| surrogate(tseries) | R Documentation |
Computes ns surrogate samples from the original data
x. If fft is FALSE, then x is mixed in
temporal order, so that all temporal dependencies are eliminated, but
the histogram of the original data is preserved. If fft, then
surrogate data with the same spectrum as x is computed by
randomizing the phases of the Fourier coefficients of x. If in
addition amplitude is TRUE, then also the amplitude
distribution of the original series is preserved.
Missing values are not allowed.
surrogate (x, ns = 1, fft = FALSE, amplitude = FALSE)
x |
a numeric vector or time series. |
ns |
the number of surrogate series to compute. |
fft |
a logical indicating whether phase randomized surrogate data is generated. |
amplitude |
a logical indicating whether amplitude-adjusted surrogate data is computed. |
To compute the phase randomized surrogate and the amplitude adjusted data algorithm 1 and 2 from Theiler et al. (1992), pp. 183, 184 are used.
A matrix with ns columns and length{x} rows containing
the surrogate data. Each column contains one surrogate sample.
A. Trapletti
J. Theiler, B. Galdrikian, A. Longtin, S. Eubank, and J. D. Farmer (1992): Using Surrogate Data to Detect Nonlinearity in Time Series, in Nonlinear Modelling and Forecasting, Eds. M. Casdagli and S. Eubank, Santa Fe Institute, Addison Wesley, pp. 163-188.
x <- 1:10 surrogate (x)