Markovian Representation of Stochastic Processes and Its Application to the Analysis of Autoregressive Moving Average Processes
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.
KeywordsStochastic System Canonical Correlation Canonical Correlation Analysis Factor Analysis Model State Space Representation
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