Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uchanganuzi wa Utengamano wa Makosa ya Utabiri (FEVD)× | Muundo wa Uhusiano wa Kiotomatiki wa Vecta (VAR)× | |
|---|---|---|
| Nyanja | Ekonometriki | Ekonometriki |
| Familia | Regression model | Regression model |
| Mwaka wa asili | 2005 | 2005 |
| Mwanzilishi≠ | Helmut Lütkepohl | Lütkepohl (textbook treatment); Sims (1980) macroeconometric tradition |
| Aina≠ | Multivariate time series analysis tool | Multivariate time-series model |
| Chanzo asilia | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. ISBN: 978-3-540-40172-8 | Lütkepohl, H. (2005). New Introduction to Multiple Time Series Analysis. Springer. DOI ↗ |
| Majina mbadala | Variance Decomposition, Error Variance Decomposition, VD Analysis, Varyans Ayrıştırması | vector autoregression, VAR, VAR Modeli (Vektör Otoregresyon), vektör otoregresyon |
| Zinazohusiana≠ | 3 | 4 |
| Muhtasari≠ | Forecast Error Variance Decomposition (FEVD) is a multivariate time series technique used within Vector Autoregression (VAR) frameworks to quantify what proportion of the forecast error variance of each variable is attributable to shocks from every other variable in the system. It is widely used by econometricians, macroeconomists, and financial researchers to assess the relative importance of different structural disturbances in driving short-run and long-run fluctuations across interconnected economic series. | 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). |
| ScholarGateSeti ya data ↗ |
|
|