Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uchanganuzi wa Regresheni wa Kiotomatiki wa Bayesian (BVAR)× | Muundo wa Uhusiano wa Kiotomatiki wa Vecta (VAR)× | |
|---|---|---|
| Nyanja | Ekonometriki | Ekonometriki |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 1986 | 2005 |
| Mwanzilishi≠ | Litterman (1986); Bańbura, Giannone & Reichlin (2010) | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| Aina≠ | Bayesian multivariate time-series model | Multivariate time-series model |
| Chanzo asilia≠ | 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 ↗ |
| Majina mbadala | BVAR, Bayesian vector autoregression, Minnesota prior VAR, Bayesian VAR (BVAR) | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| Zinazohusiana≠ | 5 | 4 |
| Muhtasari≠ | 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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