Testing for nonlinearity in irregular fluctuations with long-term trends.

Phys Rev E Stat Nonlin Soft Matter Phys

Department of Electronic and Information Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong.

Published: August 2006

We describe a method for investigating nonlinearity in irregular fluctuations (short-term variability) of time series even if the data exhibit long-term trends (periodicities). Such situations are theoretically incompatible with the assumption of previously proposed methods. The null hypothesis addressed by our algorithm is that irregular fluctuations are generated by a stationary linear system. The method is demonstrated for numerical data generated by known systems and applied to several actual time series.

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http://dx.doi.org/10.1103/PhysRevE.74.026205DOI Listing

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