, Bedartha ; Macau, Elbert E. N. ; Kurths, Juergen ; Marwan, Norbert
Total Authors: 7
Document type: Journal article
Source: Physical Review E; v. 95, n. 5 MAY 11 2017.
Web of Science Citations: 7

Identifying causal relations from observational data sets has posed great challenges in data-driven causality inference studies. One of the successful approaches to detect direct coupling in the information theory framework is transfer entropy. However, the core of entropy-based tools lies on the probability estimation of the underlying variables. Herewe propose a data-driven approach for causality inference that incorporates recurrence plot features into the framework of information theory. We define it as the recurrence measure of conditional dependence (RMCD), and we present some applications. The RMCD quantifies the causal dependence between two processes based on joint recurrence patterns between the past of the possible driver and present of the potentially driven, excepting the contribution of the contemporaneous past of the driven variable. Finally, it can unveil the time scale of the influence of the sea-surface temperature of the Pacific Ocean on the precipitation in the Amazonia during recent major droughts. (AU)

FAPESP's process: 14/14229-2 - Non-linear and chaotic dynamics with spatial distribution and their characterization by using the complex network approach
Grantee:Antônio Mário de Torres Ramos
Support type: Scholarships in Brazil - Post-Doctorate
FAPESP's process: 15/07373-2 - Development of quantifiers through Information Theory techniques and probabilistic graphical models with application in the Amazon Region
Grantee:Antônio Mário de Torres Ramos
Support type: Scholarships abroad - Research Internship - Post-doctor
FAPESP's process: 15/50122-0 - Dynamic phenomena in complex networks: basics and applications
Grantee:Elbert Einstein Nehrer Macau
Support type: Research Projects - Thematic Grants