WaveletComp (version 1.0)

SurrogateData: Simulation of surrogates for a given time series x, subject to the specified method and parameters

Description

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 WaveletCo).

Usage

SurrogateData(x, method = "white.noise", 
              params = list(
                       AR = list(p = 1), 
                       ARIMA = list(p = 1, q = 1, 
                                    include.mean = T, sd.fac = 1, 
                                    trim = F, trim.prop = 0.01))
             )

Arguments

x

the given time series

method

the method of generating surrogate time series, select from: rlll{ "white.noise" : white noise "shuffle" : shuffling the given time series "Fourier.rand" : time series with a similar

params

a list of assignments between methods (AR, and ARIMA) and lists of parameter values applying to surrogates. Default: NULL. Default includes: AR = list(p=1), where: rlll

Value

• 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.

References

Tian, H., and Cazelles, B., 2012. WaveletCo. Available at http://cran.r-project.org/src/contrib/Archive/WaveletCo/, archived April 2013; accessed July 26, 2013.

See Also

analyze.wavelet, analyze.coherency, AR, ARIMA, FourierRand