It simulates a surrogate for the time series x to be analyzed by wavelet transformation using either function
analyze.wavelet or function
analyze.coherency. A set of surrogates is used for significance assessment
to test the hypothesis of equal periodic components.
Simulation is subject to model/method specification and parameter setting: Currently, one can choose from a variety of 6 methods (white noise, series shuffling, Fourier randomization, AR, and ARIMA) with respective lists of parameters to set.
The name and layout were inspired by a similar function developed by Huidong Tian (archived R package
1 2 3 4
the given time series
the method of generating surrogate time series; select from:
a list of assignments between methods (AR, and ARIMA) and lists of parameter values
applying to surrogates. Default:
A surrogate series for x is returned which has the same length and properties according to estimates resulting from the model/method specification and parameter setting.
Angi Roesch and Harald Schmidbauer; credits are also due to Huidong Tian.
Tian, H., and Cazelles, B., 2012.
Available at https://cran.r-project.org/src/contrib/Archive/WaveletCo/, archived April 2013; accessed July 26, 2013.
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