There are three M-files:
1. third.m, calculates the third-order moment for a time series
2. aaft.m, calculates the Amplitude Adjusted Fourier Transform (for more details see: D. Kugiumtzis, Surrogate data test for nonlinearity including monotonic transformations, Phys Rev E, vol. 62, 1, 2000)
3. boot.m, uses the above two m-files to calculate a bootstrap test of non-linearity. The graphical output from the test is useful for: a) identifying the type of non-linearity, and b)informally checking non-stationarity.
Full details of the test are in the paper: Barnett & Wolff, A Time-Domain Test for Some Types of Nonlinearity, IEEE Transactions on Signal Processing (2005, vol 53, issue 1).
Adrian Barnett (2021). Test of non-linearity (https://www.mathworks.com/matlabcentral/fileexchange/16062-test-of-non-linearity), MATLAB Central File Exchange. Retrieved .
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Dear Adrain,
Thank you for sharing the code.
I notice that the codes are bootstraps using AAFT mehtods.
Could you please send me this nonlinearity test method code with CAAFT?
thanks very much!
LEE
Dear Adrain,
Thank you for sharing the code.
I notice that the codes are bootstraps using AAFT mehtods.
Could you please send me this nonlinearity test method code with CAAFT?
thanks very much!
Gan
Thanks alot. It is a very useful tool
Dear Asim
Sorry for the delay in replying. Have you tried reading the paper in the 'IEEE Transactions on Signal Processing', vol 53, issue 1, pages 26-33?
There are two parts to the output: i) A graphical part that shows the co-ordinates of the third order moment that are outside the test limits, ii) An overall boostrap test of non-linearity based on the third order moment.
Adrian
Dear Adrain,
Thank you for sharing the code. I ran tha code with a dataset. However, I could read the out comes properly. is there any clear way of explaining the outcomes. ow to interpret the results.
thanks
Thank You, it saves my time.