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Practical implementation of nonlinear time series methods: The TISEAN package

Open access
Hegger, Rainer, Kantz, Holger, Schreiber, Thomas·1999·Chaos: An Interdisciplinary Journal of Nonlinear Science

Abstract

We describe the implementation of methods of nonlinear time series analysis which are based on the paradigm of deterministic chaos. A variety of algorithms for data representation, prediction, noise reduction, dimension and Lyapunov estimation, and nonlinearity testing are discussed with particular emphasis on issues of implementation and choice of parameters. Computer programs that implement the resulting strategies are publicly available as the TISEAN software package. The use of each algorithm will be illustrated with a typical application. As to the theoretical background, we will essentially give pointers to the literature.

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Metadata

Authors
Hegger, R., Kantz, H., & Schreiber, T.
Venue
Chaos: An Interdisciplinary Journal of Nonlinear Science
Published
1999-06-01
Volume
9
Issue
2
Pages
413-435
ISSN
  • 1054-1500 (ISSN-L)
  • 1089-7682
OpenAlex
W1979957032
Cited by
1,491
References
2
FWCI
28.61
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Practical implementation of nonlinear time series methods: The TISEAN package. https://app.cochat.ai/papers/10.1063/1.166424
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Hegger, R., Kantz, H., & Schreiber, T. (1999). Practical implementation of nonlinear time series methods: The TISEAN package. Chaos: An Interdisciplinary Journal of Nonlinear Science. https://doi.org/10.1063/1.166424

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.