A method for testing nonlinearity in time series is described based on
information-theoretic functionals -- redundancies, linear and nonlinear forms
of which allow either qualitative, or, after incorporating the surrogate data
technique, quantitative evaluation of dynamical properties of scrutinized data.
An interplay of quantitative and qualitative testing on both the linear and
nonlinear levels is analyzed and robustness of this combined approach against
spurious nonlinearity detection is demonstrated. Evaluation of redundancies and
redundancy-based statistics as functions of time lag and embedding dimension
can further enhance insight into dynamics of a system under study.Comment: 32 pages + 1 table in separate postscript files, 12 figures in 12
encapsulated postscript files, all in uuencoded, compressed tar file. Also
available by anon. ftp to santafe.edu, in directory pub/Users/mp/qq. To be
published in Physica D., [email protected]