A nonparametric relative entropy summary of intermittent time series, combined with BIC lag selection and CUSUM change-point detection, outperforms approximate entropy in locating complexity changes.
Proof of Theorem 3.1.Following the Theorems A.6 – A.9 in Hong and White (2005), one can extend their theory to multivariate U-statistics with boundedm
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Modelling Loss of Complexity in Intermittent Time Series and its Application
A nonparametric relative entropy summary of intermittent time series, combined with BIC lag selection and CUSUM change-point detection, outperforms approximate entropy in locating complexity changes.