Сравнение методов
Просматривайте выбранные методы рядом; строки с различиями подсвечены.
| Bayesian ARIMA Model× | Векторная авторегрессия (VAR)× | |
|---|---|---|
| Область | Эконометрика | Эконометрика |
| Семейство | Regression model | Regression model |
| Год появления≠ | 1970s (ARIMA); Bayesian extension prominent from 1990s | 1980 |
| Автор метода≠ | Pole, West & Harrison (Bayesian treatment); Box & Jenkins (ARIMA foundation) | Christopher A. Sims |
| Тип≠ | Bayesian time series model | Multivariate time-series model |
| Основополагающий источник≠ | Pole, A., West, M., & Harrison, J. (1994). Applied Bayesian Forecasting and Time Series Analysis. Chapman & Hall. ISBN: 978-0412416903 | Sims, C. A. (1980). Macroeconomics and Reality. Econometrica, 48(1), 1–48. DOI ↗ |
| Другие названия | Bayesian ARIMA, BARIMA, Bayesian Box-Jenkins model, Bayesian integrated time series model | VAR, VAR model, vector autoregressive model, multivariate autoregression |
| Связанные≠ | 6 | 5 |
| Сводка≠ | The Bayesian ARIMA model combines the classical Box-Jenkins ARIMA framework with Bayesian inference. Instead of obtaining single point estimates for autoregressive and moving average parameters, it places prior distributions over them and uses observed data to update beliefs into a full posterior distribution, enabling coherent 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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