Abstract
The choice of test statistics has a significant impact on the nonlinearity detection of time series. This paper proposes a new test statistic - multi-dimensional information entropy for the nonlinearity test. After applying IAAFT algorithm to create surrogate data, five test statistic methods, which include time reversibility, higher order autocovariance, nonlinear prediction error, approximate entropy and multi-dimensional information entropy, are employed to test the nonlinearity of AR signal, Henon signal, Lorenz signal, ECG signal and EDA signal. By comparing the test results, it indicates that the multidimensional information entropy is an effective and stable nonlinear test statistic. The multi-dimensional information entropy has high noise immunity and more sensitive to nonlinear signal.
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