Adaptive MV ARMA Identification Under the Presence of Noise
An adaptive method for simultaneous order estimation and parameter identification of multivariate (MV) ARMA models under the presence of noise is addressed. The proposed method is based on the well known multi-model partitioning (MMP) theory. Computer simulations indicate that the method is 100% successful in selecting the correct model order in very few steps. The results are compared with two other established order selection criteria, namely, Akaike’s information criterion (AIC) and Schwarz’s Bayesian information criterion (BIC).
KeywordsRoot Mean Square Error Posterior Probability Kalman Filter Bayesian Information Criterion Model Order
This paper is dedicated to the memory of Prof. Dimitrios G. Lainiotis, the founder of the multi-model partitioning theory, who passed away suddenly in 2006.
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