Description Usage Arguments Details Value Author(s) References See Also Examples
For significance testing wavelet coherence and other purposes
1 | surrog(dat, nsurrogs, surrtype, syncpres)
|
dat |
A locations x time matrix of observations (for multiple-time series input), or a single vector |
nsurrogs |
The number of surrogates to produce |
surrtype |
Either "fft" (for Fourier surrogates) or "aaft" (for amplitude adjusted Fourier surrogates). Fourier surrogates are appropriate for time series with normal marginals; otherwise consider aaft surrogates. |
syncpres |
Logical. TRUE for "synchrony preserving" surrogates (same phase randomizations used for all time series). FALSE leads to independent phase randomizations for all time series. |
Fourier surrogates are somewhat faster than aaft
surrogates, and may be much faster when
some of the time series in the data have ties. Prenormalization (e.g., using cleandat
) can
make it possible to use fft
surrogates.
surrog
returns a list of nsurrogs surrogate datasets
Jonathan Walter, jaw3es@virginia.edu; Lawrence Sheppard, lwsheppard@ku.edu; Daniel Reuman, reuman@ku.edu
Sheppard, LW, et al. (2016) Changes in large-scale climate alter spatial synchrony of aphid pests. Nature Climate Change. DOI: 10.1038/nclimate2881
Schreiber, T and Schmitz, A (2000) Surrogate time series. Physica D 142, 346-382.
Prichard, D and Theiler, J (1994) Generating surrogate data for time series with several simultaneously measured variables. Physical Review Letters 73, 951-954.
wpmf
, coh
, wlmtest
, synmat
,
browseVignettes("wsyn")
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