我想更好地理解python seasonal_decompose()模块中statsmodel函数的工作原理。
文档有点稀疏，因为它只说明：
This is a naive decomposition. More sophisticated methods should be preferred.
The additive model is Y[t] = T[t] + S[t] + e[t]
The multiplicative model is Y[t] = T[t] * S[t] * e[t]
The seasonal component is first removed by applying a convolution filter to
the data. The average of this smoothed series for each period is the returned
seasonal component.
是否有关于此方法的进一步文档？估算季节性成分后，如何提取趋势？我更愿意探索理论解释，而不是直接深入研究代码。