Порівняння методів
Переглядайте обрані методи поруч; рядки з відмінностями підсвічено.
| Bayesian ARIMA Model× | Байєсівський тест меж ARDL× | |
|---|---|---|
| Галузь | Економетрика | Економетрика |
| Родина | Regression model | Regression model |
| Рік появи≠ | 1970s (ARIMA); Bayesian extension prominent from 1990s | 2001 (ARDL); Bayesian extension 2010s |
| Автор методу≠ | Pole, West & Harrison (Bayesian treatment); Box & Jenkins (ARIMA foundation) | Pesaran, Shin & Smith (ARDL framework, 2001); Bayesian adaptation by subsequent literature |
| Тип≠ | Bayesian time series model | Cointegration / bounds testing |
| Основоположне джерело≠ | Pole, A., West, M., & Harrison, J. (1994). Applied Bayesian Forecasting and Time Series Analysis. Chapman & Hall. ISBN: 978-0412416903 | Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326. DOI ↗ |
| Інші назви | Bayesian ARIMA, BARIMA, Bayesian Box-Jenkins model, Bayesian integrated time series model | Bayesian ARDL, Bayesian bounds testing approach, Bayes ARDL cointegration, Bayesian PSS bounds test |
| Пов'язані≠ | 6 | 5 |
| Підсумок≠ | 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. | The Bayesian ARDL Bounds Test extends the classical Pesaran-Shin-Smith (2001) bounds testing approach to cointegration by embedding it within a Bayesian inferential framework. Instead of relying on frequentist F- and t-statistics with tabulated critical values, the researcher specifies prior distributions on the model parameters and derives posterior evidence of a long-run level relationship between variables that may be integrated of order zero or one. |
| ScholarGateНабір даних ↗ |
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