Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Muundo wa Modelu ya MWazo ya Kujenga Upya (Structural Break MA Model)× | Mfumo wa ARIMA (Autoregressive Integrated Moving Average)× | |
|---|---|---|
| Nyanja | Ekonometriki | Ekonometriki |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 1989–1992 | 1970 |
| Mwanzilishi≠ | Perron (1989); Zivot & Andrews (1992) | George Box and Gwilym Jenkins |
| Aina≠ | Time series model with structural change | Time series forecasting model |
| Chanzo asilia≠ | Perron, P. (1989). The great crash, the oil price shock, and the unit root hypothesis. Econometrica, 57(6), 1361–1401. DOI ↗ | Box, G. E. P., & Jenkins, G. M. (1970). Time Series Analysis: Forecasting and Control. Holden-Day. link ↗ |
| Majina mbadala | MA model with structural change, broken MA model, MA with regime shift, structural break moving average | ARIMA, Box-Jenkins model, integrated ARMA, ARIMA(p,d,q) |
| Zinazohusiana≠ | 5 | 6 |
| Muhtasari≠ | A Moving Average (MA) time series model augmented to accommodate one or more structural breaks — abrupt shifts in the mean, variance, or MA coefficients occurring at known or unknown break dates. Ignoring structural breaks in an MA process inflates forecast errors and distorts inference on the error dynamics. | The ARIMA(p,d,q) model is the standard workhorse for univariate time series forecasting. It combines autoregressive terms (past values), differencing to induce stationarity, and moving average terms (past shocks) into a unified linear framework. Developed by Box and Jenkins (1970), it remains one of the most widely applied models in econometrics and applied statistics. |
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