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Behavioural Approximation of Stochastic Processes by Rank Reduced Spectra

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  • Heij, C.
  • Scherrer, W.

Abstract

Behaviours provide an elegant, parameter free characterization of deterministic systems. We discuss a possible application of behaviours in the approximation of stochastic systems. This can be seen as an extension to the dynamic case of the well-known static factor analysis model. An essential difference is that we see modelling primarily as a matter of process approximation, not as a method to recover the true data generating process. In particular we see "noise properties" as a kind of prior model assumption that can be compared with the resulting quality of the process approximation.

Suggested Citation

  • Heij, C. & Scherrer, W., 1996. "Behavioural Approximation of Stochastic Processes by Rank Reduced Spectra," Econometric Institute Research Papers EI 9610/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
  • Handle: RePEc:ems:eureir:1374
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    File URL: https://repub.eur.nl/pub/1374/feweco19971104115458.pdf
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    References listed on IDEAS

    as
    1. Heij, C. & Scherrer, W. & Destler, M., 1996. "System Identification by Dynamic Factor Models," Econometric Institute Research Papers EI 9501-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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    1. Heij, C. & Scherrer, W., 1996. "Consistency of System Identification by Global Total Least Squares," Econometric Institute Research Papers EI 9635-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    2. Heij, C. & Scherrer, W. & Destler, M., 1996. "System Identification by Dynamic Factor Models," Econometric Institute Research Papers EI 9501-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

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