Results 21 to 30 of about 54,062 (250)
Ordinal synchronization: Using ordinal patterns to capture interdependencies between time series [PDF]
Chaos, Solitons & Fractals, 2019 We introduce Ordinal Synchronization ($OS$) as a new measure to quantify synchronization between dynamical systems. $OS$ is calculated from the extraction of the ordinal patterns related to two time series, their transformation into $D$-dimensional ordinal vectors and the adequate quantification of their alignment.
I. Echegoyen +4 more
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Conditional entropy of ordinal patterns [PDF]
Physica D: Nonlinear Phenomena, 2014 In this paper we investigate a quantity called conditional entropy of ordinal patterns, akin to the permutation entropy. The conditional entropy of ordinal patterns describes the average diversity of the ordinal patterns succeeding a given ordinal pattern.
Unakafov, Anton M., Keller, Karsten
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Statistical properties of the entropy from ordinal patterns
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2022 The ultimate purpose of the statistical analysis of ordinal patterns is to characterize the distribution of the features they induce. In particular, knowing the joint distribution of the pair entropy-statistical complexity for a large class of time series models would allow statistical tests that are unavailable to date.
E. T. C. Chagas +5 more
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Time-Delay Identification Using Multiscale Ordinal Quantifiers
Entropy, 2021 Time-delayed interactions naturally appear in a multitude of real-world systems due to the finite propagation speed of physical quantities. Often, the time scales of the interactions are unknown to an external observer and need to be inferred from time ...
Miguel C. Soriano, Luciano Zunino
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Ordinal Pattern Dependence in the Context of Long-Range Dependence
Entropy, 2021 Ordinal pattern dependence is a multivariate dependence measure based on the co-movement of two time series. In strong connection to ordinal time series analysis, the ordinal information is taken into account to derive robust results on the dependence ...
Ines Nüßgen, Alexander Schnurr
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Continuous ordinal patterns: Creating a bridge between ordinal analysis and deep learning
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2023 We introduce a generalization of the celebrated ordinal pattern approach for the analysis of time series, in which these are evaluated in terms of their distance to ordinal patterns defined in a continuous way. This allows us to naturally incorporate information about the local amplitude of the data and to optimize the ordinal pattern(s) to the problem
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20 years of ordinal patterns: Perspectives and challenges
Europhysics Letters, 2022 Abstract In 2002, in a seminal article, Bandt and Pompe proposed a new methodology for the analysis of complex time series, now known as Ordinal Analysis. The ordinal methodology is based on the computation of symbols (known as ordinal patters) which are defined in terms of the temporal ordering of data points in a time series, and whose
Leyva Callejas, Inmaculada +4 more
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Ordinal patterns in the Duffing oscillator: Analyzing powers of characterization [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2021 Ordinal patterns are a time-series data analysis tool used as a preliminary step to construct the permutation entropy, which itself allows the same characterization of dynamics as chaotic or regular as more theoretical constructs such as the Lyapunov exponent.
Ivan Gunther +2 more
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Testing for Structural Breaks via Ordinal Pattern Dependence [PDF]
Journal of the American Statistical Association, 2017 We propose new concepts in order to analyze and model the dependence structure between two time series. Our methods rely exclusively on the order structure of the data points. Hence, the methods are stable under monotone transformations of the time series and robust against small perturbations or measurement errors.
Schnurr, Alexander, Dehling, Herold
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Ordinal pattern dependence as a multivariate dependence measure [PDF]
Journal of Multivariate Analysis, 2021 In this article, we show that the recently introduced ordinal pattern dependence fits into the axiomatic framework of general multivariate dependence measures, i.e., measures of dependence between two multivariate random objects. Furthermore, we consider multivariate generalizations of established univariate dependence measures like Kendall's ...
Annika Betken +3 more
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