Published April 6, 2018
| Version v1
Software
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Non-stationary surrogate time series
Authors/Creators
Description
R codes implementing the non-stationary surrogate algorithm described in:
M. Chavez, B. Cazelles (2018). Detecting dynamic spatial correlation patterns with generalized wavelet coherence and non-stationary surrogate data. Arxiv: 1801.04778 [physics.data-an]
Briefly, in contrast with classical methods, the surrogate data used here are realisations of a non-stationary stochastic process, preserving both the amplitude and time-frequency distributions of original data.
To reproduce the results in the figure, please run the routine instructionsSurrogates.R (it requires the R packages pragma, signal, and viridis)
IMPORTANT: R codes for the standard stationary surrogates are those made by Henning Rust, available here
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screen_Shot_Nonstationary_Surrogate.png
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