Joint order and parameter estimation of multivariate autoregressive models using multi-model partitioning theory

Authors:
Stylianos Sp. Pappas;Assimakis K. Leros;Sokratis K. Katsikas
Affiliations:
Department of Information and Communication Systems Engineering, University of the Aegean, Karlovassi GR-83200, Greece;Department of Information and Communication Systems Engineering, University of the Aegean, Karlovassi GR-83200, Greece;Department of Information and Communication Systems Engineering, University of the Aegean, Karlovassi GR-83200, Greece
Venue:
Digital Signal Processing
Year:
2006

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Abstract

In this paper the multi-model partitioning theory is used for simultaneous order and parameter estimation of multivariate autoregressive models. Simulation experiments show that the proposed method successfully selects the correct model order and estimates the parameters accurately, in very few steps, even with a small sample size. They also show that the proposed method performs equally well when the complexity of the model is increased. The results are compared to those obtained using well-established order selection criteria. Finally, it is shown that the method is also successful in tracking model order changes, in real time.