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Markovian Representation of Stochastic Processes and Its Application to the Analysis of Autoregressive Moving Average Processes

  • Hirotugu Akaike
Part of the Springer Series in Statistics book series (SSS)

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.

Keywords

Stochastic System Canonical Correlation Canonical Correlation Analysis Factor Analysis Model State Space Representation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1998

Authors and Affiliations

  • Hirotugu Akaike

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