Võrdle meetodeid

	Granger'i põhjuslikkuse test	Rekurrensi kvantifitseerimise analüüs (RQA)
Valdkond	Ökonomeetria	Komplekssüsteemid
Perekond	Regression model	Machine learning
Tekkeaasta	1969	2007
Looja	Clive W. J. Granger	Marwan, Romano, Thiel & Kurths
Tüüp	Time-series predictive causality test	Nonlinear time-series characterization
Algallikas	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.
Rööpnimetused	Granger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik Testi	RQA, Recurrence Plot Analysis, Nonlinear Recurrence Analysis, Tekrarlama Kantifikasyon Analizi
Seotud	5	2
Kokkuvõte	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.