A pattern recognition approach based on the frequency domain measure of squared coherence is a useful approach to identify linearly related groupings of time series over different periods of time. It is considered in an application to identify similar patterns of the yearly rates of change in the Gross Domestic Product (GDP) of twenty two highly developed countries in an econophysics context. The approach is also tested in simulation studies using linearly related time series, and it is shown to have a very good success rate of correct pattern matching. (C) 2010 Elsevier B.V. All rights reserved.

A coherence-based approach for the pattern recognition of time series / Elizabeth Ann, Maharaj; D'Urso, Pierpaolo. - In: PHYSICA. A. - ISSN 0378-4371. - 389:17(2010), pp. 3516-3537. [10.1016/j.physa.2010.03.051]

A coherence-based approach for the pattern recognition of time series

D'URSO, Pierpaolo
2010

Abstract

A pattern recognition approach based on the frequency domain measure of squared coherence is a useful approach to identify linearly related groupings of time series over different periods of time. It is considered in an application to identify similar patterns of the yearly rates of change in the Gross Domestic Product (GDP) of twenty two highly developed countries in an econophysics context. The approach is also tested in simulation studies using linearly related time series, and it is shown to have a very good success rate of correct pattern matching. (C) 2010 Elsevier B.V. All rights reserved.
2010
squared coherence measure; linearly related time series; pattern recognition of time series; gross domestic product; econophysics; partitioning around medoids
01 Pubblicazione su rivista::01a Articolo in rivista
A coherence-based approach for the pattern recognition of time series / Elizabeth Ann, Maharaj; D'Urso, Pierpaolo. - In: PHYSICA. A. - ISSN 0378-4371. - 389:17(2010), pp. 3516-3537. [10.1016/j.physa.2010.03.051]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/129389
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