Non-stationary surrogate time series
Mario Chávez, Bernard Cazelles · Zenodo (CERN European Organization for Nuclear Research) · 2018
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