A Note on the Recursions of Multichannel Complex Subset Autoregressions - Financial and Economic Forecasting (Chapter 2)
10 Pages Posted: 19 Dec 2002
Date Written: October 2002
Abstract
The recursive algorithm to select the optimum multivariate real subset autoregressive model (AR) [1] is generalized to apply to multichannel complex subset AR's. It is initiated by fitting all 'forward' and 'backward' one-lag AR's. The method then allows one to develop successively all complex subset AR's of size (the number of lags with nonzero coefficient matrices) from 1 to K. Finally, the best subsets of each size with the minimum generalized residual power for that size are compared to any one of three model selection criteria to find the optimum multichannel complex subset AR.
Keywords: Subset AR, recursions, model selection criteria
JEL Classification: C10, C63
Suggested Citation: Suggested Citation
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