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Test di causalità di Granger×Analisi Quantitativa delle Ricorrenze (RQA)×
CampoEconometriaSistemi complessi
FamigliaRegression modelMachine learning
Anno di origine19692007
IdeatoreClive W. J. GrangerMarwan, Romano, Thiel & Kurths
TipoTime-series predictive causality testNonlinear time-series characterization
Fonte seminaleGranger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. DOI ↗Marwan, N., Romano, M. C., Thiel, M., & Kurths, J. (2007). Recurrence plots for the analysis of complex systems. Physics Reports, 438(5–6), 237–329. DOI ↗
AliasGranger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik TestiRQA, Recurrence Plot Analysis, Nonlinear Recurrence Analysis, Tekrarlama Kantifikasyon Analizi
Correlati52
SintesiThe Granger causality test, introduced by Clive W. J. Granger in 1969, assesses whether the past values of one time series help predict another beyond what the latter's own past already explains. It defines causality in a strictly predictive sense rather than as a structural or physical cause.Recurrence Quantification Analysis (RQA) is a nonlinear method for characterizing the dynamics of a time series by quantifying the small-scale structure of its recurrence plot. Introduced in its modern, comprehensive form by Marwan, Romano, Thiel, and Kurths in 2007, RQA extracts scalar measures — such as recurrence rate, determinism, laminarity, and Shannon entropy — that capture periodicity, chaos, stationarity, and transitions in complex dynamical systems.
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ScholarGateConfronta i metodi: Granger Causality · Recurrence Quantification Analysis. Consultato il 2026-06-18 da https://scholargate.app/it/compare