A wavelet-based method for surrogate data generation

DOI10.1016/j.physd.2006.10.012zbMath1106.62095OpenAlexW1981820607MaRDI QIDQ870864

Christopher J. Keylock

Publication date: 15 March 2007

Published in: Physica D (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.physd.2006.10.012

zbMATH Keywords

surrogate datahypothesis testingwavelet transformconstrained realisations

Mathematics Subject Classification ID

Numerical methods for wavelets (65T60) Non-Markovian processes: hypothesis testing (62M07)

Related Items (3)

Surrogate data for hypothesis testing of physical systems ⋮ Gradual multifractal reconstruction of time-series: formulation of the method and an application to the coupling between stock market indices and their Hölder exponents ⋮ Transforming Gaussian correlations. Applications to generating long-range power-law correlated time series with arbitrary distribution

Uses Software

• wmtsa

Cites Work

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• Testing for nonlinearity in time series: the method of surrogate data
• Construction of multivariate surrogate sets from nonlinear data using the wavelet transform
• Applying the method of surrogate data to cyclic time series
• A time domain characterization of the fine local regularity of functions.
• Constrained-realization Monte-Carlo method for hypothesis testing
• Correlation dimension: A pivotal statistic for non-constrained realizations of composite hypotheses in surrogate data analysis
• A practical method for calculating largest Lyapunov exponents from small data sets
• An equation for continuous chaos
• Statistical Properties and Uses of the Wavelet Variance Estimator for the Scale Analysis of Time Series

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