On Structural Time Series Models and the Characterization of Components
分析了一类结构时间序列模型的性质，该模型对观测序列的不可观测成分施加特定结构，并展示了如何通过向趋势和季节成分分配白噪声来实现模型识别，同时提出改进以避免噪声污染。
Abstract This article analyzes certain properties of a class of recently proposed structural time series models in which particular structures are imposed upon the unobserved components of an observed time series. It is shown how the overall model can be expected to fit series, such as those for which the X-11 or Airline models are appropriate. As for the components, identification of the model is achieved by assigning a certain amount of white noise variation to the trend and seasonal components. It is shown that the structural approach can be modified to avoid trend and seasonal components contaminated by noise. KEY WORDS: Seasonal adjustmentX-11ARIMA modelsAirline modelUnobserved componentsCanonical decomposition