自回归移动平均模型(ARIMA)是一种常用于时间序列分析和预测的线性模型。 statsmodels库提供了Python中使用ARIMA的实现。ARIMA模型可以保存到文件中，以便以后对新数据进行预测。差分自回归移动平均模型（ARIMA）是时间序列分析和预测领域流行的一个线性模型。原文地址：https://machinelearningmastery.com/save-ar
R basically has default holiday regression effects for trading days and other holidays like Easter. If set to NULL, would result in a similar series as generated by Python earlier. Although capturing calendar effects(Trading days, moving holidays) would be significant in adjusting for seasonality, ...
I know statsmodels.tsa.x13.x13_arima_analysis is the Python wrapper. Using statsmodels, is it possible to provide the inputs (specification) files into the Seasonal adjustment procedure? Eg, I want to add/drop certain outliers or regressors. How do I go about doing it in statsmodels?