Abstract
Previous work on the stochastic realization and approximation problem has cast this problem in the framework of theRV-coefficient, a measure of correlation recently introduced in the multivariate statistical literature. This allowed the introduction of a common measure for the “goodness of fit” for the different realization algorithms. This paper explores the deeper geometrical and logical foundation for this common measure in a unified theory for the data-driven and the exact covariance approaches.
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Verriest, E.I., Finkelstein, D. Unified theory of model reduction via Gleason measures. Int J Theor Phys 30, 1703–1714 (1991). https://doi.org/10.1007/BF00673647
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DOI: https://doi.org/10.1007/BF00673647