Convergence rates and data requirements for Jacobian-based estimates of Lyapunov exponents from data

S. Ellner, Andrew Ronald Gallant, D. McCaffrey, D. Nychka

Research output: Contribution to journalArticlepeer-review

75 Scopus citations

Abstract

We present a method for estimating the dominant Lyapunov exponent from time-series data, based on nonparametric regression. For data from a finite-dimensional deterministic system with additive stochastic perturbations, we show that the estimate converges to the true values as the sample size increases, and give the asymptotic rate of convergence.

Original languageEnglish (US)
Pages (from-to)357-363
Number of pages7
JournalPhysics Letters A
Volume153
Issue number6-7
DOIs
StatePublished - Mar 11 1991

All Science Journal Classification (ASJC) codes

  • Physics and Astronomy(all)

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