Salīdzināt metodes
Apskatiet izvēlētās metodes blakus; rindas, kas atšķiras, ir izceltas.
| ARIMA (autoregresīvais integrētais slīdošā vidējā) modelis× | Dībolda-Mariāno tests par prognožu precizitātes līdzvērtību× | |
|---|---|---|
| Nozare | Ekonometrija | Ekonometrija |
| Saime≠ | Regression model | Hypothesis test |
| Izcelsmes gads≠ | 2015 | 1995 |
| Autors≠ | Box & Jenkins (Box-Jenkins methodology) | Francis Diebold & Roberto Mariano |
| Tips≠ | Univariate time-series model | Non-parametric forecast comparison test |
| Pirmavots≠ | Box, G. E. P., Jenkins, G. M., Reinsel, G. C. & Ljung, G. M. (2015). Time Series Analysis: Forecasting and Control (5th ed.). Wiley. ISBN: 978-1118675021 | Diebold, F. X., & Mariano, R. S. (1995). Comparing predictive accuracy. Journal of Business & Economic Statistics, 13(3), 253–263. DOI ↗ |
| Citi nosaukumi≠ | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli | DM Test, Test of Equal Forecast Accuracy, Diebold-Mariano Forecast Comparison Test, Tahmin Doğruluğu Eşitliği Testi |
| Saistītās≠ | 5 | 3 |
| Kopsavilkums≠ | ARIMA is a univariate time-series forecasting model that combines autoregressive, integrated (differencing), and moving-average components to predict a single continuous series from its own past. It is the centrepiece of the Box-Jenkins methodology set out in Box, Jenkins, Reinsel & Ljung's Time Series Analysis (5th ed., 2015). | The Diebold-Mariano (DM) test, introduced by Diebold and Mariano in 1995, is a widely used non-parametric procedure for formally comparing the predictive accuracy of two competing forecasting models. It evaluates whether the difference in forecast errors between two models is statistically significant, without requiring nested models or specific distributional assumptions about the forecasts, making it broadly applicable across economics, finance, and time-series analysis. |
| ScholarGateDatu kopa ↗ |
|
|