aaft function

Amplitude Adjusted Fourier Transform (AAFT)

Generates random linear surrogate data of a time series with the same second-order properties.

aaft(data, nsur)

Arguments

• data: a vector of equally spaced numeric observations (time series).
• nsur: the number of surrogates to generate (1 or more).

Returns

• surrogates: a matrix of the nsur surrogates.

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.

Examples

data(CVD)
surr = aaft(CVD$cvd, nsur=1)
plot(CVD$cvd, type='l')
lines(surr[,1], col='red')

References

Kugiumtzis D (2000) Surrogate data test for nonlinearity including monotonic transformations, Phys. Rev. E, vol 62

Author(s)

Adrian Barnett a.barnett@qut.edu.au