Summary
The problem of identifiability of a multivariate autoregressive moving average process is considered and a complete solution is obtained by using the Markovian representation of the process. The maximum likelihood procedure for the fitting of the Markovian representation is discussed. A practical procedure for finding an initial guess of the representation is introduced and its feasibility is demonstrated with numerical examples.
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Akaike, H. (1998). Markovian Representation of Stochastic Processes and Its Application to the Analysis of Autoregressive Moving Average Processes. In: Parzen, E., Tanabe, K., Kitagawa, G. (eds) Selected Papers of Hirotugu Akaike. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1694-0_17
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DOI: https://doi.org/10.1007/978-1-4612-1694-0_17
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