Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Байесовская авторегрессионная (AR) модель× | Векторная авторегрессия (VAR)× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1971 | 1980 |
| Автор метода≠ | Arnold Zellner; foundational Bayesian time-series work by West & Harrison | Christopher A. Sims |
| Тип≠ | Bayesian time-series model | Multivariate time-series model |
| Основополагающий источник≠ | Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley. ISBN: 978-0471169376 | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| Другие названия | Bayesian autoregressive model, BAR model, Bayesian AR, Bayesian time-series autoregression | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| Связанные≠ | 6 | 5 |
| Сводка≠ | The Bayesian AR model estimates an autoregressive time-series process by combining a likelihood derived from the AR structure with prior distributions over the lag coefficients and error variance. Rather than producing single point estimates, it yields full posterior distributions, enabling principled uncertainty quantification and probabilistic forecasting. | Vector Autoregression is a multivariate time-series model in which each variable is regressed on its own lags and the lags of all other variables in the system. Originally proposed by Sims (1980) as a data-driven alternative to large structural macroeconomic models, VAR has become the standard workhorse for dynamic analysis in empirical economics and finance. |
| ScholarGateНабор данных ↗ |
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