DOI: 10.1016/s0167-2789(02)00382-2. Applying the method of surrogate data to cyclic time series

Applying the method of surrogate data to cyclic time series

10.1016/s0167-2789(02)00382-2

Crossref journal-article

Elsevier BV

Physica D: Nonlinear Phenomena (78)

Bibliography

Small, M., & Tse, C. K. (2002). Applying the method of surrogate data to cyclic time series. Physica D: Nonlinear Phenomena, 164(3â4), 187â201.

Authors 2

Michael Small (first)
C.K. Tse (additional)

References 29 Referenced 60

H.D. Abarbanel, Analysis of Observed Chaotic Data, Institute for Nonlinear Science, Springer, New York, 1996. (10.1007/978-1-4612-0763-4)
10.1142/S0218127400000402 / Int. J. Bifurcat. Chaos / Control of human atrial fibrillation by Ditto (2000)
10.1103/PhysRevE.59.5235 / Phys. Rev. E / Surrogates for finding unstable periodic orbits in noisy data sets by Dolan (1999)
10.1103/PhysRevLett.59.845 / Phys. Rev. Lett. / Predicting chaotic time series by Farmer (1987)
J. Guckenheimer, P. Holmes, Nonlinear Oscillations, Dynamical Systems, and Bifurcations of Vector Fields, Applied Mathematical Sciences, Vol. 42, Springer, New York, 1983. (10.1007/978-1-4612-1140-2)
10.1063/1.166424 / Chaos / Practical implementation of nonlinear time series methods: the TISEAN package by Hegger (1999)
10.1016/0167-2789(92)90025-I / Physica D / An improved estimator of dimension and some comments on providing confidence intervals by Judd (1992)
10.1016/0167-2789(94)90008-6 / Physica D / Estimating dimension from small samples by Judd (1994)
10.1016/0167-2789(95)00050-E / Physica D / On selecting models for nonlinear time series by Judd (1995)
10.1016/S0167-2789(98)00089-X / Physica D / Embedding as a modelling problem by Judd (1998)
10.1016/S0167-2789(99)00152-9 / Physica D / Towards long-term prediction by Judd (2000)
K. Judd, M. Small, A.I. Mees, Achieving good nonlinear models: keep it simple, vary the embedding, and get the dynamics right, in: A.I. Mees (Ed.), Nonlinear Dynamics and Statistics, Birkhauser, Boston, 2001, pp. 65–80 (Chapter 3). (10.1007/978-1-4612-0177-9_3)
10.1016/S0167-2789(97)00171-1 / Physica D / Regularized local linear prediction of chaotic time series by Kugiumtzis (1998)
10.1142/S0218127491000579 / Int. J. Bifurcat. Chaos / Dynamical systems and tesselations: detecting determinism in data by Mees (1991)
10.1103/PhysRevLett.80.2105 / Phys. Rev. Lett. / Constrained randomization of time series by Schreiber (1998)
10.1016/S0167-2789(00)00043-9 / Physica D / Surrogate time series by Schreiber (2000)
B.W. Silverman, Density Estimation for Statistics and Data Analysis, Monographs on Statistics and Applied Probability, Chapman & Hall, London, 1986. (10.1007/978-1-4899-3324-9)
10.1016/S0167-2789(98)00088-8 / Physica D / Correlation dimension: a pivotal statistic for non-constrained realizations of composite hypotheses in surrogate data analysis by Small (1998)
10.1142/S0218127498000966 / Int. J. Bifurcat. Chaos / Detecting nonlinearity in experimental data by Small (1998)
10.1103/PhysRevE.59.1379 / Phys. Rev. E / Detecting periodicity in experimental data using linear modeling techniques by Small (1999)
M. Small, D. Yu, R.G. Harrison, A surrogate test for pseudo-periodic time series data, Phys. Rev. Lett. 87, in press. (10.1103/PhysRevLett.87.188101)
10.1016/S0167-2789(97)00183-8 / Physica D / Reliable detection of nonlinearity in experimental time series with strong periodic components by Stam (1998)
10.1038/344734a0 / Nature / Nonlinear forecasting as a way of distinguishing chaos from measurement error in time series by Sugihara (1990)
10.1007/BFb0091924 / Lect. Notes Math. / Detecting strange attractors in turbulence by Takens (1981)
10.1016/0375-9601(94)00856-K / Phys. Lett. A / On the evidence for low-dimensional chaos in an epileptic electroencephalogram by Theiler (1995)
10.1016/0167-2789(92)90102-S / Physica D / Testing for nonlinearity in time series: the method of surrogate data by Theiler (1992)
10.1016/0167-2789(96)00050-4 / Physica D / Constrained-realization Monte-Carlo method for hypothesis testing by Theiler (1996)
10.1016/0013-4694(95)00240-5 / Electroencephalogr. Clin. Neurophysiol. / Re-examination of the evidence for low-dimensional, nonlinear structure in the human electroencephalogram by Theiler (1996)
J. Thompson, H. Stewart, Nonlinear Dynamics and Chaos, Wiley, Chichester, UK, 1986.

Dates

Type	When
Created	22 years, 10 months ago (Oct. 14, 2002, 4:38 p.m.)
Deposited	5 years, 7 months ago (Jan. 7, 2020, 8:54 p.m.)
Indexed	2 weeks, 4 days ago (Aug. 19, 2025, 7:11 a.m.)
Issued	23 years, 5 months ago (April 1, 2002)
Published	23 years, 5 months ago (April 1, 2002)
Published Print	23 years, 5 months ago (April 1, 2002)

Funders 0

None

BibTeX

@article{Small_2002, title={Applying the method of surrogate data to cyclic time series}, volume={164}, ISSN={0167-2789}, url={http://dx.doi.org/10.1016/s0167-2789(02)00382-2}, DOI={10.1016/s0167-2789(02)00382-2}, number={3–4}, journal={Physica D: Nonlinear Phenomena}, publisher={Elsevier BV}, author={Small, Michael and Tse, C.K.}, year={2002}, month=apr, pages={187–201} }

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