SurrogateData: Generate surrogate data for permutation/randomization tests

In rEDM: Empirical Dynamic Modeling ('EDM')

Generate surrogate data for permutation/randomization tests

Description

SurrogateData generates surrogate data under several different null models.

Usage

SurrogateData( ts, method = c("random_shuffle", "ebisuzaki",
"seasonal"), num_surr = 100, T_period = 1, alpha = 0 )

Arguments

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)

Details

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).

Value

A matrix where each column is a separate surrogate with the same length as ts.

Examples

data("block_3sp")
ts <- block_3sp$x_t
SurrogateData(ts, method = "ebisuzaki")

rEDM documentation built on May 29, 2024, 12:02 p.m.