方法对比
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| 贝叶斯格兰杰因果关系× | 格兰杰因果检验× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1969 (frequentist); 1984 (Bayesian treatment) | 1969 |
| 提出者≠ | Clive W. J. Granger (frequentist basis, 1969); Bayesian extension by Geweke (1984) and subsequent literature | Clive W. J. Granger |
| 类型≠ | Bayesian causal inference test | Causality test (F-test on VAR) |
| 开创性文献≠ | Geweke, 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 ↗ |
| 别名 | Bayesian Granger test, Bayesian predictive causality, BGC, Bayesian causality in mean | Granger test, GC test, predictive causality test, Granger non-causality test |
| 相关≠ | 6 | 5 |
| 摘要≠ | Bayesian 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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