Regression model
TBATS — 适用于复杂季节性的三角指数平滑
TBATS是由De Livera、Hyndman和Snyder（2011年）引入的一种创新状态空间预测模型，它结合了Box-Cox变换、ARMA误差和三角（傅里叶）季节性项。它旨在一次性处理具有多个嵌套季节性周期的连续时间序列——例如，同时具有小时、日、周和年重复模式的数据。
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来源
- De Livera, A. M., Hyndman, R. J. & Snyder, R. D. (2011). Forecasting Time Series with Complex Seasonal Patterns Using Exponential Smoothing. Journal of the American Statistical Association, 106(496), 1513-1527. DOI: 10.1198/jasa.2011.tm09771 ↗
- Hyndman, R. J. & Athanasopoulos, G. (2021). Forecasting: Principles and Practice (3rd ed.). OTexts. link ↗
如何引用本页
ScholarGate. (2026, June 1). Trigonometric, Box-Cox, ARMA, Trend and Seasonal Components Model. ScholarGate. https://scholargate.app/zh/econometrics/tbats
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