Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Mfumo wa SARIMA wa Paneli× | Modeli wa Paneli wa ARMA× | |
|---|---|---|
| Nyanja | Ekonometriki | Ekonometriki |
| Familia | Regression model | Regression model |
| Mwaka wa asili≠ | 1976 (SARIMA); 1990s (panel extensions) | 1980s–2000s |
| Mwanzilishi≠ | Box & Jenkins (SARIMA foundation); panel extension via mean-group and pooled estimators | Baltagi, Hsiao and related panel data literature |
| Aina≠ | Seasonal time series panel model | Panel time series model |
| Chanzo asilia≠ | Box, G. E. P., Jenkins, G. M., & Reinsel, G. C. (1976). Time Series Analysis: Forecasting and Control. Holden-Day. ISBN: 978-0470272848 | Baltagi, B. H. (2008). Econometric Analysis of Panel Data (4th ed.). John Wiley & Sons. ISBN: 978-0470518861 |
| Majina mbadala | Panel SARIMA, Seasonal ARIMA panel model, SARIMA panel estimation, grouped seasonal time series model | Panel ARMA, ARMA panel model, panel autoregressive moving average, cross-sectional ARMA |
| Zinazohusiana | 5 | 5 |
| Muhtasari≠ | The Panel SARIMA model applies the Seasonal Autoregressive Integrated Moving Average (SARIMA) framework to panel data, fitting individual or pooled seasonal time series models across multiple cross-sectional units. It captures both non-seasonal and seasonal autocorrelation, trends, and periodicity, making it suitable for datasets where multiple entities share a common seasonal structure over time. | The Panel ARMA model extends the classical Autoregressive Moving Average (ARMA) framework to panel data, allowing each cross-sectional unit to carry an individual effect while the within-unit error dynamics follow an ARMA(p, q) process. It captures both autocorrelation and moving-average dependence in panel residuals, yielding efficient estimates when the error structure is correctly specified. |
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