Abstract
In this paper we will describe a deterministic approach to time series analysis. The central problem consists of approximate modelling of an observed time series by means of a deterministic dynamical system. The quality of a model with respect to data will depend on the purpose of modelling. We will consider the purpose of description and that of prediction. We define the quality by means of complexity and misfit measures, expressed in terms of canonical parametrizations of dynamical systems. We give algorithms to determine optimal models for a given time series and investigate some consistency properties. Finally we present some simulations of these modelling procedures.
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Heij, C., Willems, J.C. (1989). A Deterministic Approach to Approximate Modelling. In: Willems, J.C. (eds) From Data to Model. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-75007-6_3
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DOI: https://doi.org/10.1007/978-3-642-75007-6_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-75009-0
Online ISBN: 978-3-642-75007-6
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