Measures of Variability for Model-Based Seasonal Adjustment Procedures
推导了一种算法，用于计算基于模型的季节调整中非季节成分估计的变异性度量，基于信号提取理论，并分析了方差成分的性质及一个常用时间序列模型下的方差行为，最后用真实数据验证。
Abstract An algorithm is derived that develops measures of variability for the estimates of the nonseasonal component computed from a model-based seasonal adjustment procedure. The measures of variability are developed from signal extraction theory. Properties of components of the variance are developed, and the behavior of the variance is investigated for one popular time series model. The results are illustrated by using real data. KEY WORDS: Seasonal adjustmentConfidence intervalVariabilityNonseasonal componentModel-based seasonal adjustmentARIMA models