So sánh phương pháp
Xem các phương pháp đã chọn cạnh nhau; những hàng khác biệt được làm nổi bật.
| Mô hình Trung bình trượt Bayes (MA)× | Mô hình ARMA Bayes× | |
|---|---|---|
| Lĩnh vực | Kinh tế lượng | Kinh tế lượng |
| Họ | Regression model | Regression model |
| Năm ra đời≠ | 1970s–1997 | 1970s–1980s |
| Người khởi xướng≠ | Bayesian framework applied to Box-Jenkins MA models; West & Harrison (1997) canonical treatment | Box & Jenkins (classical ARMA); Bayesian treatment developed through work of Zellner, Geweke, and others in 1970s–1980s |
| Loại | Bayesian time series model | Bayesian time series model |
| Công trình gốc≠ | West, M., & Harrison, J. (1997). Bayesian Forecasting and Dynamic Models (2nd ed.). Springer. ISBN: 978-0387947259 | Geweke, J., & Meese, R. (1981). Estimating regression models of finite but unknown order. International Economic Review, 22(1), 55–70. link ↗ |
| Tên gọi khác | Bayesian MA, Bayesian moving average, BMA time series, MA model with Bayesian estimation | Bayesian ARMA, B-ARMA, Bayesian autoregressive moving average, ARMA with Bayesian inference |
| Liên quan | 6 | 6 |
| Tóm tắt≠ | The Bayesian MA model estimates a moving average time series model within a fully Bayesian framework, placing prior distributions on the MA parameters and error variance and updating them via Bayes' theorem. This approach yields full posterior distributions over model parameters and produces probabilistic forecasts with coherent uncertainty quantification. | The Bayesian ARMA model applies Bayesian inference to the classical autoregressive moving average framework for stationary univariate time series. Rather than producing single point estimates for the AR and MA parameters, it yields full posterior distributions, naturally incorporating prior knowledge and providing coherent uncertainty quantification over forecasts and impulse responses. |
| ScholarGateBộ dữ liệu ↗ |
|
|