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Bayesowska przyczynowość Grangera×Autoregresja Wektorowa (VAR)×
DziedzinaEkonometriaEkonometria
RodzinaRegression modelRegression model
Rok powstania1969 (frequentist); 1984 (Bayesian treatment)1980
TwórcaClive W. J. Granger (frequentist basis, 1969); Bayesian extension by Geweke (1984) and subsequent literatureChristopher A. Sims
TypBayesian causal inference testMultivariate time-series model
Źródło pierwotneGeweke, J. (1984). Inference and causality in economic time series models. Handbook of Econometrics, 2, 1101-1144. Elsevier. link ↗Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗
Inne nazwyBayesian Granger test, Bayesian predictive causality, BGC, Bayesian causality in meanVAR, VAR model, vector autoregressive model, multivariate autoregression
Pokrewne65
PodsumowanieBayesian 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.Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance.
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ScholarGatePorównaj metody: Bayesian Granger Causality · Vector Autoregression. Pobrano 2026-06-15 z https://scholargate.app/pl/compare