Сравнение на методи
Прегледайте избраните методи един до друг; редовете с разлики са откроени.
| Методът Тета× | Модел ARIMA (Autoregressive Integrated Moving Average)× | |
|---|---|---|
| Област | Иконометрия | Иконометрия |
| Семейство | Regression model | Regression model |
| Година на възникване≠ | 2000 | 2015 |
| Създател≠ | Assimakopoulos & Nikolopoulos | Box & Jenkins (Box-Jenkins methodology) |
| Тип≠ | Univariate time-series forecasting model | Univariate time-series model |
| Основополагащ източник≠ | Assimakopoulos, V. & Nikolopoulos, K. (2000). The Theta Model: A Decomposition Approach to Forecasting. International Journal of Forecasting, 16(4), 521-530. DOI ↗ | 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 |
| Други названия | theta model, theta forecasting, Theta Yöntemi — M3 Tahmin Yarışması Birincisi | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli |
| Свързани≠ | 4 | 5 |
| Резюме≠ | The Theta Method is a univariate time-series forecasting model introduced by Assimakopoulos and Nikolopoulos in 2000. It decomposes a series into two theta lines that capture its long-run trend and its short-run dynamics, forecasts each line separately, and combines them by a weighted average. Its simplicity and accuracy made it the winner of the M3 forecasting competition. | 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). |
| ScholarGateНабор от данни ↗ |
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