手法を比較
選択した手法を並べて確認できます。異なる行はハイライト表示されます。
| ベイズ型ベクトル自己回帰（BVAR）× | ベクトル自己回帰（VAR）モデル× | |
|---|---|---|
| 分野 | 計量経済学 | 計量経済学 |
| 系統 | Regression model | Regression model |
| 提唱年≠ | 1986 | 2005 |
| 提唱者≠ | Litterman (1986); Bańbura, Giannone & Reichlin (2010) | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| 種類≠ | Bayesian multivariate time-series model | Multivariate time-series model |
| 原典≠ | Litterman, R. B. (1986). Forecasting with Bayesian Vector Autoregressions—Five Years of Experience. Journal of Business & Economic Statistics, 4(1), 25-38. DOI ↗ | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗ |
| 別名 | BVAR, Bayesian vector autoregression, Minnesota prior VAR, Bayesian VAR (BVAR) | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| 関連≠ | 5 | 4 |
| 概要≠ | Bayesian VAR adds Minnesota or other prior distributions to a vector autoregressive model to control over-parameterisation. Introduced by Litterman (1986) and extended to high dimensions by Bańbura, Giannone and Reichlin (2010), it outperforms classical VAR on short series and high-dimensional macroeconomic forecasts. | Vector Autoregression is a multivariate time-series model that treats several interdependent series symmetrically, letting each variable depend on its own past values and the past values of all the others. It is the standard tool for capturing mutual causality and joint dynamics, developed in the modern multiple-time-series tradition treated by Lütkepohl (2005). |
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