From Nonlinearity to Predictability
نویسنده
چکیده
Detection of nonlinearity in experimental time series is usually based on rejection of a linear null hypothesis by a statistical test. Typically, the null hypothesis is a Gaussian process or a Gaussian process passed through a static nonlinear transformation or a similar simple alternative. Rejection of such a null is frequently interpreted as a detection of a deterministic nonlinear relation in data under study, which is, however, only one of possible alternatives. We show how variable variance, or seasonality in variance could lead to spurious identiication of deterministic nonlinearity and discuss how to distinguish actual determinism in studied time series.
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