aaft {season} | R Documentation |
Amplitude Adjusted Fourier Transform (AAFT)
Description
Generates random linear surrogate data of a time series with the same second-order properties.
Usage
aaft(data, nsur)
Arguments
data |
a vector of equally spaced numeric observations (time series). |
nsur |
the number of surrogates to generate (1 or more). |
Details
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
nonlintest
.
Value
surrogates |
a matrix of the |
Author(s)
Adrian Barnett a.barnett@qut.edu.au
References
Kugiumtzis D (2000) Surrogate data test for nonlinearity including monotonic transformations, Phys. Rev. E, vol 62
Examples
data(CVD)
surr = aaft(CVD$cvd, nsur=1)
plot(CVD$cvd, type='l')
lines(surr[,1], col='red')
[Package season version 0.3.15 Index]