Generates random linear surrogate data of a time series with the same second-order properties.
a vector of equally spaced numeric observations (time series).
the number of surrogates to generate (1 or more).
The AAFT uses phase-scrambling to create a surrogate of the time series that
has a similar spectrum (and hence similar second-order statistics). The AAFT
is useful for testing for non-linearity in a time series, and is used by
a matrix of the
Adrian Barnett firstname.lastname@example.org
Kugiumtzis D (2000) Surrogate data test for nonlinearity including monotonic transformations, Phys. Rev. E, vol 62
data(CVD) surr = aaft(CVD$cvd, nsur=1) plot(CVD$cvd, type='l') lines(surr[,1], col='red')
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