قارن الطرق
راجع الطرق التي اخترتها جنبًا إلى جنب؛ الصفوف المختلفة مميَّزة.
| الانحدار الذاتي المتجه البايزي (BVAR)× | نموذج الانحدار الذاتي المتجهي (VAR)× | |
|---|---|---|
| المجال | الاقتصاد القياسي | الاقتصاد القياسي |
| العائلة | Regression model | Regression model |
| سنة النشأة≠ | 1986 | 2005 |
| صاحب الطريقة≠ | Litterman (1986); Bańbura, Giannone & Reichlin (2010) | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| النوع≠ | Bayesian multivariate time-series model | Multivariate time-series model |
| المصدر التأسيسي≠ | 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 ↗ |
| الأسماء البديلة | BVAR, Bayesian vector autoregression, Minnesota prior VAR, Bayesian VAR (BVAR) | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| ذات صلة≠ | 5 | 4 |
| الملخص≠ | 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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