SurrogateData | R Documentation |

`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")
```

rEDM documentation built on Nov. 10, 2023, 5:08 p.m.

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