方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| Croston方法用于间歇性需求× | ARIMA（自回归积分滑动平均）模型× | |
|---|---|---|
| 领域 | 计量经济学 | 计量经济学 |
| 方法族 | Regression model | Regression model |
| 起源年份≠ | 1972 | 2015 |
| 提出者≠ | J. D. Croston (1972) | Box & Jenkins (Box-Jenkins methodology) |
| 类型≠ | Intermittent demand time-series forecasting | Univariate time-series model |
| 开创性文献≠ | 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 |
| 别名 | Croston method, intermittent demand forecasting, Croston Yöntemi — Aralıklı Talep Tahmini | Box-Jenkins model, ARIMA(p,d,q), ARIMA Modeli |
| 相关≠ | 4 | 5 |
| 摘要≠ | 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). |
| ScholarGate数据集 ↗ |
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