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Forecasting chaotic systems: The role of local Lyapunov exponents

Dominique Guegan and Justin Leroux

Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) from HAL

Abstract: We propose a novel methodology for forecasting chaotic systems which is based on exploiting the information conveyed by the local Lyapunov exponents of a system. This information is used to correct for the inevitable bias of most non-parametric predictors. Using simulated data, we show that gains in prediction accuracy can be substantial.

Keywords: chaotic; systems (search for similar items in EconPapers)
Date: 2009-09
Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00431726v2
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Published in Chaos, Solitons and Fractals, Elsevier, 2009, 41 (5), pp.2401-2404. 〈10.1016/j.chaos.2008.09.017〉

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Related works:
Working Paper: Forecasting chaotic systems: the role of local Lyapunov exponents (2008) Downloads
Working Paper: Forecasting chaotic systems: the role of local Lyapunov exponents (2008) Downloads
Working Paper: Forecasting chaotic systems: The role of local Lyapunov exponents (2007) Downloads
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