Information directionality in coupled time series using transcripts

Abstract

In ordinal symbolic dynamics, transcripts describe the algebraic relationship between ordinal patterns. Using the concept of transcript, we exploit the mathematical structure of the group of permutations to derive properties and relations among information measures of the symbolic representations of time series. These theoretical results are then applied for the assessment of coupling directionality in dynamical systems, where suitable coupling directionality measures are introduced depending only on transcripts. These novel measures estimate information flow in lower space dimension and reduce to well-established coupling directionality quantifiers when some general conditions are satisfied. Furthermore, by generalizing the definition of transcript to ordinal patterns of different lengths, several of the commonly used information directionality measures can be encompassed within the same framework.

24 pages, 9 figures

References in corpus (6)

• Measuring Information Transfer
• Robustly estimating the flow direction of information in complex physical systems
• Partial Transfer Entropy on Rank Vectors
• Reducing the Bias of Causality Measures
• Characterizing Synchronization in Time Series using Information Measures Extracted from Symbolic Representations
• Permutation complexity of interacting dynamical systems

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