Abstract
It is shown that monotonicity of the transform in the surrogate data test, which diminishes the applicability of the test, is not necessary and concerns only the prominent algorithm of amplitude adjusted Fourier transform (AAFT) for surrogate data generation. The failure of AAFT under nonmonotonicity is explained and a modified algorithm appropriate for nonmonotonic transforms, called corrected AAFT (CAAFT), is proposed. The superiority of CAAFT over AAFT is demonstrated with simulated and real data and compared also to the iterated AAFT algorithm.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
