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.
(25) Let ˆm = arg min σ2 λ(m), we haveσ2 0( ˆmλ)/σ2 0(m0) → 1 almost surely
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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.