Abstract
In this paper a method of identifying stationary and invertible vector autoregressive moving-average time series is proposed. The models are presumed to be represented in (reversed) echelon canonical form. Consideration is given to both parameter estimation and the determination of structural indices, the evaluations being based on the use of closed form least squares calculations. Consistency of the technique is shown and the operational characteristics of the procedure when employed as a means of approximating more general processes is discussed.
Citation
D. S. Poskitt. "Identification of Echelon Canonical Forms for Vector Linear Processes Using Least Squares." Ann. Statist. 20 (1) 195 - 215, March, 1992. https://doi.org/10.1214/aos/1176348518
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