Fast Filtering for Seasonal Moving Average Models
本文在Pearlman(1980)的ARMA快速滤波算法基础上，利用Kohn & Ansley(1984)和Melard(1984)发现的结构零，并识别出第二组结构零，从而进一步显著节省季节性移动平均模型的计算量，可用于快速计算平稳ARMA模型的似然函数。
Pearlman (1980) gives a fast filtering algorithm for an ARMA, i.e. autoregressive-moving average, model. When the algorithm is applied to a seasonal moving average model significant computational savings can be obtained by taking advantage of the structural zeros noted by Kohn & Ansley (1984) and Melard (1984). In this paper we identify a second set of structural zeros which leads to further significant computational savings. Our results can be applied to produce a fast algorithm for obtaining the likelihood of a stationary ARMA model with a seasonal moving average.