1.5k citations · 3.3k across the 6 of their papers we have counts for
6 papers
Discrimination power of measures for nonlinearity in a time series
Thomas Schreiber, Andreas Schmitz
The performance of a number of different measures of nonlinearity in a time series is compared numerically. Their power to distinguish noisy chaotic data from linear stochastic sur…
Improved surrogate data for nonlinearity tests
Thomas Schreiber, Andreas Schmitz
Current tests for nonlinearity compare a time series to the null hypothesis of a Gaussian linear stochastic process. For this restricted null assumption, random surrogates can be c…
Surrogate time series
Thomas Schreiber, Andreas Schmitz
Before we apply nonlinear techniques, for example those inspired by chaos theory, to dynamical phenomena occurring in nature, it is necessary to first ask if the use of such advanc…
Surrogate data for non-stationary signals
Andreas Schmitz, Thomas Schreiber
Standard tests for nonlinearity reject the null hypothesis of a Gaussian linear process whenever the data is non-stationary. Thus, they are not appropriate to distinguish nonlinear…
Constrained randomization of time series for hypothesis testing
Thomas Schreiber, Andreas Schmitz
We propose a general scheme to create time sequences that fulfill given constraints but are random otherwise. Significance levels for nonlinearity tests are as usually obtained by…
Testing for nonlinearity in unevenly sampled time series
Andreas Schmitz, Thomas Schreiber
We generalize the method of surrogate data of testing for nonlinearity in time series to the case that the data are sampled with uneven time intervals. The null hypothesis will be…