Methoden vergelijken
Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.
| MA-model met tijdvariërende parameters× | Moving Average (MA) Model× | |
|---|---|---|
| Vakgebied | Econometrie | Econometrie |
| Familie | Regression model | Regression model |
| Jaar van ontstaan≠ | 1990s | 1970 |
| Grondlegger≠ | Harvey, A. C.; Durbin, J. & Koopman, S. J. | Box and Jenkins |
| Type≠ | Time-varying state-space model | Linear time series model |
| Oorspronkelijke bron≠ | Harvey, A. C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press. ISBN: 9780521321969 | Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control (revised ed.). Holden-Day. ISBN: 978-0130607744 |
| Aliassen | TVP-MA model, state-space MA, Kalman filter MA, time-varying MA | MA model, MA(q) process, moving-average process, Box-Jenkins MA |
| Verwant≠ | 6 | 5 |
| Samenvatting≠ | 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 Moving Average model of order q — written MA(q) — expresses the current value of a time series as a linear combination of the current and past random shocks (innovations). Unlike the AR model which uses lagged values of the series itself, the MA model uses lagged error terms, making it well-suited for capturing short-lived disturbances that dissipate over q periods. |
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