Módszerek összehasonlítása

	Granger Causality	Rekurrencia Kvantifikációs Analízis (RQA)
Tudományterület	Ökonometria	Komplex rendszerek
Módszercsalád	Regression model	Machine learning
Keletkezés éve	1969	2007
Megalkotó	Clive W. J. Granger	Marwan, Romano, Thiel & Kurths
Típus	Time-series predictive causality test	Nonlinear time-series characterization
Alapmű	Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438.	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.
Alternatív nevek	Granger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi	RQA, Recurrence Plot Analysis, Nonlinear Recurrence Analysis, Tekrarlama Kantifikasyon Analizi
Kapcsolódó	5	2
Összefoglaló	The 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.