Process / pipelineTrend & seasonality
STL分解：使用Loess的季节-趋势分解
STL分解由Cleveland、Cleveland、McRae和Terpenning（1990）提出，是一种非参数方法，它使用迭代局部加权回归（loess）将时间序列分解为三个可加成分——趋势、季节和残差。该方法广泛应用于经济学、气象学和数据科学领域，能够处理任何周期性的时间序列，并且对异常值的存在具有鲁棒性，使其成为经典分解方法的高度灵活的替代方案。
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来源
- Cleveland, R. B., Cleveland, W. S., McRae, J. E., & Terpenning, I. (1990). STL: A seasonal-trend decomposition procedure based on loess. Journal of Official Statistics, 6(1), 3–73. link ↗
如何引用本页
ScholarGate. (2026, June 2). STL: Seasonal-Trend Decomposition using Loess. ScholarGate. https://scholargate.app/zh/econometrics/stl-decomposition
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