方法对比
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| 时变参数移动平均模型× | 时变参数自回归积分滑动平均模型 (TVP-ARIMA)× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1990s | 1976–1989 |
| 提出者≠ | Harvey, A. C.; Durbin, J. & Koopman, S. J. | Cooley & Prescott (1976); Harvey (1989) state-space formulation |
| 类型≠ | Time-varying state-space model | Time series model with evolving coefficients |
| 开创性文献≠ | Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. ISBN: 9780521321969 | Harvey, A. C. (1989). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. ISBN: 9780521405737 |
| 别名 | TVP-MA model, state-space MA, Kalman filter MA, time-varying MA | TVP-ARIMA, time-varying ARIMA, adaptive ARIMA, state-space ARIMA |
| 相关≠ | 6 | 3 |
| 摘要≠ | The time-varying parameter moving average (TVP-MA) model extends the standard MA model by allowing the moving-average coefficients to change over time. Cast as a state-space system, it is estimated via the Kalman filter and smoother, making it well suited for series where the shock-transmission dynamics evolve across the sample. | The time-varying parameter ARIMA model extends the classical ARIMA framework by allowing its autoregressive and moving-average coefficients to evolve over time rather than remaining fixed. Cast in state-space form and estimated via the Kalman filter, it is designed for economic and financial time series whose dynamic structure shifts in response to structural breaks, policy changes, or regime transitions. |
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