Physical Review E · 2006 · 44 citations · 18 references
ComputingMathematicsDynamical SystemsForecastingTime Series AnalysisAutocorrelation AnalysisChaos TheoryComputational Time Series AnalysisTrend AnalysisLong-term Fluctuation AnalysisNonlinear Time-series AnalysisNull HypothesisNull Hypothesis FormulationNumerical ModelingStationary Time SeriesTime Series Fluctuation AnalysisTime Series Trend Detection
We describe a method for investigating nonlinearity in irregular fluctuations (short-term variability) of time series even if the data exhibit long-term trends (periodicities). Such situations are theoretically incompatible with the assumption of previously proposed methods. The null hypothesis addressed by our algorithm is that irregular fluctuations are generated by a stationary linear system. The method is demonstrated for numerical data generated by known systems and applied to several actual time series.
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Testing for nonlinearity in time series: the method of surrogate data
James Theiler, Stephen Eubank, André Longtin et al. · Physica D Nonlinear Phenomena · 1992 · 3.8K citations
Improved Surrogate Data for Nonlinearity Tests
Thomas Schreiber, Andreas Schmitz · Physical Review Letters · 1996 · 1.5K citations · Full text
Computing, Biostatistics, Statistics +13
Physica D Nonlinear Phenomena · 2000 · 1.5K citations · Full text