Modeling Time Series With Calendar Variation
研究了包含日历变化（如交易日和复活节假期）的时间序列建模方法，结合ARIMA模型和回归模型，并讨论了识别、估计、推断和诊断检验，适合时间序列分析者参考。
Abstract The modeling of time series data that include calendar variation is considered. Autocorrelation, trends, and seasonality are modeled by ARIMA models. Trading day variation and Easter holiday variation are modeled by regression-type models. The overall model is a sum of ARIMA and regression models. Methods of identification, estimation, inference, and diagnostic checking are discussed. The ideas are illustrated through actual examples.