ScholarGate
Asistents

Salīdzināt metodes

Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.

Grindžera koeficientu pārbaude×Rekurences kvantitatīvās analīzes (RQA) metode×
NozareEkonometrijaKompleksās sistēmas
SaimeRegression modelMachine learning
Izcelsmes gads19692007
AutorsClive W. J. GrangerMarwan, Romano, Thiel & Kurths
TipsTime-series predictive causality testNonlinear time-series characterization
PirmavotsGranger, 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 ↗
Citi nosaukumiGranger causality test, Granger non-causality test, predictive causality test, Granger Nedensellik TestiRQA, Recurrence Plot Analysis, Nonlinear Recurrence Analysis, Tekrarlama Kantifikasyon Analizi
Saistītās52
KopsavilkumsThe 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.
ScholarGateDatu kopa
  1. v1
  2. 1 Avoti
  3. PUBLISHED
  1. v1
  2. 1 Avoti
  3. PUBLISHED

Doties uz meklēšanu Lejupielādēt slaidus

ScholarGateSalīdzināt metodes: Granger Causality · Recurrence Quantification Analysis. Izgūts 2026-06-18 no https://scholargate.app/lv/compare