Comparar métodos
Revisa los métodos seleccionados uno junto a otro; las filas que difieren aparecen resaltadas.
| Método de Croston para Demanda Intermitente× | Modelo ARIMA (Autoregressive Integrated Moving Average)× | |
|---|---|---|
| Campo | Econometría | Econometría |
| Familia | Regression model | Regression model |
| Año de origen≠ | 1972 | 2015 |
| Autor original≠ | J. D. Croston (1972) | Box & Jenkins (Box-Jenkins methodology) |
| Tipo≠ | Intermittent demand time-series forecasting | Univariate time-series model |
| Fuente seminal≠ | Croston, J. D. (1972). Forecasting and Stock Control for Intermittent Demands. Operational Research Quarterly, 23(3), 289-303. 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 |
| Alias | Croston method, intermittent demand forecasting, Croston Yöntemi — Aralıklı Talep Tahmini | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli |
| Relacionados≠ | 4 | 5 |
| Resumen≠ | Croston's method, introduced by J. D. Croston in 1972, is a time-series forecasting technique built for intermittent demand series in which periods of zero demand are frequent. Instead of forecasting the raw series, it models the size of demand when it occurs and the interval between demand occurrences as two separate processes. | 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). |
| ScholarGateConjunto de datos ↗ |
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