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Identification of System Behaviours by Approximation of Time Series Data

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Author Info
Scherrer, W.
Heij, C.
Abstract

The behavioural framework has several attractions to offer for the identification of multivariable systems. Some of the variables may be left unexplained without the need for a distinction between inputs and outputs; criteria for model quality are independent of the chosen parameterization; and behaviours allow for a global (i.e., non-local) approximation of the system dynamics. This is illustrated with a behavioural least squares method with an application in dynamic factor analysis.

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Publisher Info
Paper provided by Erasmus University of Rotterdam - Econometric Institute in its series Papers with number 9710/a.

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Length: 10 pages
Date of creation: 1997
Date of revision:
Handle: RePEc:fth:erroem:9710/a

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Related research
Keywords: LINEAR MODELS ; LEAST SQUARE;

Find related papers by JEL classification:
C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Hypothesis Testing
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions

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This page was last updated on 2009-12-16.


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