aaft: Amplitude Adjusted Fourier Transform (AAFT)

In season: Seasonal analysis of health data

Description

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

Usage

aaft(data, n.sur)

Arguments

data	a vector of equally spaced numeric observations (time series).
n.sur	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 n.sur 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

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

season documentation built on May 2, 2019, 5:22 p.m.