aaft: Amplitude Adjusted Fourier Transform (AAFT)

Description Usage Arguments Details Value Author(s) References Examples

View source: R/aaft.R

Description

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

Usage

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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 nsur surrogates.

Author(s)

Adrian Barnett a.barnett<at>qut.edu.au

References

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

Examples

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

season documentation built on June 3, 2021, 5:06 p.m.