Recurrence threshold selection for obtaining robust recurrence characteristics in different embedding dimensions

Fuente: arXiv
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Auteurs principaux: Kraemer, K. Hauke, Donner, Reik V., Heitzig, Jobst, Marwan, Norbert
Format: Preprint
Publié: 2025
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author Kraemer, K. Hauke
Donner, Reik V.
Heitzig, Jobst
Marwan, Norbert
author_facet Kraemer, K. Hauke
Donner, Reik V.
Heitzig, Jobst
Marwan, Norbert
contents The appropriate selection of recurrence thresholds is a key problem in applications of recurrence quantification analysis and related methods across disciplines. Here, we discuss the distribution of pairwise distances between state vectors in the studied system's state space reconstructed by means of time-delay embedding as the key characteristic that should guide the corresponding choice for obtaining an adequate resolution of a recurrence plot. Specifically, we present an empirical description of the distance distribution, focusing on characteristic changes of its shape with increasing embedding dimension. Our results suggest that selecting the recurrence threshold according to a fixed percentile of this distribution reduces the dependence of recurrence characteristics on the embedding dimension in comparison with other commonly used threshold selection methods. Numerical investigations on some paradigmatic model systems with time-dependent parameters support these empirical findings.
format Preprint
id arxiv_https___arxiv_org_abs_2502_13036
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Recurrence threshold selection for obtaining robust recurrence characteristics in different embedding dimensions
Kraemer, K. Hauke
Donner, Reik V.
Heitzig, Jobst
Marwan, Norbert
Data Analysis, Statistics and Probability
Chaotic Dynamics
The appropriate selection of recurrence thresholds is a key problem in applications of recurrence quantification analysis and related methods across disciplines. Here, we discuss the distribution of pairwise distances between state vectors in the studied system's state space reconstructed by means of time-delay embedding as the key characteristic that should guide the corresponding choice for obtaining an adequate resolution of a recurrence plot. Specifically, we present an empirical description of the distance distribution, focusing on characteristic changes of its shape with increasing embedding dimension. Our results suggest that selecting the recurrence threshold according to a fixed percentile of this distribution reduces the dependence of recurrence characteristics on the embedding dimension in comparison with other commonly used threshold selection methods. Numerical investigations on some paradigmatic model systems with time-dependent parameters support these empirical findings.
title Recurrence threshold selection for obtaining robust recurrence characteristics in different embedding dimensions
topic Data Analysis, Statistics and Probability
Chaotic Dynamics
url https://arxiv.org/abs/2502.13036