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Bayesiläinen Granger-kausaliteetti×Granger-kausaalisuustesti×
TieteenalaEkonometriaEkonometria
MenetelmäperheRegression modelRegression model
Syntyvuosi1969 (frequentist); 1984 (Bayesian treatment)1969
KehittäjäClive W. J. Granger (frequentist basis, 1969); Bayesian extension by Geweke (1984) and subsequent literatureClive W. J. Granger
TyyppiBayesian causal inference testCausality test (F-test on VAR)
AlkuperäislähdeGeweke, J. (1984). Inference and causality in economic time series models. Handbook of Econometrics, 2, 1101-1144. Elsevier. link ↗Granger, C. W. J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424–438. DOI ↗
RinnakkaisnimetBayesian Granger test, Bayesian predictive causality, BGC, Bayesian causality in meanGranger test, GC test, predictive causality test, Granger non-causality test
Liittyvät65
TiivistelmäBayesian Granger causality tests whether past values of one time series carry predictive information about another, framing the hypothesis through Bayesian inference rather than frequentist p-values. It combines a vector autoregressive (VAR) structure with prior distributions over coefficients and evaluates causal claims via posterior probabilities or Bayes factors, providing a probabilistic and nuanced alternative to the classical Granger test.The Granger causality test is a statistical hypothesis test that determines whether past values of one time series help predict future values of another, beyond what that series' own past already explains. Introduced by Clive Granger in 1969, it is the standard approach for assessing predictive causality in VAR-based time-series analysis.
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ScholarGateVertaile menetelmiä: Bayesian Granger Causality · Granger Causality Test. Haettu 2026-06-17 osoitteesta https://scholargate.app/fi/compare