Generate surrogate data for permutation/randomization tests
SurrogateData generates surrogate data under several different
null models.
SurrogateData( ts, method = c("random_shuffle", "ebisuzaki",
"seasonal"), num_surr = 100, T_period = 1, alpha = 0 )ts |
the original time series |
method |
which algorithm to use to generate surrogate data |
num_surr |
the number of null surrogates to generate |
T_period |
the period of seasonality for seasonal surrogates (ignored for other methods) |
alpha |
additive noise factor: N(0,alpha) |
Method "random_shuffle" creates surrogates by randomly permuting the values of the original time series.
Method "Ebisuzaki" creates surrogates by randomizing the phases of a Fourier transform, preserving the power spectra of the null surrogates.
Method "seasonal" creates surrogates by computing a mean seasonal trend of the specified period and shuffling the residuals. It is presumed that the seasonal trend can be exracted with a smoothing spline. Additive Gaussian noise is included according to N(0,alpha).
A matrix where each column is a separate surrogate with the same
length as ts.
data("block_3sp")
ts <- block_3sp$x_t
SurrogateData(ts, method = "ebisuzaki")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.