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| Mô hình Tự hồi quy Bayes (AR)× | Mô hình ARIMA Bayes× | |
|---|---|---|
| Lĩnh vực | Kinh tế lượng | Kinh tế lượng |
| Họ | Regression model | Regression model |
| Năm ra đời≠ | 1971 | 1970s (ARIMA); Bayesian extension prominent from 1990s |
| Người khởi xướng≠ | Arnold Zellner; foundational Bayesian time-series work by West & Harrison | Pole, West & Harrison (Bayesian treatment); Box & Jenkins (ARIMA foundation) |
| Loại≠ | Bayesian time-series model | Bayesian time series model |
| Công trình gốc≠ | Zellner, A. (1971). An Introduction to Bayesian Inference in Econometrics. Wiley. ISBN: 978-0471169376 | Pole, A., West, M., & Harrison, J. (1994). Applied Bayesian Forecasting and Time Series Analysis. Chapman & Hall. ISBN: 978-0412416903 |
| Tên gọi khác | Bayesian autoregressive model, BAR model, Bayesian AR, Bayesian time-series autoregression | Bayesian ARIMA, BARIMA, Bayesian Box-Jenkins model, Bayesian integrated time series model |
| Liên quan | 6 | 6 |
| Tóm tắt≠ | 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. | 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. |
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