Autoregressive models of singular spectral matrices
This paper deals with autoregressive (AR) models of singular spectra, whose corresponding transfer function matrices can be expressed in a stable AR matrix fraction description D- 1(q)B with B a tall constant matrix of full column rank and with the determinantal zeros of D(q) all stable, i.e. in |q|>1,q∈C. To obtain a parsimonious AR model, a canonical form is derived and a number of advantageous properties are demonstrated. First, the maximum lag of the canonical AR model is shown to be...[Show more]
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