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| Модел ARIMA (Autoregressive Integrated Moving Average)× | Тест на Диболд-Мариано за равна прогнозна точност× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство≠ | Regression model | Hypothesis test |
| Година на възникване≠ | 2015 | 1995 |
| Създател≠ | Box & Jenkins (Box-Jenkins methodology) | Francis Diebold & Roberto Mariano |
| Тип≠ | Univariate time-series model | Non-parametric forecast comparison test |
| Основополагащ източник≠ | 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 ↗ |
| Други названия≠ | 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 |
| Свързани≠ | 5 | 3 |
| Резюме≠ | 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. |
| ScholarGateНабор от данни ↗ |
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