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.
Title resolution pending
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
stat.ME 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
citing papers explorer
-
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.