Stationarization via Surrogates
Abstract
The method of surrogate data, classically used for nonlinearity tests, amounts to the use of some constrained noise providing reference for statistical test. It is revisited here as a method for stationarization and this feature is put forward in the context of nonstationarity testing. The stationarization property of surrogates is first explored in a time-frequency perspective and used for devising a test of stationarity relative to an observation time. Then, more general forms of surrogates are developed, directly in time-frequency or mixed domains of representation (ambiguity and time-lag domains included) and it is shown how they allow for other tests of nonstationary features: detection of the existence of a transient in some noise; assessment of nonstationary cross-correlations.
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