Regression model
ETS：误差、趋势、季节性指数平滑
ETS是一个全面的指数平滑框架，它能自动选择时间序列的误差（E）、趋势（T）和季节性（S）成分的加性或乘性组合。Hyndman、Koehler、Ord和Snyder于2008年将其形式化为创新状态空间模型，统一并推广了Holt-Winters族预测方法。
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Method map
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来源
- Hyndman, R. J., Koehler, A. B., Ord, J. K. & Snyder, R. D. (2008). Forecasting with Exponential Smoothing: The State Space Approach. Springer. DOI: 10.1007/978-3-540-71918-2 ↗
- Hyndman, R. J. & Athanasopoulos, G. (2021). Forecasting: Principles and Practice (3rd ed.). OTexts. link ↗
如何引用本页
ScholarGate. (2026, June 1). Error, Trend, Seasonal (ETS) Exponential Smoothing. ScholarGate. https://scholargate.app/zh/econometrics/ets-model
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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- 状态空间模型（卡尔曼滤波器）计量经济学↔ compare
- 结构时间序列模型（基本结构模型）计量经济学↔ compare