Unobserved-Components Models for Seasonal Adjustment Filters
提出时间序列模型，使线性最小二乘信号提取的季节成分估计接近Census X-11程序的标准选项，并扩展了模型类别和不对称滤波器的研究。
Time series models are presented, for which the seasonal-component estimates delivered by linear least squares signal extraction closely approximate those of the standard option of the widely-used Census X-11 program. Earlier work is extended by consideration of a broader class of models and by examination of asymmetric filters, in addition to the symmetric filter implicit in the adjustment of historical data. Various criteria that guide the specification of unobserved- components models are discussed, and a new preferred model is presented. Some nonstandard options in X-11 are considered in the Appendix.